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Endogeneity in Semiparametric Threshold Regression

Listed author(s):
  • Andros Kourtellos

    ()

    (Department of Economics, University of Cyprus, Cyprus; The Rimini Centre for Economic Analysis)

  • Thanasis Stengos

    ()

    (Department of Economics and Finance, University of Guelph, Canada; The Rimini Centre for Economic Analysis)

  • Yiguo Sun

    ()

    (Department of Economics and Finance, University of Guelph, Canada)

In this paper, we investigate semiparametric threshold regression models with endogenous threshold variables based on a nonparametric control function approach. Using a series approximation we propose a two-step estimation method for the threshold parameter. For the regression coefficients we consider least-squares estimation in the case of exogenous regressors and two-stage least-squares estimation in the case of endogenous regressors. We show that our estimators are consistent and derive their asymptotic distribution for weakly dependent data. Furthermore, we propose a test for the endogeneity of the threshold variable, which is valid regardless of whether the threshold effect is zero or not. Finally, we assess the performance of our methods using a Monte Carlo simulation.

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File URL: http://www.rcea.org/RePEc/pdf/wp17-13.pdf
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Paper provided by The Rimini Centre for Economic Analysis in its series Working Paper Series with number 17-13.

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Date of creation: Jul 2017
Handle: RePEc:rim:rimwps:17-13
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  1. 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.
  2. Andrews, Donald W K, 1991. "Asymptotic Normality of Series Estimators for Nonparametric and Semiparametric Regression Models," Econometrica, Econometric Society, vol. 59(2), pages 307-345, March.
  3. Durlauf, Steven N, 1996. "A Theory of Persistent Income Inequality," Journal of Economic Growth, Springer, vol. 1(1), pages 75-93, March.
  4. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
  5. Oded Galor & Joseph Zeira, 1993. "Income Distribution and Macroeconomics," Review of Economic Studies, Oxford University Press, vol. 60(1), pages 35-52.
  6. Newey, Whitney K., 1997. "Convergence rates and asymptotic normality for series estimators," Journal of Econometrics, Elsevier, vol. 79(1), pages 147-168, July.
  7. Deniz Ozabaci & Daniel J. Henderson & Liangjun Su, 2014. "Additive Nonparametric Regression in the Presence of Endogenous Regressors," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 555-575, October.
  8. Seo, Myung Hwan & Shin, Yongcheol, 2016. "Dynamic panels with threshold effect and endogeneity," Journal of Econometrics, Elsevier, vol. 195(2), pages 169-186.
  9. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
  10. Zongwu Cai & Jianqing Fan & Qiwei Yao, 2000. "Functional-coefficient regression models for nonlinear time series," LSE Research Online Documents on Economics 6314, London School of Economics and Political Science, LSE Library.
  11. Athreya, Krishna B. & Pantula, Sastry G., 1986. "A note on strong mixing of ARMA processes," Statistics & Probability Letters, Elsevier, vol. 4(4), pages 187-190, June.
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