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Structural Threshold Regression

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  • Andros Kourtellos
  • Thanasis Stengos
  • Chih Ming Tan

Abstract

This 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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File URL: http://papers.econ.ucy.ac.cy/RePEc/papers/13-2011.pdf
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Bibliographic Info

Paper provided by University of Cyprus Department of Economics in its series University of Cyprus Working Papers in Economics with number 13-2011.

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Length: 50 pages
Date of creation: Nov 2011
Date of revision:
Handle: RePEc:ucy:cypeua:13-2011

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Web page: http://www.econ.ucy.ac.cy

Related research

Keywords: nonlinear regression; endogenous threshold; sample split; regime shifts; inverse Mills ratio;

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  1. Papageorgiou, Chris, 2006. "Trade as a threshold variable for multiple regimes: Reply," Economics Letters, Elsevier, vol. 91(3), pages 460-461, June.
  2. Bruce E. Hansen, 1996. "Sample Splitting and Threshold Estimation," Boston College Working Papers in Economics 319., Boston College Department of Economics, revised 12 May 1998.
  3. Oliver Linton & Myunghwan Seo, 2005. "A smoothed least squares estimator for threshold regression models," LSE Research Online Documents on Economics 4434, London School of Economics and Political Science, LSE Library.
  4. repec:cup:cbooks:9780521496032 is not listed on IDEAS
  5. William Easterly & Ross Levine, 2002. "Tropics, Germs, and Crops: How Endowments Influence Economic Development," Working Papers, Center for Global Development 15, Center for Global Development.
  6. Li, Qi & Wooldridge, Jeffrey M., 2002. "Semiparametric Estimation Of Partially Linear Models For Dependent Data With Generated Regressors," Econometric Theory, Cambridge University Press, vol. 18(03), pages 625-645, June.
  7. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
  8. Jesús Gonzalo & Michael Wolf, 2001. "Subsampling inference in threshold autoregressive models," Economics Working Papers 573, Department of Economics and Business, Universitat Pompeu Fabra.
  9. Caner, Mehmet & Hansen, Bruce E., 2004. "Instrumental Variable Estimation Of A Threshold Model," Econometric Theory, Cambridge University Press, vol. 20(05), pages 813-843, October.
  10. Daron Acemoglu & Simon Johnson & James A. Robinson, 2001. "The Colonial Origins of Comparative Development: An Empirical Investigation," American Economic Review, American Economic Association, vol. 91(5), pages 1369-1401, December.
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