Hi,
I am having some trouble trying to match OLS regression output done in
SAS to a OLS regression done in STATA. Basically, I was given a SAS
program, and when run on SAS, it produces the exact results we are
looking for. However, I'm trying to "convert" it into a STATA program.
The program itself appends and merges a number of datasets, creates some
variables from the final merged dataset using some simple arithmetic
commands, drops certain observations, and then runs a OLS regression on
certain variables. It is really not all that complex of a program, but
I cannot for the life of me get my STATA regression results to match the
SAS results. This is made even more bizarre by how similar the final
datasets appear to be. All of the summary statistics (i.e. mean, std.
Dev., max, min, number of observations) are identical in both programs.
Moreover, I generated an "id" variable that simply numbers the
observations in the first (and largest dataset) in both programs, and
after all the datasets are merged and transformed, both datasets contain
the exact same observations from that first dataset (e.g. the id
variables from both programs are identical). When I run the regressions
in STATA, the coefficients for the variables all come very, very close,
if not exactly the same as the coefficients in SAS. The only exception
to this is the constant, which bizarrely is nearly 100 times larger than
the constant in SAS. And I cannot figure out why! Does anyone know
what would cause supposedly identical datasets to produce such different
results in the constants? I have a pocket theory that it is because the
programs treat blanks and zeros differently, but I have been unable to
prove it, and the problem could very well be something else. If anyone
can offer any help, I would greatly appreciate it!
Thanks.
Thomas
_______________________________
Thomas Goerner
NERA White Plains
50 Main St.
White Plains, NY 10606
Tel: 1-914-448-4009
Fax: 914-448-4040
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