Effect of Bank Specific And Macroeconomic Determinants on Capital Adequacy Ratio A Study on Ethiopian Private Commercial Banks

ADDISALEM TADESSE BOGALE

Abstract


Capital adequacy implies the conventional assessment of the minimal level of capital, according to certain parameters, which reflect the dimension of banking activity and of related risks, capable to provide a correlation between the supposed obtained benefits and potential loss caused by a certain risk level. Since Capital adequacy ratio (CAR) is the ratio that is set by the regulatory authority in the banking sector, and this ratio can be used to test the health of the banking system. Thus, this study examines the effect of bank specific (Bank Size ,Deposit to Asset Ratio, Loan to Asset Ratio, Loan to Deposit Ratio, Return on Asset, Return on Equity ,Loan Loss Provision)  and macroeconomic determinants (Gross Domestic Product and Inflation) on capital adequacy ratio of Ethiopian Private Commercial Banks. In order to investigate these issues a quantitative method research approach is utilized, by using documentary analysis. More specifically, the study uses five years (2016 – 2020) data for fourteen private commercial banks in Ethiopia. The study used multiple linear regression models to determine the relative importance of each independent variable using OLS to estimate the relationship between CAR its determinants by STATA 13 econometric software. The findings show that bank size, return on equity ,loan to asset ratio affect capital adequacy ratio negatively whereas return on asset ,loan  loss provision  affect capital adequacy ratio positively   .Hence , it is recommended that to be sure that to be sure that bank have adequate adequacy reserve ,commercial bank and national bank of Ethiopia should give attention to the risk associated with bank size ,caring  bank loan and deposit initiating to increase their return on their return on their asset and to manage their equity return.

Keywords: Capital adequacy ratio, Ethiopian Private Commercial Banks, Panel data analysis

DOI: 10.7176/RJFA/11-21-01

Publication date: November 30th 2020


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ISSN (Paper)2222-1697 ISSN (Online)2222-2847

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