Approximate conditional inference for panel logit models allowing for state dependence and unobserved heterogeneity

Details Approximate conditional inference for panel logit models allowing for state dependence and unobserved heterogeneity Approximate conditional inference for panel logit models allowing for state dependence and unobserved heterogeneity

2007-02-26

arxiv.org/abs/math/0702774v1

Mathematics

Statistics Theory

Scientific paper

We show that a dynamic logit model for binary panel data allowing for state dependence and unobserved heterogeneity may be accurately approximated by a quadratic exponential model, the parameters of which have the same interpretation that they have in the true model. We also show how we can eliminate the parameters for the unobserved heterogeneity from the approximating model by conditioning on the total scores, i.e. sum of the response variables for any individual in the panel. This allows to construct an approximate conditional likelihood for the dynamic logit model, by maximizing which we can estimate the parameters for the covariates and the state dependence. This estimator is very simple to compute and, by means of a simulation study, we show that it is competitive in terms of efficiency with the estimator of Honore' & Kyriazidou (2000). Finally, we outline the extension of the proposed approach to the case of more elaborated structures for the state dependence and to that of categorical response variables with more than two levels.

Affiliated with

Also associated with

No associations

Rating

Approximate conditional inference for panel logit models allowing for state dependence and unobserved heterogeneity does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Approximate conditional inference for panel logit models allowing for state dependence and unobserved heterogeneity, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Approximate conditional inference for panel logit models allowing for state dependence and unobserved heterogeneity will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-131785