#StackBounty: #r #generalized-linear-model #stata #quasi-likelihood How flexible is Stata's ivpois? Could I use it for a (quasi) bi…

Bounty: 50

According to this post on statalist, Stata’s ivpois (an instrumental variable approach) is pretty flexible, with very little assumptions.

The problem mentioned in the post is:

"I have a database with counts as dependent variable. This variable suffers from over-dispersion problem."

Wooldridge mentions:

"I would strongly recommend trying IVPOIS, too. Regrettably, this command name is a misnomer. It should be called something like IVEXPON, as it works for any exponential model with multiplicative error. It does not care whether the EEV is continuous or discrete, so it produces consistent estimators under much weaker assumptions."

My thought was, if it works for any exponential model, does that mean it also works for my model, which is technically a quasibinomial, but according to this fine post, that boils down to a binomial with robust standard errors?

Hence my question: How flexible is Stata’s ivpois? Could I use it for a (quasi) binomial distribution?

Background: How to do a Control Function (CF) / Two Stage Residual Inclusion (2SRI) with an ordinal dependent variable in the first stage and a glm in the second


Get this bounty!!!

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