Description/Abstract
This paper considers the problem of hypotheses testing in a simple panel data regression model with random individual effects and serially correlated disturbances. Following Baltagi, Kao and Liu (2008), we allow for the possibility of non-stationarity in the regressor and/or the disturbance term. While Baltagi et al. (2008) focus on the asymptotic properties and distributions of the standard panel data estimators, this paper focuses on test of hypotheses in this setting. One important finding is that unlike the time series case, one does not necessarily need to rely on the “super-efficient” type AR estimator by Perron and Yabu (2009) to make inference in panel data. In fact, we show that the simple t-ratio always converges to the standard normal distribution regardless of whether the disturbances and/or the regressor are stationary.
Document Type
Working Paper
Date
5-2011
Keywords
Panel Data, OLS, Fixed-Effects, First-Difference, GLS, t-ratio
Series
Working Papers Series
Disciplines
Economics
Recommended Citation
Baltagi, Badi H.; Kao, Chihwa; and Na, Sanggon, "Test of Hypotheses In Panel Data Models When The Regressor And Disturbances Are Possibly Nonstationary" (2011). Center for Policy Research. 163.
https://surface.syr.edu/cpr/163
Source
local input
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Additional Information
Working paper no. 128