Management Today
  • Year: 2019
  • Volume: 9
  • Issue: 3

Determinants of Dividend Policy with Reference to Select Indian Companies: A Panel Data Regression Analysis

  • Author:
  • Rajbinder Kaur1, Arup Kumar Chattopadhyay2, Debdas Rakshit3
  • Total Page Count: 10
  • Page Number: 148 to 157

1Research Scholar, Department of Commerce, The University of Burdwan, Burdwan-713104, West Bengal, India, Email: itsrajk13@gmail.com

2Supervisor, Department of Economics, The University of Burdwan, Burdwan-713104, West Bengal, India, Email: arup.chatto@yahoo.co.in

3Supervisor, Department of Commerce, The University of Burdwan, Burdwan-713104, West Bengal, India, Email: debdas_rakshit@yahoo.co.in

Online published on 4 October, 2019.

Abstract

The purpose of this paper is to examine the determinants of dividend policy of 50 BSE listed companies selecting 5 sample companies from each of 10 Indian industries, namely, Cement, Computer Hardware, Large Heavy Engineering, Fertilizer, FMCG, Large Electric Equipment, Mining/Mineral, Textile, Large Tyres and Pharmaceutical for a time span of 15 years’ beginning from 1999–2000 to 2013–14 using panel data regression methodology. Firstly, we have conducted industry-wise empirical analysis of dividend policy with reference to five microeconomic determinants such as profitability, size, liquidity, investment opportunities and business risk. Next, we made a comparative analysis of determinants of dividend policy in order to decide the financial behaviour of dividend policy in the light of four dividend policy theories, namely, pecking order theory, signalling theory, agency cost theory and transaction cost theory. The regression results found little evidence in support of any specific theory or theories for explaining the dividend behaviour of select industries. In case of Cement, Large Heavy Engineering, Fertilizer, Large Electric Equipment, and Pharmaceutical industries all selected determinants are found to be insignificant in determining their dividend policy.

Keywords

Dividend policy, determinants, panel data, regression analysis