Title: Determinants of bank profitability in India: applications of count data models

Authors: Muhammadriyaj Faniband

Addresses: Department of Commerce, CHRIST (Deemed to be University), Bengaluru – 560029, India

Abstract: This paper employs count data models, namely Poisson and negative binomial regression to investigate whether macroeconomic factors increase or decrease the count of number of 18 Indian public sector banks in losses. The analysis is based on quarterly data from Q3 2009 to Q4 2019. This paper also considers one and two lagged macroeconomic factors. The results provide a new perspective for understanding the determinants of bank profitability. The contemporary, one and two lagged gross domestic product (GDP) growth rate and inflation increase the count of number of banks in losses. Further, the count of number of banks in losses surges with increase in contemporary and one lagged index of industrial production (IIP). However, one and two lagged exchange rates are significant to shrink the count of number of banks in losses. This study enables banks and policy makers to deliberate on the macroeconomic determinants considered for this study.

Keywords: macroeconomic factors; GDPs; gross domestic products; inflation; IIP; index of industrial production; exchange rates; bank profitability; count data models; Poisson regression; negative binomial regression; India.

DOI: 10.1504/IJMEF.2020.10030106

International Journal of Monetary Economics and Finance, 2020 Vol.13 No.6, pp.531 - 544

Received: 28 Mar 2020
Accepted: 01 May 2020

Published online: 23 Dec 2020 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article