Seminar by Satyendra Gupta (DSE)

by

Venue:  Room 107

Abstract:-
We estimate India’s potential output and output gap from quarterly data for 1996Q2–2025Q3. Following Tóth [2021], we add core inflation, capacity utilisation and a production function with capital and employment to GDP-only benchmarks. GDP alone gives widely differing estimates of slack. Core inflation adds limited information, while capacity utilisation changes the decomposition much more. On actual observations alone, the main model, M4, puts the gap at about -3 per cent in 2019Q4 and at 0.9 to 1.0 per cent in 2025Q3, under both Bayesian and maximum-likelihood estimation. The Bayesian 90 per cent band for 2025Q3 is -1.0 to 2.8 per cent, so a small positive gap is likely but zero cannot be ruled out. Potential growth is about 6.7 log points, with a band of 5.6 to 7.8. A wider prior on the persistence of the cycle nearly doubles the gap bands, and potential growth stays volatile under four diagnostic checks. Capital accounts for about half of potential growth before the pandemic; the later split between employment and productivity is less secure because employment measurement changed. The gap rests heavily on one manufacturing survey, which receives about 84 per cent of the post-2008 variation in a conditional allocation. With manufacturing industrial production in its place, the 2019Q4 gap is smaller and its band includes zero, although the negative pre-pandemic gap survives when the most recent factor inputs are withheld. Adding rural wages or industrial production changes the M4 gap little. The production function gives no clear general gain over M3 in revisions or forecasts. The models forecast core CPI-C competitively at longer horizons, but not GDP growth or CPI-IW, and Clark–West tests find no evidence that the real-time gap improves inflation forecasts beyond AR(4). The estimates are better suited to judging episodes and ranges of slack than to fixing a precise policy threshold.

All are cordially invited.

back to seminars…