DYNAMIC TIME SERIES BINARY CHOICE

Robert M. de Jong, Tiemen M Woutersen

Research output: Contribution to journalArticle

43 Citations (Scopus)

Abstract

This paper considers dynamic time series binary choice models. It proves near epoch dependence and strong mixing for the dynamic binary choice model with correlated errors. Using this result, 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's smoothed maximum score estimation of dynamic binary choice models with lags of the dependent variable as regressors. For the semiparametric model, 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.

Original languageEnglish (US)
Pages (from-to)1-30
Number of pages30
JournalEconometric Theory
DOIs
StateAccepted/In press - Mar 3 2011
Externally publishedYes

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time series
Binary choice
Binary choice model
Lag

ASJC Scopus subject areas

  • Social Sciences (miscellaneous)
  • Economics and Econometrics

Cite this

DYNAMIC TIME SERIES BINARY CHOICE. / de Jong, Robert M.; Woutersen, Tiemen M.

In: Econometric Theory, 03.03.2011, p. 1-30.

Research output: Contribution to journalArticle

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