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st: Is xtmixed is the appropriate estimation method?
we want to estimate a Cobb-Douglas production function,
ln y_r=ln A+b ln K_r + c ln L_r
where K is capital and L is labor input. We have only observation of one
year for almost 200 different regions (labeled with _r). There is no panel
so far. However, we have detailed information of the labor force within each
region. I.e. we have information of single workers (_i) within each region
(_r). Therefore we have about 1 million of rows. We think that regional
parameters vary randomly because of the regional labor force. Hence, we
where age is the individual age of a person within each region.
The data set looks as follows
Region lny lnK lnL Personid age
1 10 5 3 1 23
1 10 5 3 2 25
2 12 7 6 1 48
2 12 7 6 2 57
2 12 7 6 3 36
As you might see, the regional information is constant over all persons of
that region but the individual information varies.
If we define ageXlnL=age*lnL,
the xtmixed command is
xtmixed lny lnK lnL ageXlnl || region: lnL
However, this model does not work. We get positive values of the
log-restricted likelihood and the Hessian can not be computed.
Therefore we have chosen the emonly option which „only“ reports positive
values oft he log-restricted likelihood.
We know that we do not have an y_ri, we have only a y_r. Is this the
problem? Is xtmixed the right model at all?
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