Dear Subscribers,
I am working with bilateral trade gravity models on a disaggregated
level to find out if bilateral trade treaties which preferentially
lowered tariffs on specific commodities enhanced respective trade
flows. I used to do that with a quite simple system of log-linear
sureg regressions like
ln(bilateralimportcommodity1)=a1 + b1 ln(incomeimporter)+c1
ln(distance)+d1 tariff-preference-dummy [and lots of control
variables]
ln(bilateralimportcommodity2)=a + b2 ln(incomeimporter) + c2
ln(distance) + d2 tariff-preference-dummy [and lots of control
variables]
for several goods
to estimate an "overall average effect" I restricted d1=d2=d3, etc.
Now I got aware of a newer literature on gravity models that bothers
about biases caused by "0" observations in the import matrix that are
excluded by taking the logs. Santos Silva and Tenreyro, The Log of
Gravity, Review of Economics and Statistics 88, 2006, 88(4), 641-658.
I now that I might estimate poisson regressions in dependent variable
levels and later use surest, but this does not allow me to impose
constraints.
Does anyone have any idea about the feasibility of my idea (a system
of SU poisson regressions with constraints) or has ever tried
something alike?
I had a look at Gary King's, A Seemingly Unrelated Poisson Regression
Model, in Sociological Methods and Research 17/3, 1989, 235-255, but
found no implementations, etc.
Thank you very much for your consideration
Markus
...
Markus Lampe
Institute for Economic and Social History
University of Muenster
Domplatz 20-22
D-48143 Muenster (Germany)
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