[Limdep Nlogit List] Sample selection models with random effects

Little, Allan a.little at lancaster.ac.uk
Tue May 23 22:53:36 EST 2006



I have a query concerning the estimation of sample selection models in LIMDEP. I'm looking to set up a model with the following features:

1.	Binary dependent variables, in both models (i.e. the selector z=0/1 and in the second-step y=0/1, conditional on z=1)
2.	Random effects components, in both models 


I have identified two possible options in LIMDEP.


1.	Run 'PROBIT' (in step 1) and HOLD the results, then run a 'SELECT' model (in step 2) 

·        This appears to allow for random effects components in both stages

·        BUT... SELECT is a linear model (?), and doesn't seem to allow for logit/probit estimation.


2.	BIVARIATE PROBIT using the 'Selection' option 

·        This does allow for probit estimation in both steps

·        BUT... doesn't seem to allow for random effects estimation (?)  


So my question is, how can I run a Heckman-style probit model, for panel data? Perhaps I'm misinterpreting the limitations of the above options, or maybe there's another way?


...Just to give a little more detail on the nature of my problem. The model is a random effects binary logit/probit, based on a panel data sample of unemployed workers. y=0 if individual remains in unemployment, and y=1 if the individual moves back into employment. The selection problem arises because employed workers are precluded from the sample. So I intend to set up the selector model, where z=1 if unemployed, z=0 if employed. Again, I have a panel of data for the estimation of the selector equation.


Any suggestions would be greatly appreciated.




Allan Little

Lancaster University

a.little at lancaster.ac.uk

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