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The scope of this research is to investigate performing loan efficiency for fifty European banks during the period 2008–2017.

The study is structured as a two-stage analysis of performing loan efficiency and its driving factors. In the first stage of the proposed methodology “Data Envelopment Analysis” is used to estimate performing loan efficiency for each bank included in the sample. A bootstrap statistical procedure enhances the findings. In the second stage, the impact of other factors on the efficiency scores of loan performance using tobit regression is investigated.

The results are consistent with the findings of the individual banks' financial analyses. According to the findings of DEA implementation, the evaluated banks may enhance their cost efficiency by 39% on average. In addition, the results indicate that loan efficiency performance improves after 2015, coinciding with the business cycle's upward trend. The tobit regression is employed in the second stage to examine the influence of bank-related and macroeconomic factors on banks' loan management efficiency. According to the findings of the tobit regression, three factors, namely the capital adequacy ratio, GDP per capita and managerial inefficiency, have a substantial influence on performing loan efficiency.

This research investigates the effectiveness of European economic policy in protecting the European banking system from the consequences of the sovereign debt crisis in several euro area members. The results highlight the distance of the Eurozone from the level of the ‘optimal currency area’.

This article outlines contingent claims created as a result of the arrangements underlying the transfer of state‐owned commercial banks’ non‐performing loans to asset management companies. An understanding of these factors is central in analysing the potential for China’s as set management companies to realise value from their acquisition of these nonperforming state‐owned enterprise loans. After establishing the scale of the non‐performing loan problem, the article identifies and describes a number of real and financial options that may assist in the consideration of the value of assets associated with the transfer of non‐performing loans from the state‐owned commercial banks to the asset management companies. Real and financial options appear in the form of implied guarantees over asset management corporation debt, implied guarantees associated with the non‐performing assets remaining with the stateowned commercial banks, and within the equity positions held by the asset management companies as a result of equity‐for‐debt swaps initiated under the current reform process. The article concludes that any gains made to the credit standing of the state‐owned commercial banks reflect the value of implied guarantees over both the asset management corporation debt and the remaining stock of non‐performing loans held by the banks. Furthermore, institutional arrangements associated with the equity positions held by the asset management corporations significantly reduce the value of options associated with operation and control of firms in which the equity positions are held. Additionally, the structure of equity positions taken under the equity‐debt swaps suggest that the value of equity positions held in state‐owned enterprises by the asset management companies will be considerably lower than hoped for and implied in the asset management companies’ mandates.

Wealth Management Products (WMPs) are the largest and most crucial component of China's Shadow banking, which are off the balance sheet and considered as a substitute for deposits. Commercial banks in China are involved in the issuance of WMPs mainly to; evade the regulatory restrictions, move non-performing loans away from the balance sheet, chase the profits and take advantage of yield spread (the difference between WMPs yield and deposit rate).

In this study, the authors investigate what bank related characteristics and needs; influenced and prompted the issuance of WMPs. By using a quarterly panel data from 2010 to 2019, this study performed the fixed effects approach favored by the Hausman specification test, and a feasible generalized least square (FGLS) estimation method is employed to deal with any issues of heteroscedasticity and auto-correlation.

This study found that there is a positive and significant association between the non-performing loan ratio and the issuance of WMPs. Moreover, profitability and spread were found to play an essential role in the issuance of WMPs. The findings of this study suggest that WMPs are issued for multi-purpose, and off the balance sheet status of these products makes them very lucrative for regulated Chinese commercial banks.

Non-guaranteed WMPs are considered as an item of shadow banking in China, as banks do not consolidate this type of WMPs into their balance sheet; due to that reason, there is no individual bank data available for the amount of WMPs. The authors use the number of WMPs issued by banks as a proxy for the bank's exposure to the WMPs business.

From a regulatory perspective, this study helps regulators to understand the risk associated with the issuance of WMPs; by providing empirical evidence that Chinese banks issue WMPs to hide the actual risk of non-performing loans, and this practice could mislead the regulators to evaluate the bank credit risk and loan quality. This study also identifies that Chinese banks issue WMPs for multi-purpose; this can help potential investors to understand the dynamics of WMPs issuance.

