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Re: st: Chow Test Statistic


From   Richard Williams <richardwilliams.ndu@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Chow Test Statistic
Date   Fri, 17 Jun 2011 10:27:48 -0500

At 12:56 AM 6/17/2011, Ian Li wrote:
Dear Statalisters,

I am analysing a linear model of labour market earnings using OLS, which can be written as:

y = a0 + B1X1+B2X2+...+BnXn+e

The same equation was estimated for disaggregated sub-groups of the data, say, for males and females.

I would like to comnpute the Chow test statistic to see if the beta estimates for females differ from those of males, for all the variables used in the analysis.

I have read the FAQ on doing that:
http://www.stata.com/support/faqs/stat/chow.html

which suggests the use of interaction terms to compute the Chow test statistic. As I have over 70 variables in the model, this is quite a tedious process. Can anyone please suggest an easier way to do this?

As Maarten notes, using interactions really isn't that hard to do in Stata 11.

That same FAQ also shows you how to do a Chow test by estimating separate regressions for each group and contrasting it with the pooled regression. A few calculations are required but the number of variables does not affect how complicated those calculations are.

You can also use the -suest- command. Here is a slightly modified version of the example that appears in the help for -suest-.

webuse income
regress inc edu exp if male
estimates store Male
regress inc edu exp if !male
estimates store Female
suest Male Female
* Test whether all coeff are same, including intercepts
test [Male_mean = Female_mean], constant coef
* Test whether all the coefficients are same, except intercepts
test [Male_mean = Female_mean], coef

When doing a Chow test, you may or may not want to impose the constraint that the intercepts are equal. It is pretty common to allow them to be different while all other coefficients are constrained to be the same.



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Richard Williams, Notre Dame Dept of Sociology
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