Regular Variation and the Identification of Generalized Accelerated Failure-Time Models
Copyright policy )Regular Variation and the Identification of Generalized Accelerated Failure-Time Models
Ridder (1990,Review of Economic Studies57, 167–182) provides an identification result for the Generalized Accelerated Failure-Time (GAFT) model. We point out that Ridder’s proof of this result is incomplete, and provide an amended proof with an additional necessary and sufficient condition that requires that a function varies regularly at 0 and ∞. We also give more readily interpretable sufficient conditions on the tails of the error distribution or the asymptotic behavior of the transformation of the dependent variable. The sufficient conditions are shown to encompass all previous results on the identification of the Mixed Proportional Hazards (MPH) model. Thus, this paper not only clarifies, but also unifies the literature on the nonparametric identification of the GAFT and MPH models.
- Institute for the Study of Labor Germany
- Tilburg University Netherlands
- University of California System United States
- Tinbergen Institute Netherlands
- University of Southern California United States
Reliability and life testing, identifiability, duration analysis; identifiability; Mixed Proportional Hazards model; regular variation, Asymptotic properties of nonparametric inference, regular variation, duration analysis, duration analysis;identifiability;Mixed Proportional Hazards model;regular variation, Mixed Proportional Hazards model, Applications of statistics to economics, jel: jel:C41, jel: jel:C14
Reliability and life testing, identifiability, duration analysis; identifiability; Mixed Proportional Hazards model; regular variation, Asymptotic properties of nonparametric inference, regular variation, duration analysis, duration analysis;identifiability;Mixed Proportional Hazards model;regular variation, Mixed Proportional Hazards model, Applications of statistics to economics, jel: jel:C41, jel: jel:C14
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