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How can one show that the OLS estimators of the slopes in a multiple linear model that contains an intercept are obtained by transforming the data to deviations from their means and then regressing the dependent variable y in deviation form on the explanatory variables, also in deviation form. Can you explain how you can get the OLS estimator of the intercept from the slope estimators.

How can one verify the bias formula by using the part above and result on the omitted variable bias (OMV)?

For example, to my understanding the bias due to the OMV is defined as $\beta_1 $+ ($X'_1$$X_1$)$^-1$ $X'_1$$X_2$$\beta_2 $ $\neq $ 0

Bonsaibubble
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  • Have a look at http://stats.stackexchange.com/questions/201919/utility-of-the-frisch-waugh-theorem/202030#202030 for an answer to your first question. For the second, what is "the" bias formula? – Christoph Hanck Nov 30 '16 at 15:29

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