Cookies?
Library Header Image
LSE Research Online LSE Library Services

Nonparametric identification of the mixed hazard model using martingale-based moments

Ruf, Johannes and Wolter, James Lewis (2018) Nonparametric identification of the mixed hazard model using martingale-based moments. Econometric Theory. ISSN 0266-4666 (In Press)

[img] Text - Accepted Version
Download (539kB)

Abstract

Nonparametric identification of the Mixed Hazard model is shown. The setup allows for covariates that are random, time-varying, satisfy a rich path structure and are censored by events. For each set of model parameters, an observed process is constructed. The process corresponding to the true model parameters is a martingale, the ones corresponding to incorrect model parameters are not. The unique martingale structure yields a family of moment conditions that only the true parameters can satisfy. These moments identify the model and suggest a GMM estimation approach. The moments do not require use of the hazard function.

Item Type: Article
Official URL: https://www.cambridge.org/core/journals/econometri...
Additional Information: © 2019 Cambridge University Press
Divisions: Mathematics
Subjects: Q Science > QA Mathematics
Sets: Departments > Mathematics
Date Deposited: 03 Jan 2019 16:54
Last Modified: 16 Apr 2019 23:06
URI: http://eprints.lse.ac.uk/id/eprint/91491

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics