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ENDOGENEITY IN SEMIPARAMETRIC THRESHOLD REGRESSION
Published online by Cambridge University Press: 27 May 2021
Abstract
This paper estimates threshold regression models with an endogenous threshold variable using a nonparametric control function approach. Assuming diminishing threshold effects, we derive the consistency and limiting distribution of our proposed estimator constructed from the series approximation method for weakly dependent data. In addition, we propose a test for the endogeneity of the threshold variable, which is valid regardless of whether the threshold effects exist. We assess the performance of our methods using Monte Carlo simulations.
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- © The Author(s), 2021. Published by Cambridge University Press
Footnotes
The first author acknowledges that this research has received funding from Marie Skłodowska-Curie Actions (Work Programme 2016-17) of the Excellence Science Pillar of the Horizon 2020 Research and Innovation Programme of the European Union under REA grant agreement No. 707990. The authors would like to thank the editor, the co-editor, and the four anonymous referees for their patience and excellent comments that significantly improved the manuscript.
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