This research is innovative in its orientation because it is designed to investigate the less explored wealth management products (WMPs) issued by Chinese banks. This study's content includes not only innovation but also contributes to the existing literature on the shadow banking sector in terms of regulatory arbitrage. Moreover, the inclusion of FGLS estimation models, ten years of quarterly data, and the top 30 Chinese banks (covers 70% of the total Chinese commercial banking system's assets) make this research more comprehensive and significant.

Directors help determine the strategic direction of a corporation and are responsible for ensuring the institution has a good system of internal control. Banking institutions without a strategic direction emphasizing sound lending practices that promote the long-run financial health and viability of the institution will be sued more frequently than peer institutions. Institutions that do not have a good system of internal control will also be sued more frequently. Hence, legal expense is a bank corporate governance measure. We compare the performance of bank legal expense and a widely cited corporate governance index in a regression framework to determine which better predicts bank performance. The regressions indicate legal expense is a much better predictor, hence a better measure of bank corporate governance. Regulators should require legal expense reporting and rank institutions by the ratio of legal expense to assets to help identify institutions with weak governance. Seven case studies illustrate the role of legal expense in corporate governance.

The purpose of this paper is to investigate whether the quality of the credit process is sensitive to reaching a particular threshold level of non-performing loans (NPLs) and, more importantly, whether higher NPLs ratios could make the monitoring activity ineffective.

The empirical design is composed of two steps: in the first step, the authors introduce a monitoring performance indicator (MPI) of the credit process by combining the non-parametric technique Data Envelopment Analysis with some financial ratios adopted as input and output variables. As second step, the authors apply a threshold panel regression model to a sample of 298 Italian banks, over the time period 2006–2014, and the authors investigate whether the quality of the credit process is sensitive to reaching a particular threshold level of NPLs.

This paper finds that, first, when the NPLs ratio remains below the threshold value estimated endogenously, an increase in the quality of monitoring has a positive impact on the NPLs ratio. Second, if the NPLs ratio exceeds the estimated threshold, the relationship between the NPLs ratio and quality of monitoring assumes a positive value and is statistically significant.

Due to the lack of data, the investigation of NPLs in the Italian industry across loan types combined with the monitoring effort by banks management was not possible. The authors plan to investigate this topic in future studies.

The identification of the threshold has a double operational valence. The first regards the Supervisory Authority, the threshold approach could be used as an early warning in order to introduce active control strategies based on the additional information requested or by on-site inspections. The second implication is highlighted in relation to the individual banks, the monitoring of credit control quality, if objective and comparable, could facilitate the emergence of best practices among banks.

A high NPLs ratio requires greater loan provisions, which reduces capital resources available for lending, and dents bank profitability. Moreover, structural weaknesses on banks’ balance sheets still persist particularly in relation to the inadequate internal governance structures. This means that bank management must able to recognise in advance early warning signals by providing prudent measurement together with an in-depth valuation of loans portfolio.

The originality of the paper is twofold: the authors introduce a new proxy of credit monitoring, called MPI; the authors provide an empirical proof of the Diamond’s (1991) economic intuition: for riskier borrowers, the monitoring activity is an inappropriate instrument depending on the bad reputational quality of borrowers.

This study aims to analyze bank lending behavior before and during the most recent financial crisis. Banks are more willing to grant loans during economic expansion. However, this behavior can result in reduced portfolio asset quality. The analysis tries to facilitate understanding of whether this relationship is always true. A second aim of the study is to highlight whether the impact of credit risk on bank lending behavior during a financial crisis is greater for banks that grew faster during the pre-crisis period than for other banks.

The analysis is based on a sample of banks in Italy, an example of a country undergoing a credit crunch without a lending bubble burst. The methodology is based on a panel regression and author uses different models to test his hypothesis: an ordinary least squares, a fixed effect, a least absolute regression and a Generalized Method of Momentum (GMM). This allows to mitigate some of the endogeneity problems.

