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Introduction/Main Objectives: This research explores how non-performing loans (NPLs) affect economic growth while assuming that the economy can sustain a certain ratio of NPLs without disruption. Background Problems: Studies employing the threshold approach have not explicitly defined the upper limit of NPLs that supports economic growth. Novelty: This study adds to the existing literature by examining the non-linear relationship between NPLs and economic growth, grounded in two key assumptions: 1) the complete elimination of NPLs is unrealistic, and 2) a threshold level of NPLs exists. Research Methods: Based on this assumption, the study constructs a non-linear model with an inverted U-shape pattern, applying annual data from 33 provinces in Indonesia during 2010–2021 and employing dynamic panel data regression with the GMM estimator. Finding/Results: The results reveal that NPLs will have a negative impact on growth when the NPL ratio exceeds 5.8% in total credit and 2.4% for household credit. However, no inverted U-shaped pattern is observed for working capital and investment credit. In addition, bank credit in total, as well as working capital credit and household credit show a significant positive coefficient on growth, while investment credit has an insignificant negative coefficient. We also introduce the concept of NPLs-growth risk, categorizing it as risk-free, low-risk, moderate-risk, and high-risk based on the area under the curve. The findings indicate that the NPLs-growth risk in Indonesia is generally at a low level. Conclusion: Ensuring that NPLs remain within a safe threshold is essential for sustaining economic growth and avoiding financial instability.

In the context of non-performing loans (NPLs) remaining a systemic risk that threatens financial stability and the efficiency of capital allocation, assessing their persistence and the factors influencing their dynamics is of critical theoretical and practical importance for Vietnam’s banking system. This study provides empirical evidence on the long-term persistence of NPLs and clarifies the role of macroeconomic conditions and bank-specific characteristics in explaining their fluctuations. A panel dataset comprising 24 listed joint-stock commercial banks over the period 2010–2024 is analyzed using complementary econometric techniques, including FE-cluster, FGLS, PCSE, and two-step System GMM estimators. These methods allow for controlling heteroskedasticity, autocorrelation, cross-sectional dependence, and endogeneity simultaneously. The findings reveal strong NPL persistence, with lagged NPL coefficients ranging from 0.65 to 0.84 (p < 0.01), indicating that NPL shocks tend to persist and propagate over time. Bank profitability (ROA) has a negative and statistically significant effect on NPLs, helping to ease credit risk pressures. In contrast, the capital ratio is positively associated with NPLs, reflecting a higher risk tolerance among better-capitalized banks. Inflation exerts a positive and significant impact, whereas GDP growth shows limited influence. Based on these results, the study proposes several policy implications: strengthening risk management and countercyclical credit control; enhancing capital buffers; coordinating monetary and fiscal policies to stabilize the macroeconomic environment; and improving credit risk forecasting and management capacity. The findings provide robust empirical evidence to support policymakers, regulators, and bank managers in designing sustainable NPL control strategies, thereby reinforcing the stability of Vietnam’s financial system.

This study explores the relationship between policy choices in financial consumer protection (FCP) and non-performing loans (NPLs) in a broad international context, recognising that NPLs negatively affect citizens’ well-being and the social pillar of sustainable development.Nine FCP indices were constructed to capture distinct regulatory choices based on regulators’ responses to the World Bank FICP surveys. The estimation framework extends standard macroprudential models by adding institutional indicators for the general environment, as well as for the corporate and household credit segment, with the latter being represented by the FCP indices. We estimate seven models using an unbalanced dataset of 113 countries. These include a within model, two supplementary cross-sectional models, and four time–cross-section panel models that serve as the main specifications. Two FCP indices show unfavourable associations with NPL dynamics – financial inclusion (moderate) and credit pricing (small) – while three show favourable associations – financial literacy (moderate), credit reporting (moderate), and regulatory capacity (large).Four other indices – information disclosure, affordability, fair treatment, and debt resolution – do not show sufficient evidence of association with NPL dynamics.Financial inclusion shows a concerning association, suggesting a potential trade-off between wider credit access and credit quality, which may be particularly acute under weak responsible-lending requirements. By contrast, the small positive association for credit pricing is economically minor and may be explained by a denominator effect arising from lower pre-COVID NPL levels.Policies on financial literacy, credit reporting, and regulatory capacity show evidence of robust negative associations, indicating favourable outcomes in terms of NPL dynamics for these policy choices. The FCP policies represented by the other four indices may still be favourable for citizens’ well-being through effects not captured in this NPL-focused analysis, which is also constrained by the short and small panel dataset.

Purpose – The study investigates the performance of non-performing financing (NPF) in the housing sector concerning the asymmetric influence of macroeconomic conditions. Methodology – The study method adopts nonlinear autoregressive distributed lag (NARDL), while the study data ranges from 2014 m6 to 2022 m2. Finding –The findings reveal an asymmetric relationship between macroeconomic variables and NPF in the short and long run. In addition, Covid-19 has worsened the NPF of Islamic banks' home financing in some sectors in the short run, while only such financing in the flat and apartment market has suffered during the pandemic in the long run. Implication – The implication of the study suggests that the Islamic banking industry and financial authority need robust risk management and financial policies, respectively, to achieve and maintain the stability of Islamic banks in home financing activities. Originality – The study is original in measuring the impact of macroeconomic influences on Islamic banks' home financing from a nonlinear viewpoint.

