tag:blogger.com,1999:blog-68371596291004633032024-03-13T00:28:57.381-07:00Information Transfer EconomicsA working paper exploring the idea that information equilibrium is a general principle for understanding economics. <a href="https://informationtransfereconomics.blogspot.com/2017/04/a-tour-of-information-equilibrium.html">[Here]</a> is an overview.Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.comBlogger1555125tag:blogger.com,1999:blog-6837159629100463303.post-88469370700789812952023-05-14T11:09:00.000-07:002023-05-14T11:09:08.386-07:00Link to my post: Ad hominem, for lack of a better word, is good<p> </p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh3XNxXszQNIsOlkY7ZSHwHmDJ2Jrv0z0E_YuDniMQiFdpGtQCspvbUUmET-0kuvy77HGEvwP5-hPBSCafR6s8k_G1KKhp0ujV1lwro8PF69GfnGwybRYIaodm_TsTz8TvT9apkqlRZu4FNb7-w4kOpN2Sk_QUc452KAIZsN7fjjGDLzHKvVLtCwijVng/s1041/sunriseOrbit.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="586" data-original-width="1041" height="225" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh3XNxXszQNIsOlkY7ZSHwHmDJ2Jrv0z0E_YuDniMQiFdpGtQCspvbUUmET-0kuvy77HGEvwP5-hPBSCafR6s8k_G1KKhp0ujV1lwro8PF69GfnGwybRYIaodm_TsTz8TvT9apkqlRZu4FNb7-w4kOpN2Sk_QUc452KAIZsN7fjjGDLzHKvVLtCwijVng/w400-h225/sunriseOrbit.png" width="400" /></a></div><br /><p></p><p><span style="background-color: white; color: #222222; font-family: Arial, Tahoma, Helvetica, FreeSans, sans-serif; font-size: 13.2px;">Due to Twitter's algorithm, this is a manual re-direct to my post:</span></p><p><a href="https://infoeqm.substack.com/p/ad-hominem-for-lack-of-a-better-word"><i>Ad hominem</i>, for lack of a better word, is good</a></p>Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com0tag:blogger.com,1999:blog-6837159629100463303.post-75057079744037800002023-05-01T20:23:00.010-07:002023-05-01T20:23:58.498-07:00Link to my substack post "On Hayek's 'The Use of Knowledge in Society' (1945)"<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiT4vOVK1CyqZYCFIxw3-8ra0DS_pugHofZAZj96JdmbdF0gFukU1YhxcvNWMe46RUhAdSmltLaQyxPNP9z8k9fvhTDgr-dW2a-Pa_woU6GHz9G8Z2qLuDhOZ6Fy6-22994z_vqT2EhdB4WR3o5hZa16D4dA9yKWcZLhf5kU7GlSMgG8dVxXlnFVxzlHg/s874/hayek.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="677" data-original-width="874" height="310" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiT4vOVK1CyqZYCFIxw3-8ra0DS_pugHofZAZj96JdmbdF0gFukU1YhxcvNWMe46RUhAdSmltLaQyxPNP9z8k9fvhTDgr-dW2a-Pa_woU6GHz9G8Z2qLuDhOZ6Fy6-22994z_vqT2EhdB4WR3o5hZa16D4dA9yKWcZLhf5kU7GlSMgG8dVxXlnFVxzlHg/w400-h310/hayek.png" width="400" /></a></div><br /><div><br /></div><div>Due to Twitter's algorithm, this is a manual re-direct to my substack post</div><div><br /></div><div><a href="https://infoeqm.substack.com/p/on-hayeks-the-use-of-knowledge-in">On Hayek's <i>The Use of Knowledge in Society</i> (1945)</a></div>Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com0tag:blogger.com,1999:blog-6837159629100463303.post-35638239559347826312023-04-07T11:51:00.004-07:002023-04-07T11:56:12.070-07:00Link to my substack post: Employment situation: core unemployment rising<p>Since Twitter has disabled likes, retweets, and replies to posts with substack links this is a manual re-direct via blogspot:</p><p><a href="https://infoeqm.substack.com/p/employment-situation-core-unemployment">https://infoeqm.substack.com/p/employment-situation-core-unemployment</a></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiMCRxB8wj6lxT85GdnI_wDVveABLPZAx0NOeN5YriAkaDySTID9rCwuX9Rs0p08gUt7MS98AIBVwbILp78FQ_i5xGCtcwOdSBMvxmYJdFrmvStq0JpE_LloLVDo8GCG07Zn57zm_AJxw0vpyMCzVpPDTfo7WgD8Y_aYHBirfpLeqwkV6QEHOJFtEdhng/s964/diem%20core%20unrate%2020230407a.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="668" data-original-width="964" height="278" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiMCRxB8wj6lxT85GdnI_wDVveABLPZAx0NOeN5YriAkaDySTID9rCwuX9Rs0p08gUt7MS98AIBVwbILp78FQ_i5xGCtcwOdSBMvxmYJdFrmvStq0JpE_LloLVDo8GCG07Zn57zm_AJxw0vpyMCzVpPDTfo7WgD8Y_aYHBirfpLeqwkV6QEHOJFtEdhng/w400-h278/diem%20core%20unrate%2020230407a.png" width="400" /></a></div><br /><p><br /></p>Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com0tag:blogger.com,1999:blog-6837159629100463303.post-58544358084077788492022-12-19T10:51:00.003-08:002023-07-27T09:34:28.353-07:00Where to find me these days<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEii6UflsEhXSHJ7ENYQ_ZbXBQ8ZfAhC2JonTsImhVMm7pnKowluItOoRwD9_bP5jeUSUAHqLmhq6x5fifuEVkFVUWOuX-wtn-K1oC7GvQMCoiCirqyFuOrjbOtyi1uEg2bm68b2IFKw5dyJhlr-bE-zSQoxhkaR1XIVlrsIPPPPgJqsQ_-tDqPdZRoqlA/s1000/1000x600banner.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="600" data-original-width="1000" height="240" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEii6UflsEhXSHJ7ENYQ_ZbXBQ8ZfAhC2JonTsImhVMm7pnKowluItOoRwD9_bP5jeUSUAHqLmhq6x5fifuEVkFVUWOuX-wtn-K1oC7GvQMCoiCirqyFuOrjbOtyi1uEg2bm68b2IFKw5dyJhlr-bE-zSQoxhkaR1XIVlrsIPPPPgJqsQ_-tDqPdZRoqlA/w400-h240/1000x600banner.png" width="400" /></a></div><p style="text-align: justify;"><br /></p><p style="text-align: justify;">This post acts as a collection of links to find me in various places for various content. This econ blog has been moved (along with the archives) over to my substack <i>Information Equilibrium</i>. It's free to sign up (and definitely more likely to get to you than twitter ever was).</p><p><a href="https://infoeqm.substack.com/">https://infoeqm.substack.com/</a></p><p>I also have an account on mastodon:</p><p><a href="https://econtwitter.net/@infotranecon">@infotranecon@econtwitter.net</a></p><p>I started a bluesky:</p><p><a href="https://bsky.app/profile/newqueuelure.bsky.social">@newqueuelure</a></p><p><b>Deactivated my twitter!</b></p><p><strike>I continue to post on twitter <a href="https://twitter.com/infotranecon">@infotranecon</a> (for econ and politics) and <a href="https://twitter.com/newqueuelure">@newqueuelure</a> (for sci fi and game stuff)</strike></p>Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com0tag:blogger.com,1999:blog-6837159629100463303.post-58962941141446445242022-09-10T20:43:00.000-07:002022-09-10T20:43:33.945-07:00Is the credibility revolution credible?<p style="text-align: justify;"><span style="background-color: white; color: #222222;"><span style="font-family: inherit;">Noah Smith made a stir with his claim that historians make theories without empirical backing — something I think is a bit of a category error. I mean even if historian's "theories" truly are "it happened in the past, so this can happen again", that the study of history gives us a sense of the available state space of human civilization, then that observation is such a small piece of the available state space as to carry zero probability on its own. You'd have to resort to some kind of historical anthropic principle that the kind of states humans have seen in the past are the more likely ones when you have a range of theoretical outcomes comparable to the string theory landscape [1]. But that claim is so dependent on its assumption it could not rise to the idea of a theory in empirical science.</span></span></p><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit;">Regardless of the original point, some of the pushback came in the form of pot/kettle tu quoque "economics isn't empirical either", to which on at least one occasion Noah countered by citing Angrist and Pischke (2010) on the so-called credibility revolution.</span></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit;"><br /></span></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit;">Does it counter, though? Let's dig in.</span></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit;"><br /></span></div><div style="background-color: white; color: #222222; text-align: justify;"><b><span style="font-family: inherit;">Introduction</span></b></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit;"><br /></span></div><span style="background-color: white; color: #222222;"><div style="text-align: justify;"><span style="font-family: inherit;">I do like the admission of inherent bias in the opening paragraph — the authors cite some critiques of econometric practice and wonder if their own grad school work was going to be taken seriously. However, they never point out that this journal article is something of an advertisement for the authors' book "Mostly Harmless Econometrics: An Empiricist's Companion" (they do note that it's available)</span></div></span><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit;"><br /></span></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit;">The main thrust of the article is that the authors claim the quality of empirical research design has improved over time with the use of randomization and natural experiments alongside increased scrutiny of confounding variables. They identify these improvements and give examples of where they are used. Almost no effort is made to quantify this improvement or show that the examples are representative (many are Angrist's own papers) — I'll get into that more later. First, let's look at research design.</span></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit;"><br /></span></div><div style="background-color: white; color: #222222; text-align: justify;"><b><span style="font-family: inherit;">Research design</span></b></div><div style="background-color: white; color: #222222; text-align: justify;"><b><span style="font-family: inherit;"><br /></span></b></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit;">The first research design is the randomization experiment. It's basically an approach wholesale borrowed from medicine (which is why the terms like treatment group show up). Randomized experiments have their own ethical issues documented by others that I won't go into here. The authors acknowledge this, so let's restrict our discussion to randomization experiments that pass ethical muster. Randomization relies on major assumptions about the regularity of every other variable — in a human system this is enormous so explicit or implicit theory is often used to justify isolation for the relevant variables. I talk more about theoretically isolating variables in the context of Dani Rodrik's book <a href="https://informationtransfereconomics.blogspot.com/2015/09/whats-wrong-with-dani-rodriks-view-of.html">here</a> — suffice to say this is where a lot of non-empirical rationalization can enter the purportedly empirical randomization experiment.</span></div><div style="background-color: white; color: #222222;"><span style="font-family: inherit;"><br /></span></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit;">The second is natural experiments. Again these rely on major assumptions about the regularity of every other variable, usually from theory. The authors discuss Card (1990) which is the good way to do this — showing there was no observable effect on wages from a labor surge in Miami.</span></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit;"><br /></span></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit;">However, contra Angrist and Pischke's thesis, Card draws conclusions based on the implicit theory that a surge of labor should normally cause wages to fall so there must be some just-so story about Miami being specifically able to absorb the immigration — the conclusion was not the one you would derive from the empirical evidence. It's true that Card was working in an environment where supply and demand in the labor market was the dominant first order paradigm so he likely had to make some concession to it. This is why this paper is best seen as "no observable effect on wages", but not really a credibility revolution because it doesn't take the empirical data seriously enough to say maybe the theory is wrong. As a side note, <a href="https://informationtransfereconomics.blogspot.com/2017/04/its-production-input-no-its-market-good.html">it's easily fixed with a better framework</a> for understanding supply and demand.</span></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit;"><br /></span></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit;">The authors go on to cite Jacob (2004) which draws the conclusion in the abstract that public housing had no effect on educational outcomes because demolishing public housing projects in Chicago has no effect on educational outcomes purportedly because the people relocate to similar areas. However, this conclusion 1) misrepresents the effect actually seen in the paper (no observable effect on outcomes for children < 14 years, but older students were more likely to drop out), and 2) misses out on the fact that the effort may be insufficient in the first place. It is possible the lack of funding for as well as the subsequent decay and demolition of public housing creates a scenario where the limited effort expended is insufficient to create a positive effect in the first place — therefore it does not mean public housing is ineffective on educational outcomes as a policy. The dose of medicine may be too small but this natural experiment assumes the dose was sufficient in order to draw its conclusion.</span></div><div style="background-color: white; color: #222222;"><span style="font-family: inherit;"><br /></span></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit;">There is also the lack of analysis of the macro scale where demolition of public housing projects is one among a myriad of public policy choices that disproportionately negatively impact Black people — that the demolition is just one thing in the way among many such that negative educational outcomes may be due to e.g. a series of similar upsets (public housing demolished, parent loses a job, parents are denied a mortgage because of racism) where not every kid experiences the same subset. The aggregate effect is negative educational outcomes overall, so you need a lot more data to tease out the effect of any single factor. There's a desert with poisonous snakes, no water, no shade, choking sand, and freezing nights — solving one of those problems and seeing people still die does not mean solving one problem was not effective.</span></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit;"><br /></span></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit;">The authors proceed in the introduction to look at the historical development of exploiting various "natural experiments" such as the variation across states. However I've pointed out the potential issues <a href="https://informationtransfereconomics.blogspot.com/2019/10/wage-growth-in-ny-and-pa.html">here</a> with regard to a particular study of the minimum wage using the NY/PA border as the natural experiment. The so-called credibility revolution often involves making these assumptions ("obviously, straight lines on maps obviously have no effects") without investigating a bit more (like I did at the link using Google maps as a true empiricist).</span></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit;"><br /></span></div><div style="background-color: white; color: #222222; text-align: justify;"><b><span style="font-family: inherit;">Credibility and non-empirical reasoning</span></b></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit;"><br /></span></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit;">Empirical credibility is like the layers of an onion. Using natural experiments and randomized quasi-experiments peels back one layer of non-empirical reasoning, but the next layer appears to be the armchair theory assumptions used to justify the interpretations of those "experiments". Per the link above about the issues with isolating variables, it is possible to do this using armchair theory if you have an empirically successful theoretical framework that already tells you how to isolate those variables — but that's not the case in economics.</span></div><div style="background-color: white; color: #222222;"><span style="font-family: inherit;"><br /></span></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit;">The biggest things in the empirical sciences that prevent this infinite regress/chicken and egg problem are successful predictions. If you regularly and accurately predict something, that goes a long way towards justifying the models and methods used because it relies on the simple physical principle that we cannot get information from the future (from all us physicists out there: you're welcome). But at a very basic level, what will turn around the credibility of economics is the production of <i>useful </i>results. Not useful from, say, a political standpoint where results back whatever policy prescription you were going to advocate anyway — useful to people's lives. <a href="https://informationtransfereconomics.blogspot.com/2016/07/ceteris-paribus-and-method-of-nascent.html">I've called this the method of nascent science</a>.</span></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit;"><br /></span></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit;">This does not necessarily include those studies out there that say natural experiment X says policy Y (with implicit assumptions Z) had no effect in the aggregate data. Raising the minimum wage seems to have no observable effect in the aggregate data, but raising the minimum wage is useful to the people who get jobs working at minimum wage at the individual level. Providing health care randomly in Oregon may not have resulted in obvious beneficial outcomes at the aggregate level, but people who have access to health care are better off at the individual level. In general, giving people more money is helpful at the individual level. If there's no observable aggregate effect in either direction (or even a 1-sigma effect in either direction), that's not evidence we shouldn't do things that obviously help the people that get the aid.</span></div><div style="background-color: white; color: #222222;"><span style="font-family: inherit;"><br /></span><div style="text-align: justify;"><span style="font-family: inherit;">The article discusses instrumental variables, but says that economists went from not explaining why instrumental variables were correct at all to creating just-so stories for them or just being clever (even dare I say it, contrarian) about confounding variables. I mean calling it a "credibility revolution" when other economists finally think a bit harder and start to point out serious flaws in research design when there was no reason these flaws couldn't have been pointed out before the 1980s is a bit of an overstatement. I mean from the looks of it, it could be equally plausible that economists only started to read each other's empirical papers in the 80s [2].<br /></span></div><div><span style="font-family: inherit;"><br /></span></div><div style="text-align: justify;"><span style="font-family: inherit;">You can see the lack of empirical credibility in the way one of these comments in the article is phrased.</span></div></div><i><span style="font-family: inherit;"></span></i><blockquote style="text-align: justify;"><i><span style="font-family: inherit;">For example, a common finding in the literature on education production is that children in smaller classes tend to do worse on standardized tests, even after controlling for demographic variables. This apparently perverse finding seems likely to be at least partly due to the fact that struggling children are often grouped into smaller classes.</span></i><div style="background-color: white; color: #222222;"><div style="text-align: justify;"></div></div></blockquote><div style="background-color: white; color: #222222;"><div style="text-align: justify;"><span style="font-family: inherit;">It's not that they proved this empirically. There's no citation. It just "seems likely" to be "at least partly" the reason. Credibility revolution! Later they mention "State-by-cohort variation in school resources also appears unrelated to omitted factors such as family background" in a study from Card and Krueger. No citation. No empirical backing. Just "appears unrelated". Credibility revolution! It should be noted that this subject is one of the author's (Angrist) common research topics and has a paper that says smaller class sizes are better discussed below — Angrist could easily be biased in these rationalizations in defense of their own work. Credibility revolution!</span></div><div style="text-align: justify;"><span style="font-family: inherit;"><br /></span></div><div style="text-align: justify;"><span style="font-family: inherit;">There's another one of these "nah, it'll be fine" assurances that I'm not entirely sure is even correct:</span></div></div><i><span style="font-family: inherit;"><blockquote style="text-align: justify;">... we would like students to have similar family backgrounds when they attend schools with grade enrollments of 35–39 and 41–45 [on either side of the 40 students per class cutoff]. One test of this assumption... is to estimate effects in an increasingly narrow range around the kink points; as the interval shrinks, the jump in class size stays the same or perhaps even grows, but the estimates should be subject to less and less omitted variables bias. </blockquote></span></i><div style="background-color: white; color: #222222;"><div style="text-align: justify;"><span style="font-family: inherit;">I wracked my brain for some time trying to think of a reason omitted variable bias would be reduced when comparing sets of schools with enrollments of 38-39 vs 41-42 as opposed to comparing sets of schools enrollments of 35-39 vs 41-45. They're still sets of different schools. By definition your omitted variables do not know about the 40 students per class cutoff, so should not have any particular behavior around this point. It just seems like your error bars get bigger due to using a subsample. Plus, the point where you have the most variation in your experimental design is in the change of class sizes from an average of ~ 40 to an average of ~ 20 in a school with an enrollment going from 40 to 41 meaning that individual students are having the most impact precisely at the point where you are trying to extract the biggest signal of your effect. See figure below. Omitted variable bias is increased at that point due to the additional weight of individual students in the sample! It could be things you wouldn't even think of because they apply to a single student — like an origami hobby or being struck by lightning.</span></div><div style="text-align: justify;"><span style="font-family: inherit;"><br /></span></div><table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto;"><tbody><tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhWv5d7Yinh6JhNLKO1ryeAA0XNzVCqzzJF71wVFgtljrImupsQBNFAC8gjRRVEREq7o6fZYiYFicq1MBqitJJf5Rgbd_hlR7t71Q26jXb2ckKemCQX4Qa95G-JDEd1TzmffNpSrrPkMuEeg8CF6Pmavur-_qWYzrRCRRxbVgmSgO7WI8SAV5S57tfCYg/s792/average%20class%20size.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><span style="font-family: inherit;"><img border="0" data-original-height="430" data-original-width="792" height="217" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhWv5d7Yinh6JhNLKO1ryeAA0XNzVCqzzJF71wVFgtljrImupsQBNFAC8gjRRVEREq7o6fZYiYFicq1MBqitJJf5Rgbd_hlR7t71Q26jXb2ckKemCQX4Qa95G-JDEd1TzmffNpSrrPkMuEeg8CF6Pmavur-_qWYzrRCRRxbVgmSgO7WI8SAV5S57tfCYg/w400-h217/average%20class%20size.png" width="400" /></span></a></td></tr><tr><td class="tr-caption" style="text-align: center;"><span style="font-family: inherit;">Average class size in the case of a maximum of 40 students versus enrollment.</span></td></tr></tbody></table><div style="text-align: justify;"><span style="font-family: inherit;"><br /></span></div><div style="text-align: justify;"><span style="font-family: inherit;">The authors then (to their credit) cite Urqiola and Verhoogen (2009) showing the exact same method fails in a different case. However, they basically handwave away that it could apply to the former result based on what could only be called armchair sociology about the differences between Israel (the first paper from one of the authors of the "credibility revolution" article [Angrist]) and Chile (the 2009 paper).</span></div><div style="text-align: justify;"><span style="font-family: inherit;"><br /></span></div><div style="text-align: justify;"><span style="font-family: inherit;">After going through the various microeconomic studies, they go through macro, growth econ, and industrial organization where they tell us 1) the empirical turn hasn't really taken hold (the credibility revolution coming soon), and 2) if you lower your standards significantly you might be able to say a few recent papers have the right "spirit".</span></div><div style="text-align: justify;"><span style="font-family: inherit;"><br /></span></div><div style="text-align: justify;"><b><span style="font-family: inherit;">Conclusion</span></b></div><div style="text-align: justify;"><span style="font-family: inherit;"><br /></span></div><div style="text-align: justify;"><span style="font-family: inherit;">Angrist and Pischke (2010) is basically "here are some examples of economists doing randomized trials, identifying natural experiments, and pointing out confounding variables" but doesn't make a case where this is a causal factor behind improving empirical accuracy, building predictive models, or producing results that are replicable or generalizable. They don't make the case that the examples are representative. I mean it's a good thing that pointing out obvious flaws in research design is en vogue in econometrics, and increased use of data is generally good when the data is good. However I still read NBER working papers all the time that fail to identify confounding variables and instead read like a just-so story for why the instrumental variable or natural experiment is valid using non-empirical reasoning. Amateur sociology still abounds from journal articles to job market papers. The authors essentially try to convince us of a credibility revolution and the rise of empirical economics by pointing to examples — which is ironic because that is not exactly good research design. The only evidence they present is the increasing use of the "right words", but as we can see from the examples above you can use the right words and still have issues.</span></div><div><span style="font-family: inherit;"><br /></span></div><div style="text-align: justify;"><span style="font-family: inherit;">In the end, it doesn't seem anyone is pointing out the obvious confounding variable here — the widespread use of computers and access to the internet increased both the amount of data, the size of regressions, and the speed with which they could be processed [3] — could lead to a big increase in <a href="https://noahpinionblog.blogspot.com/2015/06/a-paradigm-shift-in-empirical-economics.html">the number of empirical papers</a> (figures borrowed from link below) without an increase in the rate of credibility among those results [4]. And don't get me started about the lack of a nexus between "empirical" and "credible" in the case of proprietary data or the <a href="https://www.theguardian.com/news/2022/jul/12/uber-paid-academics-six-figure-sums-for-research-to-feed-to-the-media">funding sources</a> of the people performing or promoting a study.</span></div><div style="text-align: justify;"><span style="font-family: inherit;"><br /></span></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh2m5V6sv-IMtk4u00JCjd4licV5UbcDLeu5nmT0F57Wx4nAOm_I3RID6iE7Ri2uHn27lS_W20h6gTX5FrAORVhtUGQY5DsBtbd4-zYwrOMhs7iKyqEPZ-sMYoq16Qa4Nm57pW2qTKMct4_yM8M46lCdBieFcMEZ-Ho6hW8cvytKjg2AK8xp2JQ5rR4sw/s831/fig1.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><span style="font-family: inherit;"><img border="0" data-original-height="492" data-original-width="831" height="236" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh2m5V6sv-IMtk4u00JCjd4licV5UbcDLeu5nmT0F57Wx4nAOm_I3RID6iE7Ri2uHn27lS_W20h6gTX5FrAORVhtUGQY5DsBtbd4-zYwrOMhs7iKyqEPZ-sMYoq16Qa4Nm57pW2qTKMct4_yM8M46lCdBieFcMEZ-Ho6hW8cvytKjg2AK8xp2JQ5rR4sw/w400-h236/fig1.png" width="400" /></span></a></div><span style="font-family: inherit;"><br /><br /></span><div style="text-align: justify;"><span style="font-family: inherit;"><br /></span><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiWndire2qWXN1Zwf0FY_5UOQqAluAe6ghaMcp3nnJaKTNLNKgw1cV6Hy5xG8J8jpUwoatFV46c3IMpfzlRlOW-GLaHgeDBxklrbFDRt4h171X9ovDXahtIGEos5seoAWhBZ_dVZotPKyGXiTAD0s647JOsuU6P-dSQHwwHDWJykUPiKi4WUB5y69i2Xg/s603/fig8.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><span style="font-family: inherit;"><img border="0" data-original-height="423" data-original-width="603" height="280" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiWndire2qWXN1Zwf0FY_5UOQqAluAe6ghaMcp3nnJaKTNLNKgw1cV6Hy5xG8J8jpUwoatFV46c3IMpfzlRlOW-GLaHgeDBxklrbFDRt4h171X9ovDXahtIGEos5seoAWhBZ_dVZotPKyGXiTAD0s647JOsuU6P-dSQHwwHDWJykUPiKi4WUB5y69i2Xg/w400-h280/fig8.png" width="400" /></span></a></div></div><div style="text-align: justify;"><span style="font-family: inherit;"><br /></span></div><div style="text-align: justify;"><span style="font-family: inherit;">So is this evidence of a credibility revolution? Not really.</span></div><div style="text-align: justify;"><span style="font-family: inherit;"><br /></span></div><div style="text-align: justify;"><span style="font-family: inherit;">But per the original question, is this a counter to people saying that economics isn't empirically testable science? It depends.</span></div><div style="text-align: justify;"><span style="font-family: inherit;"><br /></span></div><div style="text-align: justify;"><span style="font-family: inherit;">I mean it's not an empirically testable science in the sense of physics or chemistry where you can run laboratory experiments that isolate individual effects. You can make predictions about measured quantities in economics that can be empirically validated, but that isn't what is being discussed here and for the most part does not seem to be done in any robust and accountable way. Some parts of econ (micro/econometrics) have some papers that have the appearance of empirical work, but 1) not all fields, and 2) there's still a lot of non-empirical rationalization going into e.g. justification of the instrumental variables.</span></div><div style="text-align: justify;"><span style="font-family: inherit;"><br /></span></div><div style="text-align: justify;"><span style="font-family: inherit;">I would say that economics is an <i>evidentiary </i>science — it utilizes empirical data and (hopefully) robust research design in some subfields, but the connective tissue of the discipline as a whole remains as always "thinking like an economist" which is a lot of narrative rationalization that can run the gamut from logical argument to armchair sociology to just-so stories used to justify the entire theory or simply an instrumental variable. Data does not decide all questions; data informs the narrative rationalization — the theory of the case built around the evidence.</span></div><div style="text-align: justify;"><span style="font-family: inherit;"><br /></span></div><div style="text-align: justify;"><span style="font-family: inherit;">A lot of the usefulness of looking at data in e.g. natural experiments is where they show no effect — or no possibility of a detectable effect. This can help us cut out the theories that are wrong or useless. Unfortunately, this has not led to a widespread reconsideration of e.g. the supply and demand framework being used in labor markets on topics from the minimum wage to immigration. If economics was truly an empirical science, the economic theory taught in Econ 101 would be dropped from the curriculum.</span></div><div><span style="font-family: inherit; font-size: x-small;"><br /></span></div><div><span style="font-family: inherit; font-size: x-small;">...</span></div><div><span style="font-family: inherit; font-size: x-small;"><br /></span></div><div style="text-align: justify;"><span style="font-family: inherit; font-size: x-small;">[1] I have more of a "history is part of the humanities" view, that the lessons are essentially more evidentially grounded lessons of fictional stories, fables, myths and legends — you learn about what it is to be a human and exist in human society, but it's not a theory of how humans and institutions behave (that's political science or psychology). A major useful aspect of history in our modern world is to counter nationalist myth-making that is destructive to democracy.</span></div><div style="text-align: justify;"><span style="font-family: inherit; font-size: x-small;"><br /></span></div><div style="text-align: justify;"><span style="font-family: inherit; font-size: x-small;">A metaphor I think is useful to extend is that if "the past is a foreign country", then historians write our travel guides. A travel guide is not a "theory" of another country but an aid to understanding other humans.</span></div></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit; font-size: x-small;"><br /></span></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit; font-size: x-small;">[2] A less snarky version of this is that the field finally developed a critical mass of economists who both had the training to use computers and could access digital data to perform regressions in a few minutes instead of hours or days — and therefore could have a lot more practice with empirical data and regressions — such that obvious bullshit no longer made the cut. Credibility revolution!</span></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit; font-size: x-small;"><br /></span></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit; font-size: x-small;">[3] The authors do actually try to dismiss this as a confounding variable, but end up just pointing out flawed studies existed in the 70s and 80s without showing that those flawed results depended on mainframe computers (or even used them). But I will add that programming a mainframe computer (batch processes done overnight with lots of time spent verifying the code lest an exception causes you to lose yet another day and possibly funding dollars spent on another run) does not yet get to the understanding generated by immediate feedback from running a regression on a personal computer.</span></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit; font-size: x-small;"><br /></span></div><div style="background-color: white; color: #222222; text-align: justify;"><span style="font-family: inherit; font-size: x-small;">[4] <i>p</i>-hacking and publication bias are pretty good examples of the possibility of a <i>reverse </i>effect on credibility from increased data and the ability to process it. A lot of these so called empirical papers could not have their results reproduced in e.g. <a href="https://www.federalreserve.gov/econresdata/feds/2015/files/2015083pap.pdf">this study</a>.</span></div><div style="background-color: white; color: #222222; font-family: Arial, Helvetica, sans-serif; font-size: small; text-align: justify;"><br /></div>Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com0tag:blogger.com,1999:blog-6837159629100463303.post-89705460743342897692022-04-22T12:48:00.000-07:002022-04-22T12:48:02.859-07:00Outbrief on Dynamic Information Equilibrium as a COVID-19 model<div style="text-align: justify;">What with the US just sort of giving up on doing anything about COVID-19 and just letting it spread it's become just too depressing to continue to track the models day after day. On the radio yesterday I heard that King county (which includes Seattle area, where I live) isn't going to be focusing on tracking cases anymore — so I imagine the quality of the data is going to drop precipitously in the coming months unless there's a new more deadly variant. Therefore I'm going to stop working on them, and this is going to be an outbrief of the successes and failures of using the <a href="#">Dynamic Information Equilibrium Model (DIEM) for COVID-19</a>.</div><div style="text-align: justify;"><br /></div><div style="text-align: center;"><b><span style="font-size: large;">* * *</span></b></div><div style="text-align: center;"><br /></div><div style="text-align: justify;">We'll start with the big failure at the end — the faster than expected rate of decline (the dynamic equilibrium) in several places after the omicron surge. The examples here are New York and Texas. Red points are after the model parameters were frozen, gray points before.</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjo0cTXOl2RZXfXJomJODqUK2RmQVzv8Y_0-wKeQ7wWHVv9qOZ3jBBl132ZX6gQl9zMtyDgwEvRYhabpSiwi05i-BXO9Rjt0PLqFZHNqKE7DSJkTRLuSGIYpVyKbKoO6VO1XjgIrpqn5W3vRhr3nOA4BcxpNvpiMbZAjIUZJQotQFO_rflJ2dsI0dPbeg/s896/diem%20NY%2020220422.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="496" data-original-width="896" height="177" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjo0cTXOl2RZXfXJomJODqUK2RmQVzv8Y_0-wKeQ7wWHVv9qOZ3jBBl132ZX6gQl9zMtyDgwEvRYhabpSiwi05i-BXO9Rjt0PLqFZHNqKE7DSJkTRLuSGIYpVyKbKoO6VO1XjgIrpqn5W3vRhr3nOA4BcxpNvpiMbZAjIUZJQotQFO_rflJ2dsI0dPbeg/s320/diem%20NY%2020220422.png" width="320" /></a></div><br /><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiIO1z2B28GusDOzd4MYFY0Y4Qg3_0wK2SS20vlNXei7WHk2q-QqhwgixS2rXQlMHkBATaDGEuWVJEhnHlxzt5omfSwgbJVnIFSSQfzmpAbpLbiOAbFFubzSibCMseO6_GemIEk_zNPsfqIwnegRfQ1bdgXLPMRQhNANXHLV8tsKMlW3Zm-KRsSsnlTQQ/s896/diem%20TX%2020220422.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="504" data-original-width="896" height="180" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiIO1z2B28GusDOzd4MYFY0Y4Qg3_0wK2SS20vlNXei7WHk2q-QqhwgixS2rXQlMHkBATaDGEuWVJEhnHlxzt5omfSwgbJVnIFSSQfzmpAbpLbiOAbFFubzSibCMseO6_GemIEk_zNPsfqIwnegRfQ1bdgXLPMRQhNANXHLV8tsKMlW3Zm-KRsSsnlTQQ/s320/diem%20TX%2020220422.png" width="320" /></a></div><br /><div style="text-align: justify;">You can see the latest BA.2 surge in March and April of 2022. These of course result in over-predictions of the cumulative cases:</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgBm9EJIN8Ndq7LhtNZW32pQsoCvCEcQrVz77dxmM4rDvjLudXj2g-vYqSIlRKaq2JJ3o_Jlam524pACEQhXf7eLDGGvH2JF8q0Smk3_1sZedxNIA-AmeLITSazeiq-8nCYT04tG93nGFLglZsx2FKhb3ZSKGffaIxm8aJhVlK4vR9RQZeChelqzXNNvA/s896/diem%20NY%2020220422a.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="493" data-original-width="896" height="176" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgBm9EJIN8Ndq7LhtNZW32pQsoCvCEcQrVz77dxmM4rDvjLudXj2g-vYqSIlRKaq2JJ3o_Jlam524pACEQhXf7eLDGGvH2JF8q0Smk3_1sZedxNIA-AmeLITSazeiq-8nCYT04tG93nGFLglZsx2FKhb3ZSKGffaIxm8aJhVlK4vR9RQZeChelqzXNNvA/s320/diem%20NY%2020220422a.png" width="320" /></a></div><br /><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjsyWR5j9HILEL41VmRra8pQ7wjgpDSCB8rCTRMbMkR1VbMs1UBluPhWcCyuAl46zrIIrLWi8wGyTUxuF5COhqFEMNowh_ODtmYq6riy3EVQ9HEdWJYNByd6iIDN8U2qFDXNq2RriPY7q9BUc1vWdyJl4hfNk2Hjk-Dmzlw92TzmA2jF0mLo0pNCwc8RQ/s896/diem%20TX%2020220422a.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="489" data-original-width="896" height="175" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjsyWR5j9HILEL41VmRra8pQ7wjgpDSCB8rCTRMbMkR1VbMs1UBluPhWcCyuAl46zrIIrLWi8wGyTUxuF5COhqFEMNowh_ODtmYq6riy3EVQ9HEdWJYNByd6iIDN8U2qFDXNq2RriPY7q9BUc1vWdyJl4hfNk2Hjk-Dmzlw92TzmA2jF0mLo0pNCwc8RQ/s320/diem%20TX%2020220422a.png" width="320" /></a></div><br /><div><br /></div><div style="text-align: justify;">The (purportedly) constant rate of decline was one of the major components of the model which means there is something serious that the model is not helping us understand. There are several possibilities that don't mean the model is useless: 1) the sparse surge assumption is violated, 2) we're seeing a more detailed aspect of the model, 3) ubiquitous vaccination/exposure, 4) omicron is different, or 5) aggregating constituencies introduces more complex behavior.</div><div style="text-align: justify;"><br /></div><div style="text-align: justify;"><b><span style="font-size: x-large;">1. </span></b>The first possibility I discussed in an update to <a href="https://informationtransfereconomics.blogspot.com/2020/07/dynamic-information-equilibrium-and.html">the original blog post on using the DIEM for COVID-19</a>. I also discussed it in <a href="https://twitter.com/infotranecon/status/1361044544620351489">this Twitter thread</a>. The basic idea was that surges were happening too close together to get a good measurement of the dynamic equilibrium rate of decline. Sweden was the prototypical case in the summer of 2020 and it started to become visible in the US in early 2021. The faster rate of decline was like seeing the actual rate for the first time without a another surge happening. We can see a new estimate of the rate of decline from all the data makes NY work just fine:</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgWmqMVljiTTHJHLe2wwlPQWj7d0JJ_U0y20Cj3zuNMws7DvM9gZRVcbTGua15AEgoSFDDxyvWPmQT9DoapEBWGH5B_dMC5c4ajHcGr6vE-SUX5yk7JeOMNvdM4gdSPLvom_347uud-cHi4gPIDpAEfXbREgA-ozIAZp_Fcg72xvVcI8Mvf4IVJnDmovg/s890/diem%20NY%2020220422b.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="496" data-original-width="890" height="223" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgWmqMVljiTTHJHLe2wwlPQWj7d0JJ_U0y20Cj3zuNMws7DvM9gZRVcbTGua15AEgoSFDDxyvWPmQT9DoapEBWGH5B_dMC5c4ajHcGr6vE-SUX5yk7JeOMNvdM4gdSPLvom_347uud-cHi4gPIDpAEfXbREgA-ozIAZp_Fcg72xvVcI8Mvf4IVJnDmovg/w400-h223/diem%20NY%2020220422b.png" width="400" /></a></div><br /><div style="text-align: justify;">Early on, this can be a compelling rationale. However, the issue with this is that we can't just keep using that excuse — <i>ok, now we have a good estimate! No wait, now we do.</i> Additionally it didn't change in other countries (see 4) which had just as much sparseness (or rather lack thereof). </div><div style="text-align: justify;"><br /></div><div style="text-align: justify;"><b><span style="font-size: x-large;">2. </span></b>The constant rate of decline is actually an approximation in the DIEM. <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3094757">In my original paper</a>, the dynamic equilibrium is related to the information transfer index <i>k</i> which can drift slowly over time as the virus spreads:</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgN5id3i-4TVmr1c2TfoCYsvVuSto-a5FId7XVhWQl3dGtI7Ja6rGcfZoezmH7ZUon-6vwLLoM8UQr-SGod5uviozg5HRTvBMRtBAGdvpKXUkU_BvNc3jEQi1_HdXqeD1nHQszhy-2bacJ9JJG8obW4wwQcCrF_6WlZ-Ej4FJ-NCSUC7K6XINnbob09Hg/s800/grave.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="180" data-original-width="800" height="90" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgN5id3i-4TVmr1c2TfoCYsvVuSto-a5FId7XVhWQl3dGtI7Ja6rGcfZoezmH7ZUon-6vwLLoM8UQr-SGod5uviozg5HRTvBMRtBAGdvpKXUkU_BvNc3jEQi1_HdXqeD1nHQszhy-2bacJ9JJG8obW4wwQcCrF_6WlZ-Ej4FJ-NCSUC7K6XINnbob09Hg/w400-h90/grave.png" width="400" /></a></div><br /><div style="text-align: justify;">Again, the question comes up as to why it changed in US states but not in the EU (see 4) — so this also isn't very compelling.</div><div style="text-align: justify;"><br /></div><div style="text-align: justify;"><b><span style="font-size: large;">3. </span></b>Ubiquitous vaccination or exposure is how outbreaks are limited in epidemiological models such as the <a href="https://en.wikipedia.org/wiki/Compartmental_models_in_epidemiology#The_SIR_model">SIR models</a> where the S stands for susceptible — i.e. the unvaccinated or those who never had the virus. Again, while the US pretty much let the virus spread unchecked such that it's likely that almost everyone got it providing some protection from getting it again, it doesn't explain why we don't see the faster rate of decline from omicron in e.g. Europe or even in smaller constituencies of the US e.g. King county, WA (see 4).</div><div style="text-align: justify;"><br /></div><div style="text-align: justify;"><b><span style="font-size: x-large;">4. </span></b>Moving on to the fourth possibility — omicron is different — we can probably discount it to some degree because in several places, the constant dynamic equilibrium prediction worked just fine. For example the EU:</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjAn6CK-FWwwV_TuxJRuI1hZrLWXCtcE5CZH3nR5sujU7u6IjVtRscnGD0Qo94UXMhhXV7oCGjb4MokvRGIcJ3LIunm7u6hbhwOGxY6vB_X2QbBcxj5lG0cPSRAftI8t-YGJ6MyPsNYcJ9HAlU1bAuN3N1SbYvr1wANHM3D-gfCrxi3osoTWL9IXvsq9A/s956/diem%20EU%2020220422a.