Center for Policy Research
Working Paper
Test of Hypotheses in a Time Trend Panel Data Model with Serially Correlated Error Component Disturbances
Badi H. Baltagi, Chihwa Kao & Long Liu
C.P.R. Working Paper no.170
June 2014
Abstract
This paper studies test of hypotheses for the slope parameter in a linear time trend panel data model with serially correlated error component disturbances. The authors propose a test statistic that uses a bias corrected estimator of the serial correlation parameter. The proposed test statistic which is based on the corresponding fixed effects feasible generalized least squares (FE-FGLS) estimator of the slope parameter has the standard normal limiting distribution which is valid whether the remainder error is I(0) or I(1). This performs well in Monte Carlo experiments and is recommended.