Quantile regression for duration models with time-varying regressors

Songnian Chen

Journal of Econometrics, 2019, vol. 209, issue 1, 1-17

Abstract: Since the seminal work of Koenker and Bassett (1978), quantile regression has become a widely used tool in duration analysis. The existing literature, however, has focused on time-invariant regressors, even though time-varying regressors are common in practice. In this paper, we introduce a quantile regression framework with time-varying regressors and develop quantile regression estimators. Our estimators are motivated by Manski’s (1975, 1985) maximum score estimator and Chen’s (2010) integrated maximum score estimator. Our estimators are consistent and asymptotically normal under some regularity conditions, and perform well in finite samples. Our method is illustrated with an unemployment duration data set.

Keywords: Quantile regression; Time-varying regressors; Duration analysis (search for similar items in EconPapers)
JEL-codes: C21 C24 C41 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304407618302574
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:209:y:2019:i:1:p:1-17

DOI: 10.1016/j.jeconom.2018.11.015

Access Statistics for this article

Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().