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Open AccessArticle

Threshold Regression with Endogeneity for Short Panels

1
Research School of Economics, The Australian National University, Acton, ACT 2601, Australia
2
CREATES and Department of Economics and Business Economics, Aarhus University, Fuglesangs Allé 4, DK-8210 Aarhus V, Denmark
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Authors to whom correspondence should be addressed.
Econometrics 2019, 7(2), 23; https://doi.org/10.3390/econometrics7020023
Received: 23 March 2019 / Revised: 8 May 2019 / Accepted: 16 May 2019 / Published: 22 May 2019
This paper considers the estimation of dynamic threshold regression models with fixed effects using short panel data. We examine a two-step method, where the threshold parameter is estimated nonparametrically at the N-rate and the remaining parameters are estimated by GMM at the N -rate. We provide simulation results that illustrate advantages of the new method in comparison with pure GMM estimation. The simulations also highlight the importance of the choice of instruments in GMM estimation. View Full-Text
Keywords: threshold regression; dynamic models; endogeneity; panel data; GMM estimation; integrated difference kernel IDK estimator; superconsistency threshold regression; dynamic models; endogeneity; panel data; GMM estimation; integrated difference kernel IDK estimator; superconsistency
MDPI and ACS Style

Gørgens, T.; Würtz, A.H. Threshold Regression with Endogeneity for Short Panels. Econometrics 2019, 7, 23.

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