The identification & economic content of ordered choice models with stochastic thresholds

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dc.contributor.author Cunha, Flavio
dc.contributor.author Heckman, James J.
dc.contributor.author Navarro, Salvador
dc.date.accessioned 2010-02-25T15:20:01Z
dc.date.available 2010-02-25T15:20:01Z
dc.date.issued 2007-07-16
dc.identifier.uri http://hdl.handle.net/10197/1887
dc.description.abstract This paper extends the widely used ordered choice model by introducing stochastic thresholds and interval-specific outcomes. The model can be interpreted as a generalization of the GAFT (MPH) framework for discrete duration data that jointly models durations and outcomes associated with different stopping times. We establish conditions for nonparametric identification. We interpret the ordered choice model as a special case of a general discrete choice model and as a special case of a dynamic discrete choice model. en
dc.description.sponsorship Claudio Haddad Dissertation Fund at the University of Chicago en
dc.description.sponsorship National Institutes of Health en
dc.description.sponsorship National Science Foundation en
dc.format.extent 387139 bytes
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher University College Dublin. Geary Institute en
dc.relation.ispartofseries UCD Geary Institute Discussion Paper Series en
dc.relation.ispartofseries WP/26/2007 en
dc.subject Discrete choice en
dc.subject Ordered choice en
dc.subject Dynamics en
dc.subject.classification C31 en
dc.subject.lcsh Analysis of variance en
dc.subject.lcsh Mathematical models en
dc.title The identification & economic content of ordered choice models with stochastic thresholds en
dc.type Working Paper en
dc.internal.availability Full text available en
dc.internal.webversions Publisher's version en
dc.internal.webversions http://geary.ucd.ie/images/Publications/WorkingPapers/GearyWp200726.pdf en
dc.status Not peer reviewed en
dc.neeo.contributor Cunha|Flavio|aut| en
dc.neeo.contributor Heckman|James J.|aut| en
dc.neeo.contributor Navarro|Salvador|aut| en


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