Are tests of dividend policy robust to estimation techniques: The case of an emerging economy?
Husam-Aldin Nizar Al-Malkawi and
M. Ishaq Bhatti
Physica A: Statistical Mechanics and its Applications, 2020, vol. 541, issue C
In recent years, there is high tendency to use either simple or complicated models to conduct empirical studies on banking and finance data without due regards being given to the structure, suitability and the choice of econometrics models. In particular, there are numerous works that have emerged to examine dividend policy, which is considered one of the most controversial topics in corporate finance literature (), using inappropriate methodologies leading to false conclusions. This paper, therefore, attempts to address this issue by proposing appropriate and robust estimation methods; the Tobit model and the Generalized Method of Moment, to model banks’ dividend policy. It uses 160 firm-year observations of banks listed in an emerging market namely Karachi Stock Exchange. We find that modelling dividend policy is sensitive to the estimation techniques. Our results show that Pakistani banks neither smooth their dividends nor follow stable dividend policy, contrary to what has been reported in the previous literature that used OLS estimates. These findings provide new implications for investors and policy makers in such an emerging economy.
Keywords: Tobit estimation; Dynamic panel data; GMM; Dividend payout; Pakistani banks (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:541:y:2020:i:c:s0378437119318072
Access Statistics for this article
Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis
More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Haili He ().