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

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschung

Standard

A panel cointegration rank test with structural breaks and cross-sectional dependence. / Arsova, Antonia; Karaman Örsal, Deniz Dilan.
Jahrestagung des Vereins für Socialpolitik 2016: Demographischer Wandel : Session: Time Series Econometrics, No. D01-V3. ZBW - Leibniz Informationszentrum Wirtschaft, 2016.

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschung

Harvard

Arsova, A & Karaman Örsal, DD 2016, A panel cointegration rank test with structural breaks and cross-sectional dependence. in Jahrestagung des Vereins für Socialpolitik 2016: Demographischer Wandel : Session: Time Series Econometrics, No. D01-V3. ZBW - Leibniz Informationszentrum Wirtschaft, Jahrestagung des Vereins für Socialpolitik - VfS 2016
, Augsburg, Deutschland, 04.09.16. <http://hdl.handle.net/10419/145822>

APA

Arsova, A., & Karaman Örsal, D. D. (2016). A panel cointegration rank test with structural breaks and cross-sectional dependence. In Jahrestagung des Vereins für Socialpolitik 2016: Demographischer Wandel : Session: Time Series Econometrics, No. D01-V3 ZBW - Leibniz Informationszentrum Wirtschaft. http://hdl.handle.net/10419/145822

Vancouver

Arsova A, Karaman Örsal DD. A panel cointegration rank test with structural breaks and cross-sectional dependence. in Jahrestagung des Vereins für Socialpolitik 2016: Demographischer Wandel : Session: Time Series Econometrics, No. D01-V3. ZBW - Leibniz Informationszentrum Wirtschaft. 2016

Bibtex

@inbook{710418fed6f64861ab283b1204adcbf9,
title = "A panel cointegration rank test with structural breaks and cross-sectional dependence",
abstract = "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.",
keywords = "Economics",
author = "Antonia Arsova and {Karaman {\"O}rsal}, {Deniz Dilan}",
year = "2016",
month = aug,
language = "English",
booktitle = "Jahrestagung des Vereins f{\"u}r Socialpolitik 2016: Demographischer Wandel",
publisher = "ZBW - Leibniz Informationszentrum Wirtschaft",
address = "Germany",
note = "Jahrestagung des Vereins f{\"u}r Socialpolitik - VfS 2016<br/> ; Conference date: 04-09-2016 Through 07-09-2016",
url = "https://www.socialpolitik.de/De/jahrestagung-2016, https://www.socialpolitik.de/De/jahrestagung-2016",

}

RIS

TY - CHAP

T1 - A panel cointegration rank test with structural breaks and cross-sectional dependence

AU - Arsova, Antonia

AU - Karaman Örsal, Deniz Dilan

PY - 2016/8

Y1 - 2016/8

N2 - 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.

AB - 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.

KW - Economics

UR - https://www.econstor.eu/escollectionhome/10419/145457/simple-search?location=10419/145457&query=&sort_by=dc.title_sort&order=ASC&filter_field_1=vfsseries&filter_type_1=equals&filter_value_1=D01#items

M3 - Article in conference proceedings

BT - Jahrestagung des Vereins für Socialpolitik 2016: Demographischer Wandel

PB - ZBW - Leibniz Informationszentrum Wirtschaft

T2 - Jahrestagung des Vereins für Socialpolitik - VfS 2016<br/>

Y2 - 4 September 2016 through 7 September 2016

ER -

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