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="473" data-original-width="956" height="198" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjAn6CK-FWwwV_TuxJRuI1hZrLWXCtcE5CZH3nR5sujU7u6IjVtRscnGD0Qo94UXMhhXV7oCGjb4MokvRGIcJ3LIunm7u6hbhwOGxY6vB_X2QbBcxj5lG0cPSRAftI8t-YGJ6MyPsNYcJ9HAlU1bAuN3N1SbYvr1wANHM3D-gfCrxi3osoTWL9IXvsq9A/w400-h198/diem%20EU%2020220422a.png" width="400" /></a></div><div><br /></div><div style="text-align: justify;">Although the surge size was underestimated, we can see not only does the omicron surge return to the same rate of decline but so does the BA.2 variant surge (indicated by diagonal lines in the graph). We also see it in the EU member France:</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgC1OMpIk90HP4mA1tA1O8C3UE6_QoFz--RQzsfWZrPt7aWx2MsRXh8koLcJRtK3nHOUaARG75YCz52DufkNrKxIu5CbjnkLwrPZAI9wl_xnbbMTEMXZ6YslnB5V5YTQSBkl1oRUbuJ7gQsg-XKvpv08Wc_Od5YcCjBVDgzxQq5W2c6qWtOcTxws1-cEg/s896/diem%20france%2020220422a.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="504" data-original-width="896" height="180" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgC1OMpIk90HP4mA1tA1O8C3UE6_QoFz--RQzsfWZrPt7aWx2MsRXh8koLcJRtK3nHOUaARG75YCz52DufkNrKxIu5CbjnkLwrPZAI9wl_xnbbMTEMXZ6YslnB5V5YTQSBkl1oRUbuJ7gQsg-XKvpv08Wc_Od5YcCjBVDgzxQq5W2c6qWtOcTxws1-cEg/s320/diem%20france%2020220422a.png" width="320" /></a></div><br /><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgz_77QjIpvuKh47_BIs1I_6RrSEy_PoniiDSoQQDkaUoAZkO63s8hBm273E8Lmd7M4SaQwHqR7FtyZ-F6e_fLyA7fTQGaPIngvMricMLWMWwUwsVoJQEDBEjpX-mT443CEXFNfYDcrHVYniVcpdeyscCt4ap00d2UOErFMXkxdZg7uJCssQhBGvdI6sw/s896/diem%20france%2020220422b.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="479" data-original-width="896" height="171" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgz_77QjIpvuKh47_BIs1I_6RrSEy_PoniiDSoQQDkaUoAZkO63s8hBm273E8Lmd7M4SaQwHqR7FtyZ-F6e_fLyA7fTQGaPIngvMricMLWMWwUwsVoJQEDBEjpX-mT443CEXFNfYDcrHVYniVcpdeyscCt4ap00d2UOErFMXkxdZg7uJCssQhBGvdI6sw/s320/diem%20france%2020220422b.png" width="320" /></a></div><br /><div style="text-align: justify;">While the decline in the omicron surge was interrupted by the BA.2 variant surge, we can see the that the model (which cannot predict new surges, only detect them) was doing fine until that point. So saying "omicron was different" is not a good answer — it would be ad hoc to say it is different for one place and not another. In fact, it wasn't even different in parts of the US — King County in Washington State (which contains Seattle) also appeared to follow the predicted rate of decline until the BA.2 surge:</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh0ZyvrvWRhkHgEJtLf9r6kXYx5DlIO2TiJUwny5AQvEO9_XtUDC6dGZDZtvKd81CmFe3aXihfjQSE3KW2IQszqo8sai89fsjkaaTP0_4bN-iWjWRTpfvzf4v56ujl8ndlAzFk-dttevt8Bdrqp13tLREpxM229HiwqkHSRi-ZplgU3TRYYU2bgGj8q2Q/s896/diem%20WA%20king%2020220422.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="506" data-original-width="896" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh0ZyvrvWRhkHgEJtLf9r6kXYx5DlIO2TiJUwny5AQvEO9_XtUDC6dGZDZtvKd81CmFe3aXihfjQSE3KW2IQszqo8sai89fsjkaaTP0_4bN-iWjWRTpfvzf4v56ujl8ndlAzFk-dttevt8Bdrqp13tLREpxM229HiwqkHSRi-ZplgU3TRYYU2bgGj8q2Q/w400-h226/diem%20WA%20king%2020220422.png" width="400" /></a></div><div><br /></div>So that's another excuse we can't get away with in any scientific sense.<div><br /></div><div style="text-align: justify;"><b><span style="font-size: x-large;">5. </span></b>The last possibility I'm listing is one that <a href="https://twitter.com/infotranecon/status/1358637200091410433">I came up with as an alternative</a> to 1) back in early 2021: we're seeing the aggregate of several surges which can have different behavior than a single surge. Part of this is borne out in the data — the surges for smaller constituencies (cities, counties) generally have faster rates of recovery than larger ones (states, countries). The dynamic equilibrium we see at the aggregate level is a combination of these faster surges. In this graph the slow rate is made up of several smaller surges with a faster rate (exponential rates shown with dashed lines) combined with a network structure i.e. some power law in the size of the surges due to starting in big cities and diffusing to smaller ones.</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgbKal7IutN30NBqcLgk4WoTSMfg3imUiFLxBE_9r0eptYEot24TkkKOiQfNmipE92zQ1cnTXNcti3oDUzwmoPflvF_8ymx9AO_Knr302DompwbFZgtEIeYwz8b-l6cZzBq1Xf9QOmKSDC5WGEtLf4HFwAGOO4to1Qz5nuqS-kyiIpKvpl57fyXj_p7lg/s792/EtrZx53UYAA4gl4.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="422" data-original-width="792" height="214" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgbKal7IutN30NBqcLgk4WoTSMfg3imUiFLxBE_9r0eptYEot24TkkKOiQfNmipE92zQ1cnTXNcti3oDUzwmoPflvF_8ymx9AO_Knr302DompwbFZgtEIeYwz8b-l6cZzBq1Xf9QOmKSDC5WGEtLf4HFwAGOO4to1Qz5nuqS-kyiIpKvpl57fyXj_p7lg/w400-h214/EtrZx53UYAA4gl4.png" width="400" /></a></div><div style="text-align: justify;">We see the faster rates at the lower level and a slower rate at the aggregate level. If there is some temporal alignment of those local surges — a holiday, a big event, or (in the omicron case) introduction of a faster spreading variant of the virus — it can align some of those "sub-surges" and briefly show us the intrinsic faster rate at the lower level in the aggregate data:</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjkl7msbck2HqZVYKv45P3vkvap85Jg0rrtZgu0sjouk2gXZQV4wVZzSmoIiQd4py4NN89ZQUadb7BJ4ieHrJGd-tpTSM35ODihbbmgsRLZb8Buqzo2Q1cwqhOBueyxmJJovFuzYssitpDjgXQQqiJNsjQWIUXMjUuPAQEocBcaBn0Yr59ihy0J6gOq-g/s792/EtrfGWDVkAAMvQe.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="422" data-original-width="792" height="214" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjkl7msbck2HqZVYKv45P3vkvap85Jg0rrtZgu0sjouk2gXZQV4wVZzSmoIiQd4py4NN89ZQUadb7BJ4ieHrJGd-tpTSM35ODihbbmgsRLZb8Buqzo2Q1cwqhOBueyxmJJovFuzYssitpDjgXQQqiJNsjQWIUXMjUuPAQEocBcaBn0Yr59ihy0J6gOq-g/w400-h214/EtrfGWDVkAAMvQe.png" width="400" /></a></div><br /><div style="text-align: justify;">This is probably the best explanation — the US is a lot more spread out and rural than the EU, and so has a lot more subcomponents from a modeling standpoint. This does require more effort to model than just information theory and <i>virus + healthy person → sick person</i>, which means that at best the DIEM is a leading order approximation. This is more satisfying in the sense that <i>the DIEM is supposed to be a leading order approximation</i> — epidemiology and economics are complex subjects and we should be surprised that the DIEM worked as well as it has for COVID-19 and the unemployment rate.</div><div style="text-align: justify;"><br /></div><div style="text-align: center;"><b><span style="font-size: large;">* * *</span></b></div><div><br /></div><div>There was one model failure that was just weird: the UK.</div><div><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiy-bNwpSPTrqsiXBOQUNnxJxcqIYjs8fxtosuSNN9UVq1DmsNy1Qn6HxE5FFlUhExdDqqFg7GsEWHk2htpR_W2wuaJWAppHq1zFc-jNtOYmqms1Gq_ozCB3q4Y7eg7G7Jwm36QNd_Yib1Xu-PPDtR_uDenud-00jnt3qPSPhSsNoj2S9-XKNb4L1x2JA/s890/diem%20uk%2020220422b.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="508" data-original-width="890" height="229" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiy-bNwpSPTrqsiXBOQUNnxJxcqIYjs8fxtosuSNN9UVq1DmsNy1Qn6HxE5FFlUhExdDqqFg7GsEWHk2htpR_W2wuaJWAppHq1zFc-jNtOYmqms1Gq_ozCB3q4Y7eg7G7Jwm36QNd_Yib1Xu-PPDtR_uDenud-00jnt3qPSPhSsNoj2S9-XKNb4L1x2JA/w400-h229/diem%20uk%2020220422b.png" width="400" /></a></div><div style="text-align: justify;">In July of 2021 the rate of decline was so fast but ended so quickly that I put in by hand the one and only negative shock — then immediately after that, the case counts just went sideways. The more recent data has given us back the surge structure apparent in the rest of the world where the case counts are high enough, but the second half of 2021 in the UK is just inexplicable in the model with any kind of confidence.</div><div style="text-align: justify;"><br /></div><div style="text-align: center;"><span style="font-size: large;"><b>* * *</b></span></div><div style="text-align: center;"><br /></div><div style="text-align: justify;">So what is the model good for? Well, first off it's incredibly simple — surges followed by a constant (exponential) rate of decline. And that constant rate of decline seems to be a reasonable first order approximation; it's a starting point. We can see it held ("fixed <i>α</i>" on the graph) in Florida from mid-2021 until recently with the faster rate of decline noted above:</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgfB2y2Od0sX6ehkMx5dPdYJJSEPl1f7F0VO2PE3CBbNpamlJJ46Sz9irhiIk-UDrXMdgxZlnwhlskbxc4rBT8Q3wUsKUJUOezuWZsYV1USerCU785Rsa7n5w_HRTM2nv6QF3WWNsp9QYyyFMbs1YdtKEe8r4w5RxmDifxD4MUqOteShoyY8p4G0zmhuQ/s896/diem%20florida%2020220422c.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="493" data-original-width="896" height="220" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgfB2y2Od0sX6ehkMx5dPdYJJSEPl1f7F0VO2PE3CBbNpamlJJ46Sz9irhiIk-UDrXMdgxZlnwhlskbxc4rBT8Q3wUsKUJUOezuWZsYV1USerCU785Rsa7n5w_HRTM2nv6QF3WWNsp9QYyyFMbs1YdtKEe8r4w5RxmDifxD4MUqOteShoyY8p4G0zmhuQ/w400-h220/diem%20florida%2020220422c.png" width="400" /></a></div><br /><div>It was also good at detecting surges getting started. The <a href="https://informationtransfereconomics.blogspot.com/2020/07/dynamic-information-equilibrium-and.html">original example</a> was Florida in May of 2020:</div><div><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhrGCaHw_5mETuqNEWm5I-QWsRrCpJ2BJ4Zfm5zM4oi_-GUflB86tscZhHgucg6O0FxRt84zK-YCekl6KiQ4FBQvyeM0-ScoM6l1NEvvspOImNd3buVTi2uQov_gf5194v84I1VX5Unxos_olNTN3XcUmj2ShedMh7QsvAG7KA1JgQe61o0ZJHNEYbI_A/s792/EYeoMkOUMAA40Qm.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="492" data-original-width="792" height="249" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhrGCaHw_5mETuqNEWm5I-QWsRrCpJ2BJ4Zfm5zM4oi_-GUflB86tscZhHgucg6O0FxRt84zK-YCekl6KiQ4FBQvyeM0-ScoM6l1NEvvspOImNd3buVTi2uQov_gf5194v84I1VX5Unxos_olNTN3XcUmj2ShedMh7QsvAG7KA1JgQe61o0ZJHNEYbI_A/w400-h249/EYeoMkOUMAA40Qm.png" width="400" /></a></div><br /><div><br /></div><div>And again in June of 2021:<br /><div><br /><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhkLnCFH-56__GbZv7-8PeLt79cB0j9zfVoH0JxvwS-3uUfPI6hUujFZjjAnhh7ynFrxbY6dmXM84dT2aZ3Qw5GYmtag-LxGCWUGkeENhL85jQ6Y5AO3SROUwpo15iWmthU30yYkrZm8CcDCgjcDPEtvk0iL0scWdugenOGYr4c2NY0XRzfRLtVsouXAw/s896/E5Jcx8qVgAMhd6t.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="508" data-original-width="896" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhkLnCFH-56__GbZv7-8PeLt79cB0j9zfVoH0JxvwS-3uUfPI6hUujFZjjAnhh7ynFrxbY6dmXM84dT2aZ3Qw5GYmtag-LxGCWUGkeENhL85jQ6Y5AO3SROUwpo15iWmthU30yYkrZm8CcDCgjcDPEtvk0iL0scWdugenOGYr4c2NY0XRzfRLtVsouXAw/w400-h226/E5Jcx8qVgAMhd6t.png" width="400" /></a></div><br /><div style="text-align: justify;">Note that despite getting the slope wrong, you can still see the new surge getting started in late February as a change from the straight line decline (on a log graph) after the omicron surge in this example from New York:</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj9pJzfd6p-ysWbZEf5tRk8NMu1RxAx9yk3BLPin0MZfYfTUgID9VKE1B1aiy330joE1JrsYyNHSwsyDJdSe4MXBCzww0eNNPcfbGF70JHHljar2LREMYHvkokuPsmnVQVjdpDimR2Pv3lc-M8KeGw_jHRmPrfZ2tZNlGUM2e71AZdA-3ebikd3hsweZw/s896/diem%20NY%2020220422.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="496" data-original-width="896" height="221" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj9pJzfd6p-ysWbZEf5tRk8NMu1RxAx9yk3BLPin0MZfYfTUgID9VKE1B1aiy330joE1JrsYyNHSwsyDJdSe4MXBCzww0eNNPcfbGF70JHHljar2LREMYHvkokuPsmnVQVjdpDimR2Pv3lc-M8KeGw_jHRmPrfZ2tZNlGUM2e71AZdA-3ebikd3hsweZw/w400-h221/diem%20NY%2020220422.png" width="400" /></a></div><br /><div style="text-align: justify;">Looking at the log graph for a deviation from exponential (i.e. straight line) decline as a sign of a new surge became more common (at least on Twitter). Those of us monitoring our log plots saw surges getting started while the media seemed to only react when it sees an actual rise in cases — typically 2-3 weeks later. It's the closest I've felt to having an actual crystal ball [1].</div><div style="text-align: justify;"><br /></div><div style="text-align: justify;">So in that sense, the DIEM has been useful in understanding the COVID-19 pandemic. It's a simple first order approximation that can help detect when surges are getting started.</div><div><br /></div><div>...</div><div><br /></div><div><b>Footnotes:</b></div><div><br /></div><div><div style="text-align: justify;"><span style="font-size: small;">[1] Side note: because of the typical duration of surges (3-4 weeks), the point when the media became focused on a surge tended to be the start of the inflection point signaling the beginning of the surge recovery.</span></div><div><div style="text-align: justify;"><br /></div><div><br /></div><p></p></div></div></div></div>Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com0tag:blogger.com,1999:blog-6837159629100463303.post-64190336865725446782021-11-07T15:40:00.001-08:002021-11-12T11:03:51.459-08:00Comparing the DIEM and the FRB/US model<p style="text-align: justify;">Per a question in my Twitter DMs, I thought I'd do a comparison between <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3094757">the Dynamic Information Equilibrium Model (DIEM)</a> and the FRB/US model of the unemployment rate. I've not done this comparison that I can recall. I've previously looked at point forecast comparisons between the different Fed models (e.g. <a href="https://informationtransfereconomics.blogspot.com/2018/10/comparing-to-fed-forecasts-from-2014.html">here</a> for 2014). <a href="https://informationtransfereconomics.blogspot.com/2018/09/forecasting-great-recession.html">In another post</a>, I took the DIEM model through the Great Recession following along with the Fed <i>Greenbook </i>forecasts. <a href="https://informationtransfereconomics.blogspot.com/2014/09/jason-versus-fed.html">And in an even older post</a> (prior to the development of the DIEM), I looked at inflation forecasts from the FRB/US model.</p><p style="text-align: justify;">The latest and most relevant Fed Tealbook forecast from the FRB/US model that seems to be available is <a href="https://www.federalreserve.gov/monetarypolicy/files/FOMC20151216tealbooka20151209.pdf">here</a> [pdf] — it's from December 2015. I've excerpted the unemployment rate forecast (along with several counterfactuals) in the following graphic:</p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/a/AVvXsEiKJ7YkchETpxxXkUerfepPSFzSAFch7gb-CXq_jRen0YKoPAhy_LucenUnoktlLmqqlrEt6qgcGKPAsonJsG8v_nGI4q6XlPZQkguolN99ZjQ5H5FKV9YSsUzaqiuQVE3uibLp41iZFMVcG5UF8Mk0WMIsdE1qg2aQC-G56erH7I83wQ3Waxm50ozuMQ=s1136" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="783" data-original-width="1136" height="276" src="https://blogger.googleusercontent.com/img/a/AVvXsEiKJ7YkchETpxxXkUerfepPSFzSAFch7gb-CXq_jRen0YKoPAhy_LucenUnoktlLmqqlrEt6qgcGKPAsonJsG8v_nGI4q6XlPZQkguolN99ZjQ5H5FKV9YSsUzaqiuQVE3uibLp41iZFMVcG5UF8Mk0WMIsdE1qg2aQC-G56erH7I83wQ3Waxm50ozuMQ=w400-h276" width="400" /></a></div><br /><p style="text-align: justify;">Now something that should be pointed out is that the FRB/US model does a lot more than the unemployment rate — GDP, interest rates, inflation, etc. While there are separate models in the information equilibrium framework covering a lot of those measures, the combination of the empirically valid relationships into a single model is still incomplete (see <a href="https://informationtransfereconomics.blogspot.com/2019/03/the-beginnings-of-information.html">here</a>). However, in the DIEM the unemployment rate is essentially unaffected by other variables in equilibrium (declining at the equilibrium rate of <i>d/dt</i> log <i>u </i>≃ −0.09/y [0]). Therefore, whatever the other variables in an eventual information equilibrium macro model, comparing the unemployment rate forecasts alone should be valid — especially since we are going to look at the period 2016 to 2020 (prior to the COVID shock).</p><p style="text-align: justify;">Setting the forecast date to be the end of Q3 of 2015 just prior to the meeting, we can see the central forecast for the DIEM does worse at first but is better over the longer run (click to enlarge):</p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/a/AVvXsEheVTiZINvqE0dnTNMWFuF67Jq6hG0hY6n7VXCZsNCCVr_MzL6Vc2_BHdfmwpiPKzZxmf1fmzmVBPprM6Uk7Tr0CIUdBYQ2sCZH608vfXNRTzh58Wt0PW79A0GdHneBtdCCkJ_ISyDybZLLG5qu2r0CRhJFm9JIuvlUoG5GmmkuquLrtpUpHpT7yIbKoA=s690" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="587" data-original-width="690" height="340" src="https://blogger.googleusercontent.com/img/a/AVvXsEheVTiZINvqE0dnTNMWFuF67Jq6hG0hY6n7VXCZsNCCVr_MzL6Vc2_BHdfmwpiPKzZxmf1fmzmVBPprM6Uk7Tr0CIUdBYQ2sCZH608vfXNRTzh58Wt0PW79A0GdHneBtdCCkJ_ISyDybZLLG5qu2r0CRhJFm9JIuvlUoG5GmmkuquLrtpUpHpT7yIbKoA=w400-h340" width="400" /></a></div><br /><p style="text-align: justify;">The big difference lies not just in the long run but in the error bands, with the DIEM being much narrower. These are apples-to-apples error bands as we can see the baseline FRB/US forecast in the graph at the top of the post is conditional on a lack of a recessionary shock (those are the red and purple lines above) [1].</p><p style="text-align: justify;">Additional differences come in what we <b><i>don't </i></b>see. Looking at <a href="https://www.federalreserve.gov/econres/notes/feds-notes/overview-of-the-changes-to-the-frb-us-model-2018-20181207.htm">the latest 2018 update to the FRB/US model</a>, we get information about the impulse responses to a 100 bp increase in the Fed funds rate. Now the Fed usually doesn't do 100 bp changes (typically 25 bp), so this is a large shock. But it also creates a forecast path that looks nothing like anything we have seen in the historical data [3]:</p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/a/AVvXsEgA0-HshYcg-thA0luiWAhrtjHmSV-s8GDMYcCRdxyCNdRO8oLnqN_a1p1ilgXAYbCbRye65wCwBeKqNhY4YgYuzJgpS_ZsLdUQNYLOa_lLH65R4fkmBNvu_mqHTh5wGjzGbw6N3GpaCKDxxD_PMuiwbYuaUrmzniIHuGIYOe4yrAPgnhTl0tFee_YC6A=s690" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="582" data-original-width="690" height="338" src="https://blogger.googleusercontent.com/img/a/AVvXsEgA0-HshYcg-thA0luiWAhrtjHmSV-s8GDMYcCRdxyCNdRO8oLnqN_a1p1ilgXAYbCbRye65wCwBeKqNhY4YgYuzJgpS_ZsLdUQNYLOa_lLH65R4fkmBNvu_mqHTh5wGjzGbw6N3GpaCKDxxD_PMuiwbYuaUrmzniIHuGIYOe4yrAPgnhTl0tFee_YC6A=w400-h338" width="400" /></a></div>We really don't see increases in the unemployment rate that look like this:<div><br /><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/a/AVvXsEiiB-v62tredTLw7lBcHaycOrDwXLGRKG2bbbU-0wW-ZQOcRbS_gyC8mY9A61z3Tdmx6UlXBmWTdSlu7hHs6O_ja8OGXXePUK0M9em9cCoDkOv9O3sYqawHxeNKuyz22zPeFPJH-dHOtqvBTJ3oxNGHmX5KbYlnw5rOgMfIf0-1N7yJNtlSwXBoz7kaFQ=s576" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="575" data-original-width="576" height="319" src="https://blogger.googleusercontent.com/img/a/AVvXsEiiB-v62tredTLw7lBcHaycOrDwXLGRKG2bbbU-0wW-ZQOcRbS_gyC8mY9A61z3Tdmx6UlXBmWTdSlu7hHs6O_ja8OGXXePUK0M9em9cCoDkOv9O3sYqawHxeNKuyz22zPeFPJH-dHOtqvBTJ3oxNGHmX5KbYlnw5rOgMfIf0-1N7yJNtlSwXBoz7kaFQ=s320" width="320" /></a></div><br /><p style="text-align: justify;">And while yes this 0.7 pp increase in the unemployment rate is following a 100 bp increase in Fed funds rate when we usually see only 25 bp increases [4], this would, per the <a href="https://en.wikipedia.org/wiki/Sahm_Rule">Sahm Rule</a>, indicate a recession — and therefore almost certainly further increases beyond the initial 0.7 pp.</p><p style="text-align: justify;">Now it is true we don't see the unemployment rate falling continuously, asymptotically approaching zero, as would be indicated in the DIEM. However, we also haven't had a period of 40 years uninterrupted by a recession required for it to happen.</p><p style="text-align: justify;">The FRB/US model has hundreds of parameters for hundreds of variables — however, it doesn't even qualitatively capture the behavior of the empirical data for the unemployment rate. This is likely due to what Noah Smith called "<a href="https://noahpinionblog.blogspot.com/2015/08/the-macromicro-validity-tradeoff.html">big unchallenged assumptions</a>" — in order to get an unemployment rate path to look more like the data, trade-offs would have to be made on other variables that make them look far worse. You could probably come up with something that looks a lot like the FRB/US model with a giant system of linear equations with several lags. Simultaneously fitting all of variables you chose to model can create results that look not entirely implausible when you look at all the model outputs as a group, but individually do not qualitatively describe what we see. The reason? You chose (and probably constrained) several variables to have relationships that are empirically invalid — therefore any fit is going to have variables that come out looking wrong.</p><p style="text-align: justify;">I imagine the impact of an increase in the Fed funds rate on the unemployment rate is one of those chosen relationships. Looking through the historical data, there is no particular evidence that raising rates <i>causes </i>unemployment to rise nor vice versa. In fact, it seems rising unemployment causes the Fed to start lowering rates [5]! But forcing such a relationship, after estimating all the model parameters, likely contributes to not just forecasting error, but making the unemployment rate do strange things.</p><p style="text-align: justify;">...</p><p><b>Footnotes</b></p><p style="text-align: justify;"><span style="font-size: x-small;">[0] See also Hall and Kudlyak (2020) which arrives at the same rate of decline.</span></p><p style="text-align: justify;"><span style="font-size: x-small;">[1] Here's what a recession shock of the same onset would look like in the DIEM (click to enlarge):</span></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/a/AVvXsEiNSr30Old0dLtafbsFtwGhqffHZ29dbkL6NgUJpA9cr2GYfPgEWbRH_mbQLIguCf3pVKGSEYICSC7LoYD-LMbZxne03TE4JDfdoiBXY5dISWTV4i-vh1mJMNTPaW-5wU88I24PcMdbCVSUJa2cFxr0ALohLwSIybieMeq0g_8NLgWfIuUVlGosnwudsg=s703" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="587" data-original-width="703" height="167" src="https://blogger.googleusercontent.com/img/a/AVvXsEiNSr30Old0dLtafbsFtwGhqffHZ29dbkL6NgUJpA9cr2GYfPgEWbRH_mbQLIguCf3pVKGSEYICSC7LoYD-LMbZxne03TE4JDfdoiBXY5dISWTV4i-vh1mJMNTPaW-5wU88I24PcMdbCVSUJa2cFxr0ALohLwSIybieMeq0g_8NLgWfIuUVlGosnwudsg=w200-h167" width="200" /></a></div><div style="text-align: justify;"><span style="font-size: x-small;">I should add there is a bit of nuance here as this is under the assumption of an historical level of temporary layoffs in a recession. The COVID recession had the largest surge of temporary layoffs in the entire time series data set — and that <a href="https://informationtransfereconomics.blogspot.com/2021/02/ongoing-evolution-of-time-series-after.html">created different dynamics</a> [2] (click to enlarge):</span></div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/a/AVvXsEji8rcjsceiV6sbi7ydDaivgF1SNEUJVhSS-mJs7lQHIShfN3Yab7mdLC-hw3lqWfnS0RapdBh-AkTsilSrIkdOJ4nCvJwnKKyj5WbmRZqmJeErT_0A6HxwUNeTLEm8DY-oP8MjGpPz-iGQD6F77KgaoVRLC5YJ5axGQcUMtZ1NmyqtoZ9_4t_zdk6mYw=s792" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="460" data-original-width="792" height="117" src="https://blogger.googleusercontent.com/img/a/AVvXsEji8rcjsceiV6sbi7ydDaivgF1SNEUJVhSS-mJs7lQHIShfN3Yab7mdLC-hw3lqWfnS0RapdBh-AkTsilSrIkdOJ4nCvJwnKKyj5WbmRZqmJeErT_0A6HxwUNeTLEm8DY-oP8MjGpPz-iGQD6F77KgaoVRLC5YJ5axGQcUMtZ1NmyqtoZ9_4t_zdk6mYw=w200-h117" width="200" /></a></div><br /><div><div style="text-align: justify;"><span style="font-size: x-small;">[2] The latest data appears to be showing <a href="https://twitter.com/infotranecon/status/1456649235466653702">a positive shock due to the stimulus</a>.</span></div><p style="text-align: justify;"><span style="font-size: x-small;">[3] I based the counterfactual "no rate increase" on the typical flattening we see in other FRB/US forecasts. It's really not a big difference to just use the last 2020 data point and say the future is constant as the counterfactual (click to enlarge):</span></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/a/AVvXsEhCgREYnsORgjd_Mm0PfRnAH_0iroTyhZEIBLvTDhCiIGe6Z-xta0sBJqvRCeIDn8F4d3D1rcWZrMcU7Gz0gr8d5yIGZO6xduafFPlk5Nt7M2uiVC1EGs2i9XapKzO0RW6D4PpiKgPyYlpKTA8MN7KfQKS3ZvdFkonuSaMb_VZi8gjzZxadXK0SkBM-Dg=s749" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="582" data-original-width="749" height="156" src="https://blogger.googleusercontent.com/img/a/AVvXsEhCgREYnsORgjd_Mm0PfRnAH_0iroTyhZEIBLvTDhCiIGe6Z-xta0sBJqvRCeIDn8F4d3D1rcWZrMcU7Gz0gr8d5yIGZO6xduafFPlk5Nt7M2uiVC1EGs2i9XapKzO0RW6D4PpiKgPyYlpKTA8MN7KfQKS3ZvdFkonuSaMb_VZi8gjzZxadXK0SkBM-Dg=w200-h156" width="200" /></a></div><div style="text-align: justify;"><span style="font-size: x-small;">[4] Here's an estimate from a 25 bp increase in the Fed funds rate where I just took the shock and multiplied it by 0.25 (click to enlarge):</span></div></div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/a/AVvXsEiQg2yITop4nXWLm7ZcjfzZCOSI8zy_IOTU0HCGxrNWdFpxwiWSdrslKMaRzO5Ae6iR46G27mWdvybCc6RCDzuoK2pvn16cDUe1h5T-sIOftiurAHNvP3S7aOWD7dUJWMh-IxsP4VhS8d2wtCEEljrVa6D7pmN_HryBNlvx6T-y9037G4aIDfgyoZfXQw=s670" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="582" data-original-width="670" height="174" src="https://blogger.googleusercontent.com/img/a/AVvXsEiQg2yITop4nXWLm7ZcjfzZCOSI8zy_IOTU0HCGxrNWdFpxwiWSdrslKMaRzO5Ae6iR46G27mWdvybCc6RCDzuoK2pvn16cDUe1h5T-sIOftiurAHNvP3S7aOWD7dUJWMh-IxsP4VhS8d2wtCEEljrVa6D7pmN_HryBNlvx6T-y9037G4aIDfgyoZfXQw=w200-h174" width="200" /></a></div><br /><div><span style="font-size: x-small;">[5] More <a href="https://informationtransfereconomics.blogspot.com/2019/04/interest-rates-and-inflation.html">here</a>.<br /></span><p><br /></p></div></div>Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com0tag:blogger.com,1999:blog-6837159629100463303.post-4042874246296395002021-07-31T14:59:00.003-07:002021-11-19T12:31:22.474-08:00The recession of 2027<p> From my "<a href="https://informationtransfereconomics.blogspot.com/2018/10/limits-to-wage-growth.html">Limits to wage growth</a>" post from roughly three years ago:</p><p></p><blockquote><p style="text-align: justify;"><i>If we project wage growth and NGDP growth using the models, we find that they cross-over in the 2019-2020 time frame. Actually, the exact cross-over is 2019.8 (October 2019) which not only eerily puts it in October (when a lot of market crashes happen in the US) but also is close to the 2019.7 value estimated for yield curve inversion based on extrapolating the path of interest rates. ...</i></p><p style="text-align: justify;"><i>This does not mean the limits to wage growth hypothesis is correct — to test that hypothesis, we'll have to see the path of wage growth and NGDP growth through the next recession. This hypothesis predicts a recession in the next couple years (roughly 2020).</i></p></blockquote><p></p><p style="text-align: justify;">We did get an NBER declared recession in 2020, but since I have ethical standards (<a href="https://informationtransfereconomics.blogspot.com/2018/10/keen.html">unlike some people</a>) I will not claim this as a successful model prediction as the causal factor is pretty obviously COVID-19. So when is the next recession going to happen? 2027.</p><p style="text-align: justify;">Let me back up a bit and review the 'limits to wage growth' hypothesis. It says that when nominal wage growth reaches nominal GDP (NGDP) growth, a recession follows pretty quickly after. There is a Marxist view that when wage growth starts to eat into firms' profits, investment declines, which triggers a recession. That's a plausible mechanism! However, I will be agnostic about the underlying cause and treat it purely as an empirical observation. Here's an updated version of the graph from the original post (click to enlarge). We see that recessions (beige shaded regions) occur roughly where wage growth (green) approaches NGDP growth (blue) — indicated by the vertical lines and arrows.</p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiNBrIill1xEkRMn-g8a4T9tlCQvCraEVuVvHeevGfJjB33H_wsr5rVZRmZXcsAJ88PktmarVL1mTaKgoSZNKt99S0pgFB7NGVrCldWTux-YWTawoUIPFopMkcYhrpxNBMlnupZT_Pcy15j/s965/limits+to+wage+growth+1.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="420" data-original-width="965" height="174" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiNBrIill1xEkRMn-g8a4T9tlCQvCraEVuVvHeevGfJjB33H_wsr5rVZRmZXcsAJ88PktmarVL1mTaKgoSZNKt99S0pgFB7NGVrCldWTux-YWTawoUIPFopMkcYhrpxNBMlnupZT_Pcy15j/w400-h174/limits+to+wage+growth+1.png" width="400" /></a></div><div><br /></div><div style="text-align: justify;">Overall, the trend of NGDP growth gives a pretty good guide to where these recessions occur with only the dot-com bubble extending the lifetime of the 90s growth in wages. In the previous graph, I also added some heuristic paths prior to the Atlanta Fed time series as a kind of plausibility argument of how this would have worked in the 60s, 70s, and 80s. If we zoom in on the recent data (click to enlarge) we can see how the COVID recession decreased wage growth:</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhqjDl1Du-ZijhcXYNX3XRSvdZIcU_eBN_NvNyC1URLBMVqD8uymh_2dleW8b3ByNsC8Mlc_kT6VRA_F8Wy2G9huSL17__Y39nP4dQ6y4NtTi-Ml4jftQQoHLjBF36b9qNXweryqfWEElFt/s792/limits+to+wage+growth+2.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="483" data-original-width="792" height="244" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhqjDl1Du-ZijhcXYNX3XRSvdZIcU_eBN_NvNyC1URLBMVqD8uymh_2dleW8b3ByNsC8Mlc_kT6VRA_F8Wy2G9huSL17__Y39nP4dQ6y4NtTi-Ml4jftQQoHLjBF36b9qNXweryqfWEElFt/w400-h244/limits+to+wage+growth+2.png" width="400" /></a></div><div style="text-align: justify;"><br /></div><div style="text-align: justify;">This is the most recent estimate of the size of the shock to wage growth with data through June 2021 (the <a href="https://twitter.com/infotranecon/status/1415390878173073410">previous estimate</a> was somewhat larger). If we show this alongside trend NGDP growth (about 3.8%, a.k.a. the <a href="https://informationtransfereconomics.blogspot.com/2018/01/24-growth-forever.html">dynamic equilibrium</a>) we see the new post-COVID path intersects it around 2027 (click to enlarge):</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEixbS_sRRAcpOj9GHC6tX6iR3VG4_4zmBGiWzFiaso5LcqWdh3BIwmwVnd8nFIr9zN49ExXBDP7B-2UgvGOWCX2RoVtgSkfx9fZjIkvzI59eehTFijR9gDfUiAlcOu5e8GiVPO2V6IieA-c/s979/limits+to+wage+growth+3.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="485" data-original-width="979" height="199" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEixbS_sRRAcpOj9GHC6tX6iR3VG4_4zmBGiWzFiaso5LcqWdh3BIwmwVnd8nFIr9zN49ExXBDP7B-2UgvGOWCX2RoVtgSkfx9fZjIkvzI59eehTFijR9gDfUiAlcOu5e8GiVPO2V6IieA-c/w400-h199/limits+to+wage+growth+3.png" width="400" /></a></div><br /><div style="text-align: justify;">Now this depends on a lack of asset boom/bust cycles in trend NGDP growth — which can push the date out by years. For example, by trend alone we should have expected a recession in 1997/8; the dot-com boom pushed the recession out to 2001 when NGDP crashed down below wage growth. However, this will be obvious in the NGDP data over the next 6 years — it's not an escape clause for the hypothesis.</div><div><p style="text-align: justify;"><b>Epilogue</b></p><p style="text-align: justify;">One reason I thought about looking back at this hypothesis was <a href="https://uneasymoney.com/2021/07/28/why-price-stickiness-matters-or-doesnt/">a blog post</a> from David Glasner, writing about an argument about the price stickiness mechanism in (new) Keynesian models [1]. I found myself reading lines like "wages and prices are stuck at a level too high to allow full employment" — something I would have seen as plausible several years ago when I first started learning about macroeconomics — and shouting (to myself, as I was on an airplane) "This has no basis in empirical reality!"</p><p style="text-align: justify;">Wage growth declines in the aftermath of a recession and then continues with its prior log growth rate of 0.04/y. Unemployment rises during a recession and then continues with its prior rate of decline −0.09/y [2]. <a href="https://informationtransfereconomics.blogspot.com/2018/10/building-models.html">These two measures are tightly linked</a>. <a href="https://informationtransfereconomics.blogspot.com/2019/03/the-beginnings-of-information.html">Inflation falls briefly</a> about 3.5 years after a decline in labor force participation — and then continues to grow at 1.7% (core PCE) to 2.5% (CPI, all items).</p><p style="text-align: justify;">These statements are entirely about <b><i>rates</i></b>, not <b><i>levels</i></b>. And if the hypothesis above is correct, the causality is backwards. It's not the failing economy reducing the level of wages that can be supported at full employment — the recession is <b><i>caused by</i></b> wage growth exceeding NGDP growth, which causes unemployment to rise, which then causes wage growth to decline about 6 months later.</p><p style="text-align: justify;">Additionally, since both NGDP and wages here are <i><b>nominal</b></i> monetary policy won't have any impact on this mechanism. And empirically, it doesn't. While the <b><i>social </i></b>effect of the Fed may stave off the panic in a falling market and rising unemployment, once the bottom is reached and the shock is over the economy (over the entire period for which we have data) just heads back to its equilibrium −0.09/y log decline in unemployment and +0.04/y log increase in wage growth.</p><p style="text-align: justify;">Of course this would mean the core of Keynesian thinking about how the economy works — in terms of wages, prices, and employment — is flawed. Everything that follows from <i>The General Theory</i> from post-Keynesian schools to the neoclassical synthesis to new Keynesian DSGE models to monetarist ideology is fruit of a poisonous tree.</p><p>Keynes <a href="https://equitablegrowth.org/must-read-john-maynard-keynes-1938-on-tinbergen-to-harrod/">famously said we shouldn't fill in the values</a>:</p><p></p><blockquote style="text-align: justify;"><i>In chemistry and physics and other natural sciences the object of experiment is to fill in the actual values of the various quantities and factors appearing in an equation or a formula; and the work when done is once and for all. In economics that is not the case, and to convert a model into a quantitative formula is to destroy its usefulness as an instrument of thought. </i></blockquote><p></p><p style="text-align: justify;">No wonder his ideas have no basis in empirical reality!</p><p>...</p><p><b>Update 19 November 2021</b></p><p style="text-align: justify;">The stimulus of 2021 seems to have pushed up both GDP growth and wage growth. In fact, wage growth appears to have returned to its prior equilibrium:</p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/a/AVvXsEjttHG4zJu7pGJkejcJ_2EKpVT53pcigsSVUqu7JZqN253RQpjQELtteWLGKUS9TOS7MLqYrjf3XZXAMgSq33KOrN9-KoOLrmu9-jxVMx1Pn3N5d6nb-iODGDXQ06imE5J3d24AwsX__yeJe_xwmEgFGnlifqZAn5NaNS13tkC6khrmGcSTEOE-i5mlYA=s792" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="483" data-original-width="792" height="244" src="https://blogger.googleusercontent.com/img/a/AVvXsEjttHG4zJu7pGJkejcJ_2EKpVT53pcigsSVUqu7JZqN253RQpjQELtteWLGKUS9TOS7MLqYrjf3XZXAMgSq33KOrN9-KoOLrmu9-jxVMx1Pn3N5d6nb-iODGDXQ06imE5J3d24AwsX__yeJe_xwmEgFGnlifqZAn5NaNS13tkC6khrmGcSTEOE-i5mlYA=w400-h244" width="400" /></a></div><div style="text-align: justify;">If this trend continues and the BIF (and/or BBB, if passed) doesn't bring GDP growth above its historical 3.8% average outside of shocks, then that brings the recession date back to ... around now. Looking at PCE (consumption) instead of GDP (as the former is updated more frequently than the latter, but both show almost the exact same structure), we are back to being above that long run growth limit (click to enlarge):</div></div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/a/AVvXsEgxZZhaeO3o497YAcfF5E6eh2RjOWKtTGnVrpANRsUsfRdWBRPDU8vH67iz7HZE3M8ocQMMdhgK0ZfvGKf-f87BFVyrzKfZSivNTTjUk5jFRv9HL8K7PuZJ7OzWgjuhx1g8wa1T7QtKu8MdjRfhRgc9VlaGVH6Moll8ElZQiHIIlc8ZFYmPQGN7_ssSVg=s792" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="452" data-original-width="792" height="229" src="https://blogger.googleusercontent.com/img/a/AVvXsEgxZZhaeO3o497YAcfF5E6eh2RjOWKtTGnVrpANRsUsfRdWBRPDU8vH67iz7HZE3M8ocQMMdhgK0ZfvGKf-f87BFVyrzKfZSivNTTjUk5jFRv9HL8K7PuZJ7OzWgjuhx1g8wa1T7QtKu8MdjRfhRgc9VlaGVH6Moll8ElZQiHIIlc8ZFYmPQGN7_ssSVg=w400-h229" width="400" /></a></div><br /><div>Zooming in on the more recent years (click to enlarge):</div><div><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/a/AVvXsEjaeZf38NbdAOtrKOfXwkLOsd_-P-4AGOXk2XcHZjnkW5U8-3Dapdi4sWMt70Rsa9XjJpmcdz_uafKRIwBWCn0Lmr_raVwL2hIU4eO8LvhG8JvrFq6zX-EjmZ0jWoy39IIQV5BSPyKkLRI1DUeJNaFrtS7oAW8NwTIT7c_L0arYfkZJst0-7_bE_tizpg=s792" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="459" data-original-width="792" height="231" src="https://blogger.googleusercontent.com/img/a/AVvXsEjaeZf38NbdAOtrKOfXwkLOsd_-P-4AGOXk2XcHZjnkW5U8-3Dapdi4sWMt70Rsa9XjJpmcdz_uafKRIwBWCn0Lmr_raVwL2hIU4eO8LvhG8JvrFq6zX-EjmZ0jWoy39IIQV5BSPyKkLRI1DUeJNaFrtS7oAW8NwTIT7c_L0arYfkZJst0-7_bE_tizpg=w400-h231" width="400" /></a></div><br /><div><br /></div><div><br /></div><div>PS: New arctan axes just dropped.<p>...</p><p>Footnotes:</p><p style="text-align: justify;">[1] Also, <a href="https://informationtransfereconomics.blogspot.com/2019/05/prices-are-sticky-except-when-they.html">wages / prices aren't individually sticky</a>. The distribution of changes might be sticky (<a href="https://informationtransfereconomics.blogspot.com/2015/04/micro-stickiness-versus-macro-stickiness.html">emergent macro nominal rigidity</a>), but prices or wages that change by 20% aren't in any sense "sticky".</p><p style="text-align: justify;">[2] Something <a href="https://www.nber.org/papers/w28111">Hall and Kudlyak (Nov 2020)</a> picked up on somewhat after <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3094757">I wrote about it</a> (and even <a href="https://twitter.com/infotranecon/status/1411384311253585921">used the same example</a>).</p></div>Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com2tag:blogger.com,1999:blog-6837159629100463303.post-37960147845084480922021-04-25T17:42:00.001-07:002021-04-25T17:42:55.785-07:00Implicit assumptions in Econ 101 made explicit<script type="text/x-mathjax-config"> MathJax.Hub.Config({tex2jax: {inlineMath: [['$','$'], ['\\(','\\)']]}}); </script> <script src="https://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML" type="text/javascript"> </script>
