Description/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. We 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.
Document Type
Working Paper
Date
Summer 7-2014
Keywords
Panel Data, Generalized Least Squares, Time Trend Model, Fixed Effects, First Difference, and Nonstationarity
Language
English
Series
Working Papers Series
Disciplines
Analysis | Econometrics | Economics | Mathematics
Recommended Citation
Kao, Chihwa; Baltagi, Badi H.; and Liu, Long, "Test of Hypotheses in a Time Trend Panel Data Model with Serially Correlated Error Component Disturbances" (2014). Center for Policy Research. 202.
https://surface.syr.edu/cpr/202
Accessible PDF version
Source
Local input
Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.
Additional Information
Working paper no. 170
Authors dedicate this paper in honor of Peter C.B. Phillips' many contributions to econometrics and in particular non-stationary time series analysis and panel data. They would like to thank an anonymous referee and the editor Tom Fomby for their helpful suggestions.