The essay shows that effectively, most of the banks that grew faster during a pre-crisis period show a higher growth of non-performing loans and a greater reduction in lending activity during a financial crisis. However, 34 per cent of banks that grew faster during a pre-crisis period have a low growth of non-performing loans in the subsequent years. Finally, the results suggest that credit risk negatively affects bank lending behavior, but a higher impact relative to fast banks with respect to other banks cannot be emphasized.

Findings have some policy implications. First, given the adverse effect of the increase of non-performing loans (NPLs) on the bank’s lending activity and on the broad economy in general, there is merit to strengthen supervision to prevent a further increase and accumulation of NPLs in the bank’s credit portfolio. In addition, the supervisors could require that banks take always high credit standard when extend credit, both during positive economic cycle and during period of contraction. The using of higher credit standard could be helpful in the reduction of the pro-cyclicality of bank’s lending behavior and credit risk. Furthermore, the fact that high level of NPLs continues to impact on the bank’s lending activity and that this activity is very important for the economic recovery underlines that banks should clean-up their credit portfolios as soon as possible.

This paper contributes to the literature in various ways. The study analyzes the cyclical effect of credit growth, i.e. banks increase their bank lending behavior during good times, which leads to an increase in bad loans and a high credit risk in their portfolio. These cyclical effects are not knowingly studied together, but the literature usually analyzes the single steps of the cycle. Second, studying listed and unlisted banks allows to have a more representative sample and to analyze better the real bank lending activity considering both commercial than cooperative banks.

This study develops a model for loan loss provision which follows the accounting practice in Malaysia. Banks are subject to generally accepted accounting principles (GAAP) in disclosing the loan loss provision. However, the expected loan losses factor should also be taken into account to counter unexpected situations. Prior studies show that banks tend to manipulate the loan loss provision through discretionary accruals for income smoothing purposes. Since the loan loss provision is important to banks' income, this study will determine factors that influence the provision. Empirical evidence state that the loan loss provision is positively related to non‐performing loans, loan loss allowance and write‐offs. Estimation results using ordinary least squares regression prove that the banks follow GAAP guidelines, whereby the loan loss provision depends on the beginning balance and the current write‐offs. In addition, the banks should also consider the expected non‐performing loans in providing loan loss provisions. In determining loan losses, the performance of each economic sector should also be considered due to different default risks.

Using time-series data on the US banking industry for the period 1984Q1-2016Q2, the present study aims to examine the impact of both aggregate and sector-specific non-performing loans (NPLs) on aggregate and sectoral product and labor markets.

Using both single equation ordinary least squares and instrumental variables regressions, the study compares the sensitivity of sector-specific gross domestic product (GDP) and employment growth to changes in both aggregate and sectoral NPLs. Moreover, the paper uses vector autoregressions (VARs) to dynamically trace the impact and duration of NPLs on different types of real economic activity..

Rise in total NPLs reduces US real GDP growth that is most accentuated for construction sector GDP. Likewise, total NPLs significantly lowers both total and non-farm employment growth, financial activities and construction sector employment growth, with the latter showing most sensitivity. Moreover, NPLs in commercial and industrial sector, consumer lending, non-farm non-residential, construction and land development, single- and multi-family residential sectors reduce corresponding sectoral employment growth. The VARs largely confirm these findings with shocks to total NPLs having the most immediate and persistent inimical impact on construction-sector GDP growth.

The deleterious impact of different categories of NPLs on both aggregate as well as sector-specific product and labor markets illustrate that a distressed banking sector is a serious obstacle to the real sector. The findings underscore the need not only to clean up NPLs for the sake of banks financial soundness but also to reduce their pernicious effects on the health of the US economy. For bank regulatory authorities in the USA, it indicates constant monitoring of banks in their jurisdiction and identifying early warning signals to mitigate the potential real sector losses due to rising NPLs.

The extant literature on NPLs has mainly focused on explaining its underlying determinants but not on its real sector consequences. The present paper examines the impact of NPLs on different facets of real economic activity, an issue that has been rarely studied and especially not on the US economy. Moreover, the overwhelming majority of existing literature focuses on aggregate NPLs. The relationships derived in such studies, while useful, can mask important differences between different types of NPLs and real economic activity. The present paper explores the impact of disaggregated NPLs in the US banking industry on corresponding sector-specific product and labor markets, again an issue that has not been studied previously.

