Breaks in persistence in fixed-T panel data

Joakim Westerlund; Marcus Nordström

doi:10.1016/j.econlet.2021.109958

Breaks in persistence in fixed-T panel data

Joakim Westerlund, Marcus Nordström

Department of Economics

Deakin University

Research output: Contribution to journal › Article › peer-review

Abstract

This paper considers an autoregressive panel data model in which the autoregressive coefficient has undergone a structural break. The object of interest is the unknown breakpoint. A least squares-based estimator is proposed that is shown to be consistent when only the number of cross-section units, N, is large and the number of time periods, T, is small, thereby enabling quick detection of the onset of a new regime.

Original language	English
Article number	109958
Journal	Economics Letters
Volume	205
DOIs	https://doi.org/10.1016/j.econlet.2021.109958
Publication status	Published - 2021 Aug 1

Bibliographical note

Funding Information:
Westerlund would like to thank the Knut and Alice Wallenberg Foundation, Sweden for financial support through a Wallenberg Academy Fellowship.

Subject classification (UKÄ)

Economics
Probability Theory and Statistics

Free keywords

Break in persistence
Explosive and unit root behaviors
Panel data

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10.1016/j.econlet.2021.109958Licence: CC BY

Cite this

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title = "Breaks in persistence in fixed-T panel data",

abstract = "This paper considers an autoregressive panel data model in which the autoregressive coefficient has undergone a structural break. The object of interest is the unknown breakpoint. A least squares-based estimator is proposed that is shown to be consistent when only the number of cross-section units, N, is large and the number of time periods, T, is small, thereby enabling quick detection of the onset of a new regime.",

keywords = "Break in persistence, Explosive and unit root behaviors, Panel data",

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N2 - This paper considers an autoregressive panel data model in which the autoregressive coefficient has undergone a structural break. The object of interest is the unknown breakpoint. A least squares-based estimator is proposed that is shown to be consistent when only the number of cross-section units, N, is large and the number of time periods, T, is small, thereby enabling quick detection of the onset of a new regime.

AB - This paper considers an autoregressive panel data model in which the autoregressive coefficient has undergone a structural break. The object of interest is the unknown breakpoint. A least squares-based estimator is proposed that is shown to be consistent when only the number of cross-section units, N, is large and the number of time periods, T, is small, thereby enabling quick detection of the onset of a new regime.

KW - Break in persistence

KW - Explosive and unit root behaviors

KW - Panel data

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ER -

Breaks in persistence in fixed-T panel data

Abstract

Bibliographical note

Subject classification (UKÄ)

Free keywords

Access to Document

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Cite this