Dear all,
I'm working with a panel dataset with yearly regional migration flows for
every pair of regions, that is 20x19x7 (origin regions-destination
regions-years).
The indepvar is the yearly migration flow from the ith region (origin) to
the jth region (destination). The covariates are per capita GDP (origin and
dest region) unemp rate (origin and dest region) population (origin and
destinat) and distance. so in total 7 covariates. All variables are in log.
I'm in the early stage of my analysis and new with Stata. So far I estimated
the model with the xtreg command and I got satisfying results, both in terms
of sign of coeff and their significance.
However I'm not sure all of this is enough (or correct). For example per
capita GDP and unemployment rate are likely to be correlated and there might
be heteroskedasticity..
My question is: do you think I'm using the proper model for such data set or
maybe I need to look for more advanced techniques? Should I use a dynamic
model (arellano bond), or maybe the xtgls command (for heteroskedasticity),
or xtivreg (for endogeneity)?
Thank you to all of you
Ivan
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