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Causal Inference for the Social Sciences
PS C236A / Stats C239A
Fall 2009
Lecture: Mondays 4-7 in 200 Wheeler
Section: Wednesdays 2-4 in 200 Wheeler

Contact Information:
Instructor: Jas Sekhon
sekhon[at]berkeley(dot)edu
Office Hours: Monday 2 pm - 3:30 pm
GSI: Danny Hidalgo
fdhidalgo[at]berkeley(dot)edu
Office Hours: Thursday 10:30am - 12pm, 715 Barrows
GSI: Erin Hartman
ekhartman[at]berkeley(dot)edu
Office Hours: Tuesday 3:45 pm - 5:15 pm, 715 Barrows


Class Syllabus
Section Syllabus
Lecture Notes: presentation version; print version


Section Notes

Section 1 - OLS
Section 2
Section 3 - Freedman
Section 4 - Randomization Inference
Section 5 - Univariate Matching and Propensity Score
Section 6 - Regression Discontinuity
Section 7 - Cross-Validation
Section 8 - GenMatch
Section 9 - KS test
Section 10 - The Bootstrap

Section Code Examples

Section 1 - Intro to R, data
Section 2 - Lists, Functions, Matrices, and Plots
Section 3 - Random Variables
Section 4 - Randomization Inference, data
Section 5 - Univariate Matching and Propensity Score, data
Section 6 - Regression Discontinuity, data
Section 7 - Cross-validation, Balance Checking
Section 8 - GenMatch
Section 9 - Balance Plots, more on loss functions
Section 10 - The Bootstrap, data 1, data 2


Assignments

- Problem Set 1, data
- Problem Set 2
- Problem Set 3, data
- Problem Set 4, data, codebook
- Problem Set 5, article, data
- Problem Set 6, data
- Problem Set 7, data, article, codebook
- Problem Set 8, data
- Problem Set 9, Water for Life Codebook

Solutions

- Problem Set 1 Solutions
- Problem Set 2 Solutions, R code
- Problem Set 3 Solutions, R code
- Problem Set 4 Solutions, R code
- Problem Set 5 - See Section 7 notes
- Problem Set 6 Solutions
- Problem Set 7 and Problem Set 9 sample code


Readings

- Chapter 1 and 2 from Fisher's The Design of Experiments

Other Useful Materials and Links

Rocio Titiunik's Website for the Course:
Probability Notes
Intro Matrix Algebra Notes
Identification of treatment effects