EM GDP NOWCASTS

← All countriesIndonesia · 2026Q3Last run 2026-09-11 02:38:29 UTC

Indonesia · real GDP, tracking

Tracker eases toward 5.1%

5.10%↓ 0.44 since 02 Sep

YoY · in-sample fit dispersion ±0.26pp · 16 runs this quarter · Trim-25 ensemble

Nowcast history — ensemble aggregations

Trim-25MeanMedianBest modelGDP outturn

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.

Latest run — all models

Availability pattern: consu_vehicle: months 1–1, moto: months 1–2, retail: months 1–1, pmi: months 1–2, cci: months 1–2, cpi: months 1–2, trade_bal: months 1–1, ip_mfg: 1m before quarter

Model	Ragged edge	YoY %	±1.96×SE	RMSE ≈pp	#RHS	#Specs
Trim-25	Ensemble	5.10	±0.26	0.13	5	118
BIC trimmed median	Ensemble	5.40	±0.39	0.20	9	806
Mean	Ensemble	5.33	±0.33	0.17	19	1641
Median	Ensemble	5.40	±0.31	0.16	19	1641
BIC trimmed mean	Ensemble	5.38	±0.43	0.22	9	806
Best model (MIDAS, Bridged)	Ensemble	4.06	±0.32	0.16	36	8
MIDAS	Bridged	4.06	—	0.16	36	8
U-MIDAS	Real-time	5.11	—	0.22	32	1
MIDAS	Real-time	5.56	—	0.22	36	8
U-MIDAS	Bridged	5.09	—	0.23	28	1
Ridge	Real-time	5.68	—	0.23	52	100
Indicator mean	Ensemble	5.71	±0.47	0.24	8	8
Bridge	Bridged	5.34	—	0.24	12	1
Ridge	Bridged	5.32	—	0.25	12	100
ElasticNet	Bridged	5.43	—	0.27	12	600
Indicator median	Ensemble	5.65	±0.54	0.28	8	8
LASSO	Bridged	5.43	—	0.28	12	100
ElasticNet	Real-time	5.40	—	0.28	52	600
MF-VAR	Real-time	5.40	—	0.29	9	1
LASSO	Real-time	5.38	—	0.29	52	100
cpi	Single indicator	5.66	—	0.32	5	1
retail	Single indicator	5.90	—	0.35	6	1
3PRF	Bridged	5.64	—	0.35	24	1
moto	Single indicator	5.57	—	0.37	5	1
U-MIDAS-PC	Bridged	5.26	—	0.40	7	1
MIDAS-PC	Real-time	5.64	—	0.40	8	8
pmi	Single indicator	5.97	—	0.41	5	1
consu_vehicle	Single indicator	5.55	—	0.41	6	1
MIDAS-PC	Bridged	5.24	—	0.41	8	8
trade_bal	Single indicator	5.80	—	0.42	6	1
cci	Single indicator	5.61	—	0.42	5	1
MF-VAR	Bridged	5.26	—	0.44	9	1
3PRF	Real-time	5.44	—	0.45	8	1
U-MIDAS-PC	Real-time	5.54	—	0.45	8	1
ip_mfg	Single indicator	5.64	—	0.51	6	1
DFM	Bridged	5.25	—	—	7	1
DFM	Real-time	5.38	—	—	8	4

37 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.

Dispersion — nowcast against accuracy

Each mark is one model: circles are Real-time, diamonds Bridged. Marks lower on the chart fit better under today's information set; the dashed rule is the Trim-25 ensemble. A tight cluster near the rule means the accurate models agree.

Indicator manifest & data on file

8 of 9 in the joint baseline · 8 with their own model

Indicator	Freq	Role	Category	Transform	Last period	Arrived (UTC)	Obs
cci	M	joint + own model	surveys	`d`	2026-08	2026-09-09 16:02	293
consu_vehicle	M	joint + own model	consumption	`dlog`	2026-07	2026-09-02 17:04	259
cpi	M	joint + own model	prices	`dlog`	2026-08	2026-09-02 17:04	560
ip_mfg	M	joint + own model	activity	`dlog`	2026-06	2026-09-02 17:04	402
moto	M	joint + own model	consumption	`dlog`	2026-08	2026-09-09 16:02	260
pmi	M	joint + own model	surveys	`d`	2026-08	2026-09-02 17:04	185
retail	M	joint + own model	consumption	`dlog`	2026-07	2026-09-02 17:04	283
trade_bal	M	joint + own model	trade	`d`	2026-07	2026-09-02 17:04	552
rgdp	Q	tracked	—	`—`	2026Q2	2026-09-02 17:04	174

The indicator manifest, and where the tracker stands whether or not anything printed today. joint + own model = in the multivariate baseline AND carrying its own single-indicator model; own model = single-indicator only (usually because its history is too short to join the baseline without truncating every joint model's sample); tracked = stored but not modelled. Transform: dlog = log difference, d = first difference (diffusion indices, rates and anything that can go negative). Last period is the newest observation held, Arrived when it first appeared in a download. Reference periods and dates only; indicator values are not redistributed.

New data releases

When (UTC)	Indicator	First ref	Last ref	# obs
Nothing yet. The log records only genuinely new prints, so it stays empty between releases — see the data-on-file table for what the nowcaster is currently holding.

One line per indicator per run: the range of reference periods that arrived.

Single-indicator models — who says what

8 indicators · median 5.66% · range 5.55–5.97%

Indicator	Category	YoY %	RMSE ≈pp
consu_vehicle	consumption	5.55	0.407
moto	consumption	5.57	0.372
cci	surveys	5.61	0.420
ip_mfg	activity	5.64	0.512
cpi	prices	5.66	0.323
trade_bal	trade	5.80	0.416
retail	consumption	5.90	0.348
pmi	surveys	5.97	0.405

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.

Out-of-sample scoreboard

archive vs first-release outturns

Model	Family	RMSE pp	MAE pp	Bias pp	N
Not enough scored quarters yet. A quarter is scored when its GDP prints: the last nowcast made before that release is compared with the first-release outturn. This is the only genuinely out-of-sample table on the page.

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.

Machine-learning cross-validation

Model	Ragged edge	Folds	α grid	Chosen α	L1 ratio	CV RMSE	Active
Ridge	Real-time	5	100	100	—	0.0076	52
Ridge	Bridged	5	100	100	—	0.0073	12
ElasticNet	Bridged	5	100	0.00965	0.10	0.0075	7
LASSO	Bridged	5	100	0.00103	—	0.0075	7
ElasticNet	Real-time	5	100	0.00497	0.10	0.0082	15
LASSO	Real-time	5	100	0.000497	—	0.0082	15

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

EM GDP nowcaster · model outputs onlyUnderlying indicator data not redistributed