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Likelihood estimation and inference in threshold regression

  • Yu, Ping
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    This paper studies likelihood-based estimation and inference in parametric discontinuous threshold regression models with i.i.d. data. The setup allows heteroskedasticity and threshold effects in both mean and variance. By interpreting the threshold point as a “middle” boundary of the threshold variable, we find that the Bayes estimator is asymptotically efficient among all estimators in the locally asymptotically minimax sense. In particular, the Bayes estimator of the threshold point is asymptotically strictly more efficient than the left-endpoint maximum likelihood estimator and the newly proposed middle-point maximum likelihood estimator. Algorithms are developed to calculate asymptotic distributions and risk for the estimators of the threshold point. The posterior interval is proved to be an asymptotically valid confidence interval and is attractive in both length and coverage in finite samples.

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    Article provided by Elsevier in its journal Journal of Econometrics.

    Volume (Year): 167 (2012)
    Issue (Month): 1 ()
    Pages: 274-294

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    Handle: RePEc:eee:econom:v:167:y:2012:i:1:p:274-294
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    1. Pakes, Ariel & Pollard, David, 1989. "Simulation and the Asymptotics of Optimization Estimators," Econometrica, Econometric Society, vol. 57(5), pages 1027-57, September.
    2. Savvides, A. & Stengos, T., 2000. "Income Inequality and Economic Development: Evidence from the Threshold Regression Model," Working Papers 2000-2, University of Guelph, Department of Economics and Finance.
    3. Jushan Bai, 1997. "Estimation Of A Change Point In Multiple Regression Models," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 551-563, November.
    4. Boetel, Brenda L. & Hoffmann, Ruben & Liu, Donald J., 2004. "Estimating Investment Rigidity Within A Threshold Regression Framework: The Case Of U.S. Hog Production Sector," Staff Papers 13790, University of Minnesota, Department of Applied Economics.
    5. Irene Gijbels & Peter Hall & Aloïs Kneip, 1999. "On the Estimation of Jump Points in Smooth Curves," Annals of the Institute of Statistical Mathematics, Springer, vol. 51(2), pages 231-251, June.
    6. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    7. Jesús Gonzalo & Michael Wolf, 2001. "Subsampling inference in threshold autoregressive models," Economics Working Papers 573, Department of Economics and Business, Universitat Pompeu Fabra.
    8. Donald W.K. Andrews, 1990. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Cowles Foundation Discussion Papers 943, Cowles Foundation for Research in Economics, Yale University.
    9. Sokbae Lee & Myung Hwan Seo, 2007. "Semiparametric estimation of a binary response model with a change-point due to a covariate threshold," LSE Research Online Documents on Economics 6806, London School of Economics and Political Science, LSE Library.
    10. Bai, Jushan, 1995. "Least Absolute Deviation Estimation of a Shift," Econometric Theory, Cambridge University Press, vol. 11(03), pages 403-436, June.
    11. Keisuke Hirano & Jack R. Porter, 2002. "Asymptotic Efficiency in Parametric Structural Models with Parameter-Dependent Support," Harvard Institute of Economic Research Working Papers 1988, Harvard - Institute of Economic Research.
    12. Bwo-Nung Huang & Chin-Wei Yang, 2006. "Demand for cigarettes revisited: an application of the threshold regression model," Agricultural Economics, International Association of Agricultural Economists, vol. 34(1), pages 81-86, 01.
    13. Simon M. Potter, 1993. "A Nonlinear Approach to U.S. GNP," UCLA Economics Working Papers 693, UCLA Department of Economics.
    14. Rudolf Beran, 1997. "Diagnosing Bootstrap Success," Annals of the Institute of Statistical Mathematics, Springer, vol. 49(1), pages 1-24, March.
    15. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
    16. Victor Chernozhukov & Han Hong, 2004. "Likelihood Estimation and Inference in a Class of Nonregular Econometric Models," Econometrica, Econometric Society, vol. 72(5), pages 1445-1480, 09.
    17. repec:att:wimass:9419 is not listed on IDEAS
    18. Durlauf, Steven N & Johnson, Paul A, 1995. "Multiple Regimes and Cross-Country Growth Behaviour," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(4), pages 365-84, Oct.-Dec..
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