MY457      Half Unit
Causal Inference for Observational and Experimental Studies

This information is for the 2015/16 session.

Teacher responsible

Dr Dominik Hangartner COL8.03

Availability

This course is compulsory on the MSc in Political Science and Political Economy. This course is available on the MPhil/PhD in Accounting, MSc in Social Research Methods, MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (Research) and MSc in Statistics (Research). This course is available with permission as an outside option to students on other programmes where regulations permit.

Pre-requisites

Students must have completed Applied Regression Analysis (MY552) and Fundamentals of Social Science Research Design (MY400).

Knowledge of multiple linear regression and some familiarity with generalised linear models, to the level of MY552 (MI452) or equivalent. Familiarity with notions of research design in the social sciences, to the level of MY400 (Mi453) or equivalent.

Course content

This course provides an introduction to statistical methods used for causal inference in the social sciences. Using the potential outcomes framework of causality, topics covered include research designs such as randomized experiments and observational studies. We explore the impact of noncompliance in randomized experiments, as well as nonignorable treatment assignment in observational studies. To analyze these research designs, the methods covered include matching, instrumental variables, difference-in-difference, and regression discontinuity. Examples are drawn from different social sciences. The course includes computer classes, where standard statistical computer packages (Stata or R) are used for computation.

Teaching

20 hours of lectures and 10 hours of computer workshops in the LT.

Formative coursework

Exercises from the computer classes are submitted for feedback.

Indicative reading

Angrist, J. D. and Pischke, J.-S. (2009). Mostly Harmless Econometrics. Princeton University Press. Rosenbaum, L. (2010). Design of Observational Studies. Springer.

Assessment

Exam (100%, duration: 2 hours) in the main exam period.

Key facts

Department: Methodology

Total students 2014/15: 54

Average class size 2014/15: 13

Controlled access 2014/15: No

Lecture capture used 2014/15: Yes (LT)

Value: Half Unit

Guidelines for interpreting course guide information

Course survey results

(2011/12 - 2013/14 combined)

1 = "best" score, 5 = "worst" score

The scores below are average responses.

Response rate: 93.6%

Question

Average
response

Reading list (Q2.1)

2.3

Materials (Q2.3)

1.9

Course satisfied (Q2.4)

1.7

Lectures (Q2.5)

1.5

Integration (Q2.6)

1.5

Contact (Q2.7)

1.8

Feedback (Q2.8)

1.8

Recommend (Q2.9)

Yes

80.9%

Maybe

15.3%

No

3.8%