Dynamic time series binary choice
Tiemen Woutersen and
Robert de Jong
No 365, Econometric Society 2004 North American Summer Meetings from Econometric Society
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
Keywords: binary choice; near epoch dependence; asymptotic theory; smoothed maximum score (search for similar items in EconPapers)
JEL-codes: C22 C25 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-dcm, nep-ecm and nep-ets
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Journal Article: DYNAMIC TIME SERIES BINARY CHOICE (2011)
Working Paper: Dynamic time series binary choice (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:ecm:nasm04:365
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