A1189
Title: Testing for second-order cross-sectional dependence and serial dependence in large dynamic panel models
Authors: Zihao Pu - The University of Hong Kong (China) [presenting]
Bing Su - The University of Hong Kong (China)
Ke Zhu - University of Hong Kong (Hong Kong)
Abstract: Testing for cross-sectional dependence (CD) and serial dependence (SD) is important for large dynamic panel models. By detecting the zero cross-sectional and serial covariances of model disturbances, existing first-order tests lack the power to detect second-order CD and SD structures in the variance of model disturbances, which have been commonly documented in many empirical studies. To address this gap, new portmanteau CD and SD tests are proposed to examine the zero values of cross-sectional and serial covariances of squared model disturbances, up to a given lag K, for large homogeneous and heterogeneous dynamic panel models. Additionally, new automatic portmanteau CD and SD tests are introduced that select lag K in a data-driven way. When both cross-sectional and serial dimensions diverge jointly at the same rate, all proposed tests have tractable limiting null distributions of chi-square, but with a calibration about the asymptotic bias for the SD-type tests. To improve size performance when either the cross-sectional or serial dimension is not large, bootstrap procedures are developed to obtain critical values for all proposed tests and their validity is justified. Finally, the usefulness of the proposed tests is illustrated by simulations and two real examples.
