2026· International Journal of Social Science & Economic Research· Vol 11, pp. 2991· 0 citations· 9 references
Abstract
This study examines the dynamics of asset quality across all twelve Indian public-sector banks
(PSBs) over fiscal years 2011–2026, using a merger-consistent (pro-forma) panel of 192 bankyears constructed from Reserve Bank of India (RBI) data and bank disclosures. The empirical
workhorse is deliberately simple: the canonical non-performing-loan (NPL) determinants panel,
in which the gross non-performing-asset (GNPA) ratio is regressed on its own lag, real GDP
growth, the ten-year government-bond yield, and lagged credit growth, with bank fixed effects
and standard errors clustered by bank. Three findings emerge. First, asset quality is highly
persistent: the autoregressive coefficient is about 0.71 with the full set of controls—implying a
half-life of roughly two years—and is robust to adding year fixed effects and to excluding the
pandemic years. Second, the relationship between GNPAs and the macroeconomy is not
structurally stable: interest rates matter, but the coefficient on GDP growth is weak and wrongsigned in the pooled panel, and when the identical regression is estimated separately before and
after the AQR the GDP coefficient collapses from +1.20 to zero—evidence that the 2016 surge
was a supervisory recognition event rather than a business-cycle effect. Third, a transparent,
calibrated stress test—reconciled to the RBI June 2026 Financial Stability Report—finds that all
twelve banks remain above the eight-per-cent CET1 prompt-corrective-action floor even under a
severe five-percentage-point GDP contraction, with the asset-weighted GNPA ratio rising from
1.94 to 3.93 per cent. Cross-sectionally, the stressed-capital ranking is governed by starting
capital and bank size rather than current asset quality.
The present paper aims to investigate the relationship between non-performing assets (NPAs) and profitability in Indian commercial banks. Focusing on the major economic disruptions, namely, the global financial crisis, demonetization and the COVID-19 pandemic, it examines their role in structurally reshaping the NPA-profitability nexus.
Our dataset comprised a balanced panel of 30 public and private sector commercial banks in India covering the period from 2004 to 2024. We applied Bai–Perron multiple breakpoint tests and Chow tests to identify regime shifts. Static panel regressions with Heteroskedasticity and Autocorrelation Consistent-corrected ordinary least squares and dynamic system generalized method of moments (GMM) estimations are employed to address heteroskedasticity, autocorrelation and endogeneity. The model incorporates bank-specific factors, market concentration indicators, macroeconomic variables and an interaction term between inflation and broad money (BM).
The findings reveal multiple statistically significant structural breaks corresponding to major economic shocks. NPAs consistently exert a significant negative impact on profitability across all regimes, while bank size positively influences return on assets, particularly during crisis periods. Market concentration yields mixed and regime-dependent effects. The interaction between inflation and BM significantly moderates profitability during transitional phases, highlighting the role of inflation-adjusted liquidity conditions in shaping bank performance.
The findings suggest that bank managers should strengthen credit risk monitoring and adopt proactive asset quality management, especially during periods of inflationary liquidity expansion. The policymakers and regulators can benefit from implementing countercyclical capital buffers and dynamic stress-testing frameworks tailored to structural shocks. However, our results should be interpreted with caution as we excluded foreign banks from our dataset and focused solely on Indian commercial banks, which may limit cross-country generalizability. Future research could extend the framework to comparative emerging-market settings.
To the best of our knowledge, this study is the first attempt to integrate structural break analysis with dynamic GMM estimation and to introduce inflation-adjusted liquidity as a moderating mechanism in the NPA-profitability relationship in an emerging economy context.
Faiza Rehman, Mohammad Ammar Ahsan, S. Akhtar et al.· Journal of Financial Regulat...· 0 citations
This paper re-examines the determinants of profitability in Bangladeshi private commercial banks, using a panel-corrected standard errors (PCSE) analysis of ten listed banks over 2014–2023 (n = 100 bank-year observations), together with a post-sample assessment of the sector's extraordinary deterioration through 2024–2025. Profitability is measured by return on assets (ROA), with return on equity (ROE) and net interest margin (NIM) used as robustness checks. Results show that capital adequacy and management efficiency significantly enhance profitability, while asset-quality deterioration and non-performing loans (NPLs) exert strong negative effects; liquidity management and bank size are largely insignificant, pointing to inefficiencies in deployment and scale. GDP growth is statistically negligible within-sample and inflation shows mixed effects, underscoring structural weaknesses in financial intermediation. A winsorization check (1st/99th percentiles) confirms that the capital-adequacy and NPL effects are stable to outlier treatment, while the management-efficiency effect is more sensitive. Extending the analysis with Bangladesh Bank, IMF, and World Bank data through 2025 shows that the sector-wide NPL ratio rose from below 10 percent in 2023 to more than 30 percent by late 2025, alongside a collapse in aggregate capital adequacy a trajectory consistent with, and considerably amplifying, the credit-quality channel identified in the panel results. The study contributes methodologically by applying PCSE in a South Asian context, and offers policy implications for strengthening credit discipline, addressing regulatory forbearance, and improving banking efficiency.
