Credit Risk and Bank Specific Factors: an Empirical Study using Panel GMM

PurposeAmong all of the world's continents, Asia is the most important continent and contributes 60% of world growth but facing the serving issue of high nonperforming loans (NPLs). Therefore, the current study aims to capture the effect of credit risk management and bank-specific factors on South Asian commercial banks' financial performance (FP). The credit risk measures used in this study were NPLs and capital adequacy ratio (CAR), while cost-efficiency ratio (CER), average lending rate (ALR) and liquidity ratio (LR) were used as bank-specific factors. On the other hand, return on equity (ROE) and return on the asset (ROA) were taken as a measure of FP.Design/methodology/approachSecondary data were collected from 19 commercial banks (10 commercial banks from Pakistan and 9 commercial banks from India) in the country for a period of 10 years from 2009 to 2018. The generalized method of moment (GMM) is used for the coefficient estimation to overcome the effects of some endogenous variables.FindingsThe results indicated that NPLs, CER and LR have significantly negatively related to FP (ROA and ROE), while CAR and ALR have significantly positively related to the FP of the Asian commercial banks.Practical implicationsThe current study result recommends that policymakers of Asian countries should create a strong financial environment by implementing that monetary policy that stimulates interest rates in this way that automatically helps to lower down the high ratio of NPLs (tied monitoring system). Liquidity position should be well maintained so that even in a high competition environment, the commercial is able to survive in that environment.Originality/valueThe present paper contributes to the prevailing literature that this is a comparison study between developed and developing countries of Asia that is a unique comparison because the study targets only one region and then on the basis of income, the results of this study are compared. Moreover, the contribution of the study is to include some accounting-based measures and market-based measures of the FP of commercial banks at a time.

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Determinants of Liquidity Considering Role of Market Competition; Evidence from Pakistan’s Banking Sector

Sustainable Business and Society in Emerging Economies ◽

10.26710/sbsee.v2i2.1617 ◽

2020 ◽

Vol 2 (2) ◽

pp. 51-59

Author(s):

Amir Rafique ◽

Muhammad Adeel ◽

Kalsoom Akhtar ◽

Muhammad Amir Alvi

Keyword(s):

Credit Risk ◽

Banking Sector ◽

Panel Data Analysis ◽

Market Competition ◽

Data Set ◽

Macroeconomic Factors ◽

Negative Effect ◽

Specific Factors ◽

Bank Specific Factors

Current study empirically analyzes bank specific factors and macroeconomic factors that determine the liquidity reserves of banks functioning in Pakistan. To highlight the association, current study performed random effects estimates on a data set of 20 banks from 2006 to 2016. Bank specific factors include bank size, capital and credit Risk. GDP and Inflation are the macroeconomic factors that were considered. Market competition has been measured through HHI. Based on panel data analysis, current study suggests that bank specific factors (except capital), macroeconomic factors and market competition significantly affect liquidity reserves of banks in Pakistan. These factors include bank size, credit risk, market competition, GDP and inflation. In addition, bank size, credit risk, GDP and Inflation revealed a negative effect on bank liquidity. On the other hand, market competition revealed a positive effect on bank liquidity. Capital showed an insignificant effect on bank liquidity.

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Determinants of Non-performing Loans

International Journal of Finance & Banking Studies (2147-4486) ◽

10.20525/ijfbs.v6i1.617 ◽

2019 ◽

Vol 6 (1) ◽

pp. 51-68

Author(s):

Muhammad Waqas ◽

Nudrat Fatima ◽

Aryan Khan ◽

Muhammad Arif

Keyword(s):

Credit Risk ◽

Method Of Moment ◽

Macroeconomic Factors ◽

Explanatory Variables ◽

Financial Firms ◽

Factors Influencing ◽

Specific Factors ◽

The Difference ◽

Risk Determinants ◽

Bank Specific Factors

The aim of the empirical study is to investigate credit risk determinants in banking sectors across three kinds of South Asian economies. An accumulated sample of 105 unbalanced panel data of financial firms over the period of 2000-2015, by applying General Method of Moment (GMM) estimation techniques one-step at the difference in order to identify factors influencing credit risk. This study is inspired by two broad categories of explanatory variables which are bank-specific and macroeconomic. Bank-specific factors influencing unsystematic risk, while macroeconomic factors promoting systematic risk. The study uses a proxy of non-performing loans for credit risk in banking sectors of Pakistan, India, and Bangladesh. The empirical results have been found aligned with theoretical arguments and literature as expected. In comparison, NPLs in Pakistan is greater than India and Bangladesh, while India has the lowest ratio of non-performing loans. The study documents that bank-specific factors (inefficiency, profitability, capital ratio and leverage) have a significant contribution towards credit risk. Further, the study also finds a significant impact of macroeconomic variables on non-performing loans. While, the result in the case of Bangladesh predicts contradictions that have no significant effect on non-performing loans at various levels. The overall results indicate that credit risk is not influenced by only external factors but also affect by internal factors like bad management and skimping etc.

