Impact of COVID-19 on the Profitability of Listed Commercial Banks in Bangladesh
Bibliographic record
Abstract
The COVID-19 pandemic, originating in Wuhan, China, causes widespread socio-economic disruptions, including in Bangladesh, which enters a lockdown from March 23 to May 30, 2020, halting trade and manufacturing. This study examines the extent of COVID-19’s impact on the profitability of commercial banks listed in Bangladesh. Analyzing the trimestral financial statements of twenty-nine banks from Q1 2017 to Q4 2023, the study finds a significant decrease in profitability (ROA, ROE, and NIM) during the COVID-19 period (from Quarter 2, 2020 to Quarter 4, 2022), with partial recovery in the post-COVID period. The study finds that COVID-19 is inversely related to the profitability indicators ROA, ROE, and NIM. This inverse relationship is also evident between the independent variables, including size, Loan to Deposit ratio, LLP, and Leverage, and the before-mentioned dependent variables. The findings contribute to understanding the pandemic’s impact on Bangladesh’s banking sector and suggest that banks strengthening capital buffers, enhancing risk management, and investing in digital transformation will be better positioned for long-term 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 | 0.001 | 0.004 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".