Stationarity tests in heterogeneous panels

Several stationarity tests in heterogeneous panel data models are proposed in this chapter. By allowing maximum degree of heterogeneity in the panel, two different ways of pooling information from independent tests, the group mean and the Fisher tests, are used to develop the panel stationarity tests. We consider the case of serially correlated errors in the level and trend stationary models. The small sample performances of the tests are investigated via Monte Carlo simulations. The simulation experiments reveal good small sample performances. In the presence of serial correlation, either the group mean or the Fisher tests based on individual KPSS tests with l2 and LMC tests with p = 1 are recommended for use in empirical work due to their good small sample performances.

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Year of publication:	2001
Authors:	Yin, Yong ; Wu, Shaowen
Published in:	Nonstationary panels, panel cointegration, and dynamic panels. - Bingley, U.K : Emerald, ISBN 978-1-84950-065-4. - 2001, p. 275-296
Subject:	Panel \| Panel study \| Theorie \| Theory \| Statistischer Test \| Statistical test \| Monte-Carlo-Simulation \| Monte Carlo simulation \| Einheitswurzeltest \| Unit root test \| Stochastischer Prozess \| Stochastic process \| Zeitreihenanalyse \| Time series analysis

Type of publication:	Article
Language:	English
Other identifiers:	10.1016/S0731-9053(00)15010-8 [DOI]
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10015390071