I've got a time-series cross sectional data set of US states that has a spatial component so I'm interested in estimating a dynamic spatial panel model. My dependent variable is wind capacity additions per state year and my regressors are various factors that may influence wind power development. I've generated my variables using ArcGIS and am estimating the statistics in Stata.
- Although most of my regressors vary by state and by year, at least one is time-invariant (but varies by state).
- Another one of my regressors, which represents technological improvements to wind machines, is the same across all the states in my panel (although it varies by time).
Given these somewhat unique aspects of my data, is a dynamic spatial panel model acceptable?
The Hausman test is nonsignificant and thus a random effects model seems appropriate. Is the Hausman test applicable to a spatial panel model?