Testing for panel cointegration using common correlated effects estimators

Anindya Banerjee; Josep Carrion-i-Sivestre

doi:10.1111/jtsa.12234

Testing for panel cointegration using common correlated effects estimators

Anindya Banerjee, Josep Carrion-i-Sivestre

Economics

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Abstract

Spurious regression analysis in panel data when the time series are cross-section dependent is analyzed in the paper. We show that consistent estimation of the long-run average parameter is possible once we control for cross-section dependence using cross-section averages in the spirit of the common correlated effects approach in Pesaran (2006). This result is used to design a panel cointegration test statistic accounting for cross-section dependence. The performance of the proposal is investigated in comparison with factor-based methods to control for cross-section dependence when strong, semi-weak and weak cross-section dependence may be present.

Original language	English
Pages (from-to)	610-636
Number of pages	27
Journal	Journal of Time Series Analysis
Volume	38
Issue number	4
Early online date	8 Mar 2017
DOIs	https://doi.org/10.1111/jtsa.12234
Publication status	Published - Jul 2017

Keywords

C12
C22
panel cointegration
cross-section dependence
common factors
spatial econometrics

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10.1111/jtsa.12234Licence: None: All rights reserved

Banerjee_&_Carrion_i_Sivestre_Testing_for_panel_cointegration_Journal_of_Time_Series_Analysis_2017
This is the peer reviewed version of the following article: Banerjee, A., and Carrion-i-Silvestre, J. L. (2017) Testing for Panel Cointegration Using Common Correlated Effects Estimators. J. Time Ser. Anal., 38: 610–636, which has been published in final form at http://dx.doi.org/10.1111/jtsa.12234. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving
Accepted author manuscript, 317 KBLicence: Other (please specify with Rights Statement)
Banerjee_&_Carrion_i_Sivestre_Testing_for_panel_cointegration_Journal_of_Time_Series_Analysis_2017_Additional_Documents
This document contains supplementary material connected with the following article: Banerjee, A., and Carrion-i-Silvestre, J. L. (2017) Testing for Panel Cointegration Using Common Correlated Effects Estimators. J. Time Ser. Anal., 38: 610–636, which has been published in final form at http://dx.doi.org/10.1111/jtsa.12234. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving
Accepted author manuscript, 153 KBLicence: Other (please specify with Rights Statement)

https://doi.org/10.1111/jtsa.12234Licence: None: All rights reserved

Cite this

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title = "Testing for panel cointegration using common correlated effects estimators",

abstract = "Spurious regression analysis in panel data when the time series are cross-section dependent is analyzed in the paper. We show that consistent estimation of the long-run average parameter is possible once we control for cross-section dependence using cross-section averages in the spirit of the common correlated effects approach in Pesaran (2006). This result is used to design a panel cointegration test statistic accounting for cross-section dependence. The performance of the proposal is investigated in comparison with factor-based methods to control for cross-section dependence when strong, semi-weak and weak cross-section dependence may be present.",

keywords = "C12, C22, panel cointegration , cross-section dependence , common factors , spatial econometrics",

author = "Anindya Banerjee and Josep Carrion-i-Sivestre",

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AB - Spurious regression analysis in panel data when the time series are cross-section dependent is analyzed in the paper. We show that consistent estimation of the long-run average parameter is possible once we control for cross-section dependence using cross-section averages in the spirit of the common correlated effects approach in Pesaran (2006). This result is used to design a panel cointegration test statistic accounting for cross-section dependence. The performance of the proposal is investigated in comparison with factor-based methods to control for cross-section dependence when strong, semi-weak and weak cross-section dependence may be present.

KW - C12

KW - C22

KW - panel cointegration

KW - cross-section dependence

KW - common factors

KW - spatial econometrics

U2 - 10.1111/jtsa.12234

DO - 10.1111/jtsa.12234

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VL - 38

SP - 610

EP - 636

JO - Journal of Time Series Analysis

JF - Journal of Time Series Analysis

IS - 4

ER -

Testing for panel cointegration using common correlated effects estimators

Abstract

Keywords

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