Nowcasting GDP Growth Using a Coincident Economic Indicator for India
Bibliographic record
Abstract
In India, the first official estimate of quarterly GDP is released approximately 7-8 weeks after the end of the reference quarter. To provide an early estimate of the current quarter GDP growth, we construct a Coincident Economic Indicator for India (CEII) using 6, 9 and 12 high-frequency indicators. These indicators represent various sectors, display high contemporaneous correlation with GDP, and track GDP turning points well. While CEII-6 includes domestic economic activity indicators, CEII-9 combines indicators on trade and services along with the indicators used in CEII-6. Finally, CEII-12 adds financial indicators to the indicators used in CEII-9. In addition to the conventional economic activity indicators, we include a financial block in CEII-12 to reflect the growing influence of the financial sector on economic activity. CEII is estimated using a dynamic factor model to extract a common trend underlying the highfrequency indicators. We use the underlying trend to gauge the state of the economy and to identify sectors contributing to economic fluctuations. Further, CEIIs are used to nowcast GDP growth, which closely tracks the actual GDP growth, both in-sample and out-of-sample.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".