New CPI data is out, and here is the "headline" CPI model last updated a couple months ago:
I did change the error bar on the derivative data to show the 1-sigma errors instead of the median error in the last update. The level forecast still shows the 90% confidence for the parameter estimates.
Now why wasn't I invited to this? One of the talks was on forecasting horizons:
How far can we forecast? Statistical tests of the predictive contentPresenter: Malte Knueppel(Bundesbank)
Coauthor: Jörg Breitung
A version of the talk appears here [pdf]. One of the measures they look at is year-over-year CPI, which according to their research seems to have a forecast horizon of 3 quarters — relative to a stationary ergodic process. The dynamic equilibrium model is approaching 4 quarters:
The thing is, however, the way the authors define whether the data is uninformative is relative to a "naïve forecast" that's constant. The dynamic equilibrium forecast does have a few shocks — one centered at 1977.7 associated with the demographic transition of women entering the workforce, and one centered at 2015.1 I've tentatively associated with baby boomers leaving the workforce  after the Great Recession (the one visible above) . But for the period from the mid-90s after the 70s shock ends until the start of the Great Recession would in fact be this "naïve forecast":
The post-recession period does involve a non-trivial (i.e. not constant) forecast, so it could be "informative" in the sense of the authors above. We will see if it continues to be accurate beyond their forecast horizon.
 Part of the reason for this shock to posited is its existence in other time series.
 In the model, there is a third significant negative shock centered at 1960.8 associated with a general slowdown in the prime age civilian labor force participation rate. I have no firm evidence of what caused this, but I'd speculate it could be about women leaving the workforce in the immediate post-war period (the 1950s-60s "nuclear family" presented in
propaganda advertising) and/or the big increase in graduate school attendance.