Econ483 Selected Topics in Program Evaluation

Fall 2015

Goal: The course will provide an introduction to the statistical tools designed to evaluate causal effects of public programs.

By the end of the course, students should be able to conduct and to critically assess the validity of program evaluation studies.

  • This is a methodological course.

  • The foundational basis for this course is BUEC333. You must have taken BUEC333 to be able to take this course.

A precise mathematical understanding of concepts is crucial to good applications.

Topics we will cover include: randomized experiments, observational studies with and without ignorable treatment assignment, instrumental variables, regression discontinuity, and sensitivity analysis.

Take-home exams:

  • Exam 2 due Nov 10

  • Exam 3 due Nov 24

    • Exam 3 is a replication exercise of Waldinger (2010). Exam 3. Paper. Data.

    • Taken from Waldinger's website

Schedule to Exam 1 - in class exam on Sept 29

Lecture 1 09/08. Causality. The potential outcome framework for causal inference. The Rubin Causal Model.

Reading

(1) Up to 1.6 in Ch 1 in Imbens and Rubin book.

Extra readings:

(1) Holland (1986) pdf, (2) Little and Rubin (2000) pdf, (3) Rubin (2005) pdf, (4) Winship and Morgan (1999) pdf

Lecture 2 09/15. Average treatment effects with and without randomization. Unconfoundedness and olverlap. Selection bias.

Readings

(1) Chapter 1 in Mastering Metrics

(2) Chapter 2 in Mostly Harmless Econometrics (MHE)

(3) Up to Section 2.3.2 in Duflo et al. (2008)

(4) Selection bias blog

Extra readings:

(1) Section 3.2 in Duflo and Kremer

(2) Up to Section IV in Blundell and Costa-Diaz (2009)

HW Homework due 9/22

  • link

  • solution

(1) Returns to Plastic Surgery in Marriage and Labor Markets by Lee and Ryu

(2) Beauty and the Labor Market by Hamermesh and Biddle

Lecture 3 09/22. More on unconfoundedness and overlap. Selection bias. ATE and linear regression.

Extra reading:

(1) Roe and Just (2009)

Exam 1 09/29. Up and to including Lecture 3.

Exam and solutions

Max 18, Min 5, Average 15.31 (77%), Std dev 3.66 (18%)

Schedule to Exam 2 - take home exam due Nov 10

Lecture 4 10/06. Causal effects and regression analysis.

Reading

(1) Section 2.2.1 in Angrist and Krueger (1999)

Extra reading:

(1) Sections 9.2, 9.5, and 9.6 here

Lecture 5 10/13. More on regression analysis. Matching. Causal graphs. IV.

Reading

(1) Sections 3.2, 3.3.1, 4.1 (up to 4.1.2) in Mostly Harmless Econometrics

(2) Chapter 3 in MM

(3) Causal graphs and IV

(4) Section 2.2.3 in Angrist and Krueger (1999)

Lecture 6 10/20. Instrumental variables.

Readings

(1) Using IVs to learn more from social policy experiments up to page 11

Extra reading:

(1) Section 2.5.4 here

(2) Instrumental variables

HW Homework due 10/27

Schedule to Exam 3 - take home exam due Nov 24

Lecture 8 11/03. Difference-in-differences.

Reading

(1) Section 2.2.2 in Angrist and Krueger (1999)

(2) Section 5.2 in Mostly Harmless

(3) Youtube videos

Intro to DID

Panel data, parallel trends, and DID 1 2 3

Applications:

Effect of Minimum Wage on Employment video

Effect of Immigration on Employment video

Lecture 9 11/10. Exam 2 due.

Lecture 10 11/17. More on DID.

Lecture 11 11/24 Exam 3 due. Fixed effects.

Presentations 12/01. Papers for presentations:

  • Angrist and Evans (1998):

    • Children and Their Parents' Labor Supply: Evidence from Exogenous Variation in Family Size

  • Black (1999):

    • Do Better Schools Matter? Parental Valuation of Elementary Education.

  • Card and Krueger (1994):

    • Minimum Wages and Employment: A Case Study of the Fast Food Industry in New Jersey and Pennsylvania

  • Dale and Krueger (2002):

    • Estimating the Payoff to Attending a More Selective College

  • Levitt (1996):

    • The Effect of Prison Population Size on Crime Rates: Evidence from Prison Overcrowding Litigation

  • Meyer et al (1995):

    • Worker’s Compensation and Injury Duration: Evidence from a Natural Experiment

  • Sacerdote (2007):

    • How Large Are the Effects from Changes in Family Environment? A Study of Korean American Adoptees

Lecture 7 10/27. IV and 2SLS.

(1) Youtube videos

  • Aaronson (1998): Using Sibling Data to Estimate the Impact of Neighborhoods on Children's Educational Outcomes

  • Bogart and Cromwell (1999): How Much Is a Neighborhood School Worth?

  • Black et al. (2003): Is the Threat of Reemployment Services More Effective Than the Services Themselves? Evidence from Random Assignment in the UI System.

  • Fikelstein et al (2012): The Oregon Health Insurance Experiment: Evidence from the First Year