Topics: selection on observables; conditional independence assumption

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Apr 30 (Monday)

Topics:

Due

Readings

• Mastering ‘Metrics, Ch. 2: “Regression”
• Mastering ‘Metrics, Ch. 6.1: “Schooling, Experience, and Earnings”
• Gelman and Hill (2007) “Causal inference using more advanced models”, Chapter 10 in Data Analysis Using Regression and Multilvel/Hierarchical Models.

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May 2 (Wednesday)

Due

Readings

• Nunn and Wantchekon (2011) “The Slave Trade and the Origins of Mistrust in Africa” American Economic Review.
• Matching as a Regression Estimator
• Aronow and Samii (2015) “Does Regression Produce Representative Estimates of Causal Effects?” American Journal of Political Science
• Keele, Elwert, Stevenson (2015) “The Perils of the All Cause Model“
• Iacus, King, and Porro (2012) “Causal Inference Without Balance Checking: Coarsened Exact Matching.” Political Analysis
• Gary King and Langche Zeng. 2006. “The Dangers of Extreme Counterfactuals” Political Analysis
• Ho, Imai, King, and Stuart. 2007. “Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference” Political Analysis
• Imai, Keele, Tingley, and Yamamoto. (2011). “Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies” American Political Science Review.

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May 4 (Friday)

Topics:

Due

Readings

None