Assessing Basel Capital Regulations: Exploring the Risk and Efficiency Relationship in Emerging Economies
Bibliographic record
Abstract
This research investigates the relationship between Basel capital regulations, bank risk, and bank efficiency in the context of Pakistani and Indian commercial banks. This study examines the period from 2009 to 2022 and specifically analyses the impact of Basel III capital requirements on risk and efficiency. Quantitative methods are employed, utilising data from central bank websites and the BankScope database to construct a comprehensive sample of commercial banks in Pakistan and India. The system-generalised method of moments (GMM) estimation technique addresses potential endogeneity issues in the regression models. The findings shed light on the effectiveness of these regulations and provide insights for policymakers and regulators in both countries. The results indicate that Basel capital regulations have generally increased banks’ risk-taking behaviour in Pakistan and India. However, they have not improved the overall efficiency of the banking sector in either country. Bank efficiency declined during the study period, highlighting the limited effectiveness of Basel capital regulations in enhancing efficiency. Furthermore, the impact of these regulations on risk and efficiency varies between the two countries. In Pakistan, the regulations do not significantly affect bank efficiency, while in India, they decrease efficiency. Additionally, Basel III capital regulations do not significantly impact the risk taken by banks in either country. This study concludes by emphasising the need for alternative mechanisms or policies to improve the banking industry’s efficiency, as Basel capital regulations alone have proven ineffective. The findings offer valuable insights for central banks and regulators in assessing the relationship between capital regulations, risk, and efficiency and implementing appropriate measures to enhance the performance of the banking sector. This study recommends the following key points: the adoption of tailored regulatory approaches to address specific challenges, achieving an optimal balance between risk management and operational efficiency, enhancing the effectiveness of management roles, considering the influence of macroeconomic factors, and evaluating the implications of long-term policy development for sustainable progress. The present study adds to the prevalent literature on the impact of capital regulations on bank risk and efficiency nexus. This study focuses on Pakistan and India, which are two important developing nations. Moreover, another important contribution of this study lies in the effect of Basel III capital regulation on bank risk, as these capital regulations are different from other Basel capital requirements.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".