<p style="text-align: justify;">One of the benefits of the information equilibrium approach to economics is that it makes several of the implicit assumptions explicit. Over the past couple days, I was part of an exchange with Theodore on twitter that started <a href="https://twitter.com/tedkalambo/status/1385656456767287301">here</a> where I learned something new about how people who have studied economics think about it — and those implicit assumptions. Per his blog, Theodore says he works in economic consulting so I imagine he has some advanced training in the field.</p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgsOZ56_fG_lmbobTV9OsHXy70Rd_o4Rxcl0Q_xgCX-kqWRgDYtK5OGwY8cXwdn0HRS3JpobUoA5NjmaKPGKqpVJ3AklNz49GJp3GipuNFLuimjOz-3NJ0jVT9CR6kRhVETwWlTm78Gx4Hw/s960/Slide27.PNG" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="720" data-original-width="960" height="300" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgsOZ56_fG_lmbobTV9OsHXy70Rd_o4Rxcl0Q_xgCX-kqWRgDYtK5OGwY8cXwdn0HRS3JpobUoA5NjmaKPGKqpVJ3AklNz49GJp3GipuNFLuimjOz-3NJ0jVT9CR6kRhVETwWlTm78Gx4Hw/w400-h300/Slide27.PNG" width="400" /></a></div><p style="text-align: justify;">The good old supply and demand diagram used in Econ 101 has a lot of implicit assumptions going into it. I'd like to make a list of some of the bigger implicit assumptions in Econ 101 and how the information transfer framework makes them explicit.</p><p style="text-align: justify;"><b>I. Macrofoundations of micro</b></p><p style="text-align: justify;">Theodore doesn't think the supply and demand curves in the information transfer framework [1] are the same thing as supply and demand curves in Econ 101. Part of this is probably a physicist's tendency to see any isomorphic system in terms of <i><a href="https://en.wikipedia.org/wiki/Effective_theory">effect</a> </i>as the same thing. <a href="https://en.wikipedia.org/wiki/Harmonic_oscillator">Harmonic oscillators</a> are basically the same thing even if the underlying models — from a pendulum, to a spring, to <a href="http://users.physik.fu-berlin.de/~kleinert/b6/psfiles/Chapter-15-spontsbo.pdf">a quantum field</a> [pdf] — result from different degrees of freedom.</p><p style="text-align: justify;">One particular difference Theodore sees is that in the derivation from the information equilibrium condition $I(D) = I(S)$, the supply curve has parameters that derive from the demand side. <a href="https://twitter.com/tedkalambo/status/1386094682195873795">He asks</a>:</p><p style="text-align: justify;"><i></i></p><blockquote style="text-align: justify;"><i>For any given price you can draw a traditional S curve, independent of [the] D curve. Is it possible to draw I(S) curve independent of I(D)?</i></blockquote><p></p><p style="text-align: justify;">Now Theodore is in good company. A <a href="https://www.soas.ac.uk/cedep-demos/000_P570_IEEP_K3736-Demo/unit1/page_25.htm">University of London 'Econ 101' tutorial</a> that he linked me to also says that they are independent:</p><p style="text-align: justify;"><i></i></p><blockquote style="text-align: justify;"><i>It is important to bear in mind that the supply curve and the demand curve are both independent of each other. The shape and position of the demand curve is not affected by the shape and position of the supply curve, and vice versa.</i></blockquote><p></p><p style="text-align: justify;">I was unable to find a similar statement in any other Econ 101 source, but I don't think the tutorial statement is terribly controversial. But what does 'independent' mean here?</p><p style="text-align: justify;">In the strictest sense, the supply curve in the information transfer framework is independent of demand independent variables because you effectively integrate out demand degrees of freedom to produce it, leaving only supply and price. Assuming constant $S \simeq S_{0}$ when integrating the information equilibrium condition:</p><div style="text-align: justify;"></div><div><p>$$\begin{eqnarray}\int_{D_{ref}}^{\langle D \rangle} \frac{dD'}{D'} & = & k \int_{S_{ref}}^{\langle S \rangle} \frac{dS'}{S'}\\<br />& = & \frac{k}{S_{0}} \int_{S_{ref}}^{\langle S \rangle} dS'\\<br />& = & \frac{k}{S_{0}} \left( \langle S \rangle - S_{ref}\right)\\<br />\log \left( \frac{\langle D \rangle}{D_{ref}}\right) & = & \frac{k}{S_{0}} \Delta S<br />\end{eqnarray}$$</p><p style="text-align: justify;">If we use the information equilibrium condition $P = k \langle D \rangle / S_{0}$, then we have an equation free of any demand independent variables [2]:</p>$$\text{(1)}\qquad \Delta S = \frac{S_{0}}{k} \log \left(\frac{P S_{0}}{k D_{ref}}\right)<br />$$<p style="text-align: justify;">There's still that 'reference value' of demand $D_{ref}$, though. That's what I believe Theodore is objecting to. What's that about?</p><p style="text-align: justify;">It's one of those implicit assumptions in Econ 101 made explicit. It represents the background market required for the idea of a price to make sense. In fact, we show this more explicitly by recognizing the the argument of the log in Eq. (1) is dimensionless. We can define a quantity with units of price (per the information equilibrium condition) $P_{ref} = k D_{ref} / S_{0}$ such that:</p>$$<br />\text{(2)}\qquad \Delta S = \frac{S_{0}}{k} \log \left(\frac{P}{P_{ref}}\right)<br />$$</div><div><p style="text-align: justify;">This constant sets the <i>scale </i>of the price. What units are prices measured in? Is it 50 € or 50 ¥? In this construction, the price is set around a market equilibrium price in that reference background. The supply curve is the behavior of the system for small perturbations around that market equilibrium when demand reacts faster than supply such that the information content of the supply <i>distribution </i>stays approximately constant at each value of price (just increasing the quantity supplied) where the scale of prices doesn't change (for example, due to inflation).</p><p style="text-align: justify;">This is why I tried to ask about what the price $P$ meant in Theodore's explanations. How can a price of a good in the supply curve mean anything independently of demand? You can see the implicit assumptions of a medium of exchange, a labor market, production capital, and raw materials in <a href="https://twitter.com/tedkalambo/status/1386129729850380288">his attempt to show</a> that the supply curve is independent of demand:</p></div><div><p style="text-align: justify;"></p><blockquote style="text-align: justify;"><i>The firm chooses to produce [quantity] Q to maximize profits = P⋅Q − C(Q) where C(Q) is the cost of producing Q. [T]he supply curve is each Q that maximizes profits for each P. The equilibrium [market] price that firms will actually end up taking is where the [supply] and [demand] curves intersect.</i></blockquote><p></p></div><div><p style="text-align: justify;">There's a whole economy implicit in the definition profits $ = P Q - C(Q)$. What are the units of $P$? What sets its scale? [4] Additionally, the profit maximization implicitly depends on the demand for your good.</p><p style="text-align: justify;">I will say that Theodore's (and the rest of Econ 101's) explanation of a supply curve is much more concrete in the sense that it's easy for any person who has put together a lemonade stand to understand. You have costs (lemons, sugar) and so you'll want to sell the lemonade for more than the cost of the lemons based on how many glasses you think you might sell. But one thing it's not is independent of a market with demand and a medium of exchange.</p><p style="text-align: justify;">Some of the assumptions going into the Theodore's supply curve aren't even necessary. The information transfer framework has a useful antecedent in Gary Becker's paper <i>Irrational Behavior in Economic Theory</i> [Journal of Political Economy 70 (1962): 1--13] that uses effectively random agents (i.e. maximum entropy) to reproduce supply and demand. I usually just stick with the explanation of the demand curve because it's far more intuitive, but there's also the supply side. That was concisely summarized by <a href="http://bactra.org/weblog/1155.html">Cosma Shalizi</a>:</p></div><div><p style="text-align: justify;"><i></i></p><blockquote style="text-align: justify;"><i>... the insight is that a wider range of productive techniques, and of <b>scales </b>of production, become profitable at higher prices. This matters, says Becker, because producers cannot keep running losses forever. If they're not running at a loss, though, they can stay in business. So, again without any story about preferences or maximization, as prices rise more firms could produce for the market and stay in it, and as prices fall more firms will be driven out, reducing supply. Again, nothing about individual preferences enters into the argument. Production processes which are <b>physically </b>perfectly feasible but un-profitable get suppressed, because capitalism has institutions to make them go away.</i></blockquote><p></p></div><div><p style="text-align: justify;">Effectively, as we move from a close-in <a href="https://worthwhile.typepad.com/worthwhile_canadian_initi/2015/12/ppfs-and-supply-curves.html">production possibilities frontier</a> (lower prices) to a far-out one (higher prices), the state space is simply larger [5]. This increasing size of the state space with price is what is captured in Eqs. (1) and (2), but it critically depends on setting a scale of the production possibilities frontier via the background macroeconomic equilibrium — we are considering perturbations around it. </p><p style="text-align: justify;">David Glasner [6] has written about these 'macrofoundations' of microeconomics, e.g. <a href="https://uneasymoney.com/2016/06/16/whats-wrong-with-econ-101/">here</a> in relation to Econ 101. A lot of microeconomics makes assumptions that are likely only valid near a <i>macroeconomic </i>equilibrium. This is something that I hope the information transfer framework makes more explicit.</p><p style="text-align: justify;"><b>II. The rates of change of supply and demand</b></p><p style="text-align: justify;">There is an assumption about the rates of change of the supply and demand distributions made leading to Eq. (1) above. That assumption about whether supply or demand is adjusting faster [2] when you are looking at supply and demand curves is another place where the information transfer framework makes an implicit Econ 101 assumption explicit — and does so in a way that I think would be incredibly beneficial to the discourse. In particular, beneficial to the <a href="https://informationtransfereconomics.blogspot.com/2017/04/its-production-input-no-its-market-good.html">discussion of labor markets</a>. As I talk about at the link in more detail, the idea that you could have e.g. a surge of immigration and somehow classify it entirely as a supply shock to labor, reducing wages, is nonsensical in the information transfer framework. Workers are working precisely so they can pay for things they need, which means we cannot assume either supply or demand is changing faster; both are changing together. Immediately we are thrown out of the supply and demand diagram logic and instead are talking about general equilibrium.</p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjQ4_X0yc1O0-jSH4UUR8QP9iGksJ4GKzkFTiu8aTamu3ga80N17eTJA6ASMc51UV4Fg4WWYT685joHCJenHbjx4vc6ZQ1nOHxXOqCMaC16-hVybvxFjEqgwulTfXBj6Hd105zio9fdPPi5/s720/supplydemandgrowthpriceSHOCK.gif" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="233" data-original-width="720" height="130" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjQ4_X0yc1O0-jSH4UUR8QP9iGksJ4GKzkFTiu8aTamu3ga80N17eTJA6ASMc51UV4Fg4WWYT685joHCJenHbjx4vc6ZQ1nOHxXOqCMaC16-hVybvxFjEqgwulTfXBj6Hd105zio9fdPPi5/w400-h130/supplydemandgrowthpriceSHOCK.gif" width="400" /></a></div><p style="text-align: justify;"><b>III. Large numbers of inscrutable agents</b></p><p style="text-align: justify;">Of course there is the even more fundamental assumption that an economy is made up of a huge number of agents and transactions. This explicitly enters into the information transfer framework twice: once to say distributions of supply and demand are close to the distributions of events drawn from those distributions (Borel law of large numbers), and once to go from discrete events to the continuous differential equation.</p><p style="text-align: justify;">This means supply and demand cannot be used to understand markets in unique objects (e.g. art), or where there are few participants (e.g. labor market for CEOs of major companies). But it also means you cannot apply facts you discern in the aggregate to individual agents — for example see <a href="https://informationtransfereconomics.blogspot.com/2017/08/lazy-econ-critique-critiques.html">here</a>. An individual did not necessarily consume fewer blueberries because of a blueberry tax, but instead had their own reasons (e.g. they had medical bills to pay, so could afford fewer blueberries) that only when aggregated across millions of people produced the ensemble average effect. This is a subtle point, but comes into play more when behavioral effects are considered. Just because a behavioral explanation aggregates to a successful description of a macro system, it does not mean the individual psychological explanation going into that behavioral effect is accurate.</p><p style="text-align: justify;">Again, this is made explicit in the information transfer framework. Agents are assumed to be inscrutable — making decisions for reasons we cannot possibly know. The assumption is only that agents fully explore the state space, or at least that the subset of the state space that is fully explored is relatively stable with only sparse shocks (see the next item). This is the <a href="https://en.wikipedia.org/wiki/Principle_of_maximum_entropy">maximum entropy</a> / <a href="https://en.wikipedia.org/wiki/Ergodic_hypothesis">ergodic</a> assumption.</p><p style="text-align: justify;"><b>IV. Equilibrium</b></p><p style="text-align: justify;">Another place where implicit assumptions are made explicit is equilibrium. The assumption of being at or near equilibrium such that $I(D) \simeq I(S)$ is even in the name: information equilibrium. The more general approach is the information <i>transfer </i>framework where $I(D) \geq I(S)$ and e.g prices fall below ideal (information equilibrium) prices. I've even distinguished these in notation, writing $D \rightleftarrows S$ for an information equilibrium relationship and $D \rightarrow S$ for an information transfer one.</p><p style="text-align: justify;">Much like the concept of macrofoundations above, the idea behind supply and demand diagrams is that they are for understanding how the system responds near equilibrium. If you're away from information equilibrium, then you can't really interpret market moves as the interplay of supply and demand (e.g. <a href="https://informationtransfereconomics.blogspot.com/2015/01/is-market-intelligent.html">for prediction markets</a>). Here's David Glasner from his <a href="https://uneasymoney.com/2016/06/16/whats-wrong-with-econ-101/">macrofoundations and Econ 101 post</a>:</p><p style="text-align: justify;"></p><blockquote><p style="text-align: justify;"><i>If the analysis did not start from equilibrium, then the effect of the parameter change on the variable could not be isolated, because the variable would be changing for reasons having nothing to do with the parameter change, making it impossible to isolate the pure effect of the parameter change on the variable of interest. ... </i><i>Not only must the exercise start from an equilibrium state, the equilibrium must be at least locally stable, so that the posited small parameter change doesn’t cause the system to gravitate towards another equilibrium — the usual assumption of a unique equilibrium being an assumption to ensure tractability rather than a deduction from any plausible assumptions – or simply veer off on some explosive or indeterminate path.</i></p></blockquote><p style="text-align: justify;"></p><p style="text-align: justify;">In the dynamic information equilibrium model (DIEM), there is an explicit assumption that equilibrium is only disrupted by <i>sparse </i>shocks. If shocks aren't sparse, there's no real way to determine the dynamic equilibrium rate $\alpha$. This assumption of sparse shocks is similar to the assumptions that go into understanding <a href="https://informationtransfereconomics.blogspot.com/2015/10/when-is-intertemporal-budget-constraint.html">the intertemporal budget constraint</a> (which also needs to have an explicit assumption that consumption <i><b>isn't </b></i>sparse).</p><p style="text-align: justify;"><b>Summary</b></p><p style="text-align: justify;">Econ 101 assumes a lot of things — from the existence of a market and a medium of exchange, to being in an approximately stable macroeconomy that's near equilibrium, to the rates of change of supply and demand in response to each other, to simply the existence of a large number of agents.</p><p style="text-align: justify;">This is usually fine — introductory physics classes often assume you're in a gravitational field, near thermodynamic equilibrium, or even a small cosmological constant such that condensed states of matter exist. Econ 101 is trying to teach students about the world in which they live, not an abstract one where an economy might not exist.</p><p style="text-align: justify;">The problem comes when you forget these assumptions or try to pretend they don't exist. A lot of 'Economism' (per <a href="https://www.penguinrandomhouse.com/books/536159/economism-by-james-kwak/">James Kwak's book</a>) or '101ism' (see <a href="http://noahpinionblog.blogspot.com/2016/01/101ism.html">Noah Smith</a>) comes from not recognizing the conclusions people drawn from Econ 101 are dependent on many background assumptions that may or may not be valid in any particular case.</p><p style="text-align: justify;">Additionally, when you forget the assumptions you lose understanding of model scope (see <a href="https://informationtransfereconomics.blogspot.com/2015/10/we-built-this-theory-on-scope-conditions.html">here</a>, <a href="https://informationtransfereconomics.blogspot.com/2016/06/macroeconomists-are-weird-about-theory.html">here</a>, or <a href="https://informationtransfereconomics.blogspot.com/2016/01/more-on-scope.html">here</a>). You start applying a model where it doesn't apply. You start thinking that people who don't think it applies are dumb. You start thinking Econ 101 is the only possible description of supply and demand. <i>It's basic Econ 101! Demand curves slope down [7]! That's not a supply curve!</i></p><p style="text-align: justify;">...</p><p><b>Footnotes:</b></p><p style="text-align: justify;">[1] The derivation of the supply and demand diagram from information equilibrium is actually older than this blog — I had written it up as a draft paper after working on the idea for about two years after learning about the information transfer framework of <a href="https://arxiv.org/abs/0905.0610">Fielitz and Borchardt</a>. I posted the derivation <a href="https://informationtransfereconomics.blogspot.com/2013/04/supply-and-demand-from-information.html">on the blog</a> the first day eight years ago.<br /></p><p style="text-align: justify;">[2] In fact, a demand curve doesn't even <i>exist</i> in this formulation because we assumed the time scale $T_{D}$ of changes in demand is much shorter than the time scale $T_{S}$ of changes in supply (i.e. supply is constant, and demand reacts faster) — $T_{S} \gg T_{D}$. In order to get a demand curve, you have to assume <i>the exact opposite relationship </i>$T_{S} \ll T_{D}$. The two conditions cannot be simultaneously true [3]. The supply and demand diagram is a useful tool for understanding the logic of particular changes in the system inputs, but the lines don't really exist — they represent counterfactual universes outside of the equilibrium.</p><p style="text-align: justify;">[3] This does not mean there's no equilibrium intersection point — it just means the equilibrium intersection point is the solution of the more general equation valid for $T_{S} \sim T_{D}$. And what's great about the information equilibrium framework is that the solution, in terms of a supply and demand diagram, is in fact a point because $P = f(S, D)$ — one price for one value of the supply distribution and one value of the demand distribution.</p><p style="text-align: justify;">[4] This is another area where economists treat economics like mathematics instead of as a science. There are no scales, and if you forget them sometimes you'll take <a href="https://informationtransfereconomics.blogspot.com/2015/11/on-limits.html">nonsense limits</a> that are fine for a real analysis class but useless in the real world where infinity does not exist.</p><p style="text-align: justify;">[5] For some fun discussion of another reason economists give for the supply curve sloping up — a 'bowed-out' production possibilities frontier — see my post <a href="https://informationtransfereconomics.blogspot.com/2016/02/production-possibilities-and-slope-of.html">here</a>. Note that I effectively reproduce that using Gary Becker's 'irrational' model by looking at the size of the state space as you move further out. Most of the volume of a high dimensional space is located near its (hyper)surface. This means that <a href="https://informationtransfereconomics.blogspot.com/2016/02/production-possibilities-and-brownian.html">selecting a random path through it</a>, assuming you can explore most of the state space, will land near that hypersurface.</p><p style="text-align: justify;">[6] David Glasner is also the economist <a href="https://informationtransfereconomics.blogspot.com/2015/10/gary-beckers-emergent-rational-agents.html">who realized the connections</a> between information equilibrium and Gary Becker's paper.</p><p style="text-align: justify;">[7] Personally like <a href="http://noahpinionblog.blogspot.com/2016/01/101ism.html">Noah Smith's rejoinder</a> about this aspect of 101ism — econ 101 does say they slope down, but not necessarily with a slope $| \epsilon | \sim 1$. They could be almost completely flat. There's nothing in econ 101 to say otherwise. PS — had a conversation about demand curves with <a href="https://twitter.com/tedkalambo/status/1354149788514709509">our friend Theodore as well</a> earlier this year.</p></div>Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com2tag:blogger.com,1999:blog-6837159629100463303.post-1336590982088855712021-04-24T15:32:00.002-07:002021-04-24T15:32:28.391-07:00Eight years of blogging<p style="text-align: justify;">I spent the past week <a href="https://twitter.com/infotranecon/status/1383528378473488387">on Twitter</a> putting up a list of my favorite posts on the blog as a kind of Irish wake for the form for the blog's 8th anniversary. As is typical on these anniversaries, a bit of statistical analysis or visualization — this time, the years of the selected favorites:</p><p style="text-align: justify;"><br /></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjOa0DkccKUH3prCrJx32ZdrBvJSXGsyvlLKxYB5FzEijupN0mxA9_JwheVA8NEG5bogaFbcF61xE7QSSNyaQaJq_dSfe9JdRsLo_Y5mqCxlo1EKjkGHZ38vEPadRR8CBwx9Oqh89mvW0gh/s792/favorites.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="430" data-original-width="792" height="217" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjOa0DkccKUH3prCrJx32ZdrBvJSXGsyvlLKxYB5FzEijupN0mxA9_JwheVA8NEG5bogaFbcF61xE7QSSNyaQaJq_dSfe9JdRsLo_Y5mqCxlo1EKjkGHZ38vEPadRR8CBwx9Oqh89mvW0gh/w400-h217/favorites.png" width="400" /></a></div><p style="text-align: justify;">Looks like 2016-2017 was my peak by the number in my own opinion. It's not just bias by the quantity of posts, either. The most prolific year was 2015 with an average rate of a post per day. Favorites per total number has been increasing steadily — at least in terms of my own opinion, quality has been rising:</p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgziLChdf6KezBAd7iR0rsOxfyaoG0AQqzNgpgKfsjlQV7A67rtNoWjK37W1Ag9hyHMT8ryPGUU99oY8wRcg2Fhuw3Bo_n8ZJTy1bsIX6Q5gBGSvO5vDSehsqFHBiOE0QdVfKIzbMUDC6SU/s792/favorites2.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="434" data-original-width="792" height="219" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgziLChdf6KezBAd7iR0rsOxfyaoG0AQqzNgpgKfsjlQV7A67rtNoWjK37W1Ag9hyHMT8ryPGUU99oY8wRcg2Fhuw3Bo_n8ZJTy1bsIX6Q5gBGSvO5vDSehsqFHBiOE0QdVfKIzbMUDC6SU/w400-h219/favorites2.png" width="400" /></a></div><p>Here's the list (not in order) for posterity:</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2016/01/its-people-economy-is-made-out-of-people.html">It's people. The economy is made out of people.</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2017/09/solow-has-science-backward.html">Solow has science backward</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2017/04/good-ideas-do-not-need-lots-of-invalid.html">Good ideas do not need lots of invalid arguments in order to gain public acceptance</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2015/09/maximum-entropy-better-than-game-theory.html">Maximum entropy better than game theory</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2017/08/lazy-econ-critique-critiques.html">Lazy econ critique critiques</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2017/10/can-macro-model-be-good-for-policy-but.html">Can a macro model be good for policy, but not for forecasting?</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2014/07/remarkable-recovery-regularity-and.html">Remarkable recovery regularity and other observations</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2019/08/a-solow-paradox-for-industrial.html">A Solow Paradox for the Industrial Revolution</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2018/05/macro-criticism-but-not-that-kind.html">Macro criticism, but not that kind</a>"</p><p>"<a href="http://informationtransfereconomics.blogspot.com/2016/07/ceteris-paribus-and-method-of-nascent.html">Ceteris paribus and method of nascent science</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2019/04/things-that-changed-in-90s.html">Things that changed in the 90s</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2016/09/the-economic-state-space-mini-seminar.html">The economic state space: a mini-seminar</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2016/12/stocks-and-k-states.html">Stocks and k-states</a>"</p><p>"<a href="http://informationtransfereconomics.blogspot.com/2017/01/the-islm-model-reference-post.html">The ISLM model (reference post)</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2014/12/an-information-transfer-traffic-model.html">An information transfer traffic model</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2017/09/my-introductory-chapter-on-economics.html">My introductory chapter on economics</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2016/10/keen-chaos-and-equilibrium.html">Keen, chaos, and equilibrium</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2017/07/what-mathematical-theory-is-for.html">What mathematical theory is for</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2019/08/the-phillips-curve-and-narrative.html">The Phillips curve and The Narrative</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2018/05/uk-productivity-and-data-interpretation.html">UK productivity and data interpretation</a>"</p><p>"<a href="http://informationtransfereconomics.blogspot.com/2017/02/qualitative-economics-done-right-part-1.html">Qualitative economics done right, part 1</a>"</p><p>"<a href="http://informationtransfereconomics.blogspot.com/2016/03/goldilocks-complexity.html">Goldilocks complexity</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2016/04/neo-fisherism-and-causality.html">Neo-Fisherism and causality</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2019/06/resolving-cambridge-capital-controversy.html">Resolving the Cambridge capital controversy with MaxEnt</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2015/05/the-irony-of-paul-romers-mathiness.html">The irony of Paul Romer's mathiness</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2016/03/more-like-stock-flow-in-consistent.html">More like stock-flow inconsistent</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2016/12/stock-flow-consistency-is-tangential-to.html">Stock-flow consistency is tangential to stock-flow consistent model claims</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2017/04/should-left-engage-with-neoclassical.html">Should the left engage with neoclassical economics?</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2019/08/milton-friedmans-thermostat-redux.html">Milton Friedman's Thermostat, redux</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2016/08/efficient-markets-and-challenger.html">Efficient markets and the Challenger disaster</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2016/03/the-irony-of-microfoundations.html">The irony of microfoundations fundamentalism</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2014/06/what-if-money-was-made-of-vinegar.html">What if money was made of vinegar?</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2017/03/the-quantity-theory-of-labor-and.html">The 'quantity theory of labor' and dynamic equilibrium</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2018/05/no-one-saw-this-coming-bezemers.html">No one saw this coming: Bezemer's misleading paper</a>" ("<a href="https://informationtransfereconomics.blogspot.com/2018/05/letter-to-dirk-bezemer.html">Letter to Dirk Bezemer</a>")</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2018/10/keen.html">Keen</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2016/08/dsge-part-5-summary.html">DSGE, part 5 (summary)</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2018/04/yes-ive-read-duncan-foley-have-you.html">Yes, I've read Duncan Foley. *Have you?*</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2015/10/utility-maximization-and-entropy.html">Utility maximization and entropy maximization</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2015/01/is-market-intelligent.html">Is the market intelligent?</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2018/07/dsge-battle-royale-christiano-v-stiglitz.html">DSGE Battle Royale: Christiano v. Stiglitz</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2013/04/the-philosophical-motivations.html">The philosophical motivations</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2019/10/wage-growth-in-ny-and-pa.html">Wage growth in NY and PA</a>" </p><div><div>"<a href="https://informationtransfereconomics.blogspot.com/2019/10/exploration-of-abstract-space-prices.html">Exploration of an abstract space: prices, money, and ... ships at sea?</a>"</div></div><p>"<a href="https://informationtransfereconomics.blogspot.com/2016/02/thought-experiment.html">Thought experiment</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2017/01/dynamic-equilibrium-unemployment-rate.html">Dynamic equilibrium: unemployment rate</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2019/07/labor-market-update-external-validity.html">Labor market update: external validity edition</a>"</p><p>"<a href="https://informationtransfereconomics.blogspot.com/2016/08/efficient-markets-and-challenger.html">Efficient markets and the Challenger disaster</a>"</p><p><br /></p><p><br /></p>Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com0tag:blogger.com,1999:blog-6837159629100463303.post-20955879685494025202021-02-28T15:35:00.000-08:002021-02-28T15:35:36.424-08:00Ongoing evolution of time series after the COVID-19 shock<p style="text-align: justify;">I haven't been blogging much the past two years — due to a) work taking nearly all of my energy, and b) the near daily update of data around COVID-19 being more conducive to Twitter than blogging. However, I thought it was time for a longer-term assessment of the economic time series in the context of <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3094757">Dynamic Information Equilibrium Models</a> (DIEMs).</p><p style="text-align: justify;">First, let's look at the consumer spending data from <a href="https://tracktherecovery.org/">tracktherecovery.org</a> (Raj Chetty and John Friedman's project using with proprietary credit card data and only bulk credit to the "OI team" of undergrad RAs) — beginning with a little history (and links to Twitter). I originally put together several models back in early <a href="https://twitter.com/infotranecon/status/1271583724467924994">June of 2020</a> to describe the shock to consumer spending data. About two months later (end of <a href="https://twitter.com/infotranecon/status/1288963635402825728">July 2020</a>) I added in long run growth because it would start to become an important factor as the recovery dragged on. <a href="https://twitter.com/infotranecon/status/1319393510810742784">Towards the end of October</a>, I decided to rank the performance of the four different models. Basically, all of them performed about equally — except for the "entropic shock" with a complete return to equilibrium. This means that there was some persistent gap in spending that wasn't made up until after the most recent round of stimulus checks in January of 2021.</p><p>Here are the four models (click to enlarge).</p><table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto;"><tbody><tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjiUNE_gjopSDDE6o7SNREag0yxGH48_LY32T9T6d63YIMau2-u-4fN4eMqzIAo6tqs2H_dCrXFNeRAvsfWsileHm6tFn8AufzUjYUbNNP0oTRR_BfXdPqWcHe0zBDbSo0_iEw1FMK_e5Zg/s917/diem+shock+model+20210228a.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="476" data-original-width="917" height="208" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjiUNE_gjopSDDE6o7SNREag0yxGH48_LY32T9T6d63YIMau2-u-4fN4eMqzIAo6tqs2H_dCrXFNeRAvsfWsileHm6tFn8AufzUjYUbNNP0oTRR_BfXdPqWcHe0zBDbSo0_iEw1FMK_e5Zg/w400-h208/diem+shock+model+20210228a.png" width="400" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;"><span style="font-size: x-small;">Positive + negative shock</span></td></tr></tbody></table><br /><table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto;"><tbody><tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhNN0Z-zhSuSS-VyG2Nk1qwkg5S1GFy1Fco2bSFE2tPrkFGnXtegvMpyFmNX8QZsLEewnkx-dGi14K20QV3HFbnfJkOdFi2eSn3AOommlLZVDEk_DitPAr8Vn_FN7QNL0YmqKEHc336pU4e/s911/diem+shock+model+20210228b.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="476" data-original-width="911" height="209" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhNN0Z-zhSuSS-VyG2Nk1qwkg5S1GFy1Fco2bSFE2tPrkFGnXtegvMpyFmNX8QZsLEewnkx-dGi14K20QV3HFbnfJkOdFi2eSn3AOommlLZVDEk_DitPAr8Vn_FN7QNL0YmqKEHc336pU4e/w400-h209/diem+shock+model+20210228b.png" width="400" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;"><span style="font-size: x-small;">Step response (see <a href="https://informationtransfereconomics.blogspot.com/2017/11/unemployment-rate-step-response-over.html">here</a>)</span></td></tr></tbody></table><br /><table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto;"><tbody><tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiI3emM_G038iWjoE45wOq6RRmj-Zu6B7KEI2dO9Xy1DxggFvhgtrkMK749xw6dWAliJoGFcBjaWKVXo_y4wlXb_mhHAz7gXOhoLB-7ztAwanV0TGAHtjGPhzn3X0yPSttg5HbxPMrKPh97/s911/diem+shock+model+20210228c.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="476" data-original-width="911" height="209" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiI3emM_G038iWjoE45wOq6RRmj-Zu6B7KEI2dO9Xy1DxggFvhgtrkMK749xw6dWAliJoGFcBjaWKVXo_y4wlXb_mhHAz7gXOhoLB-7ztAwanV0TGAHtjGPhzn3X0yPSttg5HbxPMrKPh97/w400-h209/diem+shock+model+20210228c.png" width="400" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;"><span style="font-size: x-small;">Negative "entropic" shock and return to equilibrium</span></td></tr></tbody></table><br /><table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto;"><tbody><tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgbhQFYkJedFFBkl7n3CIKL4DJji0EgAjchrPH58xYzBwifWSL2M9kayJO1g1JvWjOECuW83HxprtIBCKoyBxWZt19XUFjH0QW1jE-Age8a8c6Y8mUjjxr2EBE2zWtk3qgCH7dWIIM0XnPe/s911/diem+shock+model+20210228d.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="476" data-original-width="911" height="209" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgbhQFYkJedFFBkl7n3CIKL4DJji0EgAjchrPH58xYzBwifWSL2M9kayJO1g1JvWjOECuW83HxprtIBCKoyBxWZt19XUFjH0QW1jE-Age8a8c6Y8mUjjxr2EBE2zWtk3qgCH7dWIIM0XnPe/w400-h209/diem+shock+model+20210228d.png" width="400" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;"><span style="font-size: x-small;">Negative "entropic" shock and return to a different equilibrium</span></td></tr></tbody></table><br /><p style="text-align: justify;">I illustrate both the "entropic" shock models in <a href="https://informationtransfereconomics.blogspot.com/2016/03/the-emh-and-evaporating-information.html">this post on evaporating information</a>. The basic idea is that there's a shock to the time series and it either evaporates entirely or leaves some residual:</p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgDCntQbQCfk6dMj5TOe0MiNTLPA7KexOw5GLI_XhB5RLBPI2cU3I7HzOBaT7Sgr5JA3HB6wxeQAR_ZiTJmyZ-f6nSgn9ooT7jQijR77QZNNpYltXgkneD2nUYk0a8WwLIsk0khqxfyytA4/s720/price1+%25281%2529.gif" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="233" data-original-width="720" height="130" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgDCntQbQCfk6dMj5TOe0MiNTLPA7KexOw5GLI_XhB5RLBPI2cU3I7HzOBaT7Sgr5JA3HB6wxeQAR_ZiTJmyZ-f6nSgn9ooT7jQijR77QZNNpYltXgkneD2nUYk0a8WwLIsk0khqxfyytA4/w400-h130/price1+%25281%2529.gif" width="400" /></a></div><div class="separator" style="clear: both; text-align: center;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjC21_hCV4KZbMCmULvzBheT9cXm8jgsAe8Yoakz7Iry23wxwb8HJpUYHwqkF1JQ-Nw6oiYchyAmW-bVt_rxdMEbxh_um1EckdBcm9wagldxiNt5k8xtmHvF9AphuEQNIBolP131QLjAQYz/s720/price2.gif" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="233" data-original-width="720" height="130" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjC21_hCV4KZbMCmULvzBheT9cXm8jgsAe8Yoakz7Iry23wxwb8HJpUYHwqkF1JQ-Nw6oiYchyAmW-bVt_rxdMEbxh_um1EckdBcm9wagldxiNt5k8xtmHvF9AphuEQNIBolP131QLjAQYz/w400-h130/price2.gif" width="400" /></a></div><br /><div style="text-align: justify;">While the full return to equilibrium model, if looked at in a vacuum, does look like it describes the entire series more accurately; however, the errors are correlated and it did poorly at forecasting up until a specific event (the January stimulus payments). We can chalk that up to luck.</div><div style="text-align: justify;"><br /></div><div style="text-align: justify;">The entropic shock with return to a different equilibrium is the most parsimonious model (fewer independent parameters, lower RMS error, so lower <a href="https://en.wikipedia.org/wiki/Akaike_information_criterion">AIC</a>), but the two shock model is probably the best explanation — if we attribute the January 2021 deviation to stimulus payments we should include some identifiable effect from the April 2020 stimulus.</div><div style="text-align: justify;"><br /></div><div>Speaking of that January 2021 stimulus, <a href="https://twitter.com/infotranecon/status/1362595341376184321?s=20">I posited a couple weeks ago</a> that it looked like an evaporating shock itself. That seems less likely once we include more data:</div><div><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgN6roT7SXpcsVXSZIba0xcCFyTJ00DBvW7bMowhnSn9qTHdOxwwngateX70yhzdz1vrzFKWfsR-8uBtvWkjgOBrk_E8rACQSCRCX5eketJ-Z_xfl_y-bSMBXdwG-JZAqgppSjKBXRF3fZQ/s922/diem+shock+model+20210228d1.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="476" data-original-width="922" height="206" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgN6roT7SXpcsVXSZIba0xcCFyTJ00DBvW7bMowhnSn9qTHdOxwwngateX70yhzdz1vrzFKWfsR-8uBtvWkjgOBrk_E8rACQSCRCX5eketJ-Z_xfl_y-bSMBXdwG-JZAqgppSjKBXRF3fZQ/w400-h206/diem+shock+model+20210228d1.png" width="400" /></a></div><div><br /></div><div>In fact, a classic DIEM shock seems more appropriate:</div><div><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgOEKiPgsfZAfPqCY58tIb50QpJRrUJ4pnCbJ64P1B_mjaeVmtNg0-YM__nCfF39Z4tLl-u-TMeRYZy9MR54OIENJwjWX7lqbNSmic0kuMwH7BSZLV26hBA77i4h7CAcMxLOfIHs6ImClkl/s922/diem+shock+model+20210228d2.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="476" data-original-width="922" height="206" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgOEKiPgsfZAfPqCY58tIb50QpJRrUJ4pnCbJ64P1B_mjaeVmtNg0-YM__nCfF39Z4tLl-u-TMeRYZy9MR54OIENJwjWX7lqbNSmic0kuMwH7BSZLV26hBA77i4h7CAcMxLOfIHs6ImClkl/w400-h206/diem+shock+model+20210228d2.png" width="400" /></a></div><div><br /></div>Time will tell.<div><br /></div><div>In the aggregate <a href="https://fred.stlouisfed.org/series/PCE">PCE</a> data, it's hard to tell if we can see the January 2021 shock at all:<br /><div><br /></div><div><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjWupassnq8Iv013xeFmcLxFUfL4Y-H-lus0wklGvajFfOBC1u36j4OQyhMh2s0B6KPEDF3pHonm7jfiRRBNL6cPzUs9EMtSLhb4WLn1oNgDN6jQbkDrRvvfU4jYgVlvqwERsbkYs3JlAKh/s959/diem+PCE+20210228.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="453" data-original-width="959" height="189" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjWupassnq8Iv013xeFmcLxFUfL4Y-H-lus0wklGvajFfOBC1u36j4OQyhMh2s0B6KPEDF3pHonm7jfiRRBNL6cPzUs9EMtSLhb4WLn1oNgDN6jQbkDrRvvfU4jYgVlvqwERsbkYs3JlAKh/w400-h189/diem+PCE+20210228.png" width="400" /></a></div><br /><div style="text-align: justify;">It's only updated monthly, so doesn't have the temporal currency or resolution of the Opportunity Insights data. In this time series we can also see the effect of the <a href="https://informationtransfereconomics.blogspot.com/2019/05/tcja-and-pce-growth.html">TCJA implemented at the end of 2017</a>. The other impact of the TCJA seems to have been a negative shock to median sales prices of houses (<a href="https://informationtransfereconomics.blogspot.com/2019/07/continuing-decline-in-median-house-price.html">last update here</a>). There has been a recent bump up that may reflect <a href="https://twitter.com/dynarski/status/1365739551554215947?s=20">lack of inventory</a> since the COVID shock hit, but again that's another place where time will tell.</div></div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh9fPi5EJjb9X9Pnotil6F0WaXaGHWszRZ-pqDUwBUdYV-eStdzPaAAGFw-M1Z86TwvaRssRzowPyudUUcYff35s8pJtwH4LOtHbPY5M2sDR-b2HN9AJvtwvi2zCbW7U8D_8KusVzhYOkEQ/s792/diem+median+house+price+20210228a.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="475" data-original-width="792" height="240" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh9fPi5EJjb9X9Pnotil6F0WaXaGHWszRZ-pqDUwBUdYV-eStdzPaAAGFw-M1Z86TwvaRssRzowPyudUUcYff35s8pJtwH4LOtHbPY5M2sDR-b2HN9AJvtwvi2zCbW7U8D_8KusVzhYOkEQ/w400-h240/diem+median+house+price+20210228a.png" width="400" /></a></div><div style="text-align: justify;">I never got around to turning the reasoning for the TCJA (and its changes to the mortgage interest deduction) to be the source of that shock into a blog post after <a href="https://twitter.com/infotranecon/status/1222314244697288704">posting it on Twitter</a> at the end of January of 2020 — just before the COVID shock. The shock begins about a year before the Fed rate increase of December 2018, the other (at least theoretically) plausible culprit. I'm sure there are just-so models where people expected the future rate increase because of the higher deficit spending brought on by the TCJA, but I personally <a href="https://informationtransfereconomics.blogspot.com/2014/12/what-does-et-pit1-mean.html">prefer causality</a> in my models.</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh8r8A9CYJi1CwXuQIh5Xil7xn6bfvaeCjgpDVk5Eqy3bwxKmntDy9dRY9Yn_reS5ceaZb-punt0rLVbBKwmFvTNp6zymijZKxYgijDKQZUOjAFiOPhyheUAIbyFCQuZaE9dPTt0GFW_wzJ/s792/diem+median+house+price+20210228b.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="476" data-original-width="792" height="240" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh8r8A9CYJi1CwXuQIh5Xil7xn6bfvaeCjgpDVk5Eqy3bwxKmntDy9dRY9Yn_reS5ceaZb-punt0rLVbBKwmFvTNp6zymijZKxYgijDKQZUOjAFiOPhyheUAIbyFCQuZaE9dPTt0GFW_wzJ/w400-h240/diem+median+house+price+20210228b.png" width="400" /></a></div><br /><div style="text-align: justify;">On to another four letter acronym: <a href="https://fred.stlouisfed.org/series/ICSA">ICSA</a> (Initial Claims Seasonally Adjusted). I pretty much accurately described this "entropic shock" path back in June of 2020 (see previous post <a href="https://informationtransfereconomics.blogspot.com/2020/12/initial-claims-and-other-covid-19-shocks.html">here</a>), but now we have some additional evidence for some slight deviations in the model. First the big picture:</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg1urIsp1iRruvcaz2IygbOiOSVz15qRcpKfU6WyBxMoo7gh1x20iOs0vnncOqTERve8JWFJY0_hY3bB5nBmEf7bkXomBlMidRtgrSQ_1tvLL9REhWJtsvczooKr09clfk-NQSSKPPqpclx/s924/diem+icsa+20210228.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="418" data-original-width="924" height="181" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg1urIsp1iRruvcaz2IygbOiOSVz15qRcpKfU6WyBxMoo7gh1x20iOs0vnncOqTERve8JWFJY0_hY3bB5nBmEf7bkXomBlMidRtgrSQ_1tvLL9REhWJtsvczooKr09clfk-NQSSKPPqpclx/w400-h181/diem+icsa+20210228.png" width="400" /></a></div><div><br /></div><div style="text-align: justify;">And now zooming in a bit, we can see two correlated deviations in the summer of 2020 and fall/winter of 2020 into 2021 pretty much match up with the surges in COVID-19 cases in the US (and the accompanying layoffs):</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgu6bztc1tqJFKautjFTX39vdmkOdoirAlt5jASF9QwFHvz9DuehE9B4EY7EvsZTi0vmRiFo_NxtBB1h6bzruyWyBFvsbOO_s0Unge_qjHzpdiCkXOn7qmLHsTqbpNamwmltpDGH8bYsvWr/s924/diem+icsa+20210228a.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="408" data-original-width="924" height="176" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgu6bztc1tqJFKautjFTX39vdmkOdoirAlt5jASF9QwFHvz9DuehE9B4EY7EvsZTi0vmRiFo_NxtBB1h6bzruyWyBFvsbOO_s0Unge_qjHzpdiCkXOn7qmLHsTqbpNamwmltpDGH8bYsvWr/w400-h176/diem+icsa+20210228a.png" width="400" /></a></div><div><br /></div><div style="text-align: justify;">Although I talked about it <a href="https://informationtransfereconomics.blogspot.com/2020/12/initial-claims-and-other-covid-19-shocks.html">in the previous post</a>, I don't think I've shown my latest view of the unemployment rate based on <a href="https://twitter.com/JedKolko/status/1357694325002358790">Jed Kolko's "core" unemployment rate</a> (U5 minus temporary layoffs) that I refined <a href="https://twitter.com/infotranecon/status/1358567552964726784">in a Twitter thread</a> (U3 minus temporary layoffs, in order to compare to "headline" unemployment). New data is coming out next week, so now would be a good time to document my forecast.</div><div style="text-align: justify;"><br /></div><div>Here's U3 and the U3 "core" rate with temporary layoffs removed:</div><div><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgENIaCnI7fvA5aGnJ3tqGbClG0mGkOgJW1-THiinzMXX27R5umtGxLAf67yxittMiBtn18662gfBR6TViLcWiA30mUNVlmjJRRhajV7YnjlF30kTEv6Lokf45gl7XCgvtaqaHVbyyFzok1/s792/diem+unrate+20210228b.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="460" data-original-width="792" height="233" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgENIaCnI7fvA5aGnJ3tqGbClG0mGkOgJW1-THiinzMXX27R5umtGxLAf67yxittMiBtn18662gfBR6TViLcWiA30mUNVlmjJRRhajV7YnjlF30kTEv6Lokf45gl7XCgvtaqaHVbyyFzok1/w400-h233/diem+unrate+20210228b.png" width="400" /></a></div><div><br /></div><div style="text-align: justify;">As you can see, the relationship between "core" U3 and U3 has been relatively stable until the COVID-19 shock with its mass "temporary" (?) layoffs. The core rate continues to be well-described by the DIEM with its standard logistic (approximately Gaussian derivative) shocks, but the temporary layoffs required — like many of the time series here — an "entropic" shock in order to be able to describe headline (U3) inflation. I believe this forecast will be pretty accurate barring any additional shocks:</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjUCtb6GqU3fGUhp4EWt8BSfLPj8lbd_kfOH5urBEWVk_1sbosBrorzn_MIcd2-rr-bTmvHAiS2e7f10x3JFVWwbJINiwMa4fmWNsZBoebEQoSK_3XYPl88v7TJfq3cLOESevBk9owH4Qy6/s792/diem+unrate+20210228a.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="460" data-original-width="792" height="233" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjUCtb6GqU3fGUhp4EWt8BSfLPj8lbd_kfOH5urBEWVk_1sbosBrorzn_MIcd2-rr-bTmvHAiS2e7f10x3JFVWwbJINiwMa4fmWNsZBoebEQoSK_3XYPl88v7TJfq3cLOESevBk9owH4Qy6/w400-h233/diem+unrate+20210228a.png" width="400" /></a></div><br /><div><br /><div><div style="text-align: justify;">That's it for the updates. One of the major lessons for modeling economic time series in the COVID era has been accounting for these rapidly evaporating "entropic" shocks — everything from the <a href="https://twitter.com/infotranecon/status/1333189970002026496">S&P 500</a> to the unemployment rate. Recession and demographic shocks are extremely slow moving by comparison.</div><div><div style="text-align: justify;"><br /></div></div></div></div>Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com0tag:blogger.com,1999:blog-6837159629100463303.post-1630018486463890872020-12-10T13:33:00.003-08:002020-12-10T13:41:12.947-08:00Initial claims and other COVID-19 shocks<p style="text-align: justify;">Back in June of 2020, <a href="https://twitter.com/infotranecon/status/1268610307917660160">I posted</a> an estimate of the future path of <a href="https://fred.stlouisfed.org/series/ICSA">initial claims</a> [1] on Twitter (click to enlarge):</p><p style="text-align: justify;"><br /></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgCg_DD9y20GNU4gwjdI9KsuZZMuz7dyAU98GBx8HhksZu6iCxwOe1KWMQmO9UM1Fr_7TsLJIzoL0Uqn_0v3UjwYTUBKB18yLQ_Xe7YWhksFueW_TOx5UR75TurN-74Z5pjamggWHenGL3t/s897/EZsB9DDVcAEgHv7.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="414" data-original-width="897" height="185" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgCg_DD9y20GNU4gwjdI9KsuZZMuz7dyAU98GBx8HhksZu6iCxwOe1KWMQmO9UM1Fr_7TsLJIzoL0Uqn_0v3UjwYTUBKB18yLQ_Xe7YWhksFueW_TOx5UR75TurN-74Z5pjamggWHenGL3t/w400-h185/EZsB9DDVcAEgHv7.png" width="400" /></a></div><div style="text-align: justify;">While the rate of improvement was overestimated, it captured the qualitative behavior quite well:</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgBUjlE-9OuEL9i8PE6pgR2JqSz0vNUuf1qCMhV4Sem9Vms37CQhSoU2_pwhQEvZBoK35HRHtxXlsTbY_2gwGtGN-uLj-w0UyrBZse5RaCsdEoDWrC7YIcpgHgbRw2XsO55xlrBpwMogfZK/s924/diem+icsa+20201210.