The purpose of this research is to investigate whether inclusion of risk assessment variables in the multiple discriminant analysis (MDA) model improved the banks ability in making correct customer classification, predict firm's performance and credit risk assessment.

The paper reviews literature on the application of financial distress and credit scoring methods, and the use of risk assessment variables in classification models. The study used a sample of 56 performing and non‐performing assets (NPA) of a privatized commercial bank in Tanzania. Financial ratios were used as independent variables for building the MDA model with a variation of five MDA models. Different statistical tests for normality, equality of covariance, goodness of fit and multi‐colinearity were performed. Using the estimation and validation samples, test results showed that the MDA base model had a higher level of predictability hence classifying correctly the performing and NPA with a correctness of 92.9 and 96.4 percent, respectively. Lagging the classification two years, the results showed that the model could predict correctly two years in advance. When MDA was used as a risk assessment model, it showed improved correct customer classification and credit risk assessment.

The findings confirmed financial ratios as good classification and predictor variables of firm's performance. If the bank had used the MDA for classifying and evaluating its customers, the probability of failure could have been known two years before actual failure, and the misclassification costs could have been calculated objectively. In this way, the bank could have reduced its non‐performing loans and its credit risk exposure.

The valiadation sample used in the study was smaller compared to the estimation sample. MDA works better as a credit scoring method in the banking environment two years before and after failure. The study was done on the current financial crisis of 2009.

Use of MDA helps banks to determine objectively the misclassification costs and its expected misclassification errors plus determining the provisions for bad debts. Banks could have reduced the non‐performing loans and their credit risks exposure if they had used the MDA method in the loan‐evaluation and classification process. The study has proved that quantitative credit scoring models improve management decision making as compared to subjective assessment methods. For improved credit and risk assessment, a combination of both qualitative and quantitave methods should be considered.

The findings have shown that using the MDA, commercial banks could have improved their objective decision making by correctly classifying the credit worthiness of a customer, predicting firm's future performance as well as assessing their credit risk. It has also shown that other than financial variables, inclusion of stability measures improves management decision making and objective provisioning of bad debts. The recent financial crisis emphasizes the need for developing objective credit scoring methods and instituting prudent risk assessment culture to limit the extent and potential of failure.

This study aims to examine the determinants of the allowance for loan losses (ALL) and loan loss provisions (LLP) for banks in the Middle East and North African (MENA) region using both a two-stage approach and simultaneous equation system to address the potential problem of estimation bias introduced by estimating the ALL and LLP separately. The paper also tests three competing hypotheses: the earnings management hypothesis, the capital management hypothesis, and the signaling hypothesis.

The authors adopt a simultaneous equation and three-stage approaches to test whether MENA banks jointly determine LLP and ALL and the determinants of the two accounts. The sample consists of all available electronic data for 75 banks (451 bank-year observations) in nine MENA countries over the period 2000-2008.

Evidence suggests that the two accounts are jointly determined. The results support the earnings management hypothesis – meaning that MENA banks have engaged in year-to-year income smoothing. The authors also find that LLP and ALL provide signals about future earnings.

The authors acknowledge that the LLP account is only one of many accounts on the income statement that could be used for signaling or to manage earnings, and that the ALL is one of several accounts that could be used for signaling, earnings or capital management. Future studies could examine other accruals for their role in managing earnings, signaling and capital.

The results indicate that bank managers use LLP and ALL accounts to manage earnings management, policy makers may want to limit the ability of banks to manipulate earnings.

Prior research on the loan loss accounting practices has been based on single equation models of the determinants of LLP and ALL. An issue that has not been adequately addressed in this literature is that ALL and LLP may be interrelated and jointly determined by banks. If the two accounts are not independent of each other, failure to include one when estimating the other may lead to an omitted variable problem, while including both in the same equation induces a potential simultaneity bias. The study is the first empirical work examining whether ALL and LLP are jointly determined by banks. By jointly estimating LLP and ALL, the study permits an assessment of the magnitude of the potential error from adopting ordinary least squares estimation of a single equation model.