NONPARAMETRIC IDENTIFICATION OF THE MIXED HAZARDS MODEL WITH TIME-VARYING COVARIATES

B-Tier
Journal: Econometric Theory
Year: 2007
Volume: 23
Issue: 2
Pages: 349-354

Score contribution per author:

2.011 = (α=2.01 / 1 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

Most nonparametric identification results for the mixed proportional hazards model for single spell duration data depend crucially on the proportional hazards assumption. Here, it is shown that variation in covariates over time, combined with variation across observations, is sufficient to ensure identification without the proportional hazards assumption. The required variation over time is minimal, and the mixed hazards model is identified without the proportional hazards assumption in the presence of standard time-varying covariates.Thanks to Kåre Bævre, Zhiyang Jia, Tore Schweder, Rolf Aaberge, and John K. Dagsvik for useful comments.

Technical Details

RePEc Handle
repec:cup:etheor:v:23:y:2007:i:02:p:349-354_07
Journal Field
Econometrics
Author Count
1
Added to Database
2026-01-24