A simple approach to the identifiability of the proportional hazards model

Melino, Angelo; Sueyoshi, Glenn T.

doi:10.1016/0165-1765(90)90201-b

Cited by 12 publications

(4 citation statements)

References 11 publications

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“…This would give a range of unique solutions Λ to expression (7). Obviously, all these solutions should be the same, which provides overidentifying restrictions that are similar to those discussed by Melino and Sueyoshi (1990) for the single-risk MPH model.…”

Section: The Main Identification Resultsmentioning

confidence: 99%

The Identifiability of the Mixed Proportional Hazards Competing Risks Model

Abbring

Berg

2003

Journal of the Royal Statistical Society Series B: Statistical Methodology

151

138

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We prove identification of dependent competing risks models in which each risk has a mixed proportional hazard specification with regressors, and the risks are dependent by way of the unobserved heterogeneity, or frailty, components. We show that the conditions for identification given by Heckman and Honoré can be relaxed. We extend the results to the case in which multiple spells are observed for each subject. Copyright 2003 Royal Statistical Society.

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Section: The Main Identification Resultsmentioning

confidence: 99%

The Identifiability of the Mixed Proportional Hazards Competing Risks Model

Abbring

Berg

2003

Journal of the Royal Statistical Society Series B: Statistical Methodology

151

138

View full text Add to dashboard Cite

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“…Finally, the result can be extended to cover the identification of a model where the baseline hazards and lagged duration functions are conditional on x and the mixing distribution G depends on x. . Since all the solutions to equations (10) should be the same, potentially testable overidentifying restrictions arise, similarly to Abbring and van den Berg (2003a) and Melino and Sueyoshi (1990).…”

Section: Mph Models With Lagged Duration Dependencementioning

confidence: 99%

Lagged duration dependence in mixed proportional hazard models

Picchio¹

2012

Economics Letters

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. www.econstor.eu The Institute for the Study of Labor (IZA) in Bonn is a local and virtual international research center and a place of communication between science, politics and business. IZA is an independent nonprofit organization supported by Deutsche Post Foundation. The center is associated with the University of Bonn and offers a stimulating research environment through its international network, workshops and conferences, data service, project support, research visits and doctoral program. IZA engages in (i) original and internationally competitive research in all fields of labor economics, (ii) development of policy concepts, and (iii) dissemination of research results and concepts to the interested public. Terms of use: Documents in D I S C U S S I O N P A P E R S E R I E SIZA Discussion Papers often represent preliminary work and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be available directly from the author. We study the non-parametric identification of a mixed proportional hazard model with lagged duration dependence when data provide multiple outcomes per individual or stratum. We show that the information conveyed by the within strata variation can be exploited to nonparametrically identify lagged duration dependence in more general models than in the literature.JEL Classification: C14, C41

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“…(There is an analogy with MPH models for micro duration data in which the role of r is replaced by observed regressors; see Van den Berg (1992) and Melino and Sueyoshi (1990).) As an illustration, consider the following equation, which follows from equations (7) for t = 1 and t = 0 with ^> 3 = 1,…”

Section: Identificationmentioning

confidence: 99%

The Anatomy of Unemployment Dynamics

1999

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This paper examines the relation between individual unemployment durations and incidence on the one hand, and the time-varying macroeconomie conditions in the economy on the other. We allow for calendar time effects acting on the exit probabilities for all currently unemployed. Also, we allow the composition of the inflow into unemployment to depend on calendar time at the moment of inflow. In both cases we distinguish between business cycle effects and seasonal effects. We apply the model to aggregate unemployment duration data, in which we aJlow for unobserved heterogeneity and correlated measurement errors. We do not make parametric assumptions on the genuine duration dependence pattern or the unobserved heterogeneity distribution. The results enable us to give a complete decomposition of the dynamics of unemployment over calendar time. This is also used to test the popular ranking model of unemployment.

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A simple approach to the identifiability of the proportional hazards model

Cited by 12 publications

References 11 publications

The Identifiability of the Mixed Proportional Hazards Competing Risks Model

The Identifiability of the Mixed Proportional Hazards Competing Risks Model

Lagged duration dependence in mixed proportional hazard models

The Anatomy of Unemployment Dynamics

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