Dear Stata users,
I am trying to estimate a Heckman sample selection model for panel data in Stata using GLLAMM.
I encountered the following problem.
Sometimes the log likelihood instead of increasing decrease. I mean that for some 'i's iteration[i] log likelihood > iteration[i+1] log likelihood (as you can see in attached printscreen for iteration[5] and iteration [6]).
Does it mean that I should try with more quadrature points or there is a problem with the data? Is it possible that despite this 'jumping' the model can still converge or I should rather abort maximalization process.
Running adaptive quadrature
Iteration 0: log likelihood = -8724.0818
Iteration 1: log likelihood = -7729.0175
Iteration 2: log likelihood = -6772.7395
Iteration 3: log likelihood = -6420.9296
Iteration 4: log likelihood = -6410.1388
Iteration 5: log likelihood = -6111.5488
Iteration 6: log likelihood = -6129.489
Iteration 7: log likelihood = -6122.5803
Iteration 8: log likelihood = -6118.6587
Iteration 9: log likelihood = -6113.8941
Iteration 10: log likelihood = -6127.7954
I would really appreciate any advice.
Thanks,
Janek
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
