Structural Threshold Regression
AbstractThis paper introduces the structural threshold regression model that allows for an endogeneous threshold variable as well as for endogenous regressors. This model provides a parsimonious way of modeling nonlinearities and has many potential applications in economics and finance. Our framework can be viewed as a generalization of the simple threshold regression framework of Hansen (2000) and Caner and Hansen (2004) to allow for the endogeneity of the threshold variable and regime specific heteroskedasticity. Our estimation of the threshold parameter is based on a concentrated least squares method that involves an inverse Mills ratio bias correction term in each regime. We derive its asymptotic distribution and propose a method to construct bootstrap confidence intervals. We also provide inference for the slope parameters based on GMM. Finally, we investigate the performance of the asymptotic approximations and the bootstrap using a Monte Carlo simulation that indicates the applicability of the method in finite samples.
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Bibliographic InfoPaper provided by The Rimini Centre for Economic Analysis in its series Working Paper Series with number 49_11.
Date of creation: Nov 2011
Date of revision:
Other versions of this item:
- 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, 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, 2009. "Structural Threshold Regression," Working Paper Series 22_09, The Rimini Centre for Economic Analysis, revised Jan 2009.
- Andros Kourtellos & Thanasis Stengos & Chih Ming Tan, 2009. "Structural Threshold Regression," Working Papers 0907, University of Guelph, Department of Economics and Finance.
- 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
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