PPPA 8022 – Econometrics for Policy Research II

George Washington University
Trachtenberg School of Public Policy and Public Administration
Spring 2015

Syllabus available at http://home.gwu.edu/~lfbrooks/leahweb/teaching/pppa6022/2015/pppa8022_spring_2015.html

Course Description and Objectives

This course is the second in a two-part graduate sequence in econometrics. It follows the content from PPPA 6013.

As a result of completing this course you should be able to

Contact and Office Hours

Professor: Leah Brooks

Media and Public Affairs Building, Room 601F
Office Hours: Tuesdays 3 to 5 PM, and by appointment
lfbrooks at gwu.edu

Contact policy: I will do my best to answer emails within 24 hours during weekdays, or within 24 hours on the soonest weekday if you email on the weekend. If you do not hear from me within this time frame, you should assume that your email has been lost and you should re-send.

Teaching Assistant: Seth Brown

sbrown at air dot org
Office Hours Thursdays 6:10 to 8, MPA 601K -- for weeks without Stata workshops
Office hour rules of engagement

Course Logistics

Wednesdays, 6:10 to 8 pm
Rome 351
No final exam


PPPA 6013: Econometrics for Policy Research I
This class is substantially more difficult than PPPA 6013 and requires either familiarity with statistical programming, or the ability and willingness to learn this skill while taking the course.
Please see me to discuss if you are unsure whether this course is appropriate for you.


Required textbook: Angrist, Joshua D. and Pischke, Jorn-Steffen. Mostly Harmless Econometrics: An Empiricist's Companion.

The textbook is on order at the campus bookstore. I have tried to link to all remaining readings from this syllabus. Please let me know if you have difficulties with any of the links, or with permissions.
Readings are subject to change, given the pace at which we move through the material.

Course Overview

Class Sessions
Class Date Topic Handout Due
1 January 14 Causality and Regression Review
2 January 21 More Regression Review and Fixed Effects Paper proposal
3 January 28 Differences-in-differences Problem Set 1 Paper Proposal
4 February 4 Differences-in-differences extensions
5 February 11 Instrumental Variables I Problem Set 1
6 February 19 Instrumental Variables II Problem Set 2
7 February 25 Regression Discontinuity I
8 March 4 Regression Discontinuity II Quantitative progress Problem Set 2
no class March 11
9 March 18 Matching I Workshop
10 March 25 Matching II Display of Quantitative Progress
11 April 1 1/2 Catch-up/Requests, 1/2 In-class workshop Final paper
12 April 9 Student Presentations on Papers
13 April 15 Student Presentations on Papers
14 April 22 Structural Estimation Final Paper

Stata Workshops: Optional but Strongly Encouraged
Led by TA Seth Brown
6:10 to 8 pm
Date Topic Location
Tuesday January 20 Stata Basics Gelman B01
Monday February 2 Pre-problem set 1 Rome 205
Monday February 23 Pre-problem set 2 Rome 205

Course Content

Outline is preliminary and subject to change.