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="418" data-original-width="924" height="181" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgBUjlE-9OuEL9i8PE6pgR2JqSz0vNUuf1qCMhV4Sem9Vms37CQhSoU2_pwhQEvZBoK35HRHtxXlsTbY_2gwGtGN-uLj-w0UyrBZse5RaCsdEoDWrC7YIcpgHgbRw2XsO55xlrBpwMogfZK/w400-h181/diem+icsa+20201210.png" width="400" /></a></div><div><br /></div><div style="text-align: justify;">Being able to predict the qualitative behavior of the time series in the future is pretty good confirming evidence for a hypothesis — not the least of which being there's no way you could have had access to data in the future without travelling through time. The underlying concept was that the rate of improvement after the initial spike would gradually fall back to the long term equilibrium (logarithmic rate) of about −0.1/y (which shows up as the line that is almost at zero):</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi7Q5UuC164oIA5z7rk8tAdxX3aQqrJcPU3Xt-BYVmaekoFtwwrI4sCA_eQ13UjUIBY-yR_FJD65z-gOEeUemgn6Z6Ko7_2A1SpfTkLGsZYpzeZc20pxyIh_Hdi_5qa5vPrZnUPOvd0s2pn/s792/diem+icsa+20201210a.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="398" data-original-width="792" height="201" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi7Q5UuC164oIA5z7rk8tAdxX3aQqrJcPU3Xt-BYVmaekoFtwwrI4sCA_eQ13UjUIBY-yR_FJD65z-gOEeUemgn6Z6Ko7_2A1SpfTkLGsZYpzeZc20pxyIh_Hdi_5qa5vPrZnUPOvd0s2pn/w400-h201/diem+icsa+20201210a.png" width="400" /></a></div><br /><div style="text-align: justify;">The hypothesis is that while the initial part of the non-equilibrium shock was a sharp spike, there is an underlying component that is a more typical, more gradual, shock. One way to visualize it is in the unemployment rate via "core" unemployment (per <a href="https://twitter.com/JedKolko/status/1334855102092308481">Jed Kolko</a>):</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEglwuBqy1WNQIanzXiFFPLtuDv5JdRxtmRvgyOIFK8K8mJc11ndXEaL5SBwxQAGsrJbW32ntT-NfPK-ILCgnthu80G3pNrmcLIFTp86BkZcPq7vG0rX3RvXPPYyaUIFTqO_aQYOMnmqHo3e/s1003/EoaxtpQUUAIVfIS.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="481" data-original-width="1003" height="191" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEglwuBqy1WNQIanzXiFFPLtuDv5JdRxtmRvgyOIFK8K8mJc11ndXEaL5SBwxQAGsrJbW32ntT-NfPK-ILCgnthu80G3pNrmcLIFTp86BkZcPq7vG0rX3RvXPPYyaUIFTqO_aQYOMnmqHo3e/w400-h191/EoaxtpQUUAIVfIS.png" width="400" /></a></div><br /><div style="text-align: justify;">Here's a cartoon version. In the current recession, we're seeing something that hasn't been that apparent (or at least as rapid) in the data [2]. There's the normal recession (solid line) as well as a sharp spike (dashed):</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiS6L80WY6zIk4Vra0OCjlf6f2MiYjFOJE0AQgnNiRTHTYfM0lvRM1rzxiP8y_q5BKlLO0FYzZbopNdcjrQ0X-1h1-wEs3YH5HvKmij8_wtLBmlFtsw1MRdw8SKVw5AkLzV_rGrMI9h2l1t/s792/diem+approach+1.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="464" data-original-width="792" height="234" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiS6L80WY6zIk4Vra0OCjlf6f2MiYjFOJE0AQgnNiRTHTYfM0lvRM1rzxiP8y_q5BKlLO0FYzZbopNdcjrQ0X-1h1-wEs3YH5HvKmij8_wtLBmlFtsw1MRdw8SKVw5AkLzV_rGrMI9h2l1t/w400-h234/diem+approach+1.png" width="400" /></a></div><br /><div style="text-align: justify;">Instead of the usual derivative that's a single (approximately Gaussian) shock (solid line), we have a more complex structure with a smoothly falling return to the usual dynamic equilibrium (here exaggerated to −0.2/y so it looks different from zero):</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEglQ72tFjOD65ev4eOmuReazoj_7rEN2YKPRA4XtMneM1OtAyQoihAQVcHo3oy0PwsY7JBxXQJbNV8SYX1roKJQnoqpFYpe4xlr-_yqos11lhfun6wKnvIl0hsiaEsqkH6R_6OT9UropVTm/s792/diem+approach+2.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="463" data-original-width="792" height="234" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEglQ72tFjOD65ev4eOmuReazoj_7rEN2YKPRA4XtMneM1OtAyQoihAQVcHo3oy0PwsY7JBxXQJbNV8SYX1roKJQnoqpFYpe4xlr-_yqos11lhfun6wKnvIl0hsiaEsqkH6R_6OT9UropVTm/w400-h234/diem+approach+2.png" width="400" /></a></div><br /><div style="text-align: justify;">Zooming in on the box in the previous graph, we get the cartoon version of the data above (dashed curve) that eventually asymptotes to the long run dynamic equilibrium rate:</div><div style="text-align: justify;"><br /></div><div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgK6HkDU9okqxeB_WMZdigZXfOyEev5ab8g3tkkLl9iM_DqhcBdnmRYrx2LnU6rmj3kU8fjYUfxHy5vMDG-crVLbxveQhLITfg7QivtZLG-6pySK75QFwCn2oOJxcxldnLs2klcLX_KWn84/s792/diem+approach+3.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="458" data-original-width="792" height="231" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgK6HkDU9okqxeB_WMZdigZXfOyEev5ab8g3tkkLl9iM_DqhcBdnmRYrx2LnU6rmj3kU8fjYUfxHy5vMDG-crVLbxveQhLITfg7QivtZLG-6pySK75QFwCn2oOJxcxldnLs2klcLX_KWn84/w400-h231/diem+approach+3.png" width="400" /></a></div><br /><div style="text-align: justify;">Since we haven't had a shock of this type before in the available data with mass temporary layoffs, it's at least not <i><b>entirely </b></i>problematic to suggest an ad hoc model like this one. The underlying "<a href="https://informationtransfereconomics.blogspot.com/2016/03/the-emh-and-evaporating-information.html">evaporation</a>" of the temporary shock information is based on the entropic shocks that appear in the stock market (including for this exact same COVID-19 event as well as the December 2018 Fed rate hike): </div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjMe5Oyi5kDFliHysUnlS7eT8u8DXFICkiILbI2ed9NzAW44ErlgaBRGnlz_2rmNEzCO3H0YHYlduBl_Dzh10vwf09PkJveiEh9c9XV9XT5x2Hf55Clx-moS44goFqmko7E1XINMANOcgvE/s576/hotpotato2.gif" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="312" data-original-width="576" height="216" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjMe5Oyi5kDFliHysUnlS7eT8u8DXFICkiILbI2ed9NzAW44ErlgaBRGnlz_2rmNEzCO3H0YHYlduBl_Dzh10vwf09PkJveiEh9c9XV9XT5x2Hf55Clx-moS44goFqmko7E1XINMANOcgvE/w400-h216/hotpotato2.gif" width="400" /></a></div><br /><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEisewEm-cD0cTVTVTyWp7BW0Fzm5NpJykD6C2HRNCooRKWsnNG9Ta8hCuwJtxVP2-A0s2mG565jgkdcEaDnjc3-Xl1CqVSbmOYrFXpYPu16dENUPFKyR8pjRUFZKRQQfOpLZTcbZYZdmjCY/s1168/fredgraph+%25288%2529.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="450" data-original-width="1168" height="154" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEisewEm-cD0cTVTVTyWp7BW0Fzm5NpJykD6C2HRNCooRKWsnNG9Ta8hCuwJtxVP2-A0s2mG565jgkdcEaDnjc3-Xl1CqVSbmOYrFXpYPu16dENUPFKyR8pjRUFZKRQQfOpLZTcbZYZdmjCY/w400-h154/fredgraph+%25288%2529.png" width="400" /></a></div><br /><div><br /></div><div><br /></div><div>...</div><div><br /></div><div><b>Footnotes:</b></div><div><br /></div><div style="text-align: justify;"><span style="font-size: x-small;">[1] This is not what would be the <a href="https://informationtransfereconomics.blogspot.com/2017/12/dynamic-information-equilibrium-model.html">technically correct model in terms of dynamic equilibrium</a>, but over this short time scale the civilian labor force has been roughly constant since June. It doesn't really change the shape except for the initial slope which is lower because it is undersampled using only monthly CLF measurements instead of weekly ICSA measurements:</span></div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiQa9fsaGMNCRCDSi3e080mxlglIeqYy8F-uJxlW9PrBOxvy2cf0ENjLD5Ur0PehkGP8_huPkohAnfutOIrzrtfHV4FYbQpuFZRZ37BEk68bam19LdZwQwqrxEER6W-lbSshd2PvvzvwpE_/s1168/fredgraph+%25287%2529.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="450" data-original-width="1168" height="77" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiQa9fsaGMNCRCDSi3e080mxlglIeqYy8F-uJxlW9PrBOxvy2cf0ENjLD5Ur0PehkGP8_huPkohAnfutOIrzrtfHV4FYbQpuFZRZ37BEk68bam19LdZwQwqrxEER6W-lbSshd2PvvzvwpE_/w200-h77/fredgraph+%25287%2529.png" width="200" /></a></div><div><span style="font-size: x-small;"><br /></span></div><div><span style="font-size: x-small;">The "real" model isn't that different:</span></div><div><span style="font-size: x-small;"><br /></span></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj5y9YC0lt48zthkezH1EKIFA8q96ZkWhuAA58_Byczm4RrzS7pyLPV_pM23GojWM19O5FMfq-Dd0aMEUgrrs2vKvQvngT_bpHf_ibGZWPa0-EOoM-FGKEzWtdtihRkoeePGVmXWnt0mIwx/s720/diem+claims+rate+1.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="441" data-original-width="720" height="122" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj5y9YC0lt48zthkezH1EKIFA8q96ZkWhuAA58_Byczm4RrzS7pyLPV_pM23GojWM19O5FMfq-Dd0aMEUgrrs2vKvQvngT_bpHf_ibGZWPa0-EOoM-FGKEzWtdtihRkoeePGVmXWnt0mIwx/w200-h122/diem+claims+rate+1.png" width="200" /></a></div><div><span style="font-size: x-small;"><br /></span></div><div><div style="text-align: justify;"><span style="font-size: small;">[2] It's possible the "</span><a href="https://informationtransfereconomics.blogspot.com/2017/11/unemployment-rate-step-response-over.html" style="font-size: small;">step response</a><span style="font-size: small;">" in the unemployment rate in the 1950s and 60s is a similar effect, but nowhere near as rapid.</span></div><p style="text-align: justify;"><br /></p></div></div>Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com0tag:blogger.com,1999:blog-6837159629100463303.post-79603601621601767652020-12-06T22:51:00.004-08:002021-09-21T19:00:53.905-07:00Qualitative economics done right, part N [1]<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgE6yTMUCaS2YN2aInNZVZvGMuAKKfoW6ZEwFUK1zTBWsOL3il6dP9l4Ie_EwJjHyNK5Eyebn2dgEKLESDSgJHcdKwGHdANly37Dj7cByGOAutDpwSrnwWXy-H5BtCzdc6Hl4ltODf5ckOt/s1400/GettyImages_1127317526.jpg" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="788" data-original-width="1400" height="225" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgE6yTMUCaS2YN2aInNZVZvGMuAKKfoW6ZEwFUK1zTBWsOL3il6dP9l4Ie_EwJjHyNK5Eyebn2dgEKLESDSgJHcdKwGHdANly37Dj7cByGOAutDpwSrnwWXy-H5BtCzdc6Hl4ltODf5ckOt/w400-h225/GettyImages_1127317526.jpg" width="400" /></a></div><br /><p style="text-align: justify;">I seem to have involved myself in a Twitter dispute with economist Roger Farmer about what it means to make macro models — or <a href="https://twitter.com/infotranecon/status/1335450024650502144">more broadly</a> "the nature of the scientific enterprise", as Roger the economist kindly tried to explain to me, a physicist. Unfortunately, due to his prolific use of the quote tweet the argument is likely impossible to follow. You can see the various threads via <a href="https://twitter.com/search?q=from%3A%40infotranecon%20to%3A%40farmerrf&f=live">this search</a>.</p><p style="text-align: justify;"><b>Background</b></p><p style="text-align: justify;">This started when I noted that Roger Farmer's claims about unemployment — in particular in papers supporting his claims that he cites <a href="https://static1.squarespace.com/static/573b5f2bf85082a897b58171/t/5744d8813c44d82d4deb92fe/1464129666308/fa-con-cra.pdf">here</a> Farmer (2011) and <a href="https://static1.squarespace.com/static/573b5f2bf85082a897b58171/t/57449cf0cf80a18d18ad6c03/1464114417622/stock_market_really.pdf">here</a> Farmer (2015) — are inconsistent with the long run qualitative behavior of the unemployment rate data. That is to say the models are not consistent with the empirical fact that the unemployment rate between recessions falls at a logarithmic rate of about −0.09/y in the US (BYDHTTMWFI: <a href="https://www.nber.org/papers/w28111">here's a recent NBER paper</a>).</p><p style="text-align: justify;">Let me say right off that I actually appreciate Roger Farmer's work — he does seem to think outside the box compared to the DSGE approach to macro that has taken over the field.</p><p style="text-align: justify;">I am going to structure this summary in a series of claims that I am <b><i><u>not</u></i></b> making because it seems many people have confused requiring qualitative agreement with data with <a href="https://en.wikipedia.org/wiki/G-factor_(physics)#Measured_g-factor_values">precise measurements of the electron magnetic moment</a>.</p><p style="text-align: justify;">Here we go!</p><p><b>I am not saying models with RMS error ε ≥ <i>x</i> must be rejected.</b></p><p style="text-align: justify;">The funniest part about this is that <a href="https://twitter.com/infotranecon/status/1335712243716038656">in my figure</a> that I use to show the Roger's model's lack of qualitative agreement actually shows the DIEM has worse RMS error over the range of the data Roger shows in his graph [2].</p><p style="text-align: justify;">The thing is it's easy to get low RMS error on past data simply by adding parameters to a fit. This does not necessarily work with projected data, but in general more parameters often yield a better fit to past data and sometimes a better short run projection.</p><p style="text-align: justify;">However, <a href="https://twitter.com/infotranecon/status/1335101554005745665">my original claim</a> that started this off was that his model based on shocks to the stock market in the supporting papers was "disconnected from the long run empirical behavior of the unemployment rate". It's true that if you take the shocks to the unemployment rate and add the dynamic equilibrium of the S&P 500 model, you get a short run correlation that lasts from 1998 to about 2010:</p><p><br /></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEioILVx-aSFA92b-m42gtEktNLbA4GkwYf-d3ZHP2Tp7Yj1QvSUAaqiDDX2HsgPIv57ggIu3VB4469n6T50__kKG3KHbnygXiDHYj2A-XIH1WyLnXcsxoZCaHVki0eCS8HHDmGGIFOSktAL/s1007/diem+sp500+unrate+2.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="416" data-original-width="1007" height="165" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEioILVx-aSFA92b-m42gtEktNLbA4GkwYf-d3ZHP2Tp7Yj1QvSUAaqiDDX2HsgPIv57ggIu3VB4469n6T50__kKG3KHbnygXiDHYj2A-XIH1WyLnXcsxoZCaHVki0eCS8HHDmGGIFOSktAL/w400-h165/diem+sp500+unrate+2.png" width="400" /></a></div><div><br /></div><div style="text-align: justify;">This correlation around the 2008 recession is pointed out in Farmer (2011) Figure 2. However, you only have to go back to the early 90s recession to get a counterexample to the idea that shocks to the S&P 500 match up with shocks to the unemployment rate.</div><div style="text-align: justify;"><br /></div><div style="text-align: justify;">Second, there is also no particular empirical evidence that the unemployment rate will flatten out at any particular level (be it the natural rate in neoclassical models, or in Farmer's models a rate based on asset prices).Third, Farmer's models do not show log-linear decline between recession shocks. </div><div style="text-align: justify;"><br /></div><div style="text-align: justify;">It is these three basic empirical facts about the unemployment rate that I was referencing when I made my claim in that initial tweet. Even if the RMS error is bad, a model of the unemployment rate is at least qualitatively consistent with the data if 1) the shocks are not entirely dependent on the stock market, 2) the rate does not flatten out at any level except possibly <i>u </i>= 0, or 3) shows an average log-linear decline of −0.09/y between recessions (a fact that was called out in <a href="https://www.nber.org/papers/w27234">a recent NBER paper</a>, <a href="https://twitter.com/hashtag/bydhttmwfi">BYDHTTMWFI</a>).</div><div style="text-align: justify;"><br /></div><div style="text-align: justify;"><b><i>What I am saying</i></b> is that Roger's models are not qualitatively consistent with the data — think a model of gravity where things fall up — and should be rejected on those grounds. The unemployment rate literally levitates in his models. Additionally there exist models with lower RMS error and qualitative agreement with the data; the existence of those models should give us pause when considering Roger's models.</div><p><b>I am not calling for Roger Farmer to stop working on his models.</b></p><p style="text-align: justify;">It's fine by me if he wants to give talks, write blog posts about his model, or think about improving it in the privacy of his own research notebook. I would prefer that he grapple with the fact that the models are not qualitatively consistent with the data instead of getting defensive and saying that they don't have to pass that low bar. I believe models that are not qualitatively consistent with the data should <b><i>not </i></b>be used for policy, though — <a href="https://twitter.com/farmerrf/status/1335398453627609089">and that is one of Roger's aims</a>.</p><p style="text-align: justify;">It's true that a lot of ideas start out kind of wrong — it's unrealistic to expect a model to match the data exactly right out of the gate. And that's fine! I've had a ton of bad ideas myself! But there is no reason we should expect half-baked ideas lacking qualitative agreement with the data to be taken seriously in the larger marketplace of ideas. </p><p style="text-align: justify;">So many comments on the feed were about working towards an insight or the models being just an initial idea that could be improved. Most of us don't get a chance to put even really good ideas in front of a lot of people, so why should we accept something that's apparently not ready for prime time just because it's from a tenured professor? I have a Phd and a lot of garbage models of economic systems that aren't even qualitatively accurate in my Mathematica notebook directory — should we consider all of those? In any case, "it may lead to future progress" is not a reason to say "oh, fine then" to models that aren't qualitatively consistent with empirical data.</p><p style="text-align: justify;"><b><i>What I am saying</i></b> is that we should set the bar higher for what we consider useful models in macro than "it might qualitatively agree with data one day". We can leave discussion of those models out of journals and policy recommendations.</p><p><b>I am not saying we should apply the standards of physics to economics.</b></p><p style="text-align: justify;">This goes along with people saying I shouldn't be applying "Popperian rejection" to economic models. First off, this misconstrues Popper who was talking about falsifiability as a condition for scientific theories as opposed to pseudoscience. Roger's models are falsifiable — I don't think they are pseudoscience. However, Popper didn't really say much about models being <i>falsified</i> despite the fact that lots of people think he did.</p><p style="text-align: justify;">General Relativity is a better model than Newtonian gravity, but both models are falsifiable. We consider Newtonian gravity to be incorrect for strong gravitational fields, precise enough measurements in weak fields, or velocities close to the speed of light. We still use good old Newton all the time — I did just the other day for an orbital dynamics question at work. I fully understand the difference between a model that is an approximation and one that is supposed to be a precise representation of reality.</p><p style="text-align: justify;">Popper, however, did not say anything about models that don't qualitatively agree with the data. That's because in most of science, such models are thrown out before they are ever published. Economics, especially macro, operates in a different mode where I guess they consider models that look nothing like the data.<i> Ok, I know the time series data is an exponentially increasing amplitude sine wave and this model says it's a straight line, but hear me out!</i></p><p style="text-align: justify;">If the standards for agreement with the data are below qualitative agreement with the data, then there's really no reason to throw out <a href="https://informationtransfereconomics.blogspot.com/2017/02/qualitative-economics-done-right-part-2.html">Steve Keen's models</a> [3]. But that's the problem — there are models that agree with the data! David Andofatto's simple model <a href="https://twitter.com/infotranecon/status/1282078731989684224">matches the data fairly well</a> qualitatively! (It gets points 1 and 3 above and could be set to <i>u*</i> = 0 to get 2.) The existence of those models should set the bar for the level of empirical accuracy we should accept in macro models.</p><p style="text-align: justify;"><b><i>What I am saying</i></b> is that there are existing models that more precisely match the data — and that is the standard I am using. It's not physics, but rather the performance other economic models. If you have a model that has worse RMS error, but has better qualitative agreement with the data, then that's ok to bring to the table. Overall, there seems to be far too much garbage that is allowed in macro because, well, there apparently wouldn't be any macro papers at all if some basic standards were enforced. When I say these models that aren't even qualitatively consistent with the data should be thrown out, I'm not talking about Popperian rejection, I am talking about <i><a href="https://en.wikipedia.org/wiki/Scholarly_peer_review#Procedure">desk rejection</a></i>.</p><p style="text-align: justify;"><b>One last point ... what is the use of a model that doesn't qualitatively agree with data?</b></p><p style="text-align: justify;">I didn't have a way to phrase this one as something I'm not saying. I literally cannot fathom how you can extract anything useful from a model that does not qualitatively agree with the data. This is lowest bar I can think of.</p><p style="text-align: justify;"><i>Yes this model looks nothing like the data but it's useful because I can use it to understand things based on ...</i></p><p style="text-align: justify;">That ellipsis is where I cannot complete the sentence. Based on gut feelings? Based on divine revelation? If the model looks nothing like the data, what is anything derived from it derived <i>from</i>? The pure mathematical beauty of its construction?</p><p style="text-align: justify;">It's like someone saying "Here's my model of a car!" and they show you a cat. <i>Yes, this cat isn't qualitatively consistent with a car, but it's a useful first step in understanding a car. The cat gives me insights into how the car works. And you really shouldn't be using Popperian rejection of the cat model of a car because automobile engineering is not the same as physics. Making a detailed car model is unnecessary for figuring out how it works — a cat is perfectly acceptable. Eventually, this cat model will be improved and will get to a point where it matches car data well. The cat model also allows me to make repair recommendations for my car. You see the cat has a front and a back end, where the front has two things that match up with the car headlights, and yes the fuel goes in the front of the cat while it goes in the side of a car but that's at least qualitatively similar ...</i></p><p>...</p><p><b>Update 7 December 2020</b></p><p style="text-align: justify;">Also realized Roger has made a <a href="https://twitter.com/farmerrf/status/1335398452218347521">major stats error here</a>:</p><blockquote style="border: none; margin: 0px 0px 0px 40px; padding: 0px;"><p style="text-align: justify;"><i>Jason Jason. @infotranecon I really don’t know where to start. 1. The unemployment rate is I(1) to a first approximation. 2. The S&P measured in real units is I(1) to a first approximation. The two series are cointegrated. The S&P Granger causes the unemployment rate.</i></p></blockquote><p style="text-align: justify;">Here's <a href="https://davegiles.blogspot.com/2015/10/cointegration-granger-causality.html">Dave Giles</a>, econometrician emeritus extraordinaire:</p><blockquote style="border: none; margin: 0px 0px 0px 40px; padding: 0px;"><p style="text-align: justify;"><i>If two time series, X and Y, are cointegrated, there must exist Granger causality either from X to Y, or from Y to X, both in both directions.</i></p></blockquote><p>...</p><p><b>Footnotes</b></p><p style="text-align: justify;"><span style="font-size: x-small;">[1] The title is a reference to <a href="https://informationtransfereconomics.blogspot.com/2017/02/qualitative-economics-done-right-part-1.html">my old series</a> that led, among other places, to realizing <a href="https://informationtransfereconomics.blogspot.com/2018/01/qualitative-economics-done-right-part-3.html">Wynne Godley has been maligned</a> by people who ostensibly support him, and that <a href="https://informationtransfereconomics.blogspot.com/2018/05/no-one-saw-this-coming-bezemers.html">Dirk Bezemer fabricated quotes</a> in his widely cited paper.</span></p><p style="text-align: justify;"><span style="font-size: x-small;">[2] I do find it problematic that Roger not only cuts off the data early compared to data that was available at the time Farmer (2015) was published, but also cuts of data that was available at the time <i>that would appear in the domain of his graph </i>— data that emphasizes that the model does not qualitatively match the data. He also uses quarterly unemployment data which further reduces the disagreement.</span></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjifTcUxFWfhngL9_pb2FFb9lLGRkKUeQgMPm2XNX7BqAVGNI-br2q-u0y1Ezu2GWuh0znXWcM3A6BkXci4Xnhs1tLYqxc78rG4kDaTkrAUOqkJq6b2bf-UqRB4Q-s5oovGLewYy9Jr3PCP/s676/farmerB.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="500" data-original-width="676" height="148" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjifTcUxFWfhngL9_pb2FFb9lLGRkKUeQgMPm2XNX7BqAVGNI-br2q-u0y1Ezu2GWuh0znXWcM3A6BkXci4Xnhs1tLYqxc78rG4kDaTkrAUOqkJq6b2bf-UqRB4Q-s5oovGLewYy9Jr3PCP/w200-h148/farmerB.png" width="200" /></a></div><span style="font-size: x-small;">[3] I mean c'mon!</span><div><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhFnZca2l3JM-MihmFLKSLid4OqklnSiUJFoMPEmMo2VSyId0_G8IyL1k3iaUgbO83WLeBQ-_SPLoLdxkhrfDZxoJg07_e_s-UPKtoVm7ZHvUARW9w0CvAqHUr0bkxY8KQKg2KDoATaR06J/s1280/Slide5.PNG" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="720" data-original-width="1280" height="181" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhFnZca2l3JM-MihmFLKSLid4OqklnSiUJFoMPEmMo2VSyId0_G8IyL1k3iaUgbO83WLeBQ-_SPLoLdxkhrfDZxoJg07_e_s-UPKtoVm7ZHvUARW9w0CvAqHUr0bkxY8KQKg2KDoATaR06J/w320-h181/Slide5.PNG" width="320" /></a></div><br /><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjYVTbGEnp59RlW05bP5AzkFD0lA6peVVc_s2T67-ZSfgBp_Xm2Dzp2BsYu762TtXBztrePh3ul1iY81wDANnNYqZDEDMSdH7eEgKyV84kRSbM3sAay-bwWtUpgDvLRc8c8DdNLm695oznb/s1280/Slide4.PNG" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="720" data-original-width="1280" height="181" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjYVTbGEnp59RlW05bP5AzkFD0lA6peVVc_s2T67-ZSfgBp_Xm2Dzp2BsYu762TtXBztrePh3ul1iY81wDANnNYqZDEDMSdH7eEgKyV84kRSbM3sAay-bwWtUpgDvLRc8c8DdNLm695oznb/w320-h181/Slide4.PNG" width="320" /></a></div><br /><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjfECOU23nD9jYeqtUjAxViycDkLEsFDlB-w-1z4i8kLIngirL2pPMfJHtwRLaK8HUQsU7o9PSUGLxK24Tan9ip_C4CpxsjFZ_nYG72NyFldcDVODVLhyq5SKJmV3nn4XDYc7jQ2-As1xfo/s1280/Slide6.PNG" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="720" data-original-width="1280" height="181" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjfECOU23nD9jYeqtUjAxViycDkLEsFDlB-w-1z4i8kLIngirL2pPMfJHtwRLaK8HUQsU7o9PSUGLxK24Tan9ip_C4CpxsjFZ_nYG72NyFldcDVODVLhyq5SKJmV3nn4XDYc7jQ2-As1xfo/w320-h181/Slide6.PNG" width="320" /></a></div><br /><div><br /><p><br /></p><br /><br /></div>Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com0tag:blogger.com,1999:blog-6837159629100463303.post-46901426616622305192020-10-18T12:14:00.004-07:002020-10-18T12:17:06.016-07:00The four failure modes of Enlightenment values<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgCZ_UuDP3dn0eaYb9AftbTPJ-_eezFMh-tCMVOeelLr43J5VORVrFcj9C-lAlE48vZxVPA4cqjCK6QUwAy0o4XMM_X0ElQnEEAd3D1itU9ny0l1tbBy2ntyX2Nd5FG_Fx6kzyE9Vo4lS2b/s1200/declaration-of-independenceFMEA.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="675" data-original-width="1200" height="225" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgCZ_UuDP3dn0eaYb9AftbTPJ-_eezFMh-tCMVOeelLr43J5VORVrFcj9C-lAlE48vZxVPA4cqjCK6QUwAy0o4XMM_X0ElQnEEAd3D1itU9ny0l1tbBy2ntyX2Nd5FG_Fx6kzyE9Vo4lS2b/w400-h225/declaration-of-independenceFMEA.png" width="400" /></a></div><br /><div style="text-align: justify;">I don't write about process as much these days — in part because I'm no longer working my previous project that had me effectively commuting across the country every month to the middle of nowhere, and in part because I'm now working a much bigger project that barely leaves me enough time to update even the existing <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3094757">dynamic information equilibrium model</a> forecasts. But recently there seems to be an upswing in calls for civility, declarations of incivility, and long sighs about about how to criticize the "correct" way. I saw George Mason economist Peter Boettke tweet out <a href="https://www.brainpickings.org/2014/03/28/daniel-dennett-rapoport-rules-criticism/">this</a> the other day that includes a list of "rules" for how to criticize:</div>
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<i>How to compose a successful critical commentary:</i></div>
<ol>
<li style="text-align: justify;"><i>You should attempt to re-express your target’s position so clearly, vividly, and fairly that your target says, "Thanks, I wish I’d thought of putting it that way."</i></li>
<li style="text-align: justify;"><i>You should list any points of agreement (especially if they are not matters of general or widespread agreement).</i></li>
<li style="text-align: justify;"><i>You should mention anything you have learned from your target.</i></li>
<li style="text-align: justify;"><i>Only then are you permitted to say so much as a word of rebuttal or criticism.</i></li>
</ol>
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It seems fitting that Boettke would tweet this out given his defense of the racist economist/public choice theorist James Buchanan. It's pure "Enlightenment" rationalism — the same Enlightenment that gave us many advances in science, but also <a href="https://slate.com/news-and-politics/2018/06/taking-the-enlightenment-seriously-requires-talking-about-race.html">racism and eugenics</a>. These rules are in general a great way to go about criticism — but if and only if certain norms are maintained. If these norms aren't maintained, these rules inculcate us with a vulnerability to what I've called <a href="https://informationtransfereconomics.blogspot.com/2017/03/academic-norms-and-charles-murray.html">viruses of the Enlightenment</a>. To put in the terms of my job: this process has not been subjected to failure mode effect analysis (FMEA) and risk management.</div>
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<br /></div><div style="text-align: justify;">This isn't intended to be a historical analysis of what the "Enlightenment" was, how it came to be, or its purpose, but rather how the rational argument process aspect is used — and misused — in discourse today. I've identified a few failure modes — the vulnerabilities of "Enlightenment" values.</div>
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<b>Failure mode 1: Morally repugnant positions</b><br />
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I'm under the impression that like bioethics, medical ethics, or scientific ethics, someone needs to convene an interdisciplinary ethics of rational thought. There are still occasions when science seems to think the pursuit of knowledge is an aim higher than any human ethics, and failures run the gamut from the recent protests to building another telescope on Mauna Kea (<a href="https://en.wikipedia.org/wiki/Thirty_Meter_Telescope_protests">part of a longer series of protests</a>) to unethical human experiments.</div>
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Rationalism seems to continue to hold this view — that anything should be up for discussion. But we've long since discovered that science can't just experiment on people without considering the ethics, so why should we believe rationalism can just say whatever it wants?</div>
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Unfortunately, since we are humans and not rational robots, the discussion of some ideas themselves might spread or exacerbate morally repugnant beliefs. This is contrary to the stated purpose of "Enlightenment values" — open discussion that leads to the "best" ideas winning out in the "marketplace of ideas". And if that direct causality breaks (open discussion → better ideas), the rationale for open discussion is weakened [0]. Simply repeating a lie or conspiracy theory i<a href="https://www.wired.com/2017/02/dont-believe-lies-just-people-repeat/">s known to strengthen the belief in it</a> — in part from <a href="https://en.wikipedia.org/wiki/Familiarity_heuristic">familiarity heuristic</a>. And we know that simply changing the framing of a question on polls can change people's agreement or disagreement. Right wing publications try to launder their ideas by simply getting mainstream publications to acknowledge them, pulling them out the "conservative ecosystem" — as Steve Bannon has specifically talked about (see <a href="https://www.washingtonpost.com/opinions/2020/10/15/trumps-fake-new-biden-scandal-has-deeper-purpose-bannon-revealed-it/">here</a>).</div>
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Rule #1 fails to acknowledge our humanity. Simply repeating a morally repugnant idea can help spread it, and in the very least requires the critic to carry water for a morally repugnant idea. I cannot be required to restate someone's position that's favorable racism because that requires giving racism my voice, and immorally helping the cause of racism.</div>
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For example, Boettke's defense of Buchanan requires him to carry water for Buchanan. If we consider the possibility that Nancy MacLean's claims of a right-wing conspiracy to undermine democracy and promote segregation are true (I am not saying they are, and people I respect — e.g. <a href="http://crookedtimber.org/2018/09/18/my-last-word-on-nancy-maclean/">Henry Farrell</a> — strongly disagree with that interpretation of the evidence), then carrying that water should be held to a level of ethical scrutiny a bit higher than, say, discussing the differences between Bayesian and frequentist interpretations of probability.</div>
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This is not to say we shouldn't talk about Buchanan or racism. It's not like we don't experiment with human subjects (e.g. clinical trials). It's just that when we do, there are various ethical questions that need to be formally addressed from informed consent to what we plan to learn from that experiment. A human experiment where we ask the question about whether humans feel pain from being punched in the face is not ethical <b><i>even if we have consent from the subjects</i></b> because the likelihood of learning something from it is almost zero. "I'm just asking questions" here is not a persuasive ethical argument.</div>
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This is in part why I think shutting down racists from speaking on college campuses isn't problematic in any way. Would we authorize a human experiment where we engage in a campaign of intimidation of minorities just to measure the effects? We already know about racist thought — it's not like these are new ideas. They're already widely discussed — <b><i>that's how students on campuses know what to protest.</i></b> And in terms of ethical controls, we might well consider that the moral risk managed solution consistent with intellectual discourse is to have these “speakers” write their “ideas” down, have the forum led by someone who is not a famous racist, or possibly is even opposed to the “ideas” [3].</div>
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<b>Failure mode 2: Over-representation of the elite</b><br />
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I criticized <a href="https://twitter.com/farmerrf/status/989503121876434944">Roger Farmer's acceptance</a> of Hayek's interpretation that prices contain information on Twitter a year or so ago (for more detail on my take, you can check out <a href="https://evonomics.com/hayek-meets-information-theory-fails/">my <i>Evonomics </i>article</a>). Farmer subsequently unfollowed me on Twitter which likely decreases the engagement I get through Twitter’s algorithms.</div>
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Now my point here is not that one is obligated to listen to every crackpot (such as myself) and engage with their “ideas”. It’s that we cannot feasibly exist in a world where all expression is heard and responded to — regardless of how misguided or uninformed. And who would want that?</div>
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But it does mean participation via the (purportedly) egalitarian Enlightenment ideals of “free speech” and “free expression” in the marketplace of ideas is already limited. And the presumption of “equals” engaging in mutual criticism behind Bottke's “rules” artificially limits the bounds of criticism <i>further</i>. Already elites pick and choose the criticism they engage with — giving them an additional power of “permission” distorts the power balance even more.</div>
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Unfortunately public speech and public attention ends up being rationed the same way most scarce resources are rationed — by money. The elite gatekeepers at major publications push the opinions and findings of their elite comrades through the soda straw of public attention. We hear the opinions of millionaires and billionaires as well as people who find themselves in circles where they occasionally encounter billionaires far more often than is academically efficient. <a href="https://www.bloomberg.com/opinion/articles/2019-09-15/free-speech-on-campus-democracy-requires-discomfort">Bloomberg</a> and <a href="https://www.insidehighered.com/news/2019/07/17/steven-pinkers-aid-jeffrey-epsteins-legal-defense-renews-criticism-increasingly">Pinker</a> talking about free speech. <a href="https://en.m.wikipedia.org/wiki/Warren_Mosler">MMT</a>. <a href="https://www.salon.com/2017/04/20/discrimination-101-how-koch-devos-families-fund-hate-speech-on-u-s-college-campuses_partner/">Charles Murray</a>.</div>
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Bloomberg writing at bloomberg.com is a particularly egregious example of breaking the egalitarian norm. Bloomberg's undergraduate education is in electrical engineering from the 1960s and he has a business degree from the same era. He has no particular qualifications to judge the quality of discourse, the merits of the freedom of speech, or who should be forced to tolerate right wing intimidation on college campuses. He is in the position he is in because he made a great deal of money which enabled him to take a chance on running for office and becoming mayor of New York.</div>
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That said, I don't have particular expertise in this area — but then I don't get to write at bloomberg.com.</div>
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As such, “cancelling” the speech of these members of the elite mitigates this bias almost regardless of the actual reason for the cancellation simply because they’re over-represented.</div>
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More market-oriented people might say having billions of dollars must mean you’ve done at least something right and therefore could result in being over-represented in the marketplace of ideas. That's an opinion you can argue — in the marketplace of ideas — not implement by fiat. Now this is just my own opinion, but I think having too much money seems to make people less intelligent. Maybe life gets too easy. Maybe you lose people around you that disagree with you because they're dependent on your largess. Lack of intellectual challenge seems to turn your brain to mush in the same way lack of physical activity turns your body to mush. You might have started out pretty sharp, but — whatever the reason — once the cash piles up it seems to take a toll. I mean, have you listened to Elon Musk lately? However, even if you believe having billions of dollars means you have something worthwhile to say, that is <b><i>not </i></b>the Enlightenment's egalitarian ethos. King George III had a lot more money than any of the founders of the United States, but it's not like they felt compelled to invite him or his representatives to speak at the signing of the Declaration of Independence.</div>
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While everyone has a right to say what they want, that right that does not grant everyone a platform. The “illiberal suppression” of speech can be a practical prioritization of speech. "Cancelling" can mitigate systemic biases, enabling a less biased, more genuine discourse. Why should we have to listen to the same garbage arguments over and over again? Even if they aren’t garbage, why the repetition? And even if the repetition is valid, <i style="font-weight: bold;">why must we have the same people doing the repeating? </i>[1] An objective function optimized for academic discussion should prioritize novel ideas, not the same people rehashing racism, sexism, or even “enlightenment” values for 30 years.</div>
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It's true that novelty for novelty's sake creates its own bias in academia — journals are biased towards novel results rather than confirmation of last year's ideas creating a whole new set of problems. In addition to novel ideas, verifiability and empirically accuracy would also be good heuristics. Expertise or credentials in a particular subject is often a good heuristic for priority, but like the other heuristics it is just that — a heuristic. Knowing when to break with a heuristic is just as valuable as the heuristic itself.</div>
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In any case, just assuming elites and experts should be free from criticism unless it meets particular forms of "civility" or that their "ideas" should be granted a platform free from being "cancelled" do not further the <i>spirit </i>of the Enlightenment values that most of us agree on — that what's true or optimal ought to win out in the marketplace of ideas.</div>
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<br /></div><div style="text-align: justify;"><div style="text-align: justify;"><b>Failure mode 3: Rational thought and academic research is not free speech</b></div><div style="text-align: justify;"><br /></div><div style="text-align: justify;">Something obvious in the norms in Boettke's list is that he appears to recognize rational argument differs from free speech. "Free speech" does not require you to speak in some proscribed manner — that would <i>ipso facto</i> fail to be free speech. </div><div style="text-align: justify;"><br /></div><div style="text-align: justify;">However, the ordinary process by which old ideas die off through rational argument seems to be conflated with suppressing free speech these days. Having your paper on race and IQ rejected for publication because it rehashes the old mistakes and poor data sets is normal rational progress, not the suppression of free speech. "Just asking questions" needs to come to grips with the fact that lots of those questions have been asked before and have lots of answers. Just as we don't need to continuously rehash 19th century aether theory, we don't need to continuously rehash 19th century race science [2].</div><div style="text-align: justify;"><br /></div><div style="text-align: justify;">When shouts of "free speech" are used as a cudgel to force academic discussion of degenerative research programs in Lakatos' sense, it represents a failure mode of "Enlightenment" values and science in general. In order for science and the academy to function, it needs to rid itself these degenerative research programs regardless of whether rural white people in the United States continue to support them. If these research programs turn out to not be degenerative — well, there's a pretty direct avenue back into being discussed via those new results showing exactly that. Assuming they follow ethical research practices, of course.</div></div><div style="text-align: justify;"><br /></div>
<b>Failure mode 4: People don't follow the spirit of the rules</b><br />
<br /><div style="text-align: justify;">Failure to follow the spirit of these rules tends to be rampant in any "school of thought" that claims to challenge orthodoxy from race science to Austrian economics. Feynman's famous "<a href="https://www.blogger.com/blog/post/edit/6837159629100463303/4690142661662230519#">cargo cult science</a>" commencement address is a paean to the spirit of the rules of science (and "Enlightenment" values generally), but unlike Boettke's rules for others Feynman asks fledgling scientists to direct the rules inward — "The first principle is that you must not fool yourself — and you are the easiest person to fool."</div><div style="text-align: justify;"><br /></div>
