Applications¶
The project runs six applications on the Smets-Wouters (2007) model, all from the 2022Q2 inflation peak or over the full history, each in an RE version and a learning version. They share the project baseline and differ only in the lines their scenario files set.
| Application | Question | Main option | Scenario folder | Runner group | Time |
|---|---|---|---|---|---|
| 1. Peak forecast | How fast does inflation fall from the peak with zero shocks? | expectations.mode |
scenarios/sw07/app1_peak/ |
app1 |
~30 s |
| 2. Shock replay | Feed in the shocks the RE model says hit the economy: what does the learning economy make of them? | shocks.source |
app2_replay/ |
app2 |
~10 s |
| 3. Policy deviations | Hold the rate 100 bp below or above the Taylor rule for a year | conditions |
app3_policy/ |
app3 |
~30 s |
| 4. Ramsey policy | Optimal policy under commitment against the rule, four sets of loss weights | policy.* |
app4_ramsey/ |
app4 |
~2.5 min |
| 5. Density forecasts | How uncertain is the forecast with mark-up or demand shocks? | density.* |
app5_density/ |
app5 |
~14 min |
| 6. History and decompositions | What history does the learning model back out, and which shocks drove inflation? | history.mode, hetlearn.decompose |
app6_history/ |
app6 |
~40 s |
Four model variants change one assumption of Application 1. They are described on the option pages:
| Variant | Change | Page |
|---|---|---|
var1_re_variant/v1_mc_learn |
model-consistent instead of anchored RE agents | RE agents |
var2_plm/v2_* |
AR(2), AR(1) without constant, regression and VAR(1) PLMs | Perceived laws of motion |
var3_allvars/v3_* |
learning on all twelve forward-looking variables, under each facility | Projection facility |
var4_gain/v4_* |
constant gain against the endogenous gain | Gains |
The recursive forecast evaluation (scenarios/sw07/eval/, group eval, about 2.7 hours of
compute) is on the Forecast evaluation page.
Running them¶
setup_paths
run_applications('app3') % one group
run_applications({'app1', 'app2'}) % several groups, in this order
run_applications('a5_markup_learn') % one scenario, logged under its group
run_applications('all') % every group, the evaluation included (~3 hours)
Every run writes results/<id>/ and adds a row to results/run_log.csv. A run that fails is
printed, logged as error and skipped; the next one runs. help run_applications gives the
group table.
Results used on these pages¶
All numbers on the application pages come from the baseline run of 2026-10-21
(results/summary_v3/key_numbers.csv) and the paper figures in paper/figures/
(FIGURE_NOTES.txt). Inflation, output and consumption growth are in % q/q annualised, the
policy rate in % a year, differences in percentage points (pp).