Diagnostic Tests of Cross‐section Independence for Limited Dependent Variable Panel Data Models*
研究了受限因变量面板数据模型中截面独立性的检验问题，推导了LM检验并比较了CD检验，蒙特卡洛实验表明CD检验更稳健，并应用于美国国会投票数据发现显著截面依赖。
Abstract This article considers the problem of testing for cross‐section independence in limited dependent variable panel data models. It derives a Lagrangian multiplier (LM) test and shows that in terms of generalized residuals of Gourieroux et al. (1987) it reduces to the LM test of Breusch and Pagan (1980) . Because of the tendency of the LM test to over‐reject in panels with large N (cross‐section dimension), we also consider the application of the cross‐section dependence test (CD) proposed by Pesaran (2004) . In Monte Carlo experiments it emerges that for most combinations of N and T the CD test is correctly sized, whereas the validity of the LM test requires T (time series dimension) to be quite large relative to N . We illustrate the cross‐sectional independence tests with an application to a probit panel data model of roll‐call votes in the US Congress and find that the votes display a significant degree of cross‐section dependence.