Outline

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Outline

• Why multiple variables? Omitted variable bias
• Extending our results to multiple regression and
  OLS
• Multicollinearity
• Measures of fit

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Omitted Variable Bias
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Conditions for Omitted variable bias
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Examples of Omitted variable bias
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Formula for Omitted Variable Bias
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The omitted variable bias formula
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Back to class size
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Return to omitted variable bias
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The Population Multiple Regression Model (SW
Section 6.2)
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The OLS Estimator in Multiple Regression (SW
Section 6.3)
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Example the California test score data
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Multiple regression in STATA
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The Least Squares Assumptions for Multiple
Regression (SW Section 6.5)
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Assumption 1 the conditional mean of u given
the included Xs is zero.
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The Sampling Distribution of the OLS Estimator
(SW Section 6.6)
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Multicollinearity, Perfect and Imperfect (SW
Section 6.7)
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The dummy variable trap
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Imperfect multicollinearity
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Imperfect multicollinearity, ctd.
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Measures of Fit for Multiple Regression (SW
Section 6.4)
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SER and RMSE
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R2 and
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R2 and , ctd.
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Measures of fit, ctd.