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This failure mode is far less intense than discussing racism, unethical human experiments or plutocracy, but is far more common. Certainly, the "straw man" application of Rule #1 falls into this. But one of the most frustrating is the one many of us feel when engaging with e.g. MMT acolytes — never acknowledging that you have "re-express[ed] your target’s position ... clearly, vividly, and fairly."</div>
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Randall Wray or William Mitchell (e.g.) simply never acknowledge any criticism is valid or accurate. Criticism is <a href="http://neweconomicperspectives.org/2019/02/response-to-doug-henwoods-trolling-in-jacobin.html">dismissed</a> as <i>ad hominem</i> attacks instead of being acknowledged. If "successful" critical commentary (per the "rules") requires the subjects to grant you permission, any criticism can be shut down by a claim that the critic doesn't know what they are talking about.</div><div style="text-align: justify;"><br /></div><div style="text-align: justify;">This failure to follow the spirit of the rules appears in numerous ways, from claims that simply expressing a counterargument isn't civil discourse to the failure of someone espousing racist views to admit that those views are actually racist [4] to general hypocrisy. However, the end effect is that failure to follow the spirit of the rules is an attempt to enable the speaker with the ability to grant permission to which facts or counterarguments are allowed and which aren't. That's not really how "Enlightenment values" are supposed to work.</div>
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Being granted permission by the subject of criticism is also generally unnecessary to actual progress. Humans — especially established public figures — rarely listen to criticism. Upton Sinclair, Bertrand Russell, and Max Planck captured different dimensions of this (a rationale, a mechanism, and a real course of progress) in pithy quotes (respectively):</div>
<blockquote class="tr_bq" style="text-align: justify;">
<i>It is difficult to get a man to understand something, when his salary depends upon his not understanding it!</i> </blockquote>
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<i>If a man is offered a fact which goes against his instincts, he will scrutinize it closely, and unless the evidence is overwhelming, he will refuse to believe it. If, on the other hand, he is offered something which affords a reason for acting in accordance to his instincts, he will accept it even on the slightest evidence.</i> </blockquote>
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<i>A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it.</i></blockquote>
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This is how the world has always been. Your audience for your criticism is never the subjects of the criticism, but rather the next generation. Explaining your subject's position before criticizing it is done as part of Feynman's "<a href="https://en.wikipedia.org/wiki/Cargo_cult_science">leaning over backward</a>" — for yourself — not legitimacy.</div><div style="text-align: justify;"><br /></div><div style="text-align: justify;"><b>Other failure modes</b></div><div style="text-align: justify;"><br /></div><div style="text-align: justify;"><span style="text-align: left;">I wanted to collect my thoughts on free speech, "cancelling", and the terrible state of "the discourse" in one essay. </span>This list is not meant to be exhaustive, and I may expand it in the future when I have new examples that don't fit in the previous four categories. For example, you might think that academic journals are a form of intellectual gatekeeping — and I'd agree — but I believe that falls under failure mode 2: the over-representation of the elite, not a separate category. There are also genuine workarounds in that case that everyone uses (arXiv, SSRN). You may also disagree with the particular choice of basis — and I'm certain another orthonormal set of failure modes could span the same failure effect space.</div>
<div style="text-align: justify;"><br /></div><div style="text-align: justify;">Also, because I talk about MMT along with Public Choice and racism, it doesn't mean I equate them. There are similarities (both get a leg up through the support of billionaires), but I am trying to find examples from across a broad spectrum of politics and political economy. There are major failures and minor. However, I think the examples I've chosen most clearly illustrate these failure modes.</div><div style="text-align: justify;"><br /></div><div style="text-align: justify;">I have been sitting on this essay for nearly a year. I was motivated to action by <a href="https://twitter.com/infotranecon/status/1317870747424096258">a tweet</a> from Martin Kulldorff, a professor at the Harvard Medical School about how Scott Atlas was "censored" [5] for spreading misinformation about the efficacy of various coronavirus mitigations (from masks to lockdowns). Atlas is on the current administration's "Coronavirus Task Force" and a fellow at the Hoover institution — a front for right wing views funded by billionaires. There is literally no universe in which this is a true egalitarian "Enlightenment" discussion — from the elite over-representation with Harvard and the billionaires at Hoover to the lack of disclosure of conflicts of interest (failure modes 2 and 4, respectively). That far too many people think Atlas being "censored" is against the spirit of the Enlightenment is exactly how it can fail.</div><br />
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<b>Footnotes:</b><br /><div style="text-align: justify;"><span style="font-size: x-small;"><br /></span></div><div style="text-align: justify;"><span style="font-size: x-small;"><span style="text-align: left;">[0] This is similar to </span><a href="https://informationtransfereconomics.blogspot.com/2015/01/is-market-intelligent.html" style="text-align: left;">the argument against markets as mechanisms for knowledge discovery</a><span style="text-align: left;"> — information leakage in the causal mechanism breaks it.</span></span></div><div style="text-align: justify;"><span style="font-size: x-small;"><span style="text-align: left;"><br /></span></span></div><div style="text-align: justify;">
<span style="font-size: x-small;"><span>[1] More on this <a href="https://informationtransfereconomics.blogspot.com/2017/03/academic-norms-and-charles-murray.html">here</a>. Why do we have to hear </span><span><b><i>specifically</i></b></span><span><b><i> </i></b>Charles Murray talk about race and IQ? (TL;DR because it's not about ideas, but rather signalling and authority.)</span></span></div><div style="text-align: justify;"><span style="font-size: x-small;"><br /></span></div><div style="text-align: justify;"><span style="font-size: x-small;"><span>[2] Personally, I think IQ tests should include a true/false question that asks if you think there's nothing wrong with believing the racial or ethnic group to which you belong has on average a higher IQ than others. Answering "true" would indicate you're probably bad at understanding self-bias that is critical to scientific inquiry and should reduce your score by at least 1/2. </span><font>As George Bernard Shaw said, </font><span style="text-align: left;"><font>“Patriotism is your conviction that this country is superior to all other countries because you were born in it.” Racism is at its heart your conviction that your race is superior to all other races because you were born into it — the rest is confirmation bias.</font></span></span></div><div style="text-align: justify;"><span style="text-align: left;"><font size="2"><br /></font></span></div><div style="text-align: justify;"><span style="text-align: left;"><font size="2">[3] In <i>Star Trek: The Next Generation </i>"Measure of a Man" (S:2 E:9), Commander Riker is tasked with prosecuting the idea that the android Lt. Commander Data is not a person, but rather Federation property — something with which Riker personally disagrees.</font></span></div><div style="text-align: justify;"><span style="text-align: left;"><font size="2"><br /></font></span></div><div style="text-align: justify;"><span style="text-align: left;"><font size="2">[4] I have never really understood this. Unless you're hopelessly obtuse, you must know if you have racist views. Why would you be upset about other people identifying them as such? The typical argument being supported by racist views is that racism is correct and right! A racist (who happens to be white by pure coincidence) who believes that other non-white people have lower IQs through some genetic effect is trying to support racism. I have so much more respect for racists, like a pudgy white British man who appears in the beginning of <i>The Filth and the Fury</i> (2000) who openly admits he is racist. That's the Enlightenment!</font></span></div><div style="text-align: justify;"><span style="text-align: left;"><font size="2"><br /></font></span></div><div style="text-align: justify;"><span style="text-align: left;"><font size="2">[5] In no way is this censorship and calling it that is risible idiocy. The tweets were removed on Twitter, a private company, not by the US government. And Atlas still has access to multiple platforms — including amplification by elite Harvard professors, which is what is actually happening.</font></span></div>
Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com4tag:blogger.com,1999:blog-6837159629100463303.post-65308731834156820902020-07-18T15:55:00.004-07:002020-10-02T14:04:33.999-07:00Dynamic information equilibrium and COVID-19<script type="text/x-mathjax-config"> MathJax.Hub.Config({tex2jax: {inlineMath: [['$','$'], ['\\(','\\)']]}}); </script> <script src="https://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML" type="text/javascript"> </script>
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Since I've gotten questions, I thought I'd put together a brief explainer on the Dynamic Information Equilibrium Model (DIEM) and its application to the path of COVID-19.</div>
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<b>Prolog</b></div>
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I wrote a preprint on the DIEM a couple years ago (<a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3094757">posted at SSRN</a>), and gave a talk about the approach at the UW economics department (<a href="https://informationtransfereconomics.blogspot.com/2018/10/outside-box-workshop.html">see here</a>). The primary application was to labor markets, specifically the unemployment rate. However, the model has <a href="https://informationtransfereconomics.blogspot.com/2017/05/explore-more-about-information.html">many other applications in economics</a> (and the original <a href="https://arxiv.org/abs/0905.0610">information equilibrium</a> approach has applications to physics). So how did I end up applying this model to COVID-19? It started from laziness.</div>
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Back in April, I was looking at the various models of COVID-19 out there, in particular <a href="https://covid19.healthdata.org/united-states-of-america">the IHME model</a>. I wanted to compare the performance to the data, but instead of coding it up myself I took a screenshot and digitized the data. Digitizing adds error and digitizing exponentially falling functions creates all kinds of problems, so I instead fit the IHME forecasts with a DIEM model since I had the code readily available.</div>
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It turned out to do a decent job of describing the IHME models, but additionally when there were discrepancies with the observed data it turned out the DIEM worked better. Thinking about the foundations of the DIEM, the reason it worked became clear.</div>
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<b>DIEM</b></div>
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The DIEM is an application of "information equilibrium" — the idea that one process $A$ can be the source of information for another process $B$ such that it takes the same number of bits of (<a href="https://en.wikipedia.org/wiki/Information_theory">information theory</a>) information to specify $A$ as it does to specify $B$. In a sense, if $A$ is in information equilibrium with $B$ then the two are informationally equivalent. Information equilibrium constrains what a process that matches e.g. $A$ with $B$ can look like.</div>
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That's all very abstract, but in economics we have demand for a good being matched with supply (creating a transaction) or job openings being matched with unemployed people (creating a hire) — in equilibrium. In the case of COVID-19, we have <i>virus</i> + <i>healthy person</i> $\rightarrow$ <i>sick person</i>. </div>
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Like any communication channel transferring information, these matches can fail to happen. Voices are garbled on a cell phone call causing a failure of the information specifying the sound waves going into the the speaker's phone being transferred completely to the sound waves coming out of the listener's phone. Information equilibrium is something of an idealized state that can be interrupted by non-equilibrium. It may seem vacuous to say sometimes you have equilibrium and sometimes you have non-equilibrium, but the information theory underlying it gives us some useful handles (e.g. failures to fully sample the underlying space, correlations, or other changes in information entropy).</div>
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<i>Dynamic </i>information equilibrium asks what information equilibrium can tell us when the processes $A$ and $B$ are growth processes.</div>
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\[<br />
\begin{align}<br />
A & \sim e^{a t}\\<br />
B & \sim e^{b t}<br />
\end{align}<br />
\]<br />
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Just because they are "growth" processes, that doesn't mean they are growing — they could be shrinking or $A$ could be growing and $B$ could be shrinking.</div>
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If you go to <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3094757">the paper</a> you can get the details of the mathematics (including how this generalizes to <i>ensembles </i>of processes), but the key result is that information equilibrium requires</div>
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\[<br />
\frac{d}{dt} \log \frac{A}{B} \simeq (k - 1) b \equiv \alpha<br />
\]<br />
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where $k$ measures the relative information content of events in process $A$ versus events in process $B$. What this says is that if you look at the data on a log plot versus time, it will consist mostly of data where the rate of growth of decline of the data will be a straight line (i.e. exponential growth or decay with constant log-linear slope).</div>
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Mostly. What makes this DIEM a model and not a theory is that there's an assumption about what happens in non-equilibrium. In the original application of the model to the unemployment rate, there was an assumption that the straight line isn't interrupted by non-equilibrium too much — that non-equilibrium events are sparse in the time series data. If this wasn't true, then it'd be impossible to measure that $\alpha$ and your model of non-equilibrium would be everything. In labor markets, recessions are the sparse non-equilibrium events in the unemployment rate and the recovery is the equilibrium:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg6YrxXznKgYZB-xrJWlaiKr2Qsj5W2ga2t32GaGqho6_mANlmis7i2R3PwzeZZIuGkM4rRfH68JjEapSH9skV31-eb6LgQtdvOdSkPBmrJRcbcdNcDF0290Q4FlBYPSq8RwNJRuzph63eV/s622/rrr.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="622" data-original-width="576" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg6YrxXznKgYZB-xrJWlaiKr2Qsj5W2ga2t32GaGqho6_mANlmis7i2R3PwzeZZIuGkM4rRfH68JjEapSH9skV31-eb6LgQtdvOdSkPBmrJRcbcdNcDF0290Q4FlBYPSq8RwNJRuzph63eV/s320/rrr.png" /></a></div>
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Adding in a logistic step function to handle the recessions shocks gives us a description of the unemployment rate (and other economic variables) over time:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiF3QaxkWSh3MvomPx2xAF5XXbBIpLP917Zw8eYPyW9nNzq1JjHCK3fzawDNLNABAfHAxwNXShCHu13oyv8gT-ouxa6IU-ssPP858yAp5lJRm7VfC9etDIBZUZvBXK5R6NsDFXG_rDjesJf/s792/Beveridge+curve+wage+growth+unemployment.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="483" data-original-width="792" height="125" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiF3QaxkWSh3MvomPx2xAF5XXbBIpLP917Zw8eYPyW9nNzq1JjHCK3fzawDNLNABAfHAxwNXShCHu13oyv8gT-ouxa6IU-ssPP858yAp5lJRm7VfC9etDIBZUZvBXK5R6NsDFXG_rDjesJf/w205-h125/Beveridge+curve+wage+growth+unemployment.png" width="205" /></a><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEibm3GLSWRYKWfaWlVUitox1gsZfRR-QV7Q1wW1WjzulWbs1WyjL-Wn32GREQHGC1jim1LejVCogA17AEpWg3JEz73zKbETlSk2QWq_dQckBJdwlq3ZKf7lA662WmHL-NdoEeyqpk2Ez15v/s680/unrate.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="411" data-original-width="680" height="123" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEibm3GLSWRYKWfaWlVUitox1gsZfRR-QV7Q1wW1WjzulWbs1WyjL-Wn32GREQHGC1jim1LejVCogA17AEpWg3JEz73zKbETlSk2QWq_dQckBJdwlq3ZKf7lA662WmHL-NdoEeyqpk2Ez15v/w205-h123/unrate.png" width="205" /></a></div>
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<b>COVID-19</b></div>
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It turns out that the DIEM is really good model of the data for COVID-19 cases and deaths and the forecast from April for the path of the outbreak in the US was remarkably accurate — at least until the 2nd surge in the most recent data (i.e. a non-equilibrium event):</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg-YnbxorM7DZ3BQBbI0Pro57OfV4Hmx6ZntI00YcuJmL9SXzcIdZlMK5MzriF_jzDur7WKlCrS3Fj3MgQbK41GHo4cpumNuo9NQYv22mjWRjrcUZRrSt2gBWY9N9GlWA-5AE_wmLbzUDPs/s792/us+forecast+2.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="464" data-original-width="792" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg-YnbxorM7DZ3BQBbI0Pro57OfV4Hmx6ZntI00YcuJmL9SXzcIdZlMK5MzriF_jzDur7WKlCrS3Fj3MgQbK41GHo4cpumNuo9NQYv22mjWRjrcUZRrSt2gBWY9N9GlWA-5AE_wmLbzUDPs/s320/us+forecast+2.png" width="320" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiGWrbQ_YYx-7eFHxkINUWjDAj-X0ZKSDqbA5zBirvRRHaJZx1ZnSULlxO1jMqw4nne-h58gIbMdrNujBVZRDKsQQYzSJfI26eZu_2s4oJ13fYTeRSCSTeq4riF8gSDTX5sm5tpmDDdryfv/s792/us+forecast+3.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="465" data-original-width="792" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiGWrbQ_YYx-7eFHxkINUWjDAj-X0ZKSDqbA5zBirvRRHaJZx1ZnSULlxO1jMqw4nne-h58gIbMdrNujBVZRDKsQQYzSJfI26eZu_2s4oJ13fYTeRSCSTeq4riF8gSDTX5sm5tpmDDdryfv/s320/us+forecast+3.png" width="320" /></a></div>
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The model works well for most countries, for example here are Italy and the UK (click to enlarge):</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjhr_ca-RnMQDGo7SdUqscyTr5u54gjtUblFHUf7KQCjZbBZxhyphenhyphen6YEia7AGO2dVrsaAkM7gEQCKrPhdWvZX8K8EilO64-p6KDPDYtxYlKZuARN5QrnKAo1gUQ3p7SJ-nJXleTW_B-YYN3XY/s792/italy+deaths+20200718.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="464" data-original-width="792" height="120" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjhr_ca-RnMQDGo7SdUqscyTr5u54gjtUblFHUf7KQCjZbBZxhyphenhyphen6YEia7AGO2dVrsaAkM7gEQCKrPhdWvZX8K8EilO64-p6KDPDYtxYlKZuARN5QrnKAo1gUQ3p7SJ-nJXleTW_B-YYN3XY/w205-h120/italy+deaths+20200718.png" width="205" /></a><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjBRqjg0k7SqxW6HSaf0klLhcnnmL3ZCXoh3cKR2ZC0HcCybiiNA-aVNQRsZE3cOSyH5tpzxv0Z6pAFk4bAe2oj9XrTZ5EglLlY1-jGbCgbh5cAQ96xYkPUiX7Rj2sjI22AmBc1scog317G/s792/uk+deaths+20200718.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="464" data-original-width="792" height="120" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjBRqjg0k7SqxW6HSaf0klLhcnnmL3ZCXoh3cKR2ZC0HcCybiiNA-aVNQRsZE3cOSyH5tpzxv0Z6pAFk4bAe2oj9XrTZ5EglLlY1-jGbCgbh5cAQ96xYkPUiX7Rj2sjI22AmBc1scog317G/w205-h120/uk+deaths+20200718.png" width="205" /></a></div>
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The fact that we can't really see that 2nd surge until it starts is due to the model being too simple to predict non-equilibrium events. It can, however, be used to see when a non-equilibrium event is getting started and then monitor its progress. For example, back on May 20th <a href="https://twitter.com/infotranecon/status/1263163398423863296">I was predicting</a> the beginning of a 2nd surge in Florida based on the DIEM model of cases there (and I later added a 2nd non-equilibrium shock, which can be handled using e.g. <a href="https://informationtransfereconomics.blogspot.com/2017/04/determining-recessions-with-algorithm.html">this algorithm</a>):</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiNf6rwy6tGJOH7_ZvLdHNssnYQpX-ogwFZ6VW_7BLetY4LH-4UsV9CWih7skkVXSXRRHr48pGcEcsaL86uASE05g7XP4R7Yw3k8sehIErGKikTiT5WzZiXpdAXJQ6n2iZE-nZ4Bv2FUQLQ/s792/EYeoMkOUMAA40Qm.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="492" data-original-width="792" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiNf6rwy6tGJOH7_ZvLdHNssnYQpX-ogwFZ6VW_7BLetY4LH-4UsV9CWih7skkVXSXRRHr48pGcEcsaL86uASE05g7XP4R7Yw3k8sehIErGKikTiT5WzZiXpdAXJQ6n2iZE-nZ4Bv2FUQLQ/s320/EYeoMkOUMAA40Qm.png" width="320" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgTGA5JkpuRE6uBIZJR9CO5YIzregHZkhnEINw1OC8nyYIjWzAFGIz2BuGoNSYNppzeL0HYoTILQlgmiJrvzQueU_7Wan9e2J5cmszTRq5Olw6Zg3Y1OBndE5DkQNHNI5Ou-QxGEZj_vntr/s792/fl+cases+20200716+a.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="483" data-original-width="792" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgTGA5JkpuRE6uBIZJR9CO5YIzregHZkhnEINw1OC8nyYIjWzAFGIz2BuGoNSYNppzeL0HYoTILQlgmiJrvzQueU_7Wan9e2J5cmszTRq5Olw6Zg3Y1OBndE5DkQNHNI5Ou-QxGEZj_vntr/s320/fl+cases+20200716+a.png" width="320" /></a></div>
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Another limitation of the model is that it has explicit assumptions that the number of events $n$ you're seeing is large $n \gg 1$. This means the model does not work well when there are just a few cases or deaths and for the initial onset of the outbreak. For example, here is South Korea:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjoINxAZshSyPnFrt-qdAL8N7bdz8aVLEGQrjZZKcSIM40UQSg6H6n7hLh_NDED6qmW2IXp9gDdBEzDX49RFLVcZHSeVKa3eU5QYTcK-73l26cut4slN81GcRcIYK7fW5DC2WIjdv55Hjhn/s792/korea+deaths+20200718.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="458" data-original-width="792" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjoINxAZshSyPnFrt-qdAL8N7bdz8aVLEGQrjZZKcSIM40UQSg6H6n7hLh_NDED6qmW2IXp9gDdBEzDX49RFLVcZHSeVKa3eU5QYTcK-73l26cut4slN81GcRcIYK7fW5DC2WIjdv55Hjhn/s320/korea+deaths+20200718.png" width="320" /></a></div>
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Related to the $n \gg 1$ assumption, we basically start an outbreak at $t_{0}$ in the midst of a non-equilibrium shock with dynamic equilibrium valid for $t \gt t_{0}$. This is effectively treated in the model as if a previous outbreak had recently ended (so that dynamic equilibrium is also valid for $t \lt t_{0}$). The model that would deal with the initial outbreak would almost certainly have to incorporate specifics of the individual virus and the networks it travels in that is beyond the scope of information equilibrium — itself a "shortcut" in describing complex systems.</div>
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<b>Other observations</b></div>
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One the things the model predicts is that after a 2nd (or 3rd) surge, the data should return to the previous log-linear path unless something has changed. This appears to be happening for several regions — Germany and King County, WA for example:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj6165m42Y6CK7SYT5f9cmELYRgD_srxGomlkn7_s6yUOXXyjG_dmY6qwF8-XnyyVu8jeIw7B6smzhUrffhZQk-Xo-Hh_AGUfLyUhWKzJOTnaAT8n1vHmgvcrFfUB8phDR87P4XDju8M-OV/s792/germany+cases+20200721+a.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="456" data-original-width="792" height="118" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj6165m42Y6CK7SYT5f9cmELYRgD_srxGomlkn7_s6yUOXXyjG_dmY6qwF8-XnyyVu8jeIw7B6smzhUrffhZQk-Xo-Hh_AGUfLyUhWKzJOTnaAT8n1vHmgvcrFfUB8phDR87P4XDju8M-OV/w205-h118/germany+cases+20200721+a.png" width="205" /></a><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgvzcqDe1g7pYZYuxAOk_5mUrx6lMymqYPHaXOpJZ6K1cMDVApQ6kKTUa9r6eAtwWgRx_L1NNpoS6bbQEHwAogWuogu3kAXUkyu9Q43fPERFJ2mmXv1gFMPp0FzZqpVGN3IpPZMzEmt5I1x/s915/king+county+cases+20200716.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="453" data-original-width="915" height="101" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgvzcqDe1g7pYZYuxAOk_5mUrx6lMymqYPHaXOpJZ6K1cMDVApQ6kKTUa9r6eAtwWgRx_L1NNpoS6bbQEHwAogWuogu3kAXUkyu9Q43fPERFJ2mmXv1gFMPp0FzZqpVGN3IpPZMzEmt5I1x/w205-h101/king+county+cases+20200716.png" width="205" /></a></div>
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This remains to be seen if this holds up. In Sweden, the rate of decline after the 2nd surge in cases seems to have improved and is now comparable to Germany's</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhD8xSxFLmIFVyP4nJjO2Sd4PRXG5ARJEpIxLWZH6nlU6FWRUQIyNXhBC7cpQ9i1fAYVZ1R6DQlOnJtkZ7rS9CFdCuUOwYZJw_NmFkfIzfIZDXXSlUBsFNYG5IXorNMjWdVKt3k2e0HSkdL/s792/sweden+cases+20200721+a.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="465" data-original-width="792" height="294" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhD8xSxFLmIFVyP4nJjO2Sd4PRXG5ARJEpIxLWZH6nlU6FWRUQIyNXhBC7cpQ9i1fAYVZ1R6DQlOnJtkZ7rS9CFdCuUOwYZJw_NmFkfIzfIZDXXSlUBsFNYG5IXorNMjWdVKt3k2e0HSkdL/w500-h294/sweden+cases+20200721+a.png" width="500" /></a></div>
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Previously, Sweden's rate of decline in cases of $\alpha \simeq$ 2% per day was approximately the same as most of the US — about half the rate of 4-5% apparent in most of Europe as well as in NY state (dominated by counts from NYC). Did people in Sweden change behavior in the face of that 2nd surge? It's an open question. [<i>See update 25 July 2020 below.</i>]</div>
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Another thing we need to keep in mind that these are <b><i>reported </i></b>cases and deaths. With testing increasing in many countries, more and more cases are discovered. This results in an obvious difference between the rate of decline for cases in the US versus that for deaths:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiZm-0kdpxRFNlPK0RcNcVr8IBm7uNrmIjusSOPVo79sezNwfV1bfOikJ1n83037815UvGTjiYsCOfEsaDlp8jBOH1oYE-it4bgie72xnRueJUBjcVkma0eRfWCXqp892a_LJ7i4GMDhIki/s1007/us+cases+and+deaths+1a.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="456" data-original-width="1007" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiZm-0kdpxRFNlPK0RcNcVr8IBm7uNrmIjusSOPVo79sezNwfV1bfOikJ1n83037815UvGTjiYsCOfEsaDlp8jBOH1oYE-it4bgie72xnRueJUBjcVkma0eRfWCXqp892a_LJ7i4GMDhIki/w500-h226/us+cases+and+deaths+1a.png" width="500" /></a></div>
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Other countries have much more similar rates of decline for the two measures. For the US, this means the rate of decline for cases is somewhat lower than would be if testing was widely available. That is to say observed $\alpha_{US} \simeq \alpha_{US}^{\text{cases}} + \alpha_{US}^{\text{testing}}$. It also means the observed rate of decline for cases must decrease at some point in the future (e.g. once testing far outpaces transmission). As it is, the "case fatality rate" (CFR) appears to be heading to zero:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgSCda3iTWAhtkroCrFXrpUg_8s-IMjILm4Bqwqj8Y5aPD9zZE1FmN8NoCgFFno_apyh_UHkcVlWR8u8t7iYo0EMeKCxz0qu4EwHzwbnyQXUbuGo0sHQUzVa7L9Tg_oPmGJkMDc-YBUJiTL/s792/ratio+US+20200721.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="420" data-original-width="792" height="266" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgSCda3iTWAhtkroCrFXrpUg_8s-IMjILm4Bqwqj8Y5aPD9zZE1FmN8NoCgFFno_apyh_UHkcVlWR8u8t7iYo0EMeKCxz0qu4EwHzwbnyQXUbuGo0sHQUzVa7L9Tg_oPmGJkMDc-YBUJiTL/w500-h266/ratio+US+20200721.png" width="500" /></a></div>
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This theoretically should flatten out at some point at the true population CFR (although it's complicated since more deaths can occur during a surge because hospitals are at capacity). Estimated CFRs are in the 0.1% order of magnitude so this point is likely far in the future for the US.</div>
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<b>Summary</b></div>
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The DIEM is an incredibly simple model. In the senses above — <i>too simple</i>. However, it has also proven useful for estimating the long run path of COVID-19 in several regions. In the places it applies, a given pandemic can be seen as an instance of a universal process with its specific parameters aggregating the effects of multiple aspects of society from policy to social networks to details of the specific virus.</div>
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Overall, we should keep in mind that the combination of policy, epidemiology, and social behavior is a social system. There might be empirical regularities from time to time, but humans can always change their behavior and thus change outcomes.<br />
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...</div>
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<b>Update 21 July 2020</b></div>
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Minor edits and updated Sweden, Germany and US ratio graphs with more recent data.</div>
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...<br />
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<b>Update 25 July 2020</b><br />
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The assumption of sparseness mentioned above may have failed us in the estimation of the dynamic equilibrium rate for Sweden — the first and second surges were too close together to properly measure it. It would resolve some inconsistencies (i.e. Sweden seeming to have a higher rate than the rest of Europe before the 2nd surge, Sweden oddly shifting to a rate more consistent with the rest of Europe after the 2nd surge). Here is the model using the most recent data (as of 11am PDT) to estimate the dynamic equilibrium $\alpha$ compared to the original fit (click or tap to enlarge):<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgUygrJ1BSnf3Bil6ZkQ-1Assmx_I4Q2CyfWAs9U_vMCozf5ZdjAyWP_M6CbXPhPjMilBbFScLtE3lfbd8eKta-jxCOzm_bOtVWWsRV-9YVRpfCvd4ZvOD1kWDyXFMcBhVh9KU3lWwZfWNQ/s1600/diem+sweden+20200725+a.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="465" data-original-width="792" height="116" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgUygrJ1BSnf3Bil6ZkQ-1Assmx_I4Q2CyfWAs9U_vMCozf5ZdjAyWP_M6CbXPhPjMilBbFScLtE3lfbd8eKta-jxCOzm_bOtVWWsRV-9YVRpfCvd4ZvOD1kWDyXFMcBhVh9KU3lWwZfWNQ/s200/diem+sweden+20200725+a.png" width="200" /></a><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgGe6wDf8roCxK-Cz8JsRH9HHCrGBEJc9F1IUbTWM98ptuKQukdvE-mW4UB1BD2XBM-_msinSIyVJ9xzCnyXH1ZC0xWzpTyDXiYtABGpEHAd5hVFBd5t1efg7gDaTUnG2J-RV7pXUx9gc2e/s1600/diem+sweden+20200725+b.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="465" data-original-width="792" height="116" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgGe6wDf8roCxK-Cz8JsRH9HHCrGBEJc9F1IUbTWM98ptuKQukdvE-mW4UB1BD2XBM-_msinSIyVJ9xzCnyXH1ZC0xWzpTyDXiYtABGpEHAd5hVFBd5t1efg7gDaTUnG2J-RV7pXUx9gc2e/s200/diem+sweden+20200725+b.png" width="200" /></a></div>
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<i>Seismograms</i><br />
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Another way to visualize multiple DIEMs is via what I call "<a href="https://informationtransfereconomics.blogspot.com/2018/03/shock-cluster-analysis-and-some-new.html">seismograms</a>" which displays the temporal information about the parameters (the shock width and the shock timing) on a timeline like this for several US states (click or tap to enlarge — the blue is only to differentiate the US aggregate, not direction of shock as in other uses):<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj8qI6t15n_Dd77GWiLuhViqYe4K_6X4-NafIbsPBfUQglt0r4IC8jRc-mnVB9P_rhb7NvtsUcwS2y-J90bW8hMCiem3Bod_ZY5JusSGCVGOfoFzQBqn_rF0QTYtzfaIxQhoej5E4IFqUln/s1600/diem+seismogram+20200724.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1136" data-original-width="1050" height="400" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj8qI6t15n_Dd77GWiLuhViqYe4K_6X4-NafIbsPBfUQglt0r4IC8jRc-mnVB9P_rhb7NvtsUcwS2y-J90bW8hMCiem3Bod_ZY5JusSGCVGOfoFzQBqn_rF0QTYtzfaIxQhoej5E4IFqUln/s400/diem+seismogram+20200724.png" width="368" /></a></div>
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The translation is fairly straightforward — a longer shock is represented by a wider band placed at the center (in time) of a non-equilibrium shock (above red-ish, below in gray). In the link above, you can add amplitude/magnitude information by scaling the color but this version just emphasizes time. Here's a graphical version of how these translate from <a href="https://informationtransfereconomics.blogspot.com/2019/06/a-workers-history-of-united-states-1948.html">my book</a>:<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgWPLTv-nafeW1cmOUCfxJsgPyr-2eCNGO6DT0ednlLIy53fH71RroOa2DinSRPvPcO-UA8JUDVQYy8WajKLz538c5p_8YlQgLEd0QuVKuo4dbUoapekROW0b7XAOHtTpVwFwpmY4rzuo87/s1600/dynamic+equilibrium+history+%2528generic+shock+1%2529+book+diagram+%2528black+and+white%2529+v4.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="857" data-original-width="1600" height="212" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgWPLTv-nafeW1cmOUCfxJsgPyr-2eCNGO6DT0ednlLIy53fH71RroOa2DinSRPvPcO-UA8JUDVQYy8WajKLz538c5p_8YlQgLEd0QuVKuo4dbUoapekROW0b7XAOHtTpVwFwpmY4rzuo87/s400/dynamic+equilibrium+history+%2528generic+shock+1%2529+book+diagram+%2528black+and+white%2529+v4.png" width="400" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjmj3JZgyTVqHvoaBFpLp3i7Jgh5Z8dtcnzdrv8CJKQCayWLB486yLlt5eLWB0KFUTYLSODNkFEmaCk4JXeUKt9c8-O7HNWqrwcingbnStkTJf3NVlr8Ec6yalCOKTcva_EbRkHhZSG616R/s1600/dynamic+equilibrium+history+%2528generic+shock+2%2529+book+diagram+%2528black+and+white%2529+v4.jpg" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="857" data-original-width="1600" height="213" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjmj3JZgyTVqHvoaBFpLp3i7Jgh5Z8dtcnzdrv8CJKQCayWLB486yLlt5eLWB0KFUTYLSODNkFEmaCk4JXeUKt9c8-O7HNWqrwcingbnStkTJf3NVlr8Ec6yalCOKTcva_EbRkHhZSG616R/s400/dynamic+equilibrium+history+%2528generic+shock+2%2529+book+diagram+%2528black+and+white%2529+v4.jpg" width="400" /></a></div>
<div style="text-align: justify;"><br /></div>...<br />
<br /><b>Update 9 September 2020</b></div><div style="text-align: justify;"><br /></div><div style="text-align: justify;">The "return to equilibrium" has turned out to be remarkably accurate for the US:</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhcPmO6qQ1UNauPa1b5_ED9rok7szcotLWZkv3DYezyBI5K4VnNZ86b0lAYV94tK-_rHTnQhe28xmMiZUTyXIBa61B8QXRcxVBeF8PY9HjSlIbNHNJtS5l42QZGcDwM-Yxck8ZAdUUQugmI/s792/diem+us+cases+3rd+surge+Qa+20200907.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="551" data-original-width="792" height="279" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhcPmO6qQ1UNauPa1b5_ED9rok7szcotLWZkv3DYezyBI5K4VnNZ86b0lAYV94tK-_rHTnQhe28xmMiZUTyXIBa61B8QXRcxVBeF8PY9HjSlIbNHNJtS5l42QZGcDwM-Yxck8ZAdUUQugmI/w400-h279/diem+us+cases+3rd+surge+Qa+20200907.png" width="400" /></a></div><div><br /></div>A 3rd surge may be getting started in the US (associated with schools opening for the new year) — zoomed in on the gray box in the previous graph:<div><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiP6H_jDwJ_bNDYDooTp8E91rlP1LDPkdFzxK-ciewvzDyc6xLz3eVVsIJtwnjTA6xtBVNAClCT-tPnMjGcGkqj7WYhsyytMane8Q1h_srCvox_LATRCdjpLJ4NjlzB8_riEVuQjoQT6Cj1/s792/diem+us+cases+3rd+surge+Qb+20200907.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="536" data-original-width="792" height="271" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiP6H_jDwJ_bNDYDooTp8E91rlP1LDPkdFzxK-ciewvzDyc6xLz3eVVsIJtwnjTA6xtBVNAClCT-tPnMjGcGkqj7WYhsyytMane8Q1h_srCvox_LATRCdjpLJ4NjlzB8_riEVuQjoQT6Cj1/w400-h271/diem+us+cases+3rd+surge+Qb+20200907.png" width="400" /></a></div><br /><div>In Sweden, there is a 3rd surge ending ...</div><div><br /><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiXepJA9ShIncYt3uAKjyOr_axr2HyE2TdQiUSLU51-YGW7ZRUWxCDrwAMPt_yu1RV-B3Tmmsn1Eo448WXsZ6ABRGbZFXVKvWsD4Zd7FwXUemOL_l42W1QjcgGBlYGLtr5tfOKtkSgPXXL5/s792/diem+sweden+1+20200907.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="465" data-original-width="792" height="235" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiXepJA9ShIncYt3uAKjyOr_axr2HyE2TdQiUSLU51-YGW7ZRUWxCDrwAMPt_yu1RV-B3Tmmsn1Eo448WXsZ6ABRGbZFXVKvWsD4Zd7FwXUemOL_l42W1QjcgGBlYGLtr5tfOKtkSgPXXL5/w400-h235/diem+sweden+1+20200907.png" width="400" /></a></div><br /><div style="text-align: justify;">Also, the predicted path of deaths in the US using cases turned out to be fairly accurate with only the lag being uncertain in advance:</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEigY_HdRjvUO1_3CYfvxmS_ESJjvDNe6BGts4k-DgWrZXWIISpxE2K28DMykL7gk-Hx0E6xCoOZqsSLFMqqazzI6grV8-MTCgx0igHNbUy79_rB7G3RcSjK1u5QReuL9m-ybjXtR2J_Lojo/s1007/diem+us+deaths+20200907.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="456" data-original-width="1007" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEigY_HdRjvUO1_3CYfvxmS_ESJjvDNe6BGts4k-DgWrZXWIISpxE2K28DMykL7gk-Hx0E6xCoOZqsSLFMqqazzI6grV8-MTCgx0igHNbUy79_rB7G3RcSjK1u5QReuL9m-ybjXtR2J_Lojo/w500-h226/diem+us+deaths+20200907.png" width="500" /></a></div><br /><div style="text-align: justify;">The ratio of deaths to cases for the US has returned to the "equilibrium" of a decline due to a likely combination of effects from demographic to increasing testing (the latter seeming like the primary contribution):</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgbmvYfc7YWfEJBngaD4bK6AX_KbLKFZdJk6-Zv-DIS86zk-Ik96EJbcOv9B3qgtZZO_hr4SAGfYD8m2XniY9YkzqVcEwlG-YstVRzqtQWmmxM01QmXwr26jY522fDadCa3ksdV1uK9Z3-Q/s792/diem+us+deaths+ratio+20200907.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="420" data-original-width="792" height="266" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgbmvYfc7YWfEJBngaD4bK6AX_KbLKFZdJk6-Zv-DIS86zk-Ik96EJbcOv9B3qgtZZO_hr4SAGfYD8m2XniY9YkzqVcEwlG-YstVRzqtQWmmxM01QmXwr26jY522fDadCa3ksdV1uK9Z3-Q/w500-h266/diem+us+deaths+ratio+20200907.png" width="500" /></a></div><div>...</div><br /><div style="text-align: justify;"><b>Update 2 October 2020</b></div><div style="text-align: justify;"><br /></div><div style="text-align: justify;">Another predictive success of the DIEM for COVID-19 — <a href="https://twitter.com/infotranecon/status/1305316884661690368">calling a 3rd surge in Florida on 9/13</a>:</div><div style="text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiZg-jjElEFrC-1AMIOV4AR00GNv6Tfqlq6l4mUXlrdcbi-SkiGy4ENoQn9hAJ_6lzVHlFG4E95E4y4LLkrYEr0Qlj6J8KMKHREP2c6PHLNtx-RiVZuWLIsGcQDYr25T_Sb8S0N5Af8wxTU/s792/Eh1qoKMUwAEWFdT.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="483" data-original-width="792" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiZg-jjElEFrC-1AMIOV4AR00GNv6Tfqlq6l4mUXlrdcbi-SkiGy4ENoQn9hAJ_6lzVHlFG4E95E4y4LLkrYEr0Qlj6J8KMKHREP2c6PHLNtx-RiVZuWLIsGcQDYr25T_Sb8S0N5Af8wxTU/s320/Eh1qoKMUwAEWFdT.png" width="320" /></a></div><div><br /></div>And its subsequent appearance:</div><div><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEijG7TBCFtASHyk93BFe49lgUNyNKPCYYMH24oqeUR9TdMoOmWSDPCd_78NTLsnF-R8OiyCXLusMq9z0C1u0VCWrK6BH2Yaw3P9BgEjumLfLE7UMDGqOvUq5WKsmBLCvNEZwPazEjoA8XOe/s792/diem+fl+20201001.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="483" data-original-width="792" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEijG7TBCFtASHyk93BFe49lgUNyNKPCYYMH24oqeUR9TdMoOmWSDPCd_78NTLsnF-R8OiyCXLusMq9z0C1u0VCWrK6BH2Yaw3P9BgEjumLfLE7UMDGqOvUq5WKsmBLCvNEZwPazEjoA8XOe/s320/diem+fl+20201001.png" width="320" /></a></div><div><div style="text-align: justify;"><br />
...<br />
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<div style="text-align: justify;">
<b>Data sources:</b></div>
<div style="text-align: justify;">
<br /></div>
<div style="text-align: justify;">
International data from European CDC</div>
<div style="text-align: justify;">
<a href="https://www.ecdc.europa.eu/en/geographical-distribution-2019-ncov-cases">https://www.ecdc.europa.eu/en/geographical-distribution-2019-ncov-cases</a></div>
<div style="text-align: justify;">
<br /></div>
<div style="text-align: justify;">
US state data from the COVID Tracking Project</div>
<div style="text-align: justify;">
<div>
<a href="https://covidtracking.com/">https://covidtracking.com/</a></div>
<div>
<br /></div>
<div>
Economic data from <a href="https://fred.stlouisfed.org/">FRED</a> and Atlanta Fed Wage Growth tracker</div>
<div>
<a href="https://www.frbatlanta.org/chcs/wage-growth-tracker.aspx?panel=1">https://www.frbatlanta.org/chcs/wage-growth-tracker.aspx?panel=1</a></div>
</div>
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<br /></div>
</div>Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com0tag:blogger.com,1999:blog-6837159629100463303.post-84279511467982456312020-05-01T18:30:00.000-07:002020-06-14T14:10:25.255-07:00What's in a name?<script type="text/x-mathjax-config"> MathJax.Hub.Config({tex2jax: {inlineMath: [['$','$'], ['\\(','\\)']]}}); </script> <script src="https://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML" type="text/javascript"> </script>
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<blockquote class="tr_bq">
<i>That which we call a model by any other name would describe as well ... or not</i></blockquote>
Shakespeare, I think.<br />
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<div style="text-align: justify;">
I'm in the process of trying to distract myself from obsessively modeling the COVID-19 outbreak, so I thought I'd write a bit about language in technical fields.</div>
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David Andolfatto didn't think <a href="https://twitter.com/dandolfa/status/1242909510525747202?s=20">this twitter thread</a> was very illuminating, but at its heart is something that's a problem in economics in general — and not just macroeconomics. It's certainly a problem in economics communication, but I also believe it's a kind of a professional economics version of "<a href="https://en.wikipedia.org/wiki/Grade_inflation">grade inflation</a>" where "hypotheses" are inflated into "theorems" and "ideas" [1] are inflated into "models".</div>
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Now every economist I've ever met or interacted with is super smart, so I don't mean "grade inflation" in the sense that economists aren't actually good enough. I mean it in the sense that I think economics as a field feels that it's made up of smart people so it should have a few "theorems" and "models" in the bag instead of only "hypotheses" and "ideas" — like how students who got into Harvard feel like they deserve A's because they got into Harvard. Economics has been around for centuries, so shouldn't there be some hard won truths worthy of the term "theorem"?</div>
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This was triggered by his claim that <a href="https://en.wikipedia.org/wiki/Ricardian_equivalence">Ricardian equivalence</a> is a theorem (made again <a href="https://twitter.com/dandolfa/status/1256381797543395339?s=20">here</a>). And I guess it is — in economics. He actually asked what definitions were being used for "model" and "theorem" at one point, and I responded (in the manner of an undergrad starting a philosophy essay [2]):</div>
<blockquote class="tr_bq">
<div style="text-align: justify;">
<i>the·o·rem </i></div>
</blockquote>
<blockquote class="tr_bq">
<div style="text-align: justify;">
