Threshold Regression in Heterogeneous Panel Data with Interactive Fixed Effects

Fuente: arXiv
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Main Authors: Barassi, Marco, Karavias, Yiannis, Zhu, Chongxian
Format: Preprint
Published: 2023
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author Barassi, Marco
Karavias, Yiannis
Zhu, Chongxian
author_facet Barassi, Marco
Karavias, Yiannis
Zhu, Chongxian
contents This paper introduces unit-specific heterogeneity in panel data threshold regression. We develop the asymptotic theory for models with heterogeneous thresholds, heterogeneous slope coefficients, and interactive fixed effects. The estimation methodology employs the Common Correlated Effects approach, which is able to handle heterogeneous parameters while maintaining computational simplicity. We also propose a semi-homogeneous model with heterogeneous slopes but a common threshold, revealing novel mean group estimator convergence rates due to the interaction of heterogeneity with the shrinking threshold assumption. Tests for linearity are provided, as well as a modified information criterion which can select between the fully heterogeneous and semi-homogeneous models. Monte Carlo simulations demonstrate the good performance of the new methods in small samples. The new theory is used to examine the Feldstein-Horioka puzzle, showing that threshold nonlinearity with respect to trade openness occurs only in a small subset of countries.
format Preprint
id arxiv_https___arxiv_org_abs_2308_04057
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Threshold Regression in Heterogeneous Panel Data with Interactive Fixed Effects
Barassi, Marco
Karavias, Yiannis
Zhu, Chongxian
Econometrics
This paper introduces unit-specific heterogeneity in panel data threshold regression. We develop the asymptotic theory for models with heterogeneous thresholds, heterogeneous slope coefficients, and interactive fixed effects. The estimation methodology employs the Common Correlated Effects approach, which is able to handle heterogeneous parameters while maintaining computational simplicity. We also propose a semi-homogeneous model with heterogeneous slopes but a common threshold, revealing novel mean group estimator convergence rates due to the interaction of heterogeneity with the shrinking threshold assumption. Tests for linearity are provided, as well as a modified information criterion which can select between the fully heterogeneous and semi-homogeneous models. Monte Carlo simulations demonstrate the good performance of the new methods in small samples. The new theory is used to examine the Feldstein-Horioka puzzle, showing that threshold nonlinearity with respect to trade openness occurs only in a small subset of countries.
title Threshold Regression in Heterogeneous Panel Data with Interactive Fixed Effects
topic Econometrics
url https://arxiv.org/abs/2308.04057