Dynamic binary outcome models with maximal heterogeneity

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dc.contributor.author Browning, Martin
dc.contributor.author Carro, Jesús M.
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Economía
dc.date.accessioned 2009-03-11T13:08:19Z
dc.date.available 2009-03-11T13:08:19Z
dc.date.issued 2009-02
dc.identifier.issn 2340-5031
dc.identifier.uri http://hdl.handle.net/10016/3802
dc.description.abstract Most econometric schemes to allow for heterogeneity in micro behaviour have two drawbacks: they do not fit the data and they rule out interesting economic models. In this paper we consider the time homogeneous first order Markov (HFOM) model that allows for maximal heterogeneity. That is, the modelling of the heterogeneity does not impose anything on the data (except the HFOM assumption for each agent) and it allows for any theory model (that gives a HFOM process for an individual observable variable). `Maximal' means that the joint distribution of initial values and the transition probabilities is unrestricted. We establish necessary and sufficient conditions for the point identification of our heterogeneity structure and show how it depends on the length of the panel. A feasible ML estimation procedure is developed. Tests for a variety of subsidiary hypotheses such as the assumption that marginal dynamic effects are homogeneous are developed. We apply our techniques to a long panel of Danish workers who are very homogeneous in terms of observables. We show that individual unemployment dynamics are very heterogeneous, even for such a homogeneous group. We also show that the impact of cyclical variables on individual unemployment probabilities differs widely across workers. Some workers have unemployment dynamics that are independent of the cycle whereas others are highly sensitive to macro shocks.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries Workign papers. Economics
dc.relation.ispartofseries 09-10
dc.relation.hasversion http://hdl.handle.net/10016/20689
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Discrete choice
dc.subject.other Markov processes
dc.subject.other Nonparametric identification
dc.subject.other Unemployment dynamics
dc.title Dynamic binary outcome models with maximal heterogeneity
dc.type workingPaper
dc.subject.jel C23
dc.subject.jel C24
dc.subject.jel J64
dc.subject.eciencia Economía
dc.rights.accessRights openAccess
dc.identifier.repec we091710
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