<i>a general proposition not self-evident but proved by a chain of reasoning; a truth established <b>by means of accepted truths</b> </i></div>
</blockquote>
<blockquote class="tr_bq">
<div style="text-align: justify;">
<i>mod·el </i></div>
</blockquote>
<blockquote class="tr_bq">
<div style="text-align: justify;">
<i>a system of postulates, data, and inferences presented as a mathematical description <b>of an entity or state of affairs</b></i></div>
</blockquote>
<div style="text-align: justify;">
I emphasized those last clauses with asterisks in the original tweet (bolded them here) because they are important aspects that economics seems to either leave off or claim very loosely. No other field (as far as I know) uses "model" and "theorem" as loosely as economics does.</div>
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The Pythagorean theorem is established from Euclid's axioms (including the <a href="https://en.wikipedia.org/wiki/Parallel_postulate">parallels axiom</a>, which is why it's only valid in Euclidean space) that include things like "all right angles are equal to each other". Ricardian equivalence (per e.g. Barro) instead based on axioms (assumptions) like "people will save in anticipation of a hypothetical future tax increase". This is <b><i>not </i></b>an accepted truth, therefore Ricardian equivalence so proven is <b><i>not </i></b>a theorem. It's a hypothesis.</div>
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You might argue that Ricardian equivalence as shown by Barro (1974) is a logical mathematical deduction from a series of axioms — just like the Pythagorean theorem — making it also a theorem. And I might be able to meet you halfway on that if Barro had just written e.g.:</div>
<br />
$$<br />
A_{1}^{y} + A_{0}^{o} = c_{0}^{o} + (1 - r) A_{1}^{o}<br />
$$<br />
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<div style="text-align: justify;">
and proceeded to make a bunch of mathematical manipulations and definitions — calling it "an algebraic theorem". But he didn't. He also wrote:</div>
<blockquote class="tr_bq">
<div style="text-align: justify;">
<i>Using the letter $c$ to denote consumption, and assuming that consumption and receipt of interest income both occur at the start of the period, the budget equation for a member of generation 1, who is currently old, is [the equation above]. The total resources available are the assets held while young, $A_{1}^{y}$, plus the bequest from the previous generation, $A_{0}^{o}$. The total expenditure is consumption while old, $c_{1}^{o}$, plus the bequest provision, $A_{1}^{o}$, which goes to a member of generation 2, less interest earnings at rate $r$ on this asset holding.</i></div>
</blockquote>
<div style="text-align: justify;">
It is this mapping from these real world concepts to the variable names that makes this a Ricardian Equivalence <i>hypothesis</i>, not a theorem, even if that equation was an accepted truth (it is not).</div>
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In the Pythagorean theorem, $a$, $b$, and $c$ aren't just nonspecific variables, but are lengths of the sides of a triangle in Euclidean space. I can't just call them apples, bananas, and cantaloupes and say I've derived a relationship between fruit such that <i>apples</i>² + <i>bananas</i>² = <i>cantaloupes</i>² called the Smith-Pythagoras Fruit Euclidean Metric Theorem.</div>
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There are real theorems that exist in the real world in the sense I am making — the <a href="https://en.wikipedia.org/wiki/CPT_symmetry">CPT theorem</a> comes to mind as well as the <a href="https://en.wikipedia.org/wiki/Noisy-channel_coding_theorem">noisy channel coding theorem</a>. That's what I mean by economists engaging in a little "grade inflation". I seriously doubt <b><i>any </i></b>theorems exist in social sciences at all.</div>
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The last clause is also important for the definition of "model" — a model describes the real world in some way. The <a href="https://en.wikipedia.org/wiki/Hodgkin%E2%80%93Huxley_model">Hodgkin-Huxley model</a> of a neuron firing is an ideal example here. It's not perfect, but it's a) based on a system of postulates (in this case, an approximate electrical circuit equivalent), and b) presented as a mathematical description of a real entity.</div>
<br />
<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjaL2wttBFU1bHBhaxqMnmbIwZxXYDJeuu-bButCKjXildwmG8pp-5C6rOABiTHxggOzAdLET-l01IU8tkfWz798mTbpJgMwLUMAm_cUsV13zNi1iUSxKzKcvfwoZScPLPWHu7qElSS1B7f/s1600/x28.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="255" data-original-width="590" height="172" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjaL2wttBFU1bHBhaxqMnmbIwZxXYDJeuu-bButCKjXildwmG8pp-5C6rOABiTHxggOzAdLET-l01IU8tkfWz798mTbpJgMwLUMAm_cUsV13zNi1iUSxKzKcvfwoZScPLPWHu7qElSS1B7f/s400/x28.png" width="400" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Reproduced from Hodgkin and Huxley (1952)</td></tr>
</tbody></table>
<div style="text-align: justify;">
The easiest way to do part b) is to compare with data but you can also compare with pseudo-data [3] or moments (while its performance is lackluster, a DSGE model meets this low bar of being a real "model" as I talk about <a href="https://informationtransfereconomics.blogspot.com/2018/07/dsge-battle-royale-christiano-v-stiglitz.html">here</a> and <a href="https://informationtransfereconomics.blogspot.com/2017/02/qualitative-economics-done-right-part-1.html">here</a>). *<i>Ahem</i>* — there's also <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3094757">this</a>.</div>
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<br /></div>
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<a href="https://en.wikipedia.org/wiki/Generalized_method_of_moments">Moment matching</a> itself gets the benefit of "grade inflation" in macro terminology. I'm not saying it's necessarily wrong or problematic — I'm saying a model that matches a few moments is too often inflated to being called "empirically accurate" when it really just means the model has "qualitatively similar statistics".</div>
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One of the problems with a lack of concern with describing a real state of affairs is that you can end up with what Paul Pfleiderer called <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2414731">chameleon models</a> — models that are proffered for use in policy, but when someone questions the reality of the assumptions the proponent changes the representation (like a chameleon) to being more of a hypothesis or plausibility argument. You may think using a so-called "model" that isn't ready for prime time can be useful when policy makers need to make decisions, but Pfleiderer put it well <a href="https://twitter.com/infotranecon/status/1215088326559981568?s=20">in a chart</a>:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjh22cnk-PFvMClUCPzXsYzH2T2CxVrcd8k1dzyOH9XNNQlCyeoM95Nq0C6pL0daaxc7bBUN2KYDlCDZ4ZRNO76KT7-msGmnLZTKBHIppa57ap-iYzNMKpxizKHUaMeoloBAuoZFvgap-PM/s1600/ENzcZF7UYAAYjUu.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="586" data-original-width="1052" height="222" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjh22cnk-PFvMClUCPzXsYzH2T2CxVrcd8k1dzyOH9XNNQlCyeoM95Nq0C6pL0daaxc7bBUN2KYDlCDZ4ZRNO76KT7-msGmnLZTKBHIppa57ap-iYzNMKpxizKHUaMeoloBAuoZFvgap-PM/s400/ENzcZF7UYAAYjUu.jpg" width="400" /></a></div>
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<div style="text-align: justify;">
But what about toy models? Don't we need those? Sure! But I'm going to say something you're probably going to disagree with — <a href="https://informationtransfereconomics.blogspot.com/2017/02/qualitative-economics-done-right-part-2a.html">toy models should come <b><i>after </i></b>empirically successful theory</a>. I am not referring to a model that matches data to 10-50% accuracy or even just gets the direction of effects right as a toy model — that's a qualitative model. A toy model is something different.</div>
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<div style="text-align: justify;">
I didn't realize it until writing this, but apparently "<a href="https://en.wikipedia.org/wiki/Toy_model">toy model</a>" on Wikipedia is a physics-only term. The first line is pretty good:</div>
<blockquote class="tr_bq">
<div style="text-align: justify;">
<i>In the modeling of physics, a toy model is a deliberately simplistic model with many details removed so that it can be used to explain a mechanism concisely.</i></div>
</blockquote>
<div style="text-align: justify;">
In grad school, the first discussion of <a href="https://en.wikipedia.org/wiki/Renormalization">renormalization</a> in my quantum field theory class used a scalar (spin-0) field. At the time, there were no empirically known "fundamental" scalar fields (the Higgs boson was still theoretical) and the only empirically successful uses of renormalization were <a href="https://en.wikipedia.org/wiki/Quantum_electrodynamics">QED</a> and <a href="https://en.wikipedia.org/wiki/Quantum_chromodynamics">QCD</a> — both theories with spin-1 <a href="https://en.wikipedia.org/wiki/Gauge_boson">gauge bosons</a> (photons or gluons) and spin-½ <a href="https://en.wikipedia.org/wiki/Fermion">fermions</a> (electrons or quarks). Those details complicate renormalization (e.g. you need <a href="https://en.wikipedia.org/wiki/BRST_quantization">a whole different quantization process</a> to handle non-Abelian QCD). The scalar field theory was a toy model of renormalization of QED — used in a class to teach renormalization to students about to learn QED <i>that had already been shown</i> to be empirically accurate to 10s of decimal places.</div>
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The scalar field theory would be horribly inaccurate if you tried to use it to describe the interactions of electrons and photons.</div>
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<div style="text-align: justify;">
The problem is not that many economic "toy models" are horribly inaccurate, but rather that they don't derive from even qualitatively accurate non-toy models. Often it seems no one even bothers to compare the models (toy or not) to data. It's like that amazing car your friend has been working on for years but never seems to drive — does it run? Does he even know how to fix it?</div>
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<div style="text-align: justify;">
At this stage, I'm often subjected to all kinds of defenses — <a href="https://informationtransfereconomics.blogspot.com/2016/03/economics-is-social-science.html">economics is <i>social </i>science</a>, <a href="https://informationtransfereconomics.blogspot.com/2017/01/complex-systems-versus-complicated.html">economics is too complex</a>, there's too much uncertainty. The first and last of those would be arguments against using mathematical models or deriving theorems at all, which <i>a fortiori</i> makes my point that the words "model" and "theorem" are inflated from their common definition in most technical fields.</div>
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<div style="text-align: justify;">
<a href="https://twitter.com/dandolfa/status/1242896104242511873?s=20">David's defense is</a> (as many economists have said) that models and theorems "organize [his] thinking". In the past, my snarky comment on this has been that economists must have really disorganized minds if they need to be organizing their thinking all the time with models. Zing!</div>
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<br /></div>
<div style="text-align: justify;">
But the thing is we have a word for organized thought — idea [4]:</div>
<blockquote class="tr_bq">
<i>i·de·a</i> </blockquote>
<blockquote class="tr_bq">
<i>a formulated thought or opinion</i></blockquote>
<div style="text-align: justify;">
But what's in a name? Does it matter if economists call Ricardian equivalence a theorem, a hypothesis, or an idea? Yes — because most human's exposure to a "theorem" (if any) is the Pythagorean Theorem. People will think that the same import applies to Ricardian Equivalence, but that is false equivalence.</div>
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<br /></div>
<div style="text-align: justify;">
Ricardian Equivalence is nowhere near as useful as the Pythagorean Theorem, to say nothing about how true it is. Ricardian Equivalence may be true in Barro's model — one that has never been compared to actual data or shown to represent any entity or state of affairs. In contrast, you could right now with a ruler, paper, and pencil draw a right triangle with sides of length 3, 4, and 5 inches [5].</div>
<div style="text-align: justify;">
<br /></div>
<div style="text-align: justify;">
I hear the final defense now: <i>But fields should be allowed their own jargon — and not policed by other fields!</i> Who are you fooling? </div>
<div style="text-align: justify;">
<br /></div>
<div style="text-align: justify;">
Well, it turns out economists are fooling people — scientists who take the pronouncements of economics at face value. I write about this <a href="https://www.amazon.com/gp/product/B0754X3PYF/">in my book</a> (using two examples of <i><a href="https://informationtransfereconomics.blogspot.com/2015/08/obviously-e-coli-is-rational-utility.html">E. coli</a></i> and <a href="https://informationtransfereconomics.blogspot.com/2015/11/monkeys-and-markets.html">capuchin monkeys</a>):</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg1VV8lQLr_ncQYKlwApJNuJOHCzSwSO8iHbY0Jr43sXPu43Nmrg7bz1Rz7rnlMdUfOHNI6GqCywbVN1fw0-kI-XrVVbSiUkSa1j2fy3R3GE_OaWQYhiDSU0XqLqBlsgUwPZlzJp-187H6Z/s1600/disservice.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="476" data-original-width="812" height="233" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg1VV8lQLr_ncQYKlwApJNuJOHCzSwSO8iHbY0Jr43sXPu43Nmrg7bz1Rz7rnlMdUfOHNI6GqCywbVN1fw0-kI-XrVVbSiUkSa1j2fy3R3GE_OaWQYhiDSU0XqLqBlsgUwPZlzJp-187H6Z/s400/disservice.png" width="400" /></a></div>
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<div style="text-align: justify;">
We have trusting scientists going along with rational agent descriptions put out there by economists when these rational agent descriptions have little to no empirical evidence in their favor — and even fewer accurate descriptions of a genuine state of affairs. In fact, economics might do well to borrow the evolutionary idea of an ecosystem being <a href="http://informationtransfereconomics.blogspot.com/2016/02/fitness-trade-offs-and-macrofoundations.html">the emergent result of agents randomly exploring the state space</a>.</div>
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...<br />
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PS</div>
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My "to be fair" items so that I'm not just "calling out economics" are "information" in information theory and "theory" in physics. The former is really unhelpful — I know it's information entropy, but people who know that often shorten it to just information and people who don't think information is like knowledge despite the fact that information entropy is maximized for e.g. random strings.</div>
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In physics, any quantum field theory Lagrangian is called a "theory" even if it doesn't describe anything in the real world. It is true that the completely made up ones don't get names like quantum electrodynamics but rather "<a href="https://en.wikipedia.org/wiki/Quartic_interaction">φ⁴ theory</a>". If it were economics, that scalar field φ would get a name like "savings" or "consumption".</div>
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<b>Footnotes:</b></div>
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<span style="font-size: x-small;">[1] I had a hard time coming up with the word here — my first choice was actually "scratch work". Also "concepts" or "musings".</span></div>
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<span style="font-size: x-small;">[2] ... at 2am in a 24 hour coffee shop on <a href="https://en.wikipedia.org/wiki/Drag_(Austin,_Texas)">the Drag</a> in Austin.</span></div>
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<span style="font-size: x-small;">[3] "<a href="https://en.wikipedia.org/wiki/Lattice_QCD">Lattice data</a>" (for QCD) or <a href="https://informationtransfereconomics.blogspot.com/2018/07/dsge-battle-royale-christiano-v-stiglitz.html">data generated with VAR models</a> (in the case of DGSE) are examples of pseudo-data.</span></div>
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<span style="font-size: x-small;">[4] Per [1], this is also why I thought "concept" would work here:</span></div>
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<i><span style="font-size: x-small;">con·cept</span></i></div>
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<i><i><span style="font-size: x-small;">something conceived in the mind</span></i></i></div>
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<span style="font-size: x-small;">[5] This is actually how ancient Egyptians used to measure right angles — <a href="https://www.radford.edu/~wacase/Math%20135%20Pythagorean%20Theorem.pdf">by creating 3-4-5 unit triangles</a> [pdf].</span></div>
Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com10tag:blogger.com,1999:blog-6837159629100463303.post-64494690179041881452020-04-24T05:00:00.000-07:002020-04-24T05:00:07.267-07:00Seven years later ...<div style="text-align: justify;">
On the 7th anniversary of this blog, we are finding ourselves in the midst of a deadly pandemic and the biggest macroeconomic shock since possibly the Great Depression. I hope everyone out there is staying healthy, practicing good mitigation, and still has a job.</div>
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The next seven years on the blog are going to be different — gone will be <a href="https://informationtransfereconomics.blogspot.com/2019/11/jobs-day-october-2019.html">the days of tracing the path of the macroeconomic equilibrium</a>, replaced with following the first non-equilibrium shock since the information equilibrium framework <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3094757">was formalized</a>. Will we see <a href="https://informationtransfereconomics.blogspot.com/2020/04/jolts-data-and-twig-crack-that-caused.html">a sharp rise in unemployment followed by the typical decline</a> we've seen over the past century in US data? Will there be a <a href="https://informationtransfereconomics.blogspot.com/2017/11/unemployment-rate-step-response-over.html">step response</a>? I hope the economy recovers from this shock faster than it has in the past, but I am not optimistic.</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiVSY3X626UQHQQsLjf0gPRPDDf7D33xc9jauz13Nfc5jXYLUMmcs3aOA72lw23NSzxwMHC3qQHHExG1K8qfEmBzX9OZSoy5BSSCwbwE6NxDF40yCnrLEsj-tuGYlRPSDGz7fyXtF5B43Or/s1600/unrateCounterfactual1.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="481" data-original-width="948" height="202" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiVSY3X626UQHQQsLjf0gPRPDDf7D33xc9jauz13Nfc5jXYLUMmcs3aOA72lw23NSzxwMHC3qQHHExG1K8qfEmBzX9OZSoy5BSSCwbwE6NxDF40yCnrLEsj-tuGYlRPSDGz7fyXtF5B43Or/s400/unrateCounterfactual1.png" width="400" /></a></div>
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PS The post title is a MST3K reference to "The Final Sacrifice". Here's to wondering if there is beer on the sun.</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEirCcrufK2Z69h-QuFgwZxlVCKFchmXve2goQvlEXBJSakV8CrQxsOg2rLdcx_mXvD7w2HF7l4KhJXR0DJYUb7SRkJgKm3JK3NZQdQPegEuq4mgVpSp2ItJkUo5-CAAYWTzUm9PfRZ9odDG/s1600/beerSun.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="216" data-original-width="236" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEirCcrufK2Z69h-QuFgwZxlVCKFchmXve2goQvlEXBJSakV8CrQxsOg2rLdcx_mXvD7w2HF7l4KhJXR0DJYUb7SRkJgKm3JK3NZQdQPegEuq4mgVpSp2ItJkUo5-CAAYWTzUm9PfRZ9odDG/s1600/beerSun.jpg" /></a></div>
<br />Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com0tag:blogger.com,1999:blog-6837159629100463303.post-261370643429674102020-04-12T12:33:00.003-07:002020-04-17T10:15:20.405-07:00What does this physicist think of economists?**<div style="text-align: justify;">
I have had fringe contact with more macroeconomics than usual as of late, for obvious reasons (e.g. I have been producing <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3094757">macroeconomic models</a> that outperform mainstream models by orders of magnitude), and I do understand this is only one corner of the discipline. I don’t mean this as a complaint dump, because most of physics suffers from similar problems due to being a similarly male-dominated field, but here are a few limitations I see in the mainstream economic models put before us:</div>
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1. They do not sufficiently grasp that <b>social forces and unpredictable human nature are more powerful than economic forces and “rational agents”</b>. In the short run you try economic stimulus, but in the long run you learn that not giving Republicans cover to dismantle democracy through “public choice” protects you the most. Or you move from doing “unemployment insurance” to “paying companies to keep people on the payroll” once you get that job search and matching is driven more by social relationships than economic theory. In this regard the economic models end up being too pessimistic about human brains (reduced to a 1-dimensional utility function!), and it seems that “the econophysics complaints about the economists” (yes there is such a thing) are largely correct on this count. On this question econophysics models (<a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3094757">e.g.</a>) really do better, though not the models of everybody.</div>
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2. They do not sufficiently incorporate <b>people's humanity</b>. An economic stimulus plan, for instance, may be freakishly amoral, which leads to adjustments along the way, and very often those adjustments are stupid policy moves suggested by impatient billionaires. This is not built into the economic models I am seeing, even though there is a large independent branch of sociology research. It is hard from them to understand, I guess? Still, it means that economic models will be too alien, rather than too human. Economists might protest that it is not the purpose of their science or models to incorporate social change and morality, but these factors are relevant for prediction, and if you try to wash your hands of them (no Easter pun intended) <a href="https://informationtransfereconomics.blogspot.com/2016/02/thought-experiment.html">you will be wrong a lot</a>.</div>
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3. <b>The <a href="http://noahpinionblog.blogspot.com/2015/09/a-bit-of-pushback-against-empirical-tide.html">concept of scope</a></b>, specifically the part that tells us that effective theories of the same system at different scales may have little relationship to each other at leading order — so much so that they may have incommensurate domains of validity. Economists seem super-unaware of this, at least much less so than physicists are these days, though it seems to be more of a “la-la-la-I-can't-hear-you” pursuit of tractable macro models aggregating “rational agents” than earnestly trying to understand the complex system they are purportedly researching. That is really hard, either in physics or economics. Still, on the predictive front without a good understanding of scope and scale a lot will go askew, as indeed it does in economics.</div>
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The economic models also do not seem to incorporate Richard Feynman-like bias offset techniques. Don't fool yourself, and you're the easiest person to fool! But economists still feel like opining about subjects well outside their domain of expertise without considering that their political priors may strongly influence their ideas. Some of their “ideas” are shown to be horribly misguided through the subsequent scrutiny. Economists might claim these factors already are incorporated in the variables they are modeling, since they claim to incorporate human behavior. Ideally you may wish to incorporate the past work of the modeler themselves (i.e. the past light cone of the observer's causal wavefunction) in the model's Bayesian prior probability, so that they do not see everything as a nail when all they have is a hammer. I have not yet seen a Dunning-Kruger-aware dimension in economic models, though you might argue many economists are “Dunning-Kruger” in their public rhetoric, blurting out what they think is good for us rather than actually learning about it first. The institutional modesty of physicists (whole theories are predicated on the principle that “we are not special in the universe”) is slightly subtler.</div>
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4. <b>Selection bias from the failures coming first.</b> The early macroeconomic models were calibrated from the Great Depression, because what else could they do? Then came the Great Recession, which was also a mess. It is the messes which are visible first, at least on average. So some of the models may have been too pessimistic at first. These days we have Japan, South Korea, and a bunch of Nordic states that haven’t quite “blown up” with several million people making initial unemployment claims and <a href="https://www.expressnews.com/news/local/article/Thousands-hit-hard-by-coronavirus-pandemic-s-15189948.php">literal Depression-era food lines we see here</a>. If the early models had access to all of that data, presumably they would be more predictive of the entire situation today. But it is no accident that the failures (<a href="https://www.newyorker.com/news/q-and-a/the-contrarian-coronavirus-theory-that-informed-the-trump-administration">like Richard Epstein</a>) will be more visible in the media early on.</div>
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And note that right now some of the very worst countries (United States, possibly the United Kingdom?) are not far enough along on the data side to yield useful inputs into the models. So currently those macro models might be picking up too many semi-positive data points of functioning governments and not enough from failed states or “train wrecks,” and thus they are too optimistic.</div>
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On this list, I think my #1 comes closest to being an actual criticism, the other points are more like observations about doing science in a messy, imperfect world. In any case, when economic models are brandished, keep these limitations in mind. But the more important point may be for when critics of economic models raise the limitations of those models. Very often the cited criticisms are chosen selectively, to support some particular agenda, when in fact the biases in the economic models almost certainly run in one direction — towards the interests of billionaires (see a. below).</div>
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Which is how a lot of macro men think it should be.</div>
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Now, to close, I have a few rude questions directed at economists that nobody seems willing to publicly acknowledge, but actually we all already know the answers to them:</div>
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a. As a class of scientists, how much are economists paid by vested interests (e.g. GMU/Mercatus, Hoover Institution, Cato)? Is is being wrong or right better for their salaries?</div>
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b. How smart are they? What are their average GRE scores?</div>
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c. Are they hired into thick, liquid academic and institutional markets? Or does it take five years to publish a paper? And how meritocratic are those markets? Is it just people from five schools who are allowed to get jobs or publish?</div>
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d. What is their overall track record on predictions, whether before or during this crisis?</div>
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e. On average, what is the political orientation of economists? And compared to other academics? Do they use <a href="https://delong.typepad.com/sdj/2009/04/hoisted-from-the-archives-a-non-socratic-dialogue-on-social-welfare-functions.html">the market social welfare function</a> when they make non-trivial recommendations?</div>
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f. We know, from physics, that if you are a French physicist, being a Frenchman predicts your space-time location better than does being an physicist (there is an old PRL paper on this somewhere). Is there a comparable phenomenon in economics?</div>
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g. How well do they understand how to model any system, relative to say what an undergrad physics major would know?</div>
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h. Are there “defunct economists” in the manner that John Maynard Keynes charges there are “defunct economists”? If so, what do you have to do to earn that designation? And are the defunct sometimes right, or right on some issues? How meta-rational are those who allege defunct-ism? Are they meta-meta-rational? How about meta-meta-meta-rational?</div>
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i. How many of them have studied Douglas Hofstadter’s now 40 year old meta-work on emergence and meta-fiction? Meta.</div>
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Just to be clear, as ITE readers will know, I have not been criticizing the mainstream macroeconomic recommendations of stimulus. But still those seem to be questions worth asking.</div>
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** PS This is a mix of parody (because it's risible) and critique (because economics doesn't really work that well compared to even epidemiology) of <a href="https://marginalrevolution.com/marginalrevolution/2020/04/what-does-this-economist-think-of-epidemiology.html">this</a>.</div>
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PPS #NotAllEconomists<br />
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PPPS Made a couple edits and slight changes (references to public choice theory, Japan).<br />
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PPPPS Update: Cowen <a href="https://marginalrevolution.com/marginalrevolution/2020/04/epidemiology-and-selection-problems.html">is now saying</a> the "debate" is becoming "emotional". That a) is exactly one point I am making here — his preferred approach to economics lacks empathy, morality, and humanity, and b) is what purportedly "rational" men often say about women, which is another.<br />
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People are literally lining up in Depression-era food lines, and Tyler wants to debate whether or not epidemiology journals should be colonized by economists.<br />
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PPPPPS I do want to emphasize that this is a parody — a physicist adopting the same self-regard and sneering tone Cowen shows towards epidemiology (but with the additional layer of irony being that physicists have produced a lot more empirically accurate theories than macroeconomists have). I think a lot of economists do good work. Unfortunately, a lot of economists (especially those more right & libertarian leaning) need to learn to, in the words of Kendrick Lamar, "be humble / sit down".</div>
Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com7tag:blogger.com,1999:blog-6837159629100463303.post-66847447932381089022020-04-07T12:02:00.000-07:002020-04-07T12:02:03.685-07:00JOLTS data — and the twig crack that caused the avalanche?<div style="text-align: justify;">
Back from a long hiatus — things were crazy at the real job trying to get set up to work from home for a month or longer. Happy to report my family and I are doing well, and I hope everyone out there is staying healthy.</div>
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The drop in the <a href="https://fred.stlouisfed.org/series/JTSJOR">JOLTS job openings rate</a> I noted in <a href="https://informationtransfereconomics.blogspot.com/2020/02/market-updates-for-bad-week.html">the previous post</a> (from February) has continued and it appears we're showing a definite deviation:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjO0yAI02lHoznWq4cl1QUP94qTBzzaZEv7Pubypn2KWBuYrrHHhD-Z1V1kaaYpr3dVJ_bKdDcfzRrvxW-p-iL0AVqr_Nt7uHYPB5tnYC9OUpBc3gnUQJLnX1agGjAFgKWyT1jrLhiXGOM_/s1600/joltsJOR.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="479" data-original-width="792" height="241" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjO0yAI02lHoznWq4cl1QUP94qTBzzaZEv7Pubypn2KWBuYrrHHhD-Z1V1kaaYpr3dVJ_bKdDcfzRrvxW-p-iL0AVqr_Nt7uHYPB5tnYC9OUpBc3gnUQJLnX1agGjAFgKWyT1jrLhiXGOM_/s400/joltsJOR.png" width="400" /></a></div>
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While you may be thinking "Yes, the COVID-19 shock", I should point out that this data is from February 2020 — <i>and the deviation starts with data from December 2019</i>. As I put it <a href="https://twitter.com/infotranecon/status/1239947706975412224?s=20">in a tweet</a> from last month's data: What if there was a recession brewing and COVID-19 just triggered the market, like the old trope of a tree branch breaking causing an avalanche?</div>
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I saw that in the 2008 recession the JOLTS measures were <a href="http://informationtransfereconomics.blogspot.com/2017/07/jolts-leading-indicators.html">some of the earlier indicators</a> in the labor market with job openings being 4-6 months ahead of the shock to the unemployment rate. That was based on a single shock, but the <a href="https://informationtransfereconomics.blogspot.com/2018/10/building-models.html">hires data averages about 5 months lead</a> using multiple shocks (in both directions) from the 1990s recession to today.</div>
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And last month's unemployment rate showed the first signs of a non-equilibrium shock with March 2020 data by either the Sahm rule or my "<a href="https://informationtransfereconomics.blogspot.com/2017/04/determining-recessions-with-algorithm.html">recession detection algorithm</a>" threshold:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhKepPjjjwKb-xDfb67abmh49m2IdZFkeeke7l6x-1rn926BDcZ6ocTpf2IOSvKiz6jBlu_5RgE-MqNO1wvANRRwar25pUnUPYNh6Rovm1ExiDpJTOJz-sqSkp7telNubv3USD3-cz_Boqv/s1600/unrate+2020-04-03.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="483" data-original-width="792" height="243" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhKepPjjjwKb-xDfb67abmh49m2IdZFkeeke7l6x-1rn926BDcZ6ocTpf2IOSvKiz6jBlu_5RgE-MqNO1wvANRRwar25pUnUPYNh6Rovm1ExiDpJTOJz-sqSkp7telNubv3USD3-cz_Boqv/s400/unrate+2020-04-03.png" width="400" /></a></div>
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December 2019 to March 2020 is 4 months — right in line with the previous recession.</div>
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Now I understand it seems odd — how could JOLTS data predict a pandemic? Or as I put it in <a href="https://twitter.com/infotranecon/status/1239947706975412224?s=20">my twitter thread referenced above</a> — how could <a href="https://informationtransfereconomics.blogspot.com/2018/06/yield-curve-inversion-and-future.html">the yield curve</a> predict a pandemic? Even the "<a href="https://informationtransfereconomics.blogspot.com/2018/10/limits-to-wage-growth.html">limits to wage growth</a>" [1] hypothesis predicts a recession!</div>
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But in this view, the pandemic was just a coordinating signal. Often, these coordinating signals come from the Fed — an interest rate hike, lack of a cut, or even <a href="https://informationtransfereconomics.blogspot.com/2019/03/two-phases-of-2008-housing-crisis.html">letting a financial institution fail</a> — and <a href="https://informationtransfereconomics.blogspot.com/2014/10/coordination-costs-money-causes.html">coordination causes recessions</a> (we all cut back on spending, we all sell our stocks, etc). Because the pandemic signal was so sudden and so unambiguous, we got a much sharper signal in the unemployment rate than usual and a bit of a compressed period between JOLTS and unemployment. For example, total separations is only barely registering a signal (it's there) while hires shows nothing yet (click to enlarge):</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjP1MTJMFveem1z1vVttakT23fcIA7XIjt1u53qNj-EmPz1iE55KS3tnGzDx4SSdHVs2oLJZBUAaHcttpQIoRBprHch9VMOfeCM8oqh9np8vK094t3PIxc9drTq4ZLIqAsdZZ5uGlgOD4Xa/s1600/joltsHIR.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="483" data-original-width="792" height="121" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjP1MTJMFveem1z1vVttakT23fcIA7XIjt1u53qNj-EmPz1iE55KS3tnGzDx4SSdHVs2oLJZBUAaHcttpQIoRBprHch9VMOfeCM8oqh9np8vK094t3PIxc9drTq4ZLIqAsdZZ5uGlgOD4Xa/s200/joltsHIR.png" width="200" /></a><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgN8M7aIAUzh3MlzmXLgRAv3ds7eMFZARbBeGzgOYd8MQwUoukF55bGTe50rNe2XRsTgcDKUqhBQ_Bl8OSdXc0Iio_HJkzLZcxRbH727yLAashzS4KV2X5A7bKuAEJlmajPSQHYEXF5HNfp/s1600/joltsTSR.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="477" data-original-width="792" height="120" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgN8M7aIAUzh3MlzmXLgRAv3ds7eMFZARbBeGzgOYd8MQwUoukF55bGTe50rNe2XRsTgcDKUqhBQ_Bl8OSdXc0Iio_HJkzLZcxRbH727yLAashzS4KV2X5A7bKuAEJlmajPSQHYEXF5HNfp/s200/joltsTSR.png" width="200" /></a></div>
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COVID-19 was the twig crack that caused an avalanche that was already building.</div>
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I've seen that some people think the recovery will be rapid. I doubt this because we are seeing a shock to the labor market — for example, <a href="https://fred.stlouisfed.org/series/ICSA">initial claims spiked into the millions</a>. A typical <a href="https://informationtransfereconomics.blogspot.com/2016/03/the-emh-and-evaporating-information.html">"surprise information shock" that evaporates</a> has a distinct pattern:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjWaoGyxPwNCkPEOfCj67Xpvv311rnub5nlrJ6DuhnEB_hm07WqZsSBfJVHBoksf-FUM9Kq_0ugmDCjzzvaGNOaBbfpNmAnSIVCW26JHLUS_yfwcryMmUE-I8NbRnZY91vHTAxOxVvUQgAI/s1600/price1.gif" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="233" data-original-width="720" height="128" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjWaoGyxPwNCkPEOfCj67Xpvv311rnub5nlrJ6DuhnEB_hm07WqZsSBfJVHBoksf-FUM9Kq_0ugmDCjzzvaGNOaBbfpNmAnSIVCW26JHLUS_yfwcryMmUE-I8NbRnZY91vHTAxOxVvUQgAI/s400/price1.gif" width="400" /></a></div>
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It would look something like the red dashed line in this graph of S&P 500 data (while I show a non-equilibrium shock the size of the 2008 recession as a counterfactual recession path for reference):</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhirI6ov34PVeSpp_eLF7H1I60ABBtk3CvD5dgolqhywWdYEzfY4KGTUGVNKnumxc_R7OTIxmcgbEIFyEp2uFMvJ3q6fbTXSL8pa2hVqO2gtrCVcPGr8HhchCf-nwc-e5J9aGIGYWPPzgsa/s1600/shocksSP500.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="498" data-original-width="792" height="251" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhirI6ov34PVeSpp_eLF7H1I60ABBtk3CvD5dgolqhywWdYEzfY4KGTUGVNKnumxc_R7OTIxmcgbEIFyEp2uFMvJ3q6fbTXSL8pa2hVqO2gtrCVcPGr8HhchCf-nwc-e5J9aGIGYWPPzgsa/s400/shocksSP500.png" width="400" /></a></div>
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However, unemployment is already rising and it falls at basically the same rate over the entire history of the data. This "<a href="https://informationtransfereconomics.blogspot.com/2014/07/remarkable-recovery-regularity-and.html">remarkable recovery regularity</a>" became the basis for the <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3094757">dynamic information equilibrium model</a> (first <a href="http://informationtransfereconomics.blogspot.com/2016/10/dynamic-unemployment-equilibrium-and.html">here</a>, then <a href="https://informationtransfereconomics.blogspot.com/2017/01/dynamic-equilibrium-unemployment-rate.html">here</a>). This implies that we are unlikely to see a sudden shift back to low unemployment but rather something more like this:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjRbCfD34B-9izf6N0aZ6S9j8S3D72ZYnllHVVaTU_5rJg1XlYW4mVoiWPXAexgETl67XhIMVmpspUttDezqtbug-5DXNSFQKCemJaxDP4UYVdUCn5EkIOItW2ksRDEyPk6t5W4YVqg-7H4/s1600/unrateCounterfactual1.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="481" data-original-width="948" height="202" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjRbCfD34B-9izf6N0aZ6S9j8S3D72ZYnllHVVaTU_5rJg1XlYW4mVoiWPXAexgETl67XhIMVmpspUttDezqtbug-5DXNSFQKCemJaxDP4UYVdUCn5EkIOItW2ksRDEyPk6t5W4YVqg-7H4/s400/unrateCounterfactual1.png" width="400" /></a></div>
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I added a <a href="https://informationtransfereconomics.blogspot.com/2017/11/unemployment-rate-step-response-over.html">step response</a> (i.e. "ringing artifacts" or overshooting) to this qualitative non-equilibrium shock because the shock seems pretty sharp, however it is possible it won't happen as the step response <a href="https://informationtransfereconomics.blogspot.com/2017/11/unemployment-rate-step-response-over.html">has been gradually disappearing over time in US data</a>. It's possible it won't be this big — though some people like <a href="https://www.bloomberg.com/news/articles/2020-03-22/fed-s-bullard-says-u-s-jobless-rate-may-soar-to-30-in-2q">James Bullard</a> are are saying 30% is possible so it might be even bigger. But even the rise to 4.4% already in the data will take <b><i>3 years</i></b> to get back to 3.5% along the dynamic equilibrium path.</div>
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It's going to be a long slog.</div>
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...</div>
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<b>Footnotes:</b></div>
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<span style="font-size: x-small;">[1] In the past several decades, when wage growth exceeds the nominal GDP growth trend, there has generally been a recession.</span></div>
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Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com0tag:blogger.com,1999:blog-6837159629100463303.post-86764192109324098412020-02-29T14:15:00.002-08:002020-03-08T19:02:30.732-07:00Market updates for a bad week<div style="text-align: justify;">
Now I don't really look at the information equilibrium models for markets as particularly informative (looking at the error band spreads should tell you all you need to know about that) — this should be taken with a grain of salt. And always remember: I'm a crackpot physicist, not a financial adviser.</div>
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<b>The stock market and recession shocks</b><br />
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With that out the way, here's what the recent drop in the markets looks like on the <a href="https://informationtransfereconomics.blogspot.com/2017/01/what-about-s-500.html">S&P 500 model</a>:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEihdp4QNIFuzugkDiKEgPugrDxn6Eqt7ZWpEUmwsgRbbfgOimv6BxGiAqkaGpHDntEdnCXOp5gZuvl_o597j6le600Ks_vZRYre_xwaQtzAHF61Rqpl1x219ovbZoKcwFoiaB4eBtifQUGZ/s1600/dynamic+equilibrium+SP500+corona.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="498" data-original-width="792" height="251" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEihdp4QNIFuzugkDiKEgPugrDxn6Eqt7ZWpEUmwsgRbbfgOimv6BxGiAqkaGpHDntEdnCXOp5gZuvl_o597j6le600Ks_vZRYre_xwaQtzAHF61Rqpl1x219ovbZoKcwFoiaB4eBtifQUGZ/s400/dynamic+equilibrium+SP500+corona.png" width="400" /></a></div>
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Curiously, we seem to be back in the post-Tariff equilibrium after the past few months of out-performing that expectation. We are at the edge of the 90% band estimated on post-recession data (blue), and entering into the 90% band estimated on the entire range of data since 1950 (lighter green).</div>
