Intersection tests for the cointegrating rank in dependent panel data
Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet
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in: Communications in Statistics - Simulation and Computation, Jahrgang 49, Nr. 4, 02.04.2020, S. 918-941.
Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet
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TY - JOUR
T1 - Intersection tests for the cointegrating rank in dependent panel data
AU - Arsova, Antonia
AU - Karaman Örsal, Deniz Dilan
N1 - Financial support by the German Research Foundation (DFG) through the project KA-3145/1-1 is gratefully acknowledged. The data for the empirical analysis was in part collected during a research stay of the second author at the Humboldt Universität in Berlin. The first author would like to thank Plamen Trayanov for helpful discussions. The authors are also grateful to two anonymous referees for their constructive comments and suggestions.
PY - 2020/4/2
Y1 - 2020/4/2
N2 - This paper takes a multiple testing perspective on the problem of determining the cointegrating rank in macroeconometric panel data with cross-sectional dependence. The testing procedure for a common rank among the panel units is based on Simes’ (1986) intersection test and requires only the p-values of suitable individual test statistics. A Monte Carlo study demonstrates that these simple tests are robust to cross-sectional dependence and have reasonable size and power properties. A multivariate version of Kendall’s tau is used to test an important assumption underlying Simes’ procedure for dependent statistics. The proposed method is illustrated by an empirical application.
AB - This paper takes a multiple testing perspective on the problem of determining the cointegrating rank in macroeconometric panel data with cross-sectional dependence. The testing procedure for a common rank among the panel units is based on Simes’ (1986) intersection test and requires only the p-values of suitable individual test statistics. A Monte Carlo study demonstrates that these simple tests are robust to cross-sectional dependence and have reasonable size and power properties. A multivariate version of Kendall’s tau is used to test an important assumption underlying Simes’ procedure for dependent statistics. The proposed method is illustrated by an empirical application.
KW - Economics
KW - common factors
KW - cross-sectional dependence
KW - Likehood-ratio
KW - Multiple testing
KW - Panel cointegration rank test
KW - Economics, empirical/statistics
UR - http://www.scopus.com/inward/record.url?scp=85082669847&partnerID=8YFLogxK
U2 - 10.1080/03610918.2018.1489552
DO - 10.1080/03610918.2018.1489552
M3 - Journal articles
VL - 49
SP - 918
EP - 941
JO - Communications in Statistics - Simulation and Computation
JF - Communications in Statistics - Simulation and Computation
SN - 0361-0918
IS - 4
ER -