Economics at your fingertips  

Estimation of competing risks duration models with unobserved heterogeneity using hsmlogit

David Troncoso Ponce

No 2018-03, Working Papers from FEDEA

Abstract: This article presents hsmlogit, a new Stata command that estimates multispells discrete time competing risks duration models with unobserved heterogeneity. hsmlogit allows for the estimation of one, two and up to three competing risks, as well as a maximum of five points of support for the identification of unobserved heterogeneity distribution ([Heckman and Singer, 1984]). The main contribution of hsmlogit is that allows for exploiting the richness of large longitudinal micro datasets, by estimating competing risks duration models, instead of one-risk models (such as hshaz and hshaz2), as well as it takes into account the presence of unobserved heterogeneity affecting transition rates. In addition to this, and taking into account the larger size of longitudinal micro datasets used for the estimation of discrete time duration models, hsmlogit also provides the algebraic expressions of both first and second order derivatives that, respectively, define the gradient vector and Hessian matrix, which significantly reduce time required to achieve model convergence.

Date: 2018-02
References: Add references at CitEc
Citations: Track citations by RSS feed

Downloads: (external link) (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this paper

More papers in Working Papers from FEDEA
Bibliographic data for series maintained by Carmen Arias ().

Page updated 2020-07-04
Handle: RePEc:fda:fdaddt:2018-03