Md. Jahidul Islam, M. Moniruzzaman, A. Haq et al.· Global Disclosure of Economi...· 0 citations
This study investigates the determinants of credit growth in Western Balkan countries over the period 2011–2023, assessing whether lending dynamics are driven by macroeconomic fundamentals or financial sector conditions. The analysis focuses on key variables, including GDP growth, foreign direct investment (FDI), inflation, and lending interest rates. Using a balanced panel dataset, the study employs pooled Ordinary Least Squares (OLS), fixed and random effects models, and a two-way fixed effects specification with Driscoll–Kraay standard errors to address cross-sectional dependence and unobserved heterogeneity. The empirical results show that lending interest rates exert a statistically significant negative effect on credit growth, indicating that financial conditions play a central role in constraining lending activity. In contrast, GDP growth and inflation are not found to be significant determinants, challenging conventional macro-financial expectations. FDI becomes significant only when introduced in a lagged specification, suggesting a delayed transmission mechanism through which external capital inflows influence credit expansion. The study contributes to the literature by providing comparative multi-country evidence from structurally constrained and bank-dominated financial systems. The findings suggest that credit growth is driven less by traditional macroeconomic factors and more by financial sector conditions and institutional characteristics. These results have important policy implications, highlighting the need to strengthen financial intermediation efficiency and credit transmission mechanisms rather than relying solely on macroeconomic expansion to stimulate lending.
Erleta Halimi, Katalin Czakó, Arben Sahiti et al.· Emerging Science Journal· 0 citations
This study develops a dynamic panel econometric framework to quantify the structural impact of macroeconomic conditions on the non-performing loan (NPL) ratios of commercial banks across a panel of twenty-eight emerging market economies observed between 2010 and 2024. Addressing dynamic persistence and the endogeneity inherent in the joint determination of credit quality and macro-financial conditions, the empirical strategy combines a two-step System Generalized Method of Moments (System GMM) estimator with a Panel Autoregressive Distributed Lag (P-ARDL) error-correction specification estimated via Pooled Mean Group (PMG). The results confirm strong dynamic persistence in NPL ratios and show that real GDP growth, the unemployment rate, consumer price inflation, and the real lending rate are statistically significant macroeconomic drivers of asset-quality deterioration. Critically, the interaction between currency depreciation and the share of unhedged foreign-currency lending is found to amplify the NPL response to exchange-rate shocks, a channel of particular relevance to partially dollarized banking systems in transition economies such as Uzbekistan, where reported and risk-based measures of asset quality have been shown to diverge materially. The error-correction estimates indicate that approximately one-third of any disequilibrium between actual and long-run equilibrium NPL levels is corrected within a single year. These findings offer a structural basis for calibrating countercyclical provisioning and macroprudential buffers in emerging banking systems exposed to currency and business-cycle volatility.
Djamalov Gofir Oribjanovich· EPRA International Journal o...· 0 citations
This study examines whether the accumulated stock of private credit provides early-warning information for subsequent deterioration in banking-sector asset quality. It combines annual Passport banking indicators with World Development Indicators for 58 countries over 2010–2024; the preferred sample contains 746 country–year observations. A second-order dynamic fixed-effects model links log(1 + NPL), where NPL denotes the non-performing loan ratio, to lagged private credit to gross domestic product (GDP), real credit growth, lending rates, bank capital, GDP growth, inflation, and unemployment. Its preferred credit-depth coefficient is 0.00377, implying that a 10-percentage-point increase is associated with approximately 0.15 percentage points more NPLs one year later at the sample median. To operationalize early-warning calibration without claiming a universal cutoff, the paper reports the sample credit-depth quartiles and estimates a country fixed-effects linear probability model using the European Banking Authority’s 5% gross-NPL supervisory trigger. In that alternative outcome, a 10-percentage-point increase in credit depth is associated with a 2.78-percentage-point higher conditional probability of NPLs reaching 5% or more (p = 0.002). On a strictly common 609-observation sample, the credit-depth coefficients at one-, two-, and three-year horizons are 0.00501, 0.00960, and 0.01266. Lending rates and unemployment are positive, whereas annual credit growth and capital ratios are not robust predictors. Pooled interactions do not reject equal slopes across broad country partitions. System generalized method of moments (GMM) passes conventional tests but violates a persistence-bound credibility check. The evidence supports an early-warning interpretation, not a causal claim.
Marco Antonio Ledesma Munive, Alejandro Anibal Aguirre-Rojas, Graciela Soledad Verastegui Velasquez et al.· Journal of Risk and Financia...· 0 citations
This study examines the relationship between financial deepening and output in Nigeria using 56
quarterly observations from 2012Q1 to 2025Q4. The supplied dataset contains current-value
naira series for gross domestic product (GDP), Point-of-Sale (POS) transactions, mobile
payments, and credit to the private sector (CPS). Consequently, the dependent variable measures
nominal output rather than real economic growth. All series were transformed into natural
logarithms. Seasonal augmented Dickey-Fuller tests show that the four log-level series are non
stationary but become stationary after first differencing. A stationary seasonal distributed-lag
model was therefore estimated in quarterly log changes, with lagged financial variables, a four
quarter output-growth term, quarterly effects, a trend, a COVID-19 intervention dummy, and a
2025Q1 data-discontinuity control. Newey-West heteroskedasticity- and autocorrelation
consistent standard errors were used. Lagged POS growth, mobile-payment growth, and CPS
growth are individually insignificant, and they are jointly insignificant (F = 0.769, p = 0.518).
The results do not support the earlier claim that the three financial-deepening indicators exert
positive and significant short-run and long-run effects on economic growth. A defensible real
growth analysis requires real GDP and consistently deflated financial variables.
Samuel Chukwuyem Okojere· International Journal of Eco...· 0 citations