An Application of Partial Adjustment Equation in Determining Payout Behavior using an Extended Instrumental Variable Approach

This paper improves on earlier research on the determinants of Payout policies by using a more advanced empirical estimation, a larger Indian representative sample of panel data (PD) controlling for economic reform effect and by using alternate proxies for a longer time window 1971-2007. To deal with variables that may be correlated with the error term, often faced in static panel data analysis; the Instrumental Variable (IV) approach using dynamic panel data is followed. The IV estimation is widely used for models with random regressors (e.g. lagged dependent variable) which exhibit the correlation with model errors. We show that using IV has an additional advantage of solving problems encountered in static models, mainly addressing the simultaneity bias between the Payout measure and the explanatory variables, and the measurement error issue. Application of Generalized Methods of Moments (GMM) in econometric modelling can be considered as a further extension of IV estimation method, and attempted herein. We estimate the GMM-in-Levels {GMM (in-Lev)} (1991) model, and its other variations viz the GMM-in-first-differences {GMM (in-Diff)} (1995) and GMM-in-Systems {GMM (in-Sys)} (1997) so to include other lag structures. It is aimed to add to the relatively limited literature on aspects of Payout decision by examining the dynamics of relationship between cash payouts and a host of other explanatory variables. The implicit and explicit implications of the economic reform process on Payout policies are also explored. This robust procedure shows us how much the size of the Payout determinants, varies across the different estimation techniques