Structural Threshold Regression
AbstractThis 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 finite samples.
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Bibliographic InfoPaper provided by University of Guelph, Department of Economics and Finance in its series Working Papers with number 0907.
Length: 23 pages
Date of creation: 2009
Date of revision:
Other versions of this item:
- Andros Kourtellos & Thanasis Stengos & Chih Ming Tan, 2011. "Structural Threshold Regression," Working Paper Series 49_11, The Rimini Centre for Economic Analysis.
- Andros Kourtellos & Thanasis Stengos & Chih Ming Tan, 2011. "Structural Threshold Regression," University of Cyprus Working Papers in Economics 13-2011, University of Cyprus Department of Economics.
- Andros Kourtellos & Thanasis Stengos & Chih Ming Tan, 2008. "Structural Threshold Regression," Discussion Papers Series, Department of Economics, Tufts University 0717, Department of Economics, Tufts University.
- Andros Kourtellos & Thanasis Stengos & Chih Ming Tan, 2009. "Structural Threshold Regression," Working Paper Series 22_09, The Rimini Centre for Economic Analysis, revised Jan 2009.
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-11-21 (All new papers)
- NEP-ECM-2009-11-21 (Econometrics)
- NEP-ETS-2009-11-21 (Econometric Time Series)
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