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I should also note that in the past, the recession process is never really a single drop straight down. It's a series of drops over the course of months with some moments of recovery:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEilcV5vgiyvCluJ1REG50jFncQ_0p2Qd8KTPxqTPFtom1UdeVt3n6SUyProlScqV2EuEhwN-Drpqmvbi2r9u5b7h4L_jcS2_qxw_S_wTZiABJPCtUx-_XQi1sEjsDj6WhKfaQP5nr4ah-Hj/s1600/dynamic+equilibrium+SP500+info+eq+longer+term.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="498" data-original-width="792" height="251" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEilcV5vgiyvCluJ1REG50jFncQ_0p2Qd8KTPxqTPFtom1UdeVt3n6SUyProlScqV2EuEhwN-Drpqmvbi2r9u5b7h4L_jcS2_qxw_S_wTZiABJPCtUx-_XQi1sEjsDj6WhKfaQP5nr4ah-Hj/s400/dynamic+equilibrium+SP500+info+eq+longer+term.png" width="400" /></a></div>
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That does not mean the recent drop is not the start of such a series, just that it's entirely possible this could turn around.</div>
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Is this a prelude to a recession? Maybe, maybe not. For one thing, it will be different from the past two "<a href="https://informationtransfereconomics.blogspot.com/2018/01/24-growth-forever.html">asset bubble era</a>" recessions (dot-com in 2001 and housing in 2008) given there's no discernible asset bubble in recent GDP data:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjSCkXQWqge-vBJBrWpTi-2vTQMbQUYqwVSX6zoks0fN9tLCjYCPJW7tjvnxD0Gbt2tzQkYKchZERNpq7xGRKLRpdZSUXBGZglrT2hebIKKPRPJusHcN96OXd-NOXTaSWCoLpo1iEsP1mzc/s1600/dynamic+equilibrium+%2528ngdp+deflator+rgdp%2529+5a.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="475" data-original-width="792" height="238" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjSCkXQWqge-vBJBrWpTi-2vTQMbQUYqwVSX6zoks0fN9tLCjYCPJW7tjvnxD0Gbt2tzQkYKchZERNpq7xGRKLRpdZSUXBGZglrT2hebIKKPRPJusHcN96OXd-NOXTaSWCoLpo1iEsP1mzc/s400/dynamic+equilibrium+%2528ngdp+deflator+rgdp%2529+5a.png" width="400" /></a></div>
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It would be an example of a non-Minky recession! (At least if this isn't some kind of shadow economy crisis — the housing boom didn't show up in the stock market, but does show up in GDP, while the dot-com boom shows up in both.)</div>
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We are basically reaching my "<a href="https://informationtransfereconomics.blogspot.com/2018/10/limits-to-wage-growth.html">limits to growth</a>" hypothesis — that recessions happen when wage growth exceeds GDP growth, thus eating into profits. (In fact, that interacts with the asset bubbles as the asset bubbles boost GDP allowing wage growth to go higher than it would have without the bubble.) This graph shows the DIEM trend of GDP (blue line), the wage growth DIEM (green line) as well as projected paths (dashed) and a recession counterfactual (dotted green).</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg5mTfaQlgFQhloBKXXjKE3G82TlGjl0ejYoEMNxwSQqWzJz98xdJz7QpmU3-irCJUx_OBb8av2xfYFc_DSkeE4iJCmeNw_xPn_UlCfDlVFTQIlYgviIEH45jaGmYahu7n-25AiIwF1F7ZX/s1600/dynamic+equilibrium+wage+growth+1.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="420" data-original-width="875" height="191" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg5mTfaQlgFQhloBKXXjKE3G82TlGjl0ejYoEMNxwSQqWzJz98xdJz7QpmU3-irCJUx_OBb8av2xfYFc_DSkeE4iJCmeNw_xPn_UlCfDlVFTQIlYgviIEH45jaGmYahu7n-25AiIwF1F7ZX/s400/dynamic+equilibrium+wage+growth+1.png" width="400" /></a></div>
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But there's another aspect that I've been carrying along <a href="https://informationtransfereconomics.blogspot.com/2014/10/coordination-costs-money-causes.html">since this blog started</a> — that spontaneous drops in "entropy" (i.e. agents bunching up in the state space by all doing the same thing, like panicking) — are behind recessions. These spontaneous falls make economics entirely different from thermodynamics where they're disallowed by the second law, by the way (atoms don't get scared and cower in the corner). This human social behavior would ostensibly be triggered by news events that serve to coordinate behavior — unexpected Fed announcements, bad employment reports, yield curve inversion, or in this case a possible global pandemic. Or all of the above? I imagine if the Fed comes out of its next meeting in March with no interest rate cut, it might make a recession inevitable.</div>
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<b>Interest rates and inversion</b><br />
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The 10-year rate is back at the bottom of the range of expected values from <a href="https://informationtransfereconomics.blogspot.com/2015/08/comparison-of-interest-rate-predictions.html">this 2015 (!) forecast</a>:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiBY-3yZSSjFrY-GPrTtBrhz21yFS7fWS5hEyVWKPBCvuDDvGvCkyEduVzXjBV8Ozx8mIsLWjMr4oZ2b_cGHjETeDn2ToLy-8Pr6lhS9PE-potoT7ddt6co0j8Ul3jmB4Y3DFYQQmWU_bnv/s1600/ITM+interest+rates+and+price+level+%2528prediction+comparison%2529.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="482" data-original-width="792" height="242" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiBY-3yZSSjFrY-GPrTtBrhz21yFS7fWS5hEyVWKPBCvuDDvGvCkyEduVzXjBV8Ozx8mIsLWjMr4oZ2b_cGHjETeDn2ToLy-8Pr6lhS9PE-potoT7ddt6co0j8Ul3jmB4Y3DFYQQmWU_bnv/s400/ITM+interest+rates+and+price+level+%2528prediction+comparison%2529.png" width="400" /></a></div>
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And the <a href="https://informationtransfereconomics.blogspot.com/2018/06/yield-curve-inversion-and-future.html">interest rate spreads</a> are trending back down and inverting again:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEikj0XuQJ3pyzgGe0QoaWVpUnxae465kNVSto1wxn16Pss8SlDXlZzaisvJxsyGirvOFYtzLV0QFFMgdlgHQVw_77oq0gNQqQGl1HBhNTzfsTLqd-6szTlSyTw-I08OAAmteoFrbTdL8dlr/s1600/interest+rate+spreads.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="501" data-original-width="884" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEikj0XuQJ3pyzgGe0QoaWVpUnxae465kNVSto1wxn16Pss8SlDXlZzaisvJxsyGirvOFYtzLV0QFFMgdlgHQVw_77oq0gNQqQGl1HBhNTzfsTLqd-6szTlSyTw-I08OAAmteoFrbTdL8dlr/s400/interest+rate+spreads.png" width="400" /></a></div>
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One thing to note is that while the median <b><i>daily </i></b>spread data (red) dipped into the range of turnaround points seen before a recession in the past three recessions several months ago, the <b style="font-style: italic;">monthly </b>(average) spread data (orange) did not go that low (n.b. the monthly average is what I used to derive the metrics). We also didn't see interest rates rise into the range seen before a recession (which tends to be caused by the Fed lowering interest rates in the face of bad economic news). An inversion or near miss followed by another inversion is not exactly <a href="https://fred.stlouisfed.org/series/T10Y2Y">unknown in the time series data</a>, either.</div>
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<b>JOLTS openings and the market</b></div>
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The latest JOLTS job openings data released earlier this month (data for December 2019) showed a dramatic drop even compared to the 2019 re-estimate of the dynamic equilibrium rate:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEge1XxJK8UjOdifoseIxn-YIkkGuaV8gcS7n4rPyTCaDP5xGlC9Xz70qvIFqOagagFyRpGlpfDF62TIMwiOSVNa7IpJEY6uLAemYjP9n2kIKQ0iW4HnDPxNsyjM1bd5JUal9xQcGlv1U2j9/s1600/dynamic+equilibrium+%2528jolts+openings%2529+data+updates+%2528fixed+recession+date+extrap+future%2529.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="479" data-original-width="792" height="241" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEge1XxJK8UjOdifoseIxn-YIkkGuaV8gcS7n4rPyTCaDP5xGlC9Xz70qvIFqOagagFyRpGlpfDF62TIMwiOSVNa7IpJEY6uLAemYjP9n2kIKQ0iW4HnDPxNsyjM1bd5JUal9xQcGlv1U2j9/s400/dynamic+equilibrium+%2528jolts+openings%2529+data+updates+%2528fixed+recession+date+extrap+future%2529.png" width="400" /></a></div>
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This appears to be right on schedule with <a href="http://informationtransfereconomics.blogspot.com/2019/09/market-correlated-fluctuations-in.html">the market correlation I noticed a few months ago</a>:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjCtP_T-3X3co9x_mafY-KwpjcB0l-Jo75sSg078YG-0WoWVJJDWAS82CgMmKpDEvFqs9fzxwJlfbZKj1bb1Zt2lbxAihLDRL66RM9gap4YFJSxw2WciINKa8Dn4yYQvoIZLHZIosXFKMB7/s1600/dynamic+equilibrium+%2528jolts+openings%2529+playing+with+different+fits+%2528SP500+match%2529.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="425" data-original-width="990" height="171" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjCtP_T-3X3co9x_mafY-KwpjcB0l-Jo75sSg078YG-0WoWVJJDWAS82CgMmKpDEvFqs9fzxwJlfbZKj1bb1Zt2lbxAihLDRL66RM9gap4YFJSxw2WciINKa8Dn4yYQvoIZLHZIosXFKMB7/s400/dynamic+equilibrium+%2528jolts+openings%2529+playing+with+different+fits+%2528SP500+match%2529.png" width="400" /></a></div>
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The recent drop (December 2019) matches up with the drop at the beginning of that same year (Jan 2019) in the aftermath of the December 2018 rate hike. If this correlation holds up, the job openings rate will rise back up and then fall again in January 2021 (about 11 months after Feb 2020). But the other possibility is that this is the first sign of a recession — <a href="http://informationtransfereconomics.blogspot.com/2017/07/jolts-leading-indicators.html">the JOLTS measures all appear to lead</a> the unemployment rate (via e.g. <a href="https://informationtransfereconomics.blogspot.com/2019/06/market-updates-fairs-model-and-sahms.html">Sahm Rule</a>) as an indicator. However, JOLTS is noiser (which requires a higher threshold parameter) and later than the unemployment rate. JOLTS comes out 2 months after the data it's representing (the data for December 2019 came out mid-February 2020, while the unemployment rate for December 2019 came out the first week of January 2020), so whether it's a better indicator than the unemployment rate remains to be seen — there's a complex interplay of noise, data availability, and <a href="https://informationtransfereconomics.blogspot.com/2019/10/calling-recession-too-early-and.html">revisions</a> (!) that makes me think we should just stick to Sahm's rule.</div>
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I'll be looking forward to the (likely revised!) JOLTS data coming with the Fed's March meeting.</div>
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<b>Update 8 March 2019</b><br />
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I updated the graphs with a few more days of data, including a Fed rate cut (visible in the spread data). Click to enlarge:<br />
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Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com2tag:blogger.com,1999:blog-6837159629100463303.post-38182703785429357162020-02-28T20:32:00.001-08:002020-02-28T20:32:06.939-08:00Dynamic equilibrium: health care CPI<div style="text-align: justify;">
Since I've been looking at a lot of health care data recently, I thought I'd run the US <a href="https://fred.stlouisfed.org/series/CPIMEDSL">medical care CPI component</a> through the <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3094757">dynamic information equilibrium model</a> (DIEM). It turns out to have roughly the same structure as CPI overall (click to enlarge):</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjzyznSX342q06GuacivkhDZopm2pzqwR4xPH7pwhO-DpBR2K_L7NLmJ66-bccuLBhC6RzbQ5DwRkQa-zboC9ooS8B4NiSNnemCNGdNiBQEpyv3mvjRGP9P9RpSYhFsspGWoTLbMlXJ4OpN/s1600/DIEM+health+care+costs.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="477" data-original-width="928" height="205" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjzyznSX342q06GuacivkhDZopm2pzqwR4xPH7pwhO-DpBR2K_L7NLmJ66-bccuLBhC6RzbQ5DwRkQa-zboC9ooS8B4NiSNnemCNGdNiBQEpyv3mvjRGP9P9RpSYhFsspGWoTLbMlXJ4OpN/s400/DIEM+health+care+costs.png" width="400" /></a></div>
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A big difference is that the dynamic equilibrium growth rate is <i>α</i> = 0.035/y, basically a full percentage point above <a href="https://informationtransfereconomics.blogspot.com/2019/06/cpi-and-diem-inflation-forecasts.html">the rate for all items</a> <i>α</i> = 0.025/y. As it's been basically at play since the 50s (at least), medical prices are now twice what prices as a whole have risen in the same period.</div>
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I was curious — was the US an outlier (<a href="https://informationtransfereconomics.blogspot.com/2020/02/leaning-over-backwards-health-care.html">lol</a>)? I ran the model over a bunch of HICP health data from Eurostat (which the UI is at best silly, at worst pathological) for several countries (Sweden, France, the Netherlands, Switzerland, Germany, the UK, Estonia, Italy, Turkey, Denmark, and Spain). This is definitely a graph you have to click to enlarge:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhyTn4p8L2BnhAOe_Uy_Shve5SBi4mZNbZS9ogRX90Fn6CFfq3w4kfjPCqTMKyXcOSX3tYzb0eq7G9j9gnPlLVSApBJ1ej__PCsgKffziruJ7X8F6EVlKug-7jzN4IdPLBwuwh3j-uzmlsv/s1600/DIEM+health+care+costs+GRID.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="867" data-original-width="1600" height="216" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhyTn4p8L2BnhAOe_Uy_Shve5SBi4mZNbZS9ogRX90Fn6CFfq3w4kfjPCqTMKyXcOSX3tYzb0eq7G9j9gnPlLVSApBJ1ej__PCsgKffziruJ7X8F6EVlKug-7jzN4IdPLBwuwh3j-uzmlsv/s400/DIEM+health+care+costs+GRID.png" width="400" /></a></div>
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They're all remarkably similar to each other except France, which came out with an equilibrium rate of <i>α </i>= 0. That could be wrong due to the recent data being in the middle of a non-equilibrium shock — time will tell.</div>
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I also compared the dynamic equilibrium to the DIEM model of the CPI (HICP) for all items for each country which produces an interesting plot:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhFjypM0KnkJJ5hywSsWCA1jJZNO8zuEWP437AmmLpl4H54gl_jRHauU6I3EnWlcN-6a1k25t95zbwUsB_GQtodTSeiuEq08CtUuZIbgqB1sSOBp2SDP1KEOgnA_q02ePkIspmr2a8bn5OS/s1600/DIEM+results+health+care+cost+findings.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="506" data-original-width="504" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhFjypM0KnkJJ5hywSsWCA1jJZNO8zuEWP437AmmLpl4H54gl_jRHauU6I3EnWlcN-6a1k25t95zbwUsB_GQtodTSeiuEq08CtUuZIbgqB1sSOBp2SDP1KEOgnA_q02ePkIspmr2a8bn5OS/s320/DIEM+results+health+care+cost+findings.png" width="318" /></a></div>
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It looks like the US is not much of an outlier on that graph — but that's a bit misleading since the possible inflation rates can't really deviate too much above the diagonal <i>y</i> = <i>x</i> line otherwise headline inflation (i.e. all the components) would rapidly be overtaken by health care price inflation (one of those components). In fact, nearly every time it came out that the health care rate was basically equal to the headline rate. You can see it if we plot the difference versus the headline CPI rate:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjkib68bm6Jr0eNmL_awleGCyE-Z75jqAhzW5c5zEoa33DSgzEW0QmuQQ3rmBCe0KGeNXwRXaASmsFpcZ6XTfzjTbz2y5PxHjIHpg6rvRe3vaJi9_DeeMl-djHuOUyhJjLQRemDGYfl7HGP/s1600/DIEM+results+health+care+cost+findings+2.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="426" data-original-width="792" height="215" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjkib68bm6Jr0eNmL_awleGCyE-Z75jqAhzW5c5zEoa33DSgzEW0QmuQQ3rmBCe0KGeNXwRXaASmsFpcZ6XTfzjTbz2y5PxHjIHpg6rvRe3vaJi9_DeeMl-djHuOUyhJjLQRemDGYfl7HGP/s400/DIEM+results+health+care+cost+findings+2.png" width="400" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhDGHc-p25A2FBc-Or1b3sT0N67CKV0ukOLvfPo4-jbwr74R9VQUiAaZs9KcKee-wOdlW_ltROYnh16wRQbh8WwYrtqO3eyqh3NgAbA88vLa1Ply33-OT83w6dgPq3LomIonnpKGbN3qR0-/s1600/DIEM+results+health+care+cost+findings+3.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="434" data-original-width="792" height="218" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhDGHc-p25A2FBc-Or1b3sT0N67CKV0ukOLvfPo4-jbwr74R9VQUiAaZs9KcKee-wOdlW_ltROYnh16wRQbh8WwYrtqO3eyqh3NgAbA88vLa1Ply33-OT83w6dgPq3LomIonnpKGbN3qR0-/s400/DIEM+results+health+care+cost+findings+3.png" width="400" /></a></div>
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Most of the countries are clustered right around zero, with outliers being the US and France. France is an outlier because its health care price inflation <a href="https://fred.stlouisfed.org/series/CP0600FRM086NEST">has been basically zero for the past decade</a> meaning the difference graphed above is essentially the negative of the inflation rate of about 2%. The US is an outlier in the other direction — by 4 standard deviations if we leave out France and the US in the estimate of the distribution.</div>
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If this is correct, the US health care prices rise at nearly a percentage point faster than prices overall, meaning prices are nearly 30% higher today from growth over the period from 1996-2020 (the Eurostat data range) than they would be if those prices grew like any other country's. And these are <i><b>prices </b></i>— not income, profits, or consumption.</div>
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<b>Appendix</b><br />
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Here are all the individual graphs. The dashed lines are lines at the dynamic equilibrium rate, but in some of the graphs they appear well off the lines — that's because in some of the cases the different levels add the shocks in different ways (e.g. the 2nd shock is positive but the 3rd shock is negative) so they add or subtract differently for each country. Couple that with the fact that I determine the sign of a shock in the parameter estimation by the sign of the width, not the amplitude but instead of using that sign I set it by hand for the dashed line guides, and well, you see the result — random dashed lines appearing across the graphs (albeit with the right slope). Anyway, click to enlarge.</div>
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<br />Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com0tag:blogger.com,1999:blog-6837159629100463303.post-55900760931187694252020-02-23T21:00:00.003-08:002020-02-29T11:23:23.371-08:00A future response from Random Critical Analysis?<div style="text-align: justify;">
<span style="background-color: white; font-size: 15px; white-space: pre-wrap;">So I have <a href="https://twitter.com/RCAFDM/status/1231303125434294277?s=20">this to look forward to</a>:</span></div>
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<i>I'll be addressing the sole constructive, objective argument you made in that blog post within the next few days. I'll try to be respectful and fair, even though you seem to be unable or unwilling to reciprocate.</i></blockquote>
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That's regarding <a href="https://informationtransfereconomics.blogspot.com/2020/02/leaning-over-backwards-health-care.html">my previous post</a>. There were quite a lot of right wing, conservative, and libertarian Twitter accounts (amazingly, groups that don't like government health care) who seemed to think that I was being a jerk, disrespectful, or making <i>ad hominem</i> arguments — and that somehow reflected on what I was saying. I pause to note that saying I'm being a jerk and using that to somehow dismiss what I was saying is itself <i>argumentum ad hominem</i>. That aside, no one is owed someone else's respect. </div>
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I was pointing out that we should not assume RCA is competent — hard to imagine that ever coming across as respectful to RCA! And it's true that is <i>ad hominem</i>! But expertise in stats as well as using software to run regressions was very much at issue. He is making arguments (and mistakes!) that are unsupportable for reasons that have to do with the details of how regressions work.</div>
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There are also additional reasons to believe RCA is entirely biased (he called me a <a href="https://twitter.com/RCAFDM/status/1231065867338878976?s=20">socialist</a>, lol), and his first response was that I was attacking his analysis <a href="https://twitter.com/RCAFDM/status/1230998733325729793?s=20">because he disagreed with my politics</a>. Overall, since he didn't disclose who he is or his politics — and that we can gather from his statements that his politics agree with the finding that health care spending in the US is perfectly normal — he really needs to do a lot more "leaning over backwards" <b><i>because</i></b> of that bias and failure to disclose.</div>
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I'm sorry to say models and statistics can be manipulated in multiple ways. And people have a way of finding out how to present results that agree with their preconceived ideas. People have a tendency to believe that regressions don't lie, but just like photographs and film editing there are lots of things you can do to present something that is not completely honest (even if it's superficially correct) — and that's especially effective on people who aren't well versed in stats (just like people who don't work with Photoshop aren't as good at spotting alterations in pictures).</div>
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If we find some paper out there touting the benefits of free market economics from the <a href="https://en.wikipedia.org/wiki/Cato_Institute">Cato Institute</a> or <a href="https://en.wikipedia.org/wiki/Mercatus_Center">Mercatus Center</a>, we all have reason to be suspect. I'm not saying it's something they can't overcome — I've actually cited a Mercatus fellow in my book. But it requires some extra leaning over backward (e.g. a Mercatus fellow writing in their paper "I know you're reading this and thinking <i>of course someone at Mercatus found this</i>,<i> but ...</i>" and going on to explain). We don't even know who RCA is which obscures our ability to do this kind of due diligence.</div>
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With that out of the way, what did he think the "sole constructive, objective argument" was?</div>
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<a href="https://twitter.com/RCAFDM/status/1231190745815638018?s=20">A tweet</a>:</div>
<blockquote class="tr_bq" style="text-align: justify;">
<i>The presumably substantive part of his argument is little more than a quibble over choice of model. Even if he were objectively correct in this, which he isn’t, it leaves the vast majority of my arguments intact. He just makes himself look like an asshole.</i></blockquote>
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<a href="https://twitter.com/RCAFDM/status/1231298128235704322?s=20">Another tweet</a>:</div>
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<i>Someone preferring a different model than you is not a priori evidence of bad faith. You're coming into this w/ the presumption that you know the one true way to do this, ignoring that this approach is quite common, and without having the perspective of the rest of the evidence.</i></blockquote>
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Apparently, he's a double space after a period person. Ugh. Unfortunately, this is incorrect in multiple ways.</div>
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First, I was to write a basic math book but started it off with a whole table of incorrect addition facts, like 2 + 2 = 5, you have no reason to continue. This doesn't leave the rest of the book "intact". There is just no reason to continue past the first point because it's fundamentally flawed, and the rest can be presumed to be as flawed.</div>
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Second, while "this approach is quite common", it is <b><i>not </i></b>used to extrapolate a nonlinear coefficient that far outside the range of the data (see the <a href="https://informationtransfereconomics.blogspot.com/2020/02/leaning-over-backwards-health-care.html">2/22 update, part II of my blog post</a> for more details). The difference of logs ceases to be a percentage for more than ~ 10% differences, and while you might extrapolate an elasticity in economics you don't do it for a factor of 2 difference from the data you used to estimate it.</div>
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Third, I do not think the linear model is a better model and never said that [1] — I said it was <i>indistinguishable </i>from the nonlinear one he uses over the non-US data and results in a different conclusion in terms of the US being an outlier. If I have two models that are equally valid and one implies one conclusion and one implies another, it's really a toss-up. You don't draw <b><i>either conclusion</i></b>. At least if you're being scientific. Leaning over backwards requires you support both conclusions or neither.</div>
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It's selecting one or the other without saying both are equally good that's evidence of bad faith. The reason RCA claims the nonlinear fit is better is because it makes it such that the US not an outlier — <i>which is the conclusion he is trying to find</i>. That is to say he has to assume the US is not an outlier in order to select his nonlinear specification. I think this point is lost on a lot of people rising to RCA's defense [2].</div>
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But I discovered something else about why he chose the nonlinear model that goes to RCA's incompetence here. He appears to have selected that nonlinear model because of the better <i>R²</i> relative to the <i>R²</i> of the linear model. This is hilariously wrong. <a href="https://twitter.com/RCAFDM/status/950728292851646464?s=20">RCA was apparently complaining</a> about being blocked by a statistics professor who complained about the exact same thing I am complaining about [3]:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgIUSWPMYqCd6CBXjH_gGfnKlRyz3ScuG_6Lzo3hPc8LOz0_waHlOVfpxExSAkxSLVEaDGdOudL8-n_pD3e5_LYWO8_hygSvbm54KXyZruHX0ZyyIvTcHuY9WmPwErl_rWC2fr9CQaF2xlm/s1600/DTGqL8-WsAAQg65.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="765" data-original-width="636" height="400" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgIUSWPMYqCd6CBXjH_gGfnKlRyz3ScuG_6Lzo3hPc8LOz0_waHlOVfpxExSAkxSLVEaDGdOudL8-n_pD3e5_LYWO8_hygSvbm54KXyZruHX0ZyyIvTcHuY9WmPwErl_rWC2fr9CQaF2xlm/s400/DTGqL8-WsAAQg65.jpg" width="332" /></a></div>
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The tweets RCA was blocked for? <a href="https://twitter.com/RCAFDM/status/950592629636521985?s=20">These</a>:<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhl6TDZ1xSEDJUCoIqOMc54rGNqm4Pt89WaMtFylY1eNf645lvsnxp1nA5S3cqf2SWPlOY8XzwDInnXYigTCrTPXYDQf0iQ3srZFYNDfrBCmiND_-pGYZO2-HVD42xDF6uoheuHldD1lvfm/s1600/rsquaredModels.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="785" data-original-width="604" height="400" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhl6TDZ1xSEDJUCoIqOMc54rGNqm4Pt89WaMtFylY1eNf645lvsnxp1nA5S3cqf2SWPlOY8XzwDInnXYigTCrTPXYDQf0iQ3srZFYNDfrBCmiND_-pGYZO2-HVD42xDF6uoheuHldD1lvfm/s400/rsquaredModels.png" width="307" /></a></div>
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<i>R²</i> is not really a valid metric for nonlinear models aside from polynomials. <a href="https://statisticsbyjim.com/regression/r-squared-invalid-nonlinear-regression/">This is a great simple explanation</a> from <a href="https://statisticsbyjim.com/jim_frost/">a statistics consultant and author</a>. I'm not sure if RCA is using a polynomial here or a nonlinear model (such as a log regression as in graph under discussion <a href="https://informationtransfereconomics.blogspot.com/2020/02/leaning-over-backwards-health-care.html">in my previous post</a>). He's used polynomials in the past, and<i> R²</i> makes sense for those. But the thing is that<i> R²</i> is a monotonically increasing function of the number of variables, so comparing a linear model and a second order polynomial, the latter will always win. That's what the stats professor ("Statistical Ideas") is saying — it's understandable why he'd block someone who obviously doesn't understand what he's talking about.</div>
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But here RCA is also <i>comparing R²</i> for a linear and either a nonlinear model or a polynomial model which is either meaningless because a) linear and 2+ order polynomial are not commensurate, or b) a nonlinear model <i>R²</i> is not valid.</div>
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I'm not optimistic about RCA actually responding to my criticisms. I imagine he'll do something like the graphs above — comparing a nonlinear <i>R²</i> to a linear one — which will just demonstrate his incompetence further. Such is the problem with the <a href="https://en.wikipedia.org/wiki/Dunning%E2%80%93Kruger_effect">Dunning-Kruger effect</a>.</div>
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<span style="background-color: white; font-size: 15px; white-space: pre-wrap;">...</span><br />
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<span style="background-color: white; font-size: 15px; white-space: pre-wrap;"><b>Update 29 February 2020</b></span><br />
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<span style="background-color: white; font-size: 15px; white-space: pre-wrap;">Here's an illustration of the fact that <i>R²</i> increases monotonically with additional orders in a polynomial fit alongside another thing I've mentioned in passing that I'll discuss first — RCA's measure of AIC he uses for the x-axis <i>includes health care</i>. That is to say he is graphing <i>y </i>versus <i>x </i>= <i>y </i>+ <i>z</i>. If you do that with random data, you can easily get what looks like a linear correlation:</span></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhlIM14EhHndc3k6hCCvJhEJOJXkatQ3qWXYhiVZRrlo03iL2hjj5tspFfoYlJo1-60Dpt8W_R8teEtwu8J5OSdSBjQs8XY3VeF3z1BDcXmpfxHI_uZkQ1X0rAqWmTNnP9uhsdyD9p8P-RP/s1600/problems+with+R2+1.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="745" data-original-width="688" height="400" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhlIM14EhHndc3k6hCCvJhEJOJXkatQ3qWXYhiVZRrlo03iL2hjj5tspFfoYlJo1-60Dpt8W_R8teEtwu8J5OSdSBjQs8XY3VeF3z1BDcXmpfxHI_uZkQ1X0rAqWmTNnP9uhsdyD9p8P-RP/s400/problems+with+R2+1.png" width="368" /></a></div>
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<span style="background-color: white; font-size: 15px; white-space: pre-wrap;">This is why Lyman Stone's and Karl Smith's belief (discussed in [2] below) that any proportional relationship validates the claims is completely wrong. It can arise purely because health care is a component of AIC.</span></div>
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<span style="background-color: white; font-size: 15px; white-space: pre-wrap;"><br /></span></div>
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<span style="background-color: white; font-size: 15px; white-space: pre-wrap;">And if we fit progressively higher order polynomials to this data, we get the (well known) result that R² increases monotonically with the order of the polynomial:</span></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhmvZQtbVf62DI7ttlRGTfUS5irSD_EiYxdhaytXz116GTyEj2nsKIMtA5UXK_5YSA0zDmVWexp8wViZFnK3LCzmksEq319qsLy0YC3y0ORC7fwqjEvLWoicioASjXgtot2-XI897YcFQ5e/s1600/problems+with+R2+2.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="477" data-original-width="697" height="272" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhmvZQtbVf62DI7ttlRGTfUS5irSD_EiYxdhaytXz116GTyEj2nsKIMtA5UXK_5YSA0zDmVWexp8wViZFnK3LCzmksEq319qsLy0YC3y0ORC7fwqjEvLWoicioASjXgtot2-XI897YcFQ5e/s400/problems+with+R2+2.png" width="400" /></a></div>
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<span style="background-color: white; font-size: 15px; white-space: pre-wrap;"><b>Footnotes:</b></span><br />
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<span style="font-size: x-small;"><span style="background-color: white; white-space: pre-wrap;">[1] </span>I did say it was better in terms of absolute error, but that's just a single metric. Otherwise I said "Over the non-US data, the linear fit (brownish dashed line) is <b>basically as good as</b> the nonlinear fit ... And over the entire range, the nonlinear fit <b>falls inside the 90% confidence limits</b> of the linear model" (emphasis added)</span></div>
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<span style="font-size: x-small;">[2] Another weird defense was that finding <i>any </i>proportional relationship, linear or not, proves that health care expenses rise with income. The thing is the data set includes a lot of developing countries. I could see health care expenses rising with income for Mexico or Latvia.</span></div>
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<span style="font-size: x-small;"><br /></span></div>
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<span style="font-size: x-small;">And if that was the case, why stand up for RCA's specific proportional relationship — not one person who made the claim that any proportional relationship proved the point also said that RCA's analysis was garbage. It was more of a rhetorical tack than a logical one. </span><span style="font-size: x-small;">We're Karl Smith and Lyman Stone agreeing that RCA's analysis was garbage?</span></div>
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<span style="font-size: x-small;"><br /></span></div>
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<span style="font-size: x-small;">"So what if this analysis is garbage, anyone who says it's proportional proves the underlying point of the garbage analysis!" </span></div>
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<br /></div>
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<span style="font-size: x-small;">If I had a study that said that minimum wages reduced employment and you came along with a critique that said my analysis made major errors and should have resulted in a much smaller effect if the math was right, I don't get to come back and say "See, there's still an effect!"</span></div>
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<span style="font-size: x-small;">[3] RCA has a habit of <a href="https://twitter.com/infotranecon/status/1231060086434385920?s=20">basically ignoring other people's expertise</a> when it disagrees with him.</span></div>
Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com2tag:blogger.com,1999:blog-6837159629100463303.post-58876923406541322502020-02-21T14:08:00.003-08:002020-02-22T14:57:39.742-08:00Leaning over backwards: health care edition<blockquote class="tr_bq">
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<i>It’s a kind of scientific integrity, a principle of scientific thought that corresponds to a kind of utter honesty—a kind of leaning over backwards. For example, if you’re doing an experiment, you should report everything that you think might make it invalid—not only what you think is right about it: other causes that could possibly explain your results; and things you thought of that you’ve eliminated by some other experiment, and how they worked—to make sure the other fellow can tell they have been eliminated.</i> </div>
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<i>—<a href="http://calteches.library.caltech.edu/51/2/CargoCult.htm">Feynman</a></i></div>
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I need to start off with what should become an obligatory statement noting that while Feynman was pretty good about describing what it means to participate in the process of science, he was also a sexist jerk and a prime example of toxic masculinity.</div>
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Anyway, I can't remember how I came across it a year ago (I think via Steve Roth), but the anonymous "random critical analysis" [RCA] is <a href="https://randomcriticalanalysis.com/why-conventional-wisdom-on-health-care-is-wrong-a-primer/">back in the econoblogosphere</a> (it's still around, I swear!) — this time amplified by Alex Tabarrok at Marginal Revolution (not going to link). He's still peddling his wares. He claims:</div>
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<i>Health spending is overwhelmingly determined by the average real income enjoyed by nations’ <b>residents </b>in the long run.</i></div>
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Emphasis in the original. I think it's a good example of how relying on an internet rando [0] to do quantitative analysis on major policy issues can lead us astray. It's also a good case study in how to identify the sometimes subtle choices that end up ensuring the conclusions as well as the sometimes even subtler hints that people are overselling their competence.</div>
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I have no idea why he emphasized "residents" because the rest of the sentence isn't exactly that precise. You could dig into the PPP adjusted AIC <i>et cetera</i>, but I'd first like to focus on the "determined". The next graph in the extended blog post is a log-linear regression that actually has no causal interpretation — health care spending is "determining" income as much as income is "determining" health care spending:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgArdCz4IFWO5kLOLBAb-QmMLKmH6WtvUfQhBjiNG2Ky-xX04pP-9dGbH9TetIY6hpbLC-WhNlzsO2xpsqUnwfW9praDRtglGXcygHNNJYT0jvsQXqJDg3H95M13yfiDzT2JmNjwzQfGurn/s1600/rcafdm_oecd_income_health_elasticity_2017.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="666" data-original-width="720" height="370" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgArdCz4IFWO5kLOLBAb-QmMLKmH6WtvUfQhBjiNG2Ky-xX04pP-9dGbH9TetIY6hpbLC-WhNlzsO2xpsqUnwfW9praDRtglGXcygHNNJYT0jvsQXqJDg3H95M13yfiDzT2JmNjwzQfGurn/s400/rcafdm_oecd_income_health_elasticity_2017.png" width="400" /></a></div>
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Just because you chose the <i>x</i>-axis to be income and the <i>y</i>-axis to be health care spending and performed a regression does not mean you've found a causal relationship that "determines" things. Certainly, there is likely some relationship! Per capita income of a country seems like a plausible variable in a model of health care expenses. In fact, it's what you'd expect if health care was becoming more and more unaffordable as costs outstrip the ability to pay for them (a mechanism that seems to be at play for housing prices in the US). RCA's big innovation is saying that instead of this being a problem, this is what people want.</div>
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RCA makes a big point about using log-log graphs in the opening paragraphs, but one of the problems here is that he shows <b><i>only </i></b>the log-log version of this graph because — as we'll see below — the linear version looks pretty silly. We'll also see that lines on log-log graphs help conceal the choice (and it is a deliberate choice) of a nonlinear function. However, there's also this: </div>
<blockquote class="tr_bq" style="text-align: justify;">
<i>In case you’re not already aware, these slopes [on log-log plots] can be readily interpreted in percentage terms. ... For example, the slope in the health expenditure-income plot below implies that a 1% increase in underlying value on the x-axis (income) predicts a 1.8% increase in value on the y-axis (health spending).</i></blockquote>
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In reading this, I'm pretty sure that RCA doesn't actually understand that the 1.8 in that slope of the log-log graph means the growth rate of health spending is 1.8 <b><i>times </i></b>the growth rate in income. Sure, if incomes rise 1%, then health care will rise 1.8%. But if incomes rise 5%, then health care will rise 9%. Taking the difference in logs, you can substitute a (small) percentage in for <i>x</i> and get a percentage out as <i>y</i>, but you can't interpret the slope as a percentage unless that percentage is 180%. It's subtle, but it's the kind of thing you look for when teaching students because it helps you see if they understand the material or are just mechanically reproducing results.</div>
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I mean, in case you're not already aware [1] ...</div>
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Ok, next I have a bit of a nit — but it's kind of a theme of general sloppiness with RCA [2]. At that footnote we can learn a bit about orthogonal polynomials, but here we can learn a bit about significant figures. I was able to reproduce the graph above, but the equation in the annotation (like in the case in footnote [2]) gives an entirely different result (click to enlarge):</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhkfaHXeJxAtEkkOYucXPWQhQo9YUjFejmOOiPpaMyB1kQfLHJbAAmS2KHMj-yXBeaNqIdgHr97fFhAgtU_ZgUBw9XWovwqT-mCIeuoCUBsCjWIcIT7shhYSOlhfP62vV4SQPgfEANJ47og/s1600/this+again+%2528random+critical+analysis+analysis%2529.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="573" data-original-width="576" height="397" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhkfaHXeJxAtEkkOYucXPWQhQo9YUjFejmOOiPpaMyB1kQfLHJbAAmS2KHMj-yXBeaNqIdgHr97fFhAgtU_ZgUBw9XWovwqT-mCIeuoCUBsCjWIcIT7shhYSOlhfP62vV4SQPgfEANJ47og/s400/this+again+%2528random+critical+analysis+analysis%2529.png" width="400" /></a></div>
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<div style="text-align: justify;">
Blue is RCA's curve, gray dashed lines are my nonlinear model lines (either fit myself, or as above, using the equation RCA wrote down or rounding), and red is the data except for the US which is in green matching the original graph.</div>
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RCA rounded the two coefficients accurately (albeit to different orders), but it's really obvious we're on logarithmic axes when rounding from 9.88 to 10 moves you entirely off the data. RCA makes the claim that the fit is robust to leaving out the US, and if you look at the equations (especially if rounded by RCA's method) they are pretty close:</div>
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<i>y = − 9.88 + 1.77 x</i> with the US</div>
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<i>y = − 9.68 + 1.75 x</i> without the US</div>
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And that new equation (dashed gray) even looks pretty close on that log plot:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgCneub8drRDF0QvRJxQlHAFsXGBKgm07z4VMnwQ_X1MQ2ahuawy6CVEYpKUMcGSUo304WTpSOdyfon6MRx8zan5pDXK4kG4P8tn55h45rcUtTIUSS9GS3DQLLfsH6CO4sCUDl8gSYPQyZw/s1600/this+again+%2528random+critical+analysis+analysis%2529+2.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="573" data-original-width="576" height="397" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgCneub8drRDF0QvRJxQlHAFsXGBKgm07z4VMnwQ_X1MQ2ahuawy6CVEYpKUMcGSUo304WTpSOdyfon6MRx8zan5pDXK4kG4P8tn55h45rcUtTIUSS9GS3DQLLfsH6CO4sCUDl8gSYPQyZw/s400/this+again+%2528random+critical+analysis+analysis%2529+2.png" width="400" /></a></div>
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<div style="text-align: justify;">
As an aside, this also tells us that RCA decided to do his analysis of the US not being an outlier in healthcare spending by <i>including the US in the fits</i>. That's just not how that works. Anyway, transforming back to linear space, we've gone down by 10% at US levels of income:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhjGUYDTFcMQzOqViF35bXLCM8LrtACmPxq4lxDjaW-ColKEZWvywSdYQM5tpVaOp9jdH9jVnUZaqhf2D0CLDJxdx6MguR40LP-bu1qGY6xsGQ2-FwXCBvKwUw8B6JxNgbsewJGRITmLTgJ/s1600/this+again+%2528random+critical+analysis+analysis%2529+3.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="551" data-original-width="576" height="382" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhjGUYDTFcMQzOqViF35bXLCM8LrtACmPxq4lxDjaW-ColKEZWvywSdYQM5tpVaOp9jdH9jVnUZaqhf2D0CLDJxdx6MguR40LP-bu1qGY6xsGQ2-FwXCBvKwUw8B6JxNgbsewJGRITmLTgJ/s400/this+again+%2528random+critical+analysis+analysis%2529+3.png" width="400" /></a></div>
