How to handle endogenous count variable in impact study

[Abdallah Alidu]

Hi,
Let me first of all apologize for the "bump posting" I did earlier. I am new to the program and I am therefore asking for your forgiveness.
I am conducting a research entitled "the impact of agricultural technology adoption on farm output in northern Ghana" and am using a cross sectional data. My Main objective is to determine the impact of agricultural technology adoption on output but my endogenous variable here is count (i.e. number of agricultural technologies adopted). My main challenge is how to correct for the endogeneity. Can I use Poisson or any count model in the first stage to predict the probabilities of adoption for the second stage?
Any help would be appreciated.
Thank you.

[Joao Santos Silva]

Dear Abdallah,

You can (should) use plain 2SLS for this. At most, you can do a preliminary step in which you estimate the Poisson regression you describe and then use the predicted values of that regression as an additional instrument in the 2SLS.

Best wishes,

Joao

[Abdallah Alidu]

Thank you very much Joao. But what if my data is overdispersed?

[Joao Santos Silva]

You can safely ignore that in this context :-)

Joao

[Abdallah Alidu]

Thanks once again.

[Joao Santos Silva]

Nice to see threads converging; see here.

Joao

[Abdallah Alidu]

OK!
Thanks to everyone. I must say am much grateful for your time and patience.