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Unformatted text preview: Omitted Variables Irrelevant Variables Specification Searches Chapter 6 Specification: Choosing the Independent Variables Masao Ogaki Department of Economics, Ohio State University October 30, 2007 Masao Ogaki Department of Economics, Ohio State University Chapter 6 Specification: Choosing the Independent Variables Omitted Variables Irrelevant Variables Specification Searches Omitted Variables An omitted variable means that an important explanatory variable that has been left out of a regression equation. The bias caused by a leaving a variable out of a equation is called omitted variable bias . Suppose that the true regression model is Y i = β + β 1 X 1 i + β 2 X 2 i + i (1) If you omit X 2 , Y i = β + β 1 X 1 i + * i (2) Masao Ogaki Department of Economics, Ohio State University Chapter 6 Specification: Choosing the Independent Variables Omitted Variables Irrelevant Variables Specification Searches where * i equals * i = i + β 2 X 2 i (3) As long as X 1 i and X 2 i are correlated, this causes Classical Assumption III to be violated in the Regression ( ?? ). Assumption III: All explanatory variables are uncorrelated with the error term. This lead to a bias in the OLS estimator: E ( ˆ β 1 ) 6 = β 1 (4) Masao Ogaki Department of Economics, Ohio State University Chapter 6 Specification: Choosing the Independent Variables Omitted Variables Irrelevant Variables Specification Searches Exercises (a) Consider a production function that states that output ( Y ) depends on the amount of labor (...
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 Fall '07
 OGAKI
 Economics, Econometrics, Regression Analysis, Department of Economics, Ohio State University, Masao Ogaki Chapter

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