Bank Capital and Lending: An Analysis of Commercial Banks in the United States

Karmakar, Sudipto; Mok, Junghwan

doi:10.2139/ssrn.2366843

Cited by 3 publications

(6 citation statements)

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“…Prior studies also reveal that portfolio risk is one of the main drivers of subsequent lending behavior. Several evidences confirm that deterioration in portfolio quality impacts credit growth negatively (Berrospide and Edge, 2010; Karmakar and Mok, 2013; Cucinelli, 2016). In this respect, Berrospide and Edge (2010) found that out of the 2.9 percentage point decline in the quarterly loan growth rate from 2008:Q4 to 2009:Q3, of which the model explains 2.2 percentage points, 1.1 percentage points is explained by changes in net charge-offs rates, which captures the deterioration in loan quality.…”

Section: Literature Reviewmentioning

confidence: 97%

“…The existing literature shows different alternative lending behavior (LB) measures: The logarithm of loans (Olokoyo, 2011), loans to asset ratio (Karmakar and Mok, 2013; Hessou and Lai, 2018), changes in the natural logarithm of loans (Covas, 2016; Gambacorta and Shin, 2018) and growth rate of loans (Thibaut and Mathias, 2014; Cucinelli, 2016). The (natural) logarithm of loans is not appropriate as we employ a cross-country data with different currencies.…”

Section: Modeling Lending Behavior: An Application To Mfismentioning

confidence: 99%

“…The existing literature shows that several studies examined the drivers of lending behavior using empirical data from the banking industry in the United States (Berrospide and Edge, 2010; Karmakar and Mok, 2013), Italy (Cucinelli, 2016; Michelangeli and Sette, 2016), European Countries (Laidroo, 2012; Thibaut and Mathias, 2014), 90 countries worldwide (Igan and Pinheiro, 2011), the eleven G10 countries plus those of Austria, Australia, and Spain (Gambacorta and Shin, 2018) and Nigeria (Olokoyo, 2011). While the prior studies provide useful insights mainly on the effects of capitalization, portfolio risk and/or business cycle on loan supply in the banking industry, studies on the determinants of lending behavior in microfinance institutions are virtually missing.…”

Section: Introductionmentioning

confidence: 99%

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What drives microfinance institution lending behavior? Empirical evidence from Sub-Saharan Africa

Tehulu

2021

IJOEM

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PurposeWhile poverty alleviation is the first core goal of Sustainable Development Goals (SDGs), and microfinance institutions (MFIs) are considered important instruments for poverty alleviation in developing countries as they provide credit access to the poor, there is surprisingly little evidence of the drivers of the lending behavior of microfinance institutions. Hence, the purpose of this study is to identify the factors that influence the credit growth of MFIs in Sub-Saharan Africa (SSA).Design/methodology/approachThe study relies on unbalanced panel dataset of 130 MFIs operating across 31 countries in SSA during the period 2004–2014 constituting 546 useable observations. The study uses the Arellano-Bover/Blundell-Bond two-step generalized method of moments (GMM) Windmeijer bias-corrected standard errors to estimate the models.FindingsThe results confirm that while capitalization, liquidity and size are positively associated with credit growth, profitability negatively impacts credit growth; whereas, other MFI specific factors namely portfolio quality, deposit growth and nondeposit borrowing growth have little direct effects on MFI credit growth. The results also show that MFI credit growth is pro-cyclical but negatively related to GDP per capita consistent with the theory of convergence. On the other hand, inflation and employment are not important covariates in the credit growth of MFIs.Practical implicationsThe findings suggest that if MFIs improve their liquidity and size by attracting more deposits and nondeposit borrowings, among others, they can increase credit access to the poor. Moreover, since the lending behavior of MFIs is not resilient to GDP shocks, different measures are needed to increase the financial stability of the microfinance industry. In this respect, since MFI capitalization is positively associated with credit growth and MFI credit growth is pro-cyclical, the findings provide useful insights to central banks/regulatory authorities and the Basel Committee as to the need for a counter-cyclical capital buffer requirement in the microfinance industry.Originality/valueThe study is the first comprehensive study to examine the drivers of MFI lending behavior as an extension to lending behavior models from the banking industry.

