Hello all,
I have panel data on 16 countries for the years 1995 to 2007 (yearly observations). Initially, I wanted to use a fixed-effects model including both country- and time-fixed effects and to instrument x with z. I obtained my results with the following code:
However, I detected that there is a strong serial correlation in the error terms, using the following commands:
Therefore, using a stacked first-differences model is preferred to a fixed-effects model according to the literature.
I generated the differences with the following code:
How do I now estimate the stacked first-differences model, maintaining the IV approach? I want to include time dummies and add country-fixed effects to the FD-model. I have been told that country-fixed effects in an FD-model capture different time trends across countries. Finally, I want to add an intercept since Woolridge recommends adding an intercept in the first-differenced equation if the time intercepts are not of direct interest.
Your help is greatly appreciated!
I have panel data on 16 countries for the years 1995 to 2007 (yearly observations). Initially, I wanted to use a fixed-effects model including both country- and time-fixed effects and to instrument x with z. I obtained my results with the following code:
Code:
xtset country year
xi: xtivreg y (x=z) i.year, fe vce(cluster country)
Code:
predict uhat
reg uhat l.uhat
I generated the differences with the following code:
Code:
bysort country: gen x_diff = x[_n]- x[_n-1]
bysort country: gen z_diff= z[_n]- z[_n-1]
bysort country: gen y_diff = y[_n]- y[_n-1]
Your help is greatly appreciated!
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