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st: Is xtmixed is the appropriate estimation method?


From   "Stephan Brunow" <Stephan.Brunow@mailbox.tu-dresden.de>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: Is xtmixed is the appropriate estimation method?
Date   Fri, 4 May 2007 11:46:01 +0200

Dear STATAListers,

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
define 

c_r=d0+d1*age_ri

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?

Thank you,

Stephan


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