Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/260335 
Erscheinungsjahr: 
2021
Schriftenreihe/Nr.: 
Working Paper No. 2021:15
Verlag: 
Lund University, School of Economics and Management, Department of Economics, Lund
Zusammenfassung: 
In this article, we propose a new estimator of panel data models with interactive fixed effects and multiple structural breaks that is suitable when the number of time periods, T, is fixed and only the number of cross-sectional units, N, is large. This is done by viewing the determination of the breaks as a shrinkage problem, and to estimate both the regression coefficients, and the number of breaks and their locations by applying a version of the Lasso approach. We show that with probability approaching one the approach can correctly determine the number of breaks and the dates of these breaks, and that the estimator of the regime-specific regression coefficients is consistent and asymptotically normal. We also provide Monte Carlo results suggesting that the approach performs very well in small samples, and empirical results suggesting that the coefficients of the deterrence model of crime are not constant as typically assumed but subject to structural change.
Schlagwörter: 
Panel data
Interactive effects
Common factors
Structural change
Lasso
JEL: 
C13
C23
C33
K42
Dokumentart: 
Working Paper

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