ABSTRACT
Using a new approach, we estimate the speed of cash-holding adjustment for a typical transitional economy by using Chinese listed firms’ samples over 1999–2011. First, we use model-averaging techniques to identify reliably important cash-holding determinants. Second, we conduct Monte Carlo simulation using the real finance data to evaluate appropriateness of the empirical estimator from a variety of dynamic estimation methods and suggest an optimized system of generalized method of moments (OPT-GMM) as an appropriate econometric approach for speed estimation. Finally, we get the speed of 46 percent, which is significantly lower than the contemporary speed in the United Kingdom and the United States.
Notes
1. Speed assumption is a key issue in method selection according to the econometric theory. According to theory, if we could know the adjustment speed is fast in advance, it would be better to use FD-GMM estimator (Arellano and Bond Citation1991). If we could know the speed is slow in advance, SYS-GMM or LONG-DIF estimator would be a more suitable choice (Blundell and Bond Citation1998; Hahn, Hausman, and Kuersteiner Citation2007).
2. The basic idea arises from Flannery and Hankins (Citation2013) but has several improvements. First, we set up the predetermined parameter according to the determinant selection estimation of instead of a meaningless arbitrary set. Second, we introduce more dynamic panel methods than Flannery and Hankins (Citation2013), especially the OPT-GMM estimation.