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Is it possible to apply hurdle models (like the Craggit, probit and truncated models) to panel data, preferably with fixed effects to control for unobserved heterogeneity?

In Stata, the user-written command craggit only allows to use pooled panel data, but not to control for unobserved heterogeneity... In general, the hurdle model is quite simple to estimate: probit model on the binary outcome variable, truncated (or lognormal) on the (positive values of the) outcome variable. Is it possible to just estimate a RE probit (or even FE logit) in a first step, and a fixed effects model in the second – and to actually call that a hurdle model? Thanks.

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  • $\begingroup$ Do you have a reference to a theoretical discussion of the models that you are wanting to implement? It might be relevant for you to find out whether the kinds of models you want to implement are theoretically feasible or not, and if so, for what kinds of panels (large/small N), etc. $\endgroup$
    – tchakravarty
    Commented Jun 4, 2015 at 9:54
  • $\begingroup$ How to implement double hurdle model in Stata 14 $\endgroup$
    – Anyonymous
    Commented Nov 11, 2017 at 15:09

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You can estimate double hurdle models to panel data with random effects using the module called dhreg.

The Stata module is described on the following article (paywall until 2017):

http://www.stata-journal.com/article.html?article=st0359

You can find and install the software by typing findit dhreg on Stata.

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  • $\begingroup$ Is there an alternative for -dhreg- in Stata 12.1? $\endgroup$
    – PGupta
    Commented Jan 13, 2022 at 13:04

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