A panel cointegration rank test with structural breaks and cross-sectional dependence

Konferenzbeitrag

This paper proposes a new likelihood-based panel cointegration rank test which allows for a linear time trend with heterogeneous breaks and cross sectional dependence. It is based on a novel modification of the inverse normal method which combines the p-values of the individual likelihood-ratio trace statistics of Trenkler et al. (2007). We call this new test a correlation augmented inverse normal (CAIN) test. It infers the unknown correlation between the probits of the individual p-values from an estimate of the average absolute correlation between the VAR processes' innovations, which is readily observable in practice. A Monte Carlo study demonstrates that this simple test is robust to various degrees of cross-sectional dependence generated by common factors. It has better size and power properties than other meta-analytic tests in panels with dimensions typically encountered in macroeconometric analysis.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: Beiträge zur Jahrestagung des Vereins für Socialpolitik 2016: Demographischer Wandel - Session: Time Series Econometrics ; No. D01-V3

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Hypothesis Testing: General ; Statistical Simulation Methods: General ; Multiple or Simultaneous Equation Models: Panel Data Models; Spatio-temporal Models

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Karaman Örsal, Deniz Dilan ; Arsova, Antonia
• Ereignis: Veröffentlichung
• (wer): ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften, Leibniz-Informationszentrum Wirtschaft
• (wo): Kiel und Hamburg
• (wann): 2016

Weitere Informationen

• Handle: http://hdl.handle.net/10419/145822
• Letzte Aktualisierung: 20.09.2024, 08:22 MESZ