Search

Managers must repeatedly make important decisions regarding the composition of their firm’s capital structure, the amount of profit they should return to investors, and the form in which such payment, if any, should be delivered. The dynamic and reoccurring nature of such salient decisions mean that the financial policies of firms do not simply manifest themselves in arbitrary or random fashions but evolve to follow distinct dynamic patterns. Through the combination of one theoretical and two empirical chapters, this thesis evaluates the underlying mechanisms behind such dynamic trends by exploiting the uniqueness of India’s emerging market context. The first study of the thesis establishes the economic impact of estimator choice on the implied speed of financial policy adjustment. The chapter utilises Monte Carlo experiments to present an extensive appraisal of the dynamic panel estimators commonly employed in the corporate finance literature. The chapter finds the least squares dummy variable corrected estimator of Kiviet (1995) and the quasi-maximum likelihood fixed-effect estimator of Hsiao et al. (2002) to be the most robust estimators across a range of experiments. In contrast, the chapter unearths that the popular generalized method of moments estimators are highly sensitive to changes in dynamic persistence, cross-sectional heterogeneity and panel unbalancedness and are therefore prone to yielding spurious estimates of financial policy adjustment. The second study investigates, empirically, how Indian listed firms facing alternative adjustment costs transition towards their capital structure target over the course of the business cycle. Accordingly, by bringing together both cross-sectional and time-series elements of autoregressive heterogeneity, the chapter finds the adjustment speeds of Indian firms to be largely pro-cyclical. Furthermore, the chapter uncovers that firms with the highest earnings and the greatest investment opportunities adjust significantly quicker in both periods of macroeconomic growth and macroeconomic decline relative to their financially constrained counterparts. The final study of this thesis investigates if the dividend decisions of Indian listed firms are influenced by the actions and characteristics of their industry peers. The chapter adopts a Spatial-Durbin style modelling approach to show that the dividend decisions made by local industry peers bear the greatest economic influence on the dividend decisions made by Indian listed firms. The chapter finds that the informational content embedded within peer dividend decisions is economically more important for dividend increases and dividend decreases than any other firm or industry related characteristics. Moreover, the chapter illustrates that the tangible decisions of peers are most economically meaningful in periods of heighten macroeconomic uncertainty, when the opaqueness of firms own information is likely to be most severe. Accordingly, the evidence of proximity related peer effects put forward in our final study presents a clear criticism of the extant literature that has predominately focused on the role of firm-specific factors on corporate payout decisions.