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An empirical analysis of bank specific factors affecting interest rate of Ugandan banking financial institutions

World Journal of Entrepreneurship Management and Sustainable Development ◽

10.1108/wjemsd-07-2017-0046 ◽

2018 ◽

Vol 14 (2) ◽

pp. 153-167

Author(s):

Sulait Tumwine ◽

Samuel Sejjaaka ◽

Edward Bbaale ◽

Nixon Kamukama

Keyword(s):

Interest Rate ◽

Credit Risk ◽

Financial Institutions ◽

Operational Efficiency ◽

African Region ◽

Regression Estimate ◽

Data Set ◽

Content Type ◽

Specific Factors ◽

Bank Specific Factors

Purpose The purpose of this paper is to investigate the effect of bank specific factors on interest rate in banking financial institutions (BFIs) of Uganda. Design/methodology/approach To analyze the effect, an OLS random effects regression estimate on a data set of 24 banks from 2008 to 2016 from Bank of Uganda Depository Corporation survey was carried out. Studied bank specific factors including liquidity, operational efficiency, credit risk, capitalization and lending ratio are considered. Findings The results indicate that liquidity, operational efficiency, capitalization and lending out ratio affect the interest rate while credit risk does not. Research limitations/implications The study has confirmed that bank specific factors influence interest rate and other factors such as industry-level and indirect macroeconomic indicators need to be explored. The differences in categories of banks on interest rate would be of importance. Finally, this study concentrated on banks in Uganda, future study would focus on the comparison of Ugandan banks with those of other countries in the East African Region. Practical implications Bank managers should invest in up-to-date technology to reduce operational costs and improve efficiency. Managers of bank should take interest on equity mobilization, because it constitutes a cheaper source of capital to finance asset used in operations and long-term needs of borrowers financing. Government should consider a legislation that provides incentives toward savings and reduction in tax for bank inputs. Originality/value This is the first study that investigates the effect of bank specific factors on interest rate in Uganda’s BFIs.

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Modelling Macroeconomic and Bank-Specific Determinants of Credit Risk in the Nigerian Banking Sector: Evidence from Bounds Test Approach to Co-Integration

European Scientific Journal ESJ ◽

10.19044/esj.2021.v17n32p221 ◽

2021 ◽

Vol 17 (32) ◽

pp. 221

Author(s):

Stanley C. Duruibe ◽

Nathaniel C. Nwezeaku ◽

Aghalugbulam B.C. Akujuobi ◽

Sampson Ikenna Ogoke ◽

Chidinma Elizabeth Nwabeke

Keyword(s):

Credit Risk ◽

Banking Sector ◽

Negative Relationship ◽

Long Run ◽

Gdp Growth Rate ◽

Short Run ◽

Specific Factors ◽

Bounds Test ◽

Nigerian Banking ◽

Bank Specific Factors

Credit risk, represented in this study by the ratio of non-performing loans to total loan (NPL), is considered as one of the critical factors that causes bank distress and failure. This study examines the macroeconomic and bankspecific determinants of credit risk in the Nigerian Banking sector from the period 1998Q1 to 2018Q4 using the bounds test approach to co-integration. Literature survey in this subject area using Google Scholar resources reveals that there seems to be a consensus of findings in terms of the negative relationship between credit risk and Gross Domestic Product (GDP) growth rate, while other macroeconomic and bank-specific factors tend to have a random pattern relationship with credit risk attributable to various countries’ economic peculiarities. This study shows that GDP growth rate, return on asset, return on equity, interest rate, unemployment rate, and real exchange rate have a negative relationship with NPL. On the other hand, inflation rate, loan deposit ratio, and ratio of bank capital to asset have positive relationship with NPL. The relationships between the three variables and NPL were found to be individually insignificant to explain credit risk trends in the long run. Moreover, the Wald short-run causality test reveals that the macroeconomic and bank specific indicators jointly influence credit risk in the Nigeria banking sector in the short run. This study, however, recommends that since the macroeconomic and bank specific factors were found to be individually insignificant to explain credit risk trend in the long run, consideration should be accorded to some psychological, political, and socioeconomic factors such as the borrower’s attitude, business climate, social dislocations and distortions, availability of good infrastructural facilities, and the direction of government policies. These factors can affect borrowers’ ability to honor their debt obligations and, thus, determine the level of credit risk in the Nigerian economy.

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