Dear Stata-Listers,
I have a dataset of social media posts created by individuals (i.e. authors) in the first six months of 2022, that comprises of both author-related and post-related variables.
Posts can be shared over the social network, and I examine the effect of author's gender on the number of shares each post receives.
To estimate the impact of gender (the variable "Female") on shares, I have used a random effects negative binomial count model with author's id as the panel variable but without a time variable (as the repeated observations are not measured at the same point in time). The variable "female" is significant in this model.
To show the robustness of the findings, is there any alternative empirical specification I could use?
I was thinking about Zero-Inflated count models as my data has excessive zeros, but could not find a Stata command for Zero-Inflated models in panel data contexts.
Your help is deeply appreciated!
Priyanga
I have a dataset of social media posts created by individuals (i.e. authors) in the first six months of 2022, that comprises of both author-related and post-related variables.
Posts can be shared over the social network, and I examine the effect of author's gender on the number of shares each post receives.
To estimate the impact of gender (the variable "Female") on shares, I have used a random effects negative binomial count model with author's id as the panel variable but without a time variable (as the repeated observations are not measured at the same point in time). The variable "female" is significant in this model.
To show the robustness of the findings, is there any alternative empirical specification I could use?
I was thinking about Zero-Inflated count models as my data has excessive zeros, but could not find a Stata command for Zero-Inflated models in panel data contexts.
Your help is deeply appreciated!
Priyanga
