Interindustry dividend policy determinants in the context of an emerging market

Abstract

This article examines the determinants of the dividend policies of public listed firms in Malaysia for the period 2005 to 2009. A panel regression estimation model is used to identify the determinants of dividend policy within Malaysian firms. These determinants are then examined across eight different industries – Technology, Industrial, Consumer Noncyclical, Basic Material, Communication, Consumer Cyclical, Diversified and Energy – to investigate possible divergences in the determinants of dividend payouts in the context of an emerging market. Empirical findings show that firm size, leverage position, and profitability are significantly and inversely related to the dividend policy of firms in Malaysia. However, the industry-specific determinants of dividend policy display a number of variances that could plausibly be used as an indication of the selection of stocks in specific industries by potential investors. The results indicate that agency cost is positively related to dividend policy for the Basic Material industry. In addition, size and leverage play an important role in determining dividend payout for firms in the Technology and Consumer Noncyclical industries. For the Industrial sector, the size and profitability significantly affect the dividend policy of firms. However, the results failed to display any significant results for the Energy and Consumer Cyclical industries.

Keywords:

• Dividend policy
• emerging market
• Malaysia
• interindustry

JEL Classifications:

• C12
• G30
• G35
• L20

Acknowledgement

This work was supported by the University of Malaya Research Grant (UMRG) particularly the Equitable Society Research Cluster under grant no. RP015D-13SBS.

Notes

1. See for example, De Santis (1997) on the topic of stock market volatility; Hull and McGroarty (2014) on the issue of stock market efficiency; Felman et al. (2014) focusing on capital market structures; and Mendoza and Smith (2014) on the area of contagion effects of global financial shocks.

2. For example, in the context of China (Zhao, 2014); and in the context of Pakistan (Batool & Javid, 2014).

3. For example, in the context of Thailand (Fairchild, Guney, & Thanatawee, 2014).

4. See, for example, Jensen et al. (1992), Agrawal and Jayaraman (1994), Faccio, Lang, & Young (2001), and Gugler and Yurtoglu (2003).

5. See, for example, Batool and Javid (2014), Zhao (2014), and Arko, Abor, Adjasi, and Amidu (2014).