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Frank Raulf's Blog – November 2019 Archive (1)

Omitted Variables in Linear Regressions

The importance of completeness of linear regressions is an often-discussed issue. By leaving out relevant variables the coefficients might be inconsistent.

But why on earth?! 

Assuming a linear complete model of the form:

z = a + bx + cy + ε.

Where z is supposed to be dependent, x and y are independent and ε is the error term.

Now we drop y to check…

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Added by Frank Raulf on November 13, 2019 at 2:00am — No Comments

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