Test of hypotheses in panel data models when the regressor and disturbances are possibly non-stationary

Badi H. Baltagi, Chihwa Kao, Sanggon Na

Research output: Contribution to journalArticle

7 Scopus citations

Abstract

This paper considers the problem of hypothesis testing in a simple panel data regression model with random individual effects and serially correlated disturbances. Following Baltagi et al. (Econom. J. 11:554-572, 2008), we allow for the possibility of non-stationarity in the regressor and/or the disturbance term. While Baltagi et al. (Econom. J. 11:554-572, 2008) focus on the asymptotic properties and distributions of the standard panel data estimators, this paper focuses on testing 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 (J. Econom. 151:56-69, 2009) to make an inference in the 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.

Original languageEnglish (US)
Pages (from-to)329-350
Number of pages22
JournalAStA Advances in Statistical Analysis
Volume95
Issue number4
DOIs
StatePublished - Dec 2011

ASJC Scopus subject areas

  • Analysis
  • Statistics and Probability
  • Modeling and Simulation
  • Social Sciences (miscellaneous)
  • Economics and Econometrics
  • Applied Mathematics

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