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3.1 Regression Fundamentals
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3.1.1 Economic Relationships and the Conditional Expectation Function
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3.1.2 Linear Regression and the CEF
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3.1.3 Asymptotic OLS Inference
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3.1.4 Saturated Models, Main Effects, and Other Regression Talk
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3.2 Regression and Causality
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3.2.1 The Conditional Independence Assumption
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3.2.2 The Omitted Variables Bias Forumla
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3.2.3 Bad Control
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3.3 Heterogeneity and Nonlinearity
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3.3.1 Regression Meets Matching
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3.3.2 Control for Covariates Using Propensity Score
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3.3.3 Propensity-Score Methods vs. Regression
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3.4 Regression Details
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3.4.1 Weighting Regression
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3.4.2 Limited Dependent Variables and Marginal Effects
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3.4.3 Why is Regression Called Regression and What Does Regression-to-the-mean Mean?
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3.5 Appendix: Derivation of the Average Derivative Weighting Function
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