Lecture 1: Multiple Regression Analysis: Introduction, Slides

Lecture 2: Multiple Regression Analysis: Properties, Slides, (Empirical example - WAGE2, VOTE1, code) (Interpreting STATA output SRM, MRM)

Lecture 3: Multiple Regression Analysis: Properties, Slides, (Empirical example - WAGE2, code) 

Lecture 4: Multiple Regression Analysis: Properties, Slides

Lecture 5: Multiple Regression Analysis: Inference, Slides, (Empirical example - WAGE2, code)

Lecture 6: Multiple Regression Analysis: Inference, Slides, (F-distribution, code for FWL) 

Lecture 7: Multiple Regression Analysis: Matrix Approach, Slides, (Empirical example - WAGE2, code) (Optional material - matrix algebra)

Lecture 8: Multiple Regression Analysis: Matrix Approach, Slides

Lecture 9: Multiple Regression Analysis: WLS & GLS, Slides, (Optional material - asymptotics)

Lecture 10: Rubin's Causal Model, Slides, (Potential outcomes framework)

Lecture 11: Rubin's Causal Model, Slides, (Potential outcomes framework)

Lecture 12: Instrumental Variables, Slides

Lecture 13: Instrumental Variables, Slides, (Empirical example - Paper, CARD, code)

Lecture 14: Panel Data and Fixed Effects, Slides, (Panel Data)

Lecture 15: Panel Data and Fixed Effects, Slides, (Additional material - slides, data, code)

Lecture 16: Panel Data and First Differences, Slides, (Empirical example - data, code)

Lecture 17: Difference-in-Differences, Slides, (Card and Krueger - code)

Lecture 18: Difference-in-Differences, Slides, (DiD)

Lecture 19: Clustering and Standard Errors, Slides, (Empirical example - data, code)

Lecture 20: Clustering and Standard Errors, Slides, (Optional material)

Lecture 21: Regression Discontinuity Design, Slides, (Simulation example - code, Additional material - RDD)

Lecture 22: Regression Discontinuity Design, Slides, (RDD in STATA, data, code, manipulation, data, code)

Lecture 23: Class Discussion on Causal Methods

Lecture 24: Class Presentations

Lecture 25: Class Presentations

Lecture 1: Introduction - Lower Pollution, Longer Lives (A Polluted Mind), (slides)

Lecture 2: Introduction - Market Failure and Pollution, (slides)

Lecture 3: Introduction - Mechanisms, (slides, Tax, PES)

Lecture 4: Space - Applications of Satellite Data, (slides, Data resources - NASA, ISRO, SHRUG, CEDA, FAOSTAT, GAEZ, WBOD, GIS with R)

Lecture 5: Space - Applications of Satellite Data, (Spatial data with STATA, NASA-FIRMS)

Lecture 6: Air - Group 1: The EKC Hypothesis

Lecture 7: Air - Group 1: The Critique of EKC Hypothesis