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Section: Literature Reviewmentioning

confidence: 97%

Section: Modeling Lending Behavior: An Application To Mfismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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What drives microfinance institution lending behavior? Empirical evidence from Sub-Saharan Africa

Tehulu

2021

IJOEM

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“…The results indicated that the banks with low capital, high cost of capital and with tightened capital requirements has negative relation with lending opportunities of banks. Karmakar & Mok (2015) examined the relationship between bank capital and their lending behavior by taking the sample data of medium sized commercial banks of USA. Our findings concluded that there was a modest impact of banks capital on their lending behavior.…”

Section: Research Objectivesmentioning

confidence: 99%

“…But because of the financial instability during the global financial crises the Basel committee has established the Basel III accord in which all these ratios have been increased to control the financial instability and to improve the quality of banking supervision all over the world. Banks must have the enough capital to absorb the negative shocks of the economy (Karmakar & Mok 2015). All these ratios have the direct link with the lending behavior of the banks.…”

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confidence: 99%

Impact of Bank Capital and Monetary policy on Lending Behavior of USA Banking Sector Before and After Global Financial Crises

Kausar¹

2021

EParadigms

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This study investigates the impact of bank capital, capital structure and monetary policy on the lending behavior of USA banks before and after global financial crises. For this purpose, sample data is collected from the annual reports of top ten banks of USA from 2001 to 2017. A panel unit root is applied to check the stationarity of variables. In order to explain the impact of bank capital, capital structure and monetary policy on lending behavior of USA banks, fixed effect and random effect model have been used. The sample data has been divided into two sets. First data set is taken from 2001 to 2008 before financial crises. Second data set is taken from 2009 to 2017 after financial crises and all above tests have been applied on these data sets. Furthermore, in order to measure the lending behavior three types of lending have been selected lending to consumers, lending to real estate and lending to commercial & industrial sector of USA banks. In order to get the better picture of lending behavior of USA banks before and after financial crises: paired sample T-test has been applied on the data of lending before and after financial crises. Results of paired sample T-test showed there is significant difference in lending to consumers, lending to commercial & industrial sector and lending to real estate before and after financial crises of USA banks because of the implementation of Basel III. So, we accept the alternative hypothesis for our second research question. Findings suggested that impact of bank capital, capital structure and monetary policy has significant impact on the lending behavior before and after the global financial crises with the positive change of sixteen percent in R-squared value. So, we accept the alternative hypothesis for our first research question. The results of coefficients shows that before financial crises (2001 to 2008) discounted interest rates have more significant impact on the lending made to consumers but after the global financial crises (2009 to 2017) discounted interest rates, capital structure and tier 1 capital ratio have more significant impact on the loan made to consumers. The results of coefficients shows that before the financial crises (2001 to 2008) discounted interest rates have more significant impact on the loan made to commercial and industrial sector but after the global financial crises (2009 to 2017) discounted interest rates, capital structure and tier 1 capital ratio have more significant impact on the loan made to commercial and industrial sector. The results of coefficients shows that before financial crises (2001 to 2008) discounted interest rates have more significant impact on the loan made to real estate but after the global financial crises (2009 to 2017) discounted interest rates and capital structure have more significant impact on the loan made to real estate. Findings of our study are aligned with Swamy (2015), who investigated the impact of bank capital on lending spreads and found that increase in capital ratio of banks would also increase their lending spreads. Our results are also matched with the findings of (Kosak et al., 2015), those concluded that capital structure significantly affect the loan growth of banks. Our results are also aligned with Chami & Cosimano (2010), they found that change in monetary policy due to Basel Accord would lead to a change in bank capital and bank loans.

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Capital adjustment process and credit growth of microfinance institutions: Evidence from Sub-Saharan Africa

Tehulu

2022

Cogent Economics & Finance

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Bank Capital and Lending: An Analysis of Commercial Banks in the United States

Cited by 3 publications

References 13 publications

What drives microfinance institution lending behavior? Empirical evidence from Sub-Saharan Africa

What drives microfinance institution lending behavior? Empirical evidence from Sub-Saharan Africa

Impact of Bank Capital and Monetary policy on Lending Behavior of USA Banking Sector Before and After Global Financial Crises

Capital adjustment process and credit growth of microfinance institutions: Evidence from Sub-Saharan Africa

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