OmittedVars - Omitted Variables Bias Charlie Gibbons...

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Unformatted text preview: Omitted Variables Bias Charlie Gibbons Economics 140 October 18, 2009 Outline 1 The problem 2 The bias 3 An example 4 Conclusion The problem Omitted variables bias is the biggest problem in econometrics. Suppose that the true model of a process is Y i = + 1 x i + 2 x i + i , but you run Y i = + 1 x i + i , where i = i + 2 x i . Here, you omitted z i , an important predictor of Y i . We use different Greek letters for the estimated parameters because we are estimating a different (biased) model. The problem Omitted variables arise in two circumstances: 1 You chose the wrong model. 2 The necessary variable isnt measurable ( i.e. , ambition) or isnt in your data set ( i.e. , IQ). The bias Suppose that you have a true model Y = + 1 x 1 i + + k x ki + k +1 z i + i . Now suppose that you omit the variable z i and instead run Y = + 1 x 1 i + + k x ki + i . The bias Imagine that you knew z i and you run this regression: z i = + 1 x 1 i + + k x ki + i , a regression of your omitted variable on all the variables that you did include....
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OmittedVars - Omitted Variables Bias Charlie Gibbons...

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