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Dynamic time series binary choice

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Author Info
Tiemen Woutersen
Robert M. de Jong
Abstract

This paper considers dynamic time series binary choice models. It shows in a time series setting the validity of the dynamic probit likelihood procedure when lags of the dependent binary variable are used as regressors, and it establishes the asymptotic validity of Horowitz' smoothed maximum score estimation of dynamic binary choice models with lags of the dependent variable as regressors. The latent error is explicitly allowed to be correlated. It turns out that no long-run variance estimator is needed for the validity of the smoothed maximum score procedure in the dynamic time series framework. One novel aspect of this paper is a proof that weak dependence properties hold for dynamic binary choice models with correlated errors

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Paper provided by Econometric Society in its series Econometric Society 2004 North American Summer Meetings with number 365.

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Date of creation: 11 Aug 2004
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Handle: RePEc:ecm:nasm04:365

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Keywords: binary choice near epoch dependence asymptotic theory smoothed maximum score

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Find related papers by JEL classification:
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models
C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Matzkin, Rosa L, 1992. "Nonparametric and Distribution-Free Estimation of the Binary Threshold Crossing and the Binary Choice Models," Econometrica, Econometric Society, vol. 60(2), pages 239-70, March. [Downloadable!] (restricted)
  2. Imbens, G.W., 1991. "An Efficient Method Of Moments Estimator For Discrete Choice Models With Choice-Based Sampling," Harvard Institute of Economic Research Working Papers 1546, Harvard - Institute of Economic Research.
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  3. Manski, Charles F., 1985. "Semiparametric analysis of discrete response : Asymptotic properties of the maximum score estimator," Journal of Econometrics, Elsevier, vol. 27(3), pages 313-333, March. [Downloadable!] (restricted)
  4. Poirier, Dale J & Ruud, Paul A, 1988. "Probit with Dependent Observations," Review of Economic Studies, Blackwell Publishing, vol. 55(4), pages 593-614, October. [Downloadable!] (restricted)
  5. repec:cup:etheor:v:13:y:1997:i:3:p:353-67 is not listed on IDEAS
  6. Cosslett, Stephen R, 1983. "Distribution-Free Maximum Likelihood Estimator of the Binary Choice Model," Econometrica, Econometric Society, vol. 51(3), pages 765-82, May. [Downloadable!] (restricted)
  7. Andrews, Donald W. K., 1987. "Laws of Large Numbers for Dependent Non-Identically Distributed Random Variables," Working Papers 645, California Institute of Technology, Division of the Humanities and Social Sciences. [Downloadable!]
  8. Horowitz, Joel L, 1992. "A Smoothed Maximum Score Estimator for the Binary Response Model," Econometrica, Econometric Society, vol. 60(3), pages 505-31, May. [Downloadable!] (restricted)
  9. Eichengreen, Barry & Watson, Mark W & Grossman, Richard S, 1985. "Bank Rate Policy under the Interwar Gold Standard: A Dynamic Probit Model," Economic Journal, Royal Economic Society, vol. 95(379), pages 725-45, September. [Downloadable!] (restricted)
  10. Donald W.K. Andrews, 1986. "Consistency in Nonlinear Econometric Models: A Generic Uniform Law of Large Numbers," Cowles Foundation Discussion Papers 790, Cowles Foundation, Yale University. [Downloadable!]
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Siddhartha Chib & Michael J. Dueker, 2004. "Non-Markovian regime switching with endogenous states and time-varying state strengths," Working Papers 2004-030, Federal Reserve Bank of St. Louis. [Downloadable!]
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