Robert ]]>

The Chow test is done to test structural changes over time. Basically, what you do is interact your time dummies with the predictor(s) of interest and test the joint significance of those interaction terms. The Chow test is actually just a regular F-test.

From Wooldridge's Introductory Econometrics: A Modern Approach (2003) (link here: http://www.amazon.com/Introductory-Econometrics-Modern-Appro ach-Economics/dp/1111531048), emphasis added:

Quote:

For many time periods and explanatory variables, constructing a full set of interactions can be tedious. First, estimate the restricted model by doing a pooled regression allowing for different time intercepts; this givesSSR_r. Then, run a regression for each of the, say, T time periods and obtain the sum of squared residuals for each time period. The unrestricted sum of squared residuals is obtained asSSR_ur = SSR_1 + SSR_2 + ... + SSR_T. If there arekexplanatory variables (not including the intercept or the time dummies) withTtime periods, then we are testing(T - 1)krestrictions, and there areT + Tkparameters estimated in the unrestricted model. So, ifn = n_1 + n_2 + ... + n_Tis the total number of observations, then thedfof the F test are(T - 1)kandn - T - Tk. We compute the F statistic as usual:[(SSR_r - SSR_ur)/SSR_ur][(n - T - Tk)/(T - 1)k].

If you are using Stata, you can accomplish this by using the -test- command post-estimation (just as you would a "regular" F-test in Stata).

Wooldridge, J. 2003.

hth,

rhs

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