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Intersection tests for the cointegrating rank in dependent panel data

Research output: Journal contributions › Journal articles › Research › peer-review

Standard

Intersection tests for the cointegrating rank in dependent panel data. / Arsova, Antonia; Karaman Örsal, Deniz Dilan.
In: Communications in Statistics - Simulation and Computation, Vol. 49, No. 4, 02.04.2020, p. 918-941.

Research output: Journal contributions › Journal articles › Research › peer-review

Harvard

Arsova, A & Karaman Örsal, DD 2020, 'Intersection tests for the cointegrating rank in dependent panel data', Communications in Statistics - Simulation and Computation, vol. 49, no. 4, pp. 918-941. https://doi.org/10.1080/03610918.2018.1489552

APA

Arsova, A., & Karaman Örsal, D. D. (2020). Intersection tests for the cointegrating rank in dependent panel data. Communications in Statistics - Simulation and Computation, 49(4), 918-941. https://doi.org/10.1080/03610918.2018.1489552

Vancouver

Arsova A, Karaman Örsal DD. Intersection tests for the cointegrating rank in dependent panel data. Communications in Statistics - Simulation and Computation. 2020 Apr 2;49(4):918-941. Epub 2019 Mar 11. doi: 10.1080/03610918.2018.1489552

Bibtex

@article{bf90cee2a1f4483889f10e8c531fe02d,
title = "Intersection tests for the cointegrating rank in dependent panel data",
abstract = "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{\textquoteright} (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{\textquoteright}s tau is used to test an important assumption underlying Simes{\textquoteright} procedure for dependent statistics. The proposed method is illustrated by an empirical application.",
keywords = "Economics, common factors, cross-sectional dependence, Likehood-ratio, Multiple testing, Panel cointegration rank test, Economics, empirical/statistics",
author = "Antonia Arsova and {Karaman {\"O}rsal}, {Deniz Dilan}",
note = "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 Universit{\"a}t 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.",
year = "2020",
month = apr,
day = "2",
doi = "10.1080/03610918.2018.1489552",
language = "English",
volume = "49",
pages = "918--941",
journal = "Communications in Statistics - Simulation and Computation",
issn = "0361-0918",
publisher = "Taylor and Francis Ltd.",
number = "4",

}

RIS

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 -

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Research output: Journal contributions › Journal articles › Research › peer-review

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Karaman Örsal, D. & Sturm, S., 2021, Hamburg: Universität Hamburg, 12 p. (Hamburg Discussion Papers in International Economics; no. 7).

Research output: Working paper › Working papers

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Karaman Örsal, D., 01.09.2021, Neuvermessung der Datenökonomie. Straubhaar, T. (ed.). Hamburg: Hamburg University Press, p. 157-173 17 p. (Edition HWWI; vol. 6).

Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Research

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Research output: Journal contributions › Journal articles › Research › peer-review

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Nguyen, H. T. & Karaman Örsal, D. D., 28.04.2020, In: Economics. 14, 1, p. 1-34 34 p., 2020-12.

Research output: Journal contributions › Journal articles › Research › peer-review

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