[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.
Thanks,
Allan Little
Lancaster University
a.little at lancaster.ac.uk
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