EM GDP NOWCASTS

One mark per scheduled run, placed at its actual run time, so several runs in a day sit close together and a pause shows as a gap. The shaded band is ±1.96×SE of the Trim-25 ensemble, where SE is the dispersion of its in-sample one-quarter-ahead fits (≈pp). It is computed on the same final-vintage data the models were fitted to, so read it as fit dispersion, not as a 95% prediction interval. The honest uncertainty measure is how far the models disagree — the indicator-disagreement figures below. The dashed rule is the last GDP outturn on record, for reference. A flat stretch means the model indicators did not move; each quarter is its own tracking exercise, and earlier quarters stay in the database.

36 rows · scroll within the table. Ragged edge: Bridged imputes the quarter's missing months by ARIMA before estimation; Real-time builds the specification from the observed cells only. #RHS = regressors in the final specification; #Specs = specifications tested (lag lengths / regularisation grid; for an ensemble, the total across its members). RMSE in 100×log terms under this run's availability pattern; dynamic factor models excluded by design.

One U-MIDAS per indicator, each with a single autoregressive lag and its own estimation sample — so a series with a short history costs nothing to any other model. The spread across these rows is the interpretable uncertainty measure on this page: it says how much the answer depends on which indicator you believe. It is a measure of disagreement, not a probability distribution.

For every quarter whose GDP has since printed, the last nowcast recorded before that release is scored against the first-release outturn. Errors are percentage points of YoY growth. Unlike the in-sample RMSE table above, nothing here was seen by the models when they were fitted — which is why N matters as much as RMSE: until this table has a couple of years in it, treat it as descriptive and do not weight models by it.

Regularisation strength chosen by k-fold cross-validation, re-tuned each run for the current availability pattern; Active = regressors with non-zero coefficients.