  1. Causation and Regression Review
    • MHE, Chapters 1, 2, and sections 3.1 (but not 3.1.3) and 3.2
    • Causation handout
    • Supplemental
      • Helpful overview: Imbens and Wooldridge, 2009. “Econometrics of Program Evaluation,” Journal of Economic Literature. [link]
      • Example of controlling for observables: Brooks et al, “The Cabals of a Few or the Confusion of a Multitude” American Economic Journal: Economic Policy 2011. [link]
  2. Fixed Effects
    • MHE, Section 5.1
    • Black, Sandra et al., 2005. “The More the Merrier? The Effect of Family Size and Birth Order on Childrens' Education” [link]
      • skip III.D.-III.G., and sections V & VI
  3. Differences-in-differences
    • MHE, Sections 5.2 and 5.2.1
    • Autor, David et al, “The Impact of Disability Benefits on Labor Supply: Evidence from the VA's Disability Compensation Program,” Working paper 2015. [link]
      • Skim section 5
  4. Differences-in-difference extensions
    • Milligan, Kevin. “Subsidizing the Stork: New Evidence on Tax Incentives and Fertility” Review of Economics and Statistics, 2005. [link]
      • Skip Section 5
    • Bertrand et al. “How Much Should We Trust Differences-in-differences Estimates?” Quarterly Journal of Economics, 2004. [link]
      • Skim Section 4, with the exception of 4C, which you should read carefully
  5. Instrumental Variables I
    • MHE, Sections 4.1 and 4.4
    • Angrist and Kreuger, “Does Compulsory School Attendance Affect Schooling and Earnings?”, Quarterly Journal of Economics, 1991. [link]
      • Section II.C is optional
  6. Instrumental Variables II
    • MHE, Section 4.6.4
    • Duranton, Gilles, et al, “Roads and Trade”, Review of Economic Studies. forthcoming. [link]
      • Skim sections 3 and 4; Sections 7.2 through 9 not required
    • Supplemental
      • Bound, Baker and Jaeger, “Problems with Instrumental Variables Estimation When the Correlation Between the Instruments and the Endogeneous Explanatory Variable is Weak,” Journal of the American Statistical Association, 1995. [link]
      • An entertaining lament from David Jaeger on the fate of this critique
  7. Regression Discontinuity I
    • MHE, Chapter 6
    • Lee and Lemiuex, “Regression Discontinuity Designs in Economics,” NBER Working Paper 14723, 2009. [link]
      • Read only through Section 3.3.
    • Keys, et al, “Did Securitization Lead to Lax Screening?” Quarterly Journal of Economics, 2010. [link]
      • Pages 307-334; focus on regression discontinuity design
  8. Regression Discontinuity II
    • Turner, Lesley, “The Road to Pell is Paved with Good Intentions: The Economic Incidence of Federal Student Grant Aid” U of Maryland Working Paper, 2013. [link]
      • Sections 5 and 6 are optional
  9. Matching I
    • MHE, Section 3.3 (skip starred section)
    • Todd, Petra, “A Practical Guide to Implementing Matching Estimators,” Unpublished notes, 1999. [link]
    • Brooks, Leah, “Volunteering to be Taxed: Business Improvement Districts and the Provision of Public Safety,” Journal of Public Economics 2008. [link]
      • Ignore Section 6
  10. Matching II: Synthetic Controls
    • Abadie, Diamond and Hainmueller, “Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program,” Journal of the American Statistical Association, 2009.[link]
    • Potential presentation by PhD student
  11. Quantile Regression and Bootstrapping
    • Poterba and Rueben, “The Distribution of Public Sector Wage Premia: New Evidence Using Quantile Regression Methods,” NBER Working Paper 4734, 1992. [link]
  12. Student Presentations
    • DW, MS, EF, JD
  13. Student Presentations
    • KY, RC, JS, MV, AK
  14. Structural Estimation
    • Steve Laufer, Federal Reserve Board, “Equity Extraction and Mortgage Default.” [link]


  1. Problem Sets (10%)
    • Problem sets are designed to practice the skills we learn in class
    • And to help you prepare with Stata for writing the paper
    • Turn them in at the beginning of class that they are due
    • Any problem set turned in after that receives half-credit
    • Problem sets should be typed
    • You're welcome to work with others, but you should each turn in your own work, in your own words
  2. Research Paper (70%)
    • 10 to 15 pages; no more than 15 pages
    • Paper is due at the final class, in class
    • Extensions will be given only the case of illness
    • Essays will be graded out of 100 points
    • Any essays submitted late will decline by ten points for each twelve hours the essay is late, e.g. if the essay is due on Friday and is received Monday, if it would have received 70%, it now receives 30%
    • To make sure you are on-track, we have two way-markers that each count for three percentage points of the paper grade
      • A proposal due January 28
      • Evidence that you've made progress on the quantitative front, due March 25
      • In-class workshop, where you comment on drafts, April 1
      • Late work for these way-marker projects receives a grade of zero
  3. Paper Summaries (10%)
    • For the semester, each of you will write three paper summaries
    • I'll randomly assign you to a week; feel free to trade weeks amongst yourselves
    • Write a one page summary of the paper we are discussing that week. At least a third of the summary should be a critique or extention of the article.
    • Weekly Assignments: [to be added here]
      Student Paper 1 Paper 2 Paper 3
      AK 4 5 9
      DW 2 6 9
      EF 3 5 8
      ER 5 8 10
      JD 3 8 9
      JS 6 8 10
      KY 2 4 7
      MS 6 7 10
      MV 2 3 4
      RC 6 7 8
  4. Class Participation (5%)
  5. Presentation on research paper (5%)
    • Comments on your classmates' presentations (2.5%)
    • Your presentation (2.5%)


Trachtenberg School Course Policies