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At 17% of GDP these days, a 10% reduction in health care spending in the US (~ 2% of GDP) would be a significant improvement! However, the US still isn't an outlier in this view — only about as much as Ireland. That's because this view is still effectively "a quadratic fit for no reason" that RCA was on about a year ago. If</div>
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<i>y = a x² </i></div>
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then</div>
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log(<i>y</i>) = log(<i>a</i>) + <i>2</i> log(<i>x</i>)</div>
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The fits above show ~ 1.8 instead of 2 so we have <i>x</i>^1.8 instead of <i>x</i>^2, but we're still fitting a nonlinear function to the data. Why? As far as I can tell the only reason is that <b><i>it tells the story the author wants</i></b>.</div>
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This is where we get back to Feynman. Leaning over backwards with honesty would force us to ask why we should throw out a simple linear fit. It's not accuracy over range of the data — unless we're already assuming the US is not an outlier and including it in the fits.</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhXz_EhJuzI2z2p0S7f8I6CpdwmMcrV04Q3Myp091LO7rpX2peQs8foQ8TQSH_P8Q0hl0dCIdQDxHyToIsq5sCBN8wcPxEvS48OArLjgYCeK3r81JP9UBn_01z99rKzuh8Le_F8uhyphenhyphenQzshc/s1600/this+again+%2528random+critical+analysis+analysis%2529+4.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="551" data-original-width="576" height="382" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhXz_EhJuzI2z2p0S7f8I6CpdwmMcrV04Q3Myp091LO7rpX2peQs8foQ8TQSH_P8Q0hl0dCIdQDxHyToIsq5sCBN8wcPxEvS48OArLjgYCeK3r81JP9UBn_01z99rKzuh8Le_F8uhyphenhyphenQzshc/s400/this+again+%2528random+critical+analysis+analysis%2529+4.png" width="400" /></a></div>
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Over the non-US data, the linear fit (brownish dashed line) is basically as good as the nonlinear fit — the brown dashed curve and the gray dashed curve fall on top of each other until we get out to the US. And over the entire range, the nonlinear fit falls inside the 90% confidence limits of the linear model [3]. In fact, the linear model is actually much better than the nonlinear model in terms of absolute error [4]:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgMqeMkmrvh-_VNZRkk7VCUWDJTUWS4boH_dgGml2WW8mGCW2nvzD1t8HZpcuZgjodE40-gkvfBSJDOGwTfrUahzG1ExDx6XGKYzktJKLjxQH4W5wj_YN3bTUpnBxppD0DFM4-aAnQrJSb3/s1600/this+again+%2528random+critical+analysis+analysis%2529+5b.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="551" data-original-width="576" height="382" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgMqeMkmrvh-_VNZRkk7VCUWDJTUWS4boH_dgGml2WW8mGCW2nvzD1t8HZpcuZgjodE40-gkvfBSJDOGwTfrUahzG1ExDx6XGKYzktJKLjxQH4W5wj_YN3bTUpnBxppD0DFM4-aAnQrJSb3/s400/this+again+%2528random+critical+analysis+analysis%2529+5b.png" width="400" /></a></div>
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RCA's nonlinear model (fit correctly) actually predicts US health care spending will be somewhere between $7000 per capita and $13000 (90% CL) — and $8000, solidly within one sigma, is right in line with the linear model. That means that unless we include the US we do not have <b><i>any </i></b>reason to select the nonlinear model here. Or another way — assuming the US is not an outlier, US is not an outlier.</div>
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You may ask why I haven't gone in depth on the rest of the avalanche of graphs that follow. Unlike a novel where an unreliable narrator can be interesting, in science it's anathema. You have to go for more than just the superficial honesty of not deliberately lying, but rather leaning over backwards to show that your biases aren't driving the conclusions. In short, this is an example of <a href="http://calteches.library.caltech.edu/51/2/CargoCult.htm">cargo cult science</a> — and it tells us more about the person doing it than it does about the world.</div>
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But screw it. Let's forget about science. Let's listen to an internet rando. Let's say RCA's claim is true that the US is not an outlier — and that <b><i>globally </i></b>health care spending rises <b><i>twice </i></b>as fast as income. We've apparently traded a US-specific problem for an enormous global problem where health care rises faster than income and becomes more and more unaffordable for everyone on Earth. The US's medical bankruptcies are just the canaries in the coal mines of a growing global problem [5]. His laser focus on showing the US is not an outlier at all costs makes him miss the forest for the trees — I'm sure RCA didn't want to imply that global health care spending is on an unsustainable path. He seems to think spending more and more money on health care (despite "diminishing returns" [6]) is the epitome of civilization:</div>
<blockquote class="tr_bq" style="text-align: justify;">
<i>The typical American household is much better fed today than in prior generations despite spending a much smaller share of their income on groceries and working fewer hours. I submit this is primarily a direct result of productivity. We can produce food so much more efficiently that we don’t need to prioritize it as we once did. The food productivity dividend, as it were, has been and is being spent on higher-order wants and needs like cutting edge healthcare, higher amenity education, and leisure activities.</i></blockquote>
I don't know about you, but I love going to the doctor [7].<br />
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...<br />
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<b>Update + 5 hours</b><br />
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<div style="text-align: justify;">
In case you might think I'm being unnecessarily harsh on RCA, please note a) that isn't the first time I've encountered him and b) this from the "discussion" of this blog post this evening (click to enlarge):</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjLRD3DgIQn-J6FNFxFyGgZLTJjWsJA2odg0xxjZWV9ivtXjW7kn0iHOzxgx3BAmHm3r_J3dqRdh2OehcCEpIRYn5CxwxYhUxtuEIf6zVxJZpoxk_jtp-GEl7GMijQJyW9fh0A_lLD7Mi1y/s1600/healthcare.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="744" data-original-width="597" height="400" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjLRD3DgIQn-J6FNFxFyGgZLTJjWsJA2odg0xxjZWV9ivtXjW7kn0iHOzxgx3BAmHm3r_J3dqRdh2OehcCEpIRYn5CxwxYhUxtuEIf6zVxJZpoxk_jtp-GEl7GMijQJyW9fh0A_lLD7Mi1y/s400/healthcare.png" width="320" /></a></div>
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...<br />
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<b>Update 2/22/2020</b><br />
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<div style="text-align: justify;">
I am wondering if this might be a clearer demonstration of what I'm getting at here. I fit another nonlinear function to RCA's data (leaving the US out because we want to see if it's an outlier). It's a logistic function. Using this function here has some basis in economic theory — e.g. <a href="https://en.wikipedia.org/wiki/Economic_satiation">satiation points</a>. At some point consuming health care is more of a hassle than a benefit, right? Only so many angioplasties you can have in a year. Well, at least that's a plausible model. If we drop RCA's data in, we get the brown-ish curve below:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgH_o5X8tA85oXVKSCp21BQ6iTOigqQb-B00dmITxhyNp1yzgNfDbxipi5j5v5clpMrDuR79csuSbWywoNDldgd-VXuk7VupJOB_RU2MFL0Da1Q_aUmDfwGb0wvxnT9tvUdcRr31CedlGw8/s1600/this+again+%2528random+critical+analysis+analysis%2529+a.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="551" data-original-width="576" height="382" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgH_o5X8tA85oXVKSCp21BQ6iTOigqQb-B00dmITxhyNp1yzgNfDbxipi5j5v5clpMrDuR79csuSbWywoNDldgd-VXuk7VupJOB_RU2MFL0Da1Q_aUmDfwGb0wvxnT9tvUdcRr31CedlGw8/s400/this+again+%2528random+critical+analysis+analysis%2529+a.png" width="400" /></a></div>
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This says the US (green dot) is overspending by about double at a point where it should be reaching satiation. I could write up a whole long blog about this, and since it matches RCA's curve (blue) for every country except the US most of the rest of his analysis would go through. The other countries in the world are on the growing part of the curve — it'd just change the conclusions about the US.</div>
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But I can't do this. At least, not in good faith — and definitely not leaning over backwards. I actually believe this picture is almost certainly more accurate. My uncertainty in the saturation level is about where the single prediction bands put it. However, I would be a charlatan if I tried to push this fit to the data and let it be used by others in policy discussions.</div>
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Sure, I might put up a blog post and say, <i>hmm, interesting — let's see how the data looks in the future!</i></div>
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<div style="text-align: justify;">
But I can't draw a conclusion — <i>US health care spending is an outlier</i> — like how RCA has done with his. That's what I mean by the plot being in bad faith.</div>
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...<br />
<br />
<b>Update 2/22/2020 part II</b><br />
<br />
These graphs were made somewhat tongue-in-cheek, but they illustrate a bit of the problem with extrapolating the nonlinear fits as far out as the US — where does it stop? At what point do we stop saying that because a point falls in the gray band, we have to conclude it's not an outlier? (Click to enlarge)<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEijq_C_IPdEwar48W85s2WcNTe84Z5P8P_47xKCqtPA3E0WR2mufp3C1t0kedmZsvmOPzs3qEgwOdDm6E1uK6vtS2LaUmuMY_JUk2xSbMkfsu6-ZPMtxERpTGoPDgtZ_VbrjxT9_MIOEzfO/s1600/this+again+%2528random+critical+analysis+analysis%2529+d.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="551" data-original-width="576" height="191" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEijq_C_IPdEwar48W85s2WcNTe84Z5P8P_47xKCqtPA3E0WR2mufp3C1t0kedmZsvmOPzs3qEgwOdDm6E1uK6vtS2LaUmuMY_JUk2xSbMkfsu6-ZPMtxERpTGoPDgtZ_VbrjxT9_MIOEzfO/s200/this+again+%2528random+critical+analysis+analysis%2529+d.png" width="200" /></a><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjRPH9n4A2IF7ebXWgDjwm6OyoHjTEgyoaVhZoRaprhPIN1hgG4TErYzih_lMgodPOxqbcV20CUJUnOh4bEX7_8_xCSLh35gywz4IV_-H51SpHmeiUb6eKOCksr2CQaXeWpzr5Id9pWa_Zh/s1600/this+again+%2528random+critical+analysis+analysis%2529+e.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="543" data-original-width="576" height="188" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjRPH9n4A2IF7ebXWgDjwm6OyoHjTEgyoaVhZoRaprhPIN1hgG4TErYzih_lMgodPOxqbcV20CUJUnOh4bEX7_8_xCSLh35gywz4IV_-H51SpHmeiUb6eKOCksr2CQaXeWpzr5Id9pWa_Zh/s200/this+again+%2528random+critical+analysis+analysis%2529+e.png" width="200" /></a></div>
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A good summary of my argument is that we can't go as far as that green dot representing the US and claim we're leaning over backwards in being honest.<br />
<br />
Additionally, the slope determined in the nonlinear fit are akin to elasticities in economics — the change in e.g. price vs quantity in elasticities of supply and demand (one of <a href="https://informationtransfereconomics.blogspot.com/2013/04/the-previous-post-with-more-words-and.html">the earliest things I looked at</a> with information equilibrium on this blog). I'd say it's a stretch to actually say slopes in this example are estimates of elasticities (we have aggregate macro data here, not micro data), but lets go with it. The thing is that 1) they are elasticities only where the difference in logs is approximately a percentage, and 2) estimating elasticities and applying that human behavioral result well beyond the data you measured is not scientifically supportable.<br />
<br />
Let's look at <i>x </i>compared to a reference value of <i>x₀</i> = 5. The blue line below is 100 × (log <i>x </i>− log <i>x₀</i>) aka difference of logs, while the yellow line is 100 × (<i>x − x₀</i>)/<i>x₀</i> aka the percent difference. We can see how this approximation breaks down as you move away from a region:<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiyC-cFPrHWkGEQzO9W3w75kJq71nIQgaLeVzIS0hOJTkiHTH8O7mK7_xnEnRoPvrqm2gr0saLtT5ynwzQ6GhpL7_29aPYlnAd-NMZP4ovVhIB3FUIV62_uWO2aZpVV2A7ZVImpYETrR1mX/s1600/this+again+%2528random+critical+analysis+analysis%2529+f.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="512" data-original-width="621" height="263" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiyC-cFPrHWkGEQzO9W3w75kJq71nIQgaLeVzIS0hOJTkiHTH8O7mK7_xnEnRoPvrqm2gr0saLtT5ynwzQ6GhpL7_29aPYlnAd-NMZP4ovVhIB3FUIV62_uWO2aZpVV2A7ZVImpYETrR1mX/s320/this+again+%2528random+critical+analysis+analysis%2529+f.png" width="320" /></a></div>
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Note that the US is about twice as far out on the graph as the highest point in the data — so in terms of the slope on the log graph representing an elasticity, we're well out of scope of the approximation.<br />
<br />
And even if the approximation was still in scope, extrapolating the <b><i>behavioral</i></b> meaning of that elasticity all the way to twice the highest point in the data is even more problematic.<br />
<br />
In a more down to earth example, we know that gas prices do not heavily impact consumption in the short run when they fluctuate at the 10-30% level. RCA's analysis is like extrapolating that finding to increases of 100% — if gas prices doubled, consumption would remain constant. That's iffy on its own. However, he takes it a bit further — if some data then showed the US didn't reduce its consumption when gas prices doubled (i.e. it was in line with that extrapolation), RCA's analysis would be claiming that gas consumption is actually <a href="https://en.wikipedia.org/wiki/Elasticity_(economics)">perfectly inelastic</a> (people everywhere don't care about the price of gas at all) instead of possible structural reasons the US didn't reduce supply (e.g. the US built roads and housing that locked in commuting and therefore gas consumption). The former is basically a conclusion derived from a single data point — like RCA's claim the US isn't an outlier.<br />
<br />
...<br />
<br />
<b>Update 2/22/2020 part III</b><br />
<br />
Per commenter rob below, here is that disallowed region (above the blue dashed line) and where RCA's curve intersects it:<br />
<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEis9N5u5odAfRpu4BUhSDTfmryYVgnFdZs-GioWz8KbSx7YpPNVH-1n1Atfxg4Qo9u-GcjtS7U4Ivas-KLziGN1Iep9eAvpY_b97cWACFiU9kuGLH3es2sQv8DnhPVigMdoBXManu5ovMGg/s1600/this+again+%2528random+critical+analysis+analysis%2529+g.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="577" data-original-width="576" height="400" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEis9N5u5odAfRpu4BUhSDTfmryYVgnFdZs-GioWz8KbSx7YpPNVH-1n1Atfxg4Qo9u-GcjtS7U4Ivas-KLziGN1Iep9eAvpY_b97cWACFiU9kuGLH3es2sQv8DnhPVigMdoBXManu5ovMGg/s400/this+again+%2528random+critical+analysis+analysis%2529+g.png" width="398" /></a></div>
<br />
I mean, if we're allowed to extrapolate to the green point, why can't we extrapolate all the way out to that intersection?<br />
<br />
n.b. This is a <a href="https://informationtransfereconomics.blogspot.com/2015/10/we-built-this-theory-on-scope-conditions.html">scope condition</a> (a limit of the region of validity of the model).<br />
<br /></div>
...<br />
<br />
<b>Footnotes:</b><br />
<br />
<div style="text-align: justify;">
<span style="font-size: x-small;">[0] Sure, I'm also an internet rando (<a href="http://www.arandomphysicist.com/">a random physicist</a> you could say), but I give my real name and you can peruse my grad school papers and thesis <a href="http://inspirehep.net/author/profile/J.R.Smith.3">here</a> if you'd like. In the interest of leaning over backward, I can also say that I am quite biased towards the left of the political spectrum. However, I don't have really strong feelings about health care policy — I do think it should be free because of basic morality, but that doesn't necessarily mean I think it should be a smaller component of GDP, but maybe a plausible future is one where most of us work in health care instead of retail (the transition appears to be <a href="https://www.cnn.com/2019/07/23/business/mall-of-america-health-clinic/index.html">already happening</a>). Other people have much better thoughts on health care policy than I do. I wrote <a href="https://www.amazon.com/dp/B07T8T9G93">a short book</a> on my views of the political economy of the US that doesn't even <i>mention </i>health care except for the possible stimulus effect of the ACA, focusing instead on racism, sexism, and other social forces as drivers of the economy.</span></div>
<div style="text-align: justify;">
<span style="font-size: x-small;"><br /></span>
<span style="font-size: x-small;">[1] "In case you're not already aware ..." is also the kind of language Trump uses when he just heard about something for the first time. [Edit: added + 30 mins.]</span><br />
<span style="font-size: x-small;"><br /></span></div>
<div style="text-align: justify;">
<span style="font-size: x-small;">[2] <a href="https://twitter.com/infotranecon/status/973704532860399616">In that Twitter thread</a> from a year ago, I found out the equation RCA printed on the graph did not give the line presented in that graph. RCA <a href="https://twitter.com/RCAFDM/status/1108708051924586496?s=20">said</a> (a week later) it was about the plotting function label being unable to handle orthogonal polynomials:</span></div>
<blockquote class="tr_bq">
<div style="text-align: justify;">
<i><span style="font-size: x-small;">I used a 3rd order polynomial with an orthogonal transformation -- poly() function in R. The labeling package isn't smart enough to transform the coefficients. No big deal.</span></i></div>
</blockquote>
<div style="text-align: justify;">
<span style="font-size: x-small;">Although this information did let me figure out what happened on RCA's graph, it's also the kind of word salad you get when a student is trying to confidently answer a question that they don't really understand. I imagine it took him that week to figure it out. Basically, RCA confused R's <a href="https://www.rdocumentation.org/packages/stats/versions/3.6.2/topics/poly">poly()</a> coefficients with R's <a href="https://www.rdocumentation.org/packages/polynom/versions/1.4-0/topics/polynomial">polynomial()</a> coefficients. I'll use Hermite polynomials (not 100% sure how R chooses the orthogonal set) to show the difference.</span></div>
<div style="text-align: justify;">
<span style="font-size: x-small;"><br /></span></div>
<div style="text-align: justify;">
<span style="font-size: x-small;">A normal ("raw") regression fits (to third order)</span></div>
<div style="text-align: justify;">
<span style="font-size: x-small;"><br /></span></div>
<div style="text-align: justify;">
<i><span style="font-size: x-small;">p(x) = a x³ + b x² + c x + d</span></i></div>
<div style="text-align: justify;">
<span style="font-size: x-small;"><br /></span></div>
<div style="text-align: justify;">
<span style="font-size: x-small;">with the fit returning <i>(a, b, c, d)</i> while an orthogonal polynomial regression fits (using <a href="https://en.wikipedia.org/wiki/Hermite_polynomials">Hermite polynomials</a> which is probably not what R is doing, but still illustrative)</span></div>
<div style="text-align: justify;">
<span style="font-size: x-small;"><br /></span></div>
<div style="text-align: justify;">
<i><span style="font-size: x-small;">p(x) = a' (x³ </span></i><i><span style="font-size: x-small;">− 3 x</span></i><i><span style="font-size: x-small;">) + b' (x² − 1) + c' x + d' · 1</span></i></div>
<div style="text-align: justify;">
<span style="font-size: x-small;"><br /></span></div>
<div style="text-align: justify;">
<span style="font-size: x-small;">with the fit returning <i>(a', b', c', d')</i>. where <i>a = a'</i>, <i>b = b'</i>, and <i>c = c' − 3 a'</i>. and <i>d = d' − b'</i>. It's quite valuable to do the latter, because it can reduce the covariance at each order — for example, Hermite polynomials of different orders are designed to have a zero overlap integral so adding each order doesn't affect the previous orders like it would for adding monomial terms at each order (<i>x²</i> looks a bit like <i>x </i>near <i>x </i>= 1, while </span><span style="font-size: x-small;"><i>x² − 1</i></span><span style="font-size: x-small;"> doesn't as much near x = 1). But RCA isn't really doing an analysis where he shows increasing or decreasing orders where this process is most valuable — fitting a linear function, then fitting a quadratic and comparing the size of the new coefficients to see if adding the quadratic was warranted. If he had done that (as well as properly testing for the US as an outlier), he would have found that adding a quadratic term was not warranted <b><i>unless </i></b>the US was added.</span></div>
<div style="text-align: justify;">
<span style="font-size: x-small;"><br /></span></div>
<div style="text-align: justify;">
<span style="font-size: x-small;">However, I'm pretty certain RCA did not understand what R was doing until I called him out — at which point he went back to the documentation and tried to figure it out ... but <i><b>still </b></i>didn't understand it. If he had, he would have written something more like:</span></div>
<blockquote class="tr_bq">
<div style="text-align: justify;">
<i><span style="font-size: x-small;">I used 3rd order orthogonal polynomials -- poly() function in R. I accidentally input the orthogonal poly coefficients in as raw poly coefficients. No big deal.</span></i></div>
</blockquote>
<div style="text-align: justify;">
<span style="font-size: x-small;">It's true that it's a simple mistake, but it also sheds light on who RCA is. Note that the common plotting package <a href="https://stackoverflow.com/questions/11949331/adding-a-3rd-order-polynomial-and-its-equation-to-a-ggplot-in-r">is in fact capable</a> of handling using poly() in the linear model and printing the correct polynomial. But sure, it's that the package isn't smart enough, not that he made a mistake or didn't understand what he was doing.</span></div>
<div style="text-align: justify;">
<span style="font-size: x-small;"><br /></span></div>
<div style="text-align: justify;">
<span style="font-size: x-small;">[3] The error bands RCA is providing seem to be either less than one sigma or (more likely) are mean prediction bands (effectively where the new regression line will shift given a new data point) rather than single prediction bands (where an individual new data point might fall) which I tend give and what a typical person tends to think of when they see error bands.</span></div>
<div style="text-align: justify;">
<span style="font-size: x-small;"><br /></span></div>
<div style="text-align: justify;">
<span style="font-size: x-small;">[4] Wanted to keep the axes above consistent, but the single prediction error is pretty broad and can only be appreciated if you zoom out a bit. Click to enlarge.</span></div>
<span style="font-size: x-small;"><br /></span>
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<span style="font-size: x-small;">[5] This may be true in a different way than RCA believes — rising US health care costs might be driving up health care costs around the world as we consume all the health care resources (<a href="https://twitter.com/infotranecon/status/1230404911231168513?s=20">Twitter thread here</a>):</span></div>
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<span style="font-size: x-small;">[6] To wit:</span></div>
<blockquote class="tr_bq" style="clear: both; text-align: justify;">
<i><span style="font-size: x-small;">America’s mediocre health outcomes can be explained by rapidly diminishing returns to [health care] spending ...</span></i></blockquote>
<div class="separator" style="clear: both; text-align: justify;">
<span style="font-size: x-small;">[7] I</span><span style="font-size: x-small;"> love this quote:</span></div>
<blockquote class="tr_bq" style="clear: both; text-align: justify;">
<span style="text-align: start;"><i><span style="font-size: x-small;">Conversely, when we look at indicators where America skews high, these are precisely the sorts of [procedures] high-income, high-spending countries like the United States do relatively more of. </span></i></span></blockquote>
<div class="separator" style="clear: both; text-align: justify;">
<span style="text-align: start;"><span style="font-size: x-small;">You know, things rich people like to do! Like coronary artery bypasses, hip replacements, knee replacements, and coronary angioplasties. Those are a much more fun use of your disposable income than a trip to Spain!</span></span></div>
Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com12tag:blogger.com,1999:blog-6837159629100463303.post-85295605972051894232020-02-09T14:58:00.001-08:002020-02-10T15:12:56.801-08:00How should we approach how people think?<div style="text-align: justify;">
A common objection to the information equilibrium approach I've run into over the years is that economics at the micro level is about incentives or at the macro level how people react to policy changes in the economy. My snarky response to exactly that objection earlier today on Twitter <a href="https://twitter.com/infotranecon/status/1226564420072964096?s=20">was this</a>:</div>
<blockquote class="tr_bq" style="text-align: justify;">
<i>The approach can be thought of as assuming people are too (algorithmically) complex for us to know how they respond to incentives, as opposed to [the] typical [economics] approach where you not only assume you know how individuals think but write down simplistic equations for it.</i></blockquote>
<div style="text-align: justify;">
Let me expand on what this means in a (slightly) less snarky way. We'll set up a simple scenario where people are given 7 choices (the "opportunity set") and must select one.</div>
<div style="text-align: justify;">
<br /></div>
<div style="text-align: justify;">
<b>The typical approach in economics</b></div>
<div style="text-align: justify;">
<br /></div>
<div style="text-align: justify;">
In economics, one would set up a utility function <i>u(x)</i> that represents your best guess at what a typical person thinks — how much "utility" (worth or value) they derive from each option. Let's say it looks like this:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi7ANNAMub3FDiQMkCpysWTePwGtk_P5iD6poNLUC5-azK4gK0xEWBFhFuvcQcS99DbT0pFAqrLFBPIiVU_gHuRorVxXzOsgApHMrEYntsWpWlNURGGwrz4Pa-amYtQjerDWL20JlR2uhbJ/s1600/infoeq+How+people+think+1.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="371" data-original-width="576" height="257" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi7ANNAMub3FDiQMkCpysWTePwGtk_P5iD6poNLUC5-azK4gK0xEWBFhFuvcQcS99DbT0pFAqrLFBPIiVU_gHuRorVxXzOsgApHMrEYntsWpWlNURGGwrz4Pa-amYtQjerDWL20JlR2uhbJ/s400/infoeq+How+people+think+1.png" width="400" /></a></div>
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<div style="text-align: justify;">
You've thought about what people think (maybe using your own experience or various thought experiments) and you assign a value <i>u(x)</i> for each choice <i>x</i>. While I've made the above function overly simplistic, it's still assigning a value to each choice.</div>
<div style="text-align: justify;">
<br /></div>
<div style="text-align: justify;">
You would then set up an optimization problem over the choices, derive the first order conditions (which are basically the derivatives in the various dimensions you are considering), and find the maximum (i.e. the location of the zero of the derivatives, or a point on the boundary of your opportunity set).</div>
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<div style="text-align: justify;">
That's the utility maximizing point and you find out your (often sole "representative") agent selects choice 5. Often, 100% of agents in your model (or 100% of a single representative agent) will select that choice. Everyone is the same. Sometimes you can have heterogeneous agents, and while each <i>type </i>of agent will make different selections each agent <i>of each type</i> will make the same selection.</div>
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<br /></div>
<div style="text-align: justify;">
Of course we can allow error, and there are <a href="https://scholar.harvard.edu/files/tomasz/files/lisbon32-post.pdf">random utility discrete choice models</a> [pdf] that effectively allow random choices among the various utility options such that in the end we have e.g. most people choosing 5 with a few 4's or 6's (for 1000 agents):</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj8AxHWpoFGYHncSeJrnQDR4krs91LJLDcz98yWkHLIKjYjYEyqDriJfgzmkLeuSfkLKrwnSnQMZuxiro37Wh4E7VOS2C_nSE2bRD85e8w1OpaLX2-jHAMn-R16NwB5ADl99LyPTmYlBKLc/s1600/infoeq+How+people+think+3.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="371" data-original-width="576" height="257" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj8AxHWpoFGYHncSeJrnQDR4krs91LJLDcz98yWkHLIKjYjYEyqDriJfgzmkLeuSfkLKrwnSnQMZuxiro37Wh4E7VOS2C_nSE2bRD85e8w1OpaLX2-jHAMn-R16NwB5ADl99LyPTmYlBKLc/s400/infoeq+How+people+think+3.png" width="400" /></a></div>
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<div style="text-align: justify;">
But basically the approach assumes that when confronted with a choice you are able to construct a really good model — a <i>u(x)</i> — of how a person will respond.</div>
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<br /></div>
<div style="text-align: justify;">
This of course sets up a problem called "<a href="https://en.wikipedia.org/wiki/Lucas_critique">Lucas critique</a>": if you make changes to policy to try and exploit something you learned this way, people can adapt to make your original model — your original utility function — moot. For example, if you make option 5 illegal, the model as is says people will start choosing 4 or 6 in roughly equal numbers. But maybe agents will adapt and choose 2 instead?</div>
<div style="text-align: justify;">
<br /></div>
<div style="text-align: justify;">
The response to the Lucas critique is generally to get ever deeper inside people's heads — to understand not just their utility functions but how their utility functions will change in response to policy, to get at the so-called deep parameters also known as <a href="https://en.wikipedia.org/wiki/Microfoundations">microfoundations</a>.</div>
<br />
<b>The approach in information equilibrium</b><br />
<br />
<div style="text-align: justify;">
In the information equilibrium approach, when asked what a person will choose out of 7 options, you furrow your brow, look up to sky, and then give one of these:</div>
<div style="text-align: justify;">
<br /></div>
<div style="text-align: justify;">
‾\_(ツ)_/‾</div>
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<br /></div>
<div style="text-align: justify;">
One agent will choose option 4 (with ex post probability 1):</div>
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Another will choose option 1:<br />
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If you ask that agent again, maybe they'll go with option 2 now:<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjrpbhuN2ZfMi0cs2NJK9AWB2BChZ0BUsxDVd_R9wFqmdF4J6ISOQneFI74c2wMHrKnpBNPMayqBbBcJlA5cxNP2EsdoFX8dxRNm0Knp8x8KbawxKbyGl0WX_Pv43d2cxs5DEazaqg2NQ3x/s1600/infoeq+How+people+think+6.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="371" data-original-width="576" height="257" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjrpbhuN2ZfMi0cs2NJK9AWB2BChZ0BUsxDVd_R9wFqmdF4J6ISOQneFI74c2wMHrKnpBNPMayqBbBcJlA5cxNP2EsdoFX8dxRNm0Knp8x8KbawxKbyGl0WX_Pv43d2cxs5DEazaqg2NQ3x/s400/infoeq+How+people+think+6.png" width="400" /></a></div>
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Why? We don't know. Maybe they had medical bills between the choices. Maybe that first agent really loves Bernie Sanders and Bernie said to choose option 4. Again:</div>
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‾\_(ツ)_/‾</div>
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If we have millions of people in an economy (here, only 1000), then you're going to get a distribution over the choices. And if you have no prior information about that choice (i.e. ‾\_(ツ)_/‾), then you're going to get a uniform distribution (with probability ~ 1/7 for 7 choices — about 14%):</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg8HTF7WtkLV8iqlUPsqT5kQELcEqfF310zzGRYiMeZT2wQ_lnUgBakfotbXPFRwhIFlg6jk_jfEywqO1L0lPrDrezJNlG-w_fB7PA2F7J9tg3cwddz-cBvwZnAZKeNXtLuVtiJzxIvAsay/s1600/infoeq+How+people+think+7.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="371" data-original-width="576" height="257" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg8HTF7WtkLV8iqlUPsqT5kQELcEqfF310zzGRYiMeZT2wQ_lnUgBakfotbXPFRwhIFlg6jk_jfEywqO1L0lPrDrezJNlG-w_fB7PA2F7J9tg3cwddz-cBvwZnAZKeNXtLuVtiJzxIvAsay/s400/infoeq+How+people+think+7.png" width="400" /></a></div>
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In this case, economics becomes more about the space of choices, the opportunity set — not about what individual people are thinking about. And that size of the opportunity set can be measured with information theory, hence information equilibrium (where we equate different spaces of choices). It turns out there is a direct formal mathematical relationship to the utility approach above, except instead of utility being about what individuals value it's about the size of that space of options.</div>
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In the information equilibrium approach, we depend on two assumptions that set up the basis of equilibrium:</div>
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<ol>
<li style="text-align: justify;">The distribution (and it doesn't have to be uniform) is stable except for a sparse subset of times.</li>
<li style="text-align: justify;">Agents fully map (i.e. select) the available choices (again, except for a sparse subset of times).</li>
</ol>
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The "sparse subset" is just the statement that we aren't in disequilibrium all the time. If we are, we never see the macroeconomic state associated with that uniform distribution and we can't get measurements about it. We have to see the uniform distribution for long enough to identify it. Agents also have to select the available choices, otherwise we'll miss information about the size of the opportunity set.</div>
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But information equilibrium also allows for non-equilibrium. Since we aren't making assumptions about how they think, people could suddenly all make the same choice, or be forced into the same choice. These "sparse non-equilibrium information events", or more simply "economic shocks" cause observables to deviate from their equilibrium values. The <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3094757">dynamic information equilibrium model</a> (DIEM) makes some assumptions about what these sparse shocks look like (e.g. the have a finite duration and amplitude), and it gives us a pretty good model of the unemployment rate [1]:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEilzFEU-HryTS6b0RMs4DYmCfNcq0RSAryB-qbJqqsIF5W_1NBHcTQuvW96fJ7RZe7DVnI4cC4ivuRP-damTbpqurc3XR9KyomIgg_S_SD_VDRezOv9a6A5WsKCr18gIE0rqH9-QZmcTzVZ/s1600/dynamic+equilibrium+%2528unrate%2529+animation.gif" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="236" data-original-width="720" height="130" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEilzFEU-HryTS6b0RMs4DYmCfNcq0RSAryB-qbJqqsIF5W_1NBHcTQuvW96fJ7RZe7DVnI4cC4ivuRP-damTbpqurc3XR9KyomIgg_S_SD_VDRezOv9a6A5WsKCr18gIE0rqH9-QZmcTzVZ/s400/dynamic+equilibrium+%2528unrate%2529+animation.gif" width="400" /></a></div>
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Those 7 choices above are translated into this toy model as jobs in various sectors (with one "sector" being unemployment).</div>
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This approach also gives us supply and demand (this is the connection to Gary Becker's 1962 paper <i><a href="http://newconsensus.org/MarxInAmerica/wp-content/uploads/2013/10/G-Becker-Irrational-Behavior-and-Economic-Theory.pdf">Irrational Behavior in Economic Theory</a></i> [pdf], see also <a href="http://bactra.org/weblog/1155.html">here</a>). We don't have 7 discrete choices here, but rather a 2-dimensional continuum between two different goods (say, blueberries and raspberries) bounded by a budget constraint (black line). The average is given by the black dot. As the price of one good goes up, on average people consume less of it.</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj8cesw8z7lVaWR90GN_EsbmDLMN2NQnuKZ_WGEB0M1d6ycsUr4vWcpRT6l4LNKlHuAweAO4xIamsD_Tx0nQasXjnYUYch_R52K86YWoVTnYZ4UsmEXNbYTS_PpCcppkWAuJt8QTGXIUMQD/s1600/beckerideal.gif" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="301" data-original-width="576" height="208" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj8cesw8z7lVaWR90GN_EsbmDLMN2NQnuKZ_WGEB0M1d6ycsUr4vWcpRT6l4LNKlHuAweAO4xIamsD_Tx0nQasXjnYUYch_R52K86YWoVTnYZ4UsmEXNbYTS_PpCcppkWAuJt8QTGXIUMQD/s400/beckerideal.gif" width="400" /></a></div>
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And again, people might "bunch up" (i.e. make similar choices and not fully map the opportunity set) in that opportunity set and that gives us non-equilibrium cases where supply and demand fails:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhm7F5_ak-_MXUE_3MmdD8zNW_DVMBrSaXuadu4OhKtdJThgYAORkcsOXjEFNj4538EqrhSGXhc-O3k7xqy7nzlpYZVnqmCg0lGNU57nRlhGHX4PDpk25V4MkeeRA86as60aK2uPFyWSMN-/s1600/beckernonideal.gif" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="301" data-original-width="576" height="208" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhm7F5_ak-_MXUE_3MmdD8zNW_DVMBrSaXuadu4OhKtdJThgYAORkcsOXjEFNj4538EqrhSGXhc-O3k7xqy7nzlpYZVnqmCg0lGNU57nRlhGHX4PDpk25V4MkeeRA86as60aK2uPFyWSMN-/s400/beckernonideal.gif" width="400" /></a></div>
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In both of these "failures" of equilibrium (recessions, bunching up in the opportunity set), I am under the impression that sociology and psychology will be more important drivers than what we traditionally think of as economics [2].</div>
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But what about that "algorithmically" in parentheses in my original tweet? That's a reference to <a href="https://en.wikipedia.org/wiki/Algorithmic_information_theory">algorithmic complexity</a>. The agents in the utility approach are not very algorithmically complex — they choose 5 either all the time or at least almost all the time:</div>
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{5, 5, 5, 5, 5, 5, 5, 4, 6, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5}</div>
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This could be approximated by a computer program that outputs 5 all the time. The agents in the information equilibrium approach are <b><i>far </i></b>more complex:</div>
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{4, 7, 3, 4, 1, 6, 6, 5, 4, 2, 3, 1, 1, 3, 6, 3, 4, 2, 2, 6}</div>
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As you make this string of numbers longer and longer, the only way a computer program can reproduce it is to effectively incorporate the string of numbers itself. That's the peak of algorithmic complexity — <a href="https://en.wikipedia.org/wiki/Algorithmic_information_theory#Precise_definitions">algorithmic randomness</a>. That's what I mean when I say I treat humans as so complex they're random. No computer program could capture a set of choices a real human made except a list of all those choices.</div>
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In a sense, you can think of the two approaches, utility and information equilibrium, as starting from two limits of human complexity — so simple you can capture what they think with a function versus so complex that you can't do it at all. I imagine the truth is somewhere in between, but given the empirical failure of macroeconomics (I call getting beaten by an AR process a failure) it's probably closer to the complex side than the simple side.</div>
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And that approach turns economics on its head — instead of being about figuring out what choices people will make, it's about measuring the set of choices made by people.</div>
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...<br />
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<b>Footnotes:</b><br />
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<div style="text-align: justify;">
<span style="font-size: x-small;">[1] That's been pretty accurate at forecasting the unemployment rate <a href="https://informationtransfereconomics.blogspot.com/2017/01/dynamic-equilibrium-unemployment-rate.html">for three years now</a> (click to enlarge, black is post-forecast data):</span></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjDCFrl1hlQxd3pWeN_zNZQhUHa-Xo1HrIk_kHTT1iU02u9TMjW5AJ3f9R_l0CxpNDNTRqwcc15uwpkxnwVsmn9ZAaaax9Pa_o7Vm4ILH1SgUqr4waUG-9o69A6Bu9jwrIhsEvRV7TQC2oT/s1600/dynamic+equilibrium+%2528unemployment%2529+data+updates.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="483" data-original-width="792" height="121" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjDCFrl1hlQxd3pWeN_zNZQhUHa-Xo1HrIk_kHTT1iU02u9TMjW5AJ3f9R_l0CxpNDNTRqwcc15uwpkxnwVsmn9ZAaaax9Pa_o7Vm4ILH1SgUqr4waUG-9o69A6Bu9jwrIhsEvRV7TQC2oT/s200/dynamic+equilibrium+%2528unemployment%2529+data+updates.png" width="200" /></a></div>
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<span style="font-size: x-small;">[2] In fact, <a href="https://www.amazon.com/dp/B07T8T9G93">I wrote a book</a> about how the post-war evolution of the US economy seems to be more about social changes than monetary and fiscal policy. Maybe it's not correct, but it at least gives some perspective of how different macroeconomic analysis can be from the way it is conducted today.</span></div>
Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com7tag:blogger.com,1999:blog-6837159629100463303.post-26915203938285788492020-01-15T13:43:00.004-08:002020-01-15T13:43:58.493-08:00Twitter talk slides: information equilibrium and dynamic information equilibriumHere are the charts for my <a href="https://twitter.com/infotranecon/status/1217533581125287937?s=20">Twitter talk from today</a>:<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjWOjLvbA04ooAv6j3BsroSkiUxd_Jtww7zATuQVwkIIui2V25uzX3-42ZsLKdEn3LQ2VqlKPMdjBW8aYaZTatztKlj-7eIBx1VWp-5vkO1XDp7CqnYhShCBz09FPr2usRpHq0V-ju88mux/s1600/infoEqGraphic0x.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="900" data-original-width="1600" height="225" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjWOjLvbA04ooAv6j3BsroSkiUxd_Jtww7zATuQVwkIIui2V25uzX3-42ZsLKdEn3LQ2VqlKPMdjBW8aYaZTatztKlj-7eIBx1VWp-5vkO1XDp7CqnYhShCBz09FPr2usRpHq0V-ju88mux/s400/infoEqGraphic0x.png" width="400" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgPKDhiN_zlCw2pFm4YKipM6aJo_ba3TT-2V54JBFlrRjv7GvJzIr0dmTZMAeqFe9q6Ti2D92PDhyphenhyphenmqbENI-M7QG0sEdYIt5HOMKSi5N5ow_51Jq31RSIfvFNg8vdJZ3LYYENb_RXrrEVZE/s1600/infoEqGraphic0y.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="900" data-original-width="1600" height="225" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgPKDhiN_zlCw2pFm4YKipM6aJo_ba3TT-2V54JBFlrRjv7GvJzIr0dmTZMAeqFe9q6Ti2D92PDhyphenhyphenmqbENI-M7QG0sEdYIt5HOMKSi5N5ow_51Jq31RSIfvFNg8vdJZ3LYYENb_RXrrEVZE/s400/infoEqGraphic0y.png" width="400" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEir5sqkG09f7rZ7k9y2vP3pMYZRvTAzytOXGLRUFHHQfZEemdgJPB7JvSw5hwLV-BE4cIKNuWsVA-6_jsJQYBa-nCaXuvTHNZB0n0LAfbX4hdDmHZeX3X-kxEb7UzY2MGTQBme3iLhASj7b/s1600/infoEqGraphic0z.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="900" data-original-width="1600" height="225" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEir5sqkG09f7rZ7k9y2vP3pMYZRvTAzytOXGLRUFHHQfZEemdgJPB7JvSw5hwLV-BE4cIKNuWsVA-6_jsJQYBa-nCaXuvTHNZB0n0LAfbX4hdDmHZeX3X-kxEb7UzY2MGTQBme3iLhASj7b/s400/infoEqGraphic0z.png" width="400" /></a></div>
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<br />Jason Smithhttp://www.blogger.com/profile/12680061127040420047noreply@blogger.com2