Difference in coefficients between regressions?

Hi - I'm looking for a way to test whether the beta coefficients are significantly different between two regression analyses. For example:
Regression 1: Prejudice toward blacks is DV, ~30 sociological/social psych variables are the IVs
Regression 2: Prejudice toward Asians is DV, ~30 sociological/social psych variables are the IVs

Now, for example, I want to test whether the effect of an independent variable, say income, is SIGNIFICANTLY different between the first regression (blacks DV) and the second regression (Asians DV). How would that be done? The theory is interesting to me, but I especially need to know how to do this in Stata or SPSS (preferably Stata). I've read about the Chow test, but that seems useable only for regressions in which the DV is the same but in which you're testing the differences between subsets (e.g., the differences in the effect of the IVs on the DV between male vs. female respondents), not between regressions in which the DV is different.
Thanks for any help.
this is a fun one

i think it is kind of neat anyway, but then again, i am hanging out on a statistics board, so what do i know?

If, and only if, your IV are the same, the only difference is your depvar response, then you do not need SPSS, just anything that can do a t-test.

the coefficient is a correlation (partial) of X1 and Y conditional on all other X's. If all other X's are the same, then a t-test of differences will tell you whether Y1 (black) or Y2(asian) have a significant effect on this partial correlation Beta1.

Any decent reg program can spit out the t-test means (the coefficients) and the standard errors that you need.

Just get the t-test formula in front of you and fill it in with the coefficient data.
Last edited: