Description/Abstract
This paper studies testing of shifts in a time trend panel data model with serially correlated error component disturbances, without any prior knowledge of whether the error term is stationary or nonstationary. This is done in case the shift is known as well as unknown. Following Vogelsang (1997) in the time series literature, we propose a Wald type test statistic that uses a fixed effects feasible generalized least squares (FE-FGLS) estimator derived in Baltagi, et al. (2014). The proposed test has a Chi-square limiting distribution and is valid for both I (0) and I (1) errors. The finite sample size and power of this Wald test is investigated using Monte Carlo simulations.
Document Type
Working Paper
Date
Winter 2-2019
Keywords
Non-Stationary Panels, Time Trends, Serial Correlation, Wald Type Tests
Language
English
Series
Working Papers Series
Disciplines
Economic Policy | Economics | Public Affairs, Public Policy and Public Administration
ISSN
1525-3066
Recommended Citation
Baltagi, Badi; Kao, Chihwa; and Liu, Long, "Testing for Shifts in a Time Trend Panel Data Model with Serially Correlated Error Component Disturbances" (2019). Center for Policy Research. 245.
https://surface.syr.edu/cpr/245
Source
Local input
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Additional Information
Working paper no. 213