Panel Threshold Regression with Unobserved Individual-Specific Threshold Effects

Ping Yu, Shengjie Hong and Peter Phillips
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Ping Yu: University of Hong Kong
Shengjie Hong: Tsinghua University, China

No 2352, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

Abstract: This paper studies the estimation and inferences in panel threshold regression with unobserved individual-specific threshold effects which is important from the practical perspective and is a distinguishing feature from traditional linear panel data models. It is shown that the within-regime differencing in the static model or the within-regime first-differencing in the dynamic model cannot generate consistent estimators of the threshold, so the correlated random effects models are suggested to handle the endogeneity in such general panel threshold models. We provide a unified estimation and inference framework that is valid for both the static and dynamic models and regardless of whether the unobserved individual-specific threshold effects exist or not. Especially, we propose alternative inference methods for the model parameters, which have better theoretical properties than the existing methods. Simulation studies and an empirical application illustrate the usefulness of our new estimation and inference methodology in practice.

Pages: 59 pages
Date: 2022-10
New Economics Papers: this item is included in nep-ecm
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