This paper investigates Gibrat's law by using a panel unit root test, as a panel unit root can increase power in contrast to a conventional individual ADF test. At first this paper uses the panel unit root test to testify Gibrat's law under independent and identical distribution, with the test results rejecting the null hypothesis of Gibrat's law. Independent and identical distributions are not reasonable in a real situation. Any firm in a given industry may have some correlation with other firms. Moreover, the limiting distribution of Im, Pesaran, and Shin (IPS) statistic is invalid and will produce a large distortion. This paper applies the Taylor and Sarno (1998) MADF test to deal with a cross-sectional correlation problem and study the issue. This paper finds that the conclusion is not the same.
This paper uses panel data of Taiwanese electronics firms to investigate the Granger causality relationship between R&D and productivity growth, while taking into account the effect of R&D spatial spillovers. Unlike previous studies, the R&D spatial spillover effect is calculated by a geographic formula of longitude and latitude. Before determining the direction of causality between the TFP growth and R&D effort, we execute the panel unit root test to examine the stationarity of the data. Results indicate that all variables in the model are stationary, and that R&D stock and R&D spatial spillovers Granger cause productivity growth.
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