Effect of<scp>COVID</scp>‐19 Lockdown on the Profitability of Firms in India*
Bibliographic record
Abstract
We examine the effect of COVID‐19‐induced lockdown on the profitability of listed firms in India. We use quarterly income statement of 4168 listed firms for the period between April–June 2020 quarter and April–June 2022 quarter and compare their financial data with previous quarters (2015–2019). Using a difference‐in‐difference estimation framework and various profitability measures, we find that the COVID‐19 lockdown has reduced profits by around 15 per cent for listed firms in India. Our results are robust to various robustness tests and alternate specifications. We find evidence of firms losing revenues more than expenses, thus leading to decline in profits. The main effect is conditioned by firm‐specific factors. Specifically, firms that are smaller, older, unlisted and that do not belong to any group witnessed larger decline in profitability due to lockdown. Additionally, the effect of lockdown is more pronounced in areas that had lower mobility and higher COVID‐19 spread. These results underscore the importance of institutional factors and pre‐existing firm characteristics in conditioning the impact of lockdown on firm profitability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".