Estimating a semi-parametric duration model without specifying heterogeneity

Jerry A. Hausman, Tiemen M Woutersen

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

This paper presents a new estimator for the mixed proportional hazard model that allows for a nonparametric baseline hazard and time-varying regressors. In particular, this paper allows for discrete measurement of the durations as happens often in practice. The integrated baseline hazard and all parameters are estimated at the regular rate, N, where N is the number of individuals. A hazard model is a natural framework for time-varying regressors. In particular, if a flow or a transition probability depends on a regressor that changes with time, a hazard model avoids the curse of dimensionality that would arise from interacting the regressors at each point in time with one another. This paper also presents a new test to detect unobserved heterogeneity.

Original languageEnglish (US)
Pages (from-to)114-131
Number of pages18
JournalJournal of Econometrics
Volume178
Issue numberPART 1
DOIs
StatePublished - Jan 2014

Fingerprint

Duration Models
Hazard Models
Semiparametric Model
Hazard
Baseline
Time-varying
Hazards
Unobserved Heterogeneity
Proportional Hazards Model
Curse of Dimensionality
Transition Probability
Estimator
Duration models
Hazard models
Framework
Curse of dimensionality
Transition probability
Unobserved heterogeneity
Proportional hazards model
Integrated

Keywords

  • Heterogeneity
  • Mixed proportional hazard model
  • Time-varying regressors

ASJC Scopus subject areas

  • Economics and Econometrics
  • Applied Mathematics
  • History and Philosophy of Science

Cite this

Estimating a semi-parametric duration model without specifying heterogeneity. / Hausman, Jerry A.; Woutersen, Tiemen M.

In: Journal of Econometrics, Vol. 178, No. PART 1, 01.2014, p. 114-131.

Research output: Contribution to journalArticle

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