Controllable anisotropic growth of perovskite nanocrystals (NCs) is challenging since it is difficult to separate the nucleation and growth processes. Here, a two-step nucleation strategy is proposed to control the binding interaction between surface ligands and NCs, resulting in facet-induced coordination competition. Oleic acid as surface activated ligand leads to the formation of defective lead bromine octahedron, and the binding interaction between 4-dodecylbenzenesulfonic acid and lead atoms promotes the formation of two kinds of binding interactions. Based on this strategy, the anisotropic growth of CsPbBr 3 nanoplatelet (NPLs) with adjusted length from 11.4 to 24 nm, and the evolution of NPLs from stacked to tongue-shaped have been realized. Elemental line scan reveals the sulfur atoms mainly distribute at the edge of NPLs. Furthermore, binding energy calculation and experimental results illustrate the coordination competition of different binding interaction on specific facets induces the anisotropic growth of NPLs. Importantly, strong emission anisotropy of highly ordered NPLs with polarization ratio up to 0.58 is illustrated. This work not only deepens our understanding of the controllable synthesis of perovskite NCs, but also provides a reference for the regulation of light emitting diode and soler cells.

Excitation-emission matrix fluorescence spectroscopy coupled with a hybrid N-way partial least squares and random forest (NPLS-RF) model was proposed for brand recognition of brick tea. A total of 300 samples belonging to 25 brands were collected, and the spectra were recorded with the excitation from 230 to 530 nm and the emission in the range of 246–845 nm. NPLS reduced the data dimension from 15,250 to 10, which was more efficient than PCA and LLE. The factor importance was evaluated by RF, and the chemical significance of the first three factors in the NPLS model revealed that the fulvic-like substances and the theabrownin were the key points for distinguishing the spectra from various brick tea brands. The performance of the five classification models including NPLS-SVM, NPLS-ELM, NPLS-GRNN, NPLS-RF, as well as NPLS-DA was compared, and the best result (accuracy 99%, F-score 0.99) was obtained using NPLS-RF. Moreover, data preprocessing was discussed, Z-score normalization of variables was necessary for NPLS while min–max normalization of each spectrum was found to be imperative for RF. The proposed method could be a simple, rapid and reliable alternative for authentication of brick tea.

Non-performing loan (NPL) is a red flag, providing signal of jeopardize for a country's economy. With respect to increase in NPLs, banking sector of Bangladesh has trapped in gridlock. This problem has become an alarming issue for bank's sustainability. The present study investigates the determinants of commercial bank's NPLs in Bangladesh. Due to data deficiency, the study collects data from 30 sampled commercial banks in Bangladesh over the period from 2011 to 2020, as during 2011, the total scheduled commercial banks in Bangladesh were 34. The study performs Random Effect Regression Model, Fixed Effect Regression Model, and one step GMM system to get the robust and significant result. The study reports that firm-specific factors like lag of NPLs, loan loss provision to total equity ratio, equity-to-total asset ratio, capital adequacy ratio, net loan to total deposit and borrowing ratio, return on equity, and macroeconomic factors such as inflation, and GDP ratio are the crucial determinants of NPLs in Bangladesh. The study concludes that commercial banks should operate its activities more efficiently and avoid reckless lending along with mandatory capital requirement in order to reduce NPLs and to ensure profit for their shareholders. The analysis of the study would provide insight guidelines regarding bank's credit risk management procedures and systems to country's regulatory body in order to design and adopt required prudential regulations in credit policy.

Given the impact of the COVID-19 pandemic on the European real economy, European banks are likely expected to be confronted by a wave of non-performing loans. Focusing on a sample of large banks in the EU area over the pre and during the COVID-19 pandemic period, the analysis shows an extended degree of divergence during the pandemic crisis, with GDP, bank profitability and risk being held the responsible factors. The findings imply that potential plans to deal with NPLs should explicitly consider strategies running from bank restructuring and resolutions to recapitalisation or any other rescue measures.

2D metal‐chalcogenide nanoplatelets (NPLs) exhibit promising photocatalysis properties due to their ultrathin morphology, high surface‐to‐volume ratio, and enhanced in‐plane electron transport mobility. However, NPLs, especially cadmium chalcogenides, encounter challenges in CO2 photoreduction due to insufficient solar energy utilization and fast recombination of photogenerated charge carriers. Defect engineering offers a potential solution but often encounters difficulties maintaining structural integrity, mechanical stability, and electrical conductivity. Herein, by taking two monolayers (2ML) CdSe NPLs as a model system, selenium (Se) vacancies confined in atomic layers can enhance charge separation and conductivity. A straightforward approach to create Se vacancies in various monolayers CdSe NPLs (2, 4, and 5ML) has been developed, enabling efficient CO2 photoreduction with a 4‐fold increase in CO generation compared to their defect‐free counterparts. Significantly, accounting for higher charge density and efficient carrier transport due to Se vacancies, defective 2ML CdSe NPLs (VSe‐2ML CdSe) exhibit CO evolution performance up to 2557.5 µmol g−¹ h−¹ with no significant decay over 5 h, which is an order of magnitude higher than that of common semiconductor catalysts. This study establishes a practical way to design advanced 2D semiconductor photocatalysts to achieve efficient CO2 photoreduction via defect engineering. A direct defect engineering approach is demonstrated to obtain CdSe nanoplatelets with Se vacancies. These nanoplatelets exhibit highly efficient photocatalytic CO₂ reduction performance, achieving a CO evolution rate of up to 2557.5 µmol g−¹ h−¹.