## November 07, 2007

### ec226 – How to be robust.

(If you are an MSc student, you might be interested in how to use robust standard errors in eviews).

As mentioned in today's classes, we do not generally assume normality and homoskedasticity, so, provided we have a large sample, we employ a robust estimator for the variance of the OLS estimator which allows for heteroskedasticity.

The video below shows:

• how to tell eviews that you want the robust standard errors.
• how to obtain the correct test statistics for the hypothesis that all the slope coefficients are equal to zero (using the Wald option after estimation)

You should use the same command to carry out tests on a subset of coefficients as you are asked to do in excercise sheet 4.

Keep in mind that the equation being estimated is:

$%7Elog%28earnings_i%29%3D%5Calpha%2B%5Cbeta_1%7Es_i%7E%2B%5Cbeta_2%7Easvabc_i%7E%2B%7E%5Cvarepsilon_i%7E$

If the video below does not appear (you need a Flash reader installed, click on PLAY, you should also be able to zoom-in by right-clicking on it) or it takes ages to upload, this pdf briefly guides you through the same things. robuststuff.pdf.

Feel free to ask if anything is not clear. I have now enabled anonymous comments.

Please, do try to solve the rest of excercise sheet 4 before the next class.

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## November 2007

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