Economics at your fingertips  

Conditional logit versus random coefficient models: An analysis using GLLAMM

Peter Haan

No 7, German Stata Users' Group Meetings 2004 from Stata Users Group

Abstract: Estimating labor supply functions using a discrete rather than a continuous specification has become increasingly popular in recent years. The main advantage of the discrete choice approach compared to continuous specifications derives from the possibility to model nonlinearities in budget functions. However, the standard discrete choice approach, the conditional logit model, is based on some restrictive assumptions. Econometric literature has suggested more general discrete choice models. However, these less restrictive specifications have shown to incur very high computational cost, which might obstruct the estimation of confidence intervals of marginal effects or elasticities. It is therefore of particular interest for applied research, which approach is more adequate when analyzing discrete choice models. In my analysis, I estimate different model specifications of a household utility function drawing on micro data of the GSOEP. For the estimation, I employ the Stata program GLLAMM, developed by Sophia Rabe-Hesketh et al. (2001). The idea is to test whether the results derived from the different specifications differ significantly. My findings suggest that for computational reasons, standard discrete choice models that are more restrictive in their assumptions regarding error variances, seem to represent the adequate model choice for the analysis of labor supply functions on basis of the GSOEP.

New Economics Papers: this item is included in nep-dcm
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) Presentation slides (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 German Stata Users' Group Meetings 2004 from Stata Users Group Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F Baum ().

Page updated 2023-06-15
Handle: RePEc:boc:dsug04:7