Structural Threshold Regression
This paper extends the simple threshold regression framework of Hansen (2000) and Caner and Hansen (2004) to allow for endogeneity of the threshold variable. We develop a concentrated least squares estimator of the threshold parameter based on an inverse Mills ratio bias correction. We show that our estimator is consistent and investigate its performance using a Monte Carlo simulation that indicates the applicability of the method in nite samples Classification-JEL: C13, C51
|Date of creation:||Jan 2009|
|Date of revision:||Jan 2009|
|Contact details of provider:|| Postal: Via Patara, 3, 47921 Rimini (RN)|
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319., Boston College Department of Economics, revised 12 May 1998.
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