2012 Workshop on Research Design for Causal Inference

We would like to invite you to attend the third annual workshop on Research Design for Causal Inference, sponsored by Northwestern University, University of Southern California, the Society for Empirical Legal Studies, and The Searle Center on Law, Regulation, and Economic Growth.

Dates and Location: Monday-Friday, August 6-10, 2012, at Northwestern Law School, Chicago, IL

Teaching Faculty and Organizers | Registration | Workshop Schedule | Hotels

We are very close to full (as of April 13), so please register soon.

Workshop Overview

Research design for causal inference is at the heart of a "credibility revolution" in empirical research. We will cover the design of true randomized experiments and contrast them to simulations and quasi-experiments, where part of the sample is "treated" in some way, and the remainder is a control group, but the researcher controls neither the assignment of cases to treatment and control groups nor administration of the treatment. We will assess the kinds of causal inferences one can and cannot draw from a research design, threats to valid inference, and research designs that can mitigate those threats.

Most empirical methods courses begin with the methods. They survey how each method works, and what assumptions each relies on. We will begin instead with the goal of causal inference, and discuss how to design research to come closer to that goal. The methods reflect the goal and are often adapted to the needs of a particular study. Some of the methods we will discuss are covered in PhD programs, but rarely in depth, and rarely with a focus on causal inference and on which methods to prefer for messy, real-world datasets with limited sample sizes.

Each day will conclude with a Stata "workshop" where we will illustrate selected methods with real data and Stata code.

Target audience
Quantitative empirical researchers (faculty and graduate students) in social science, including law, political science, economics, many business-school areas (finance, accounting, management, marketing, etc), sociology, education, psychology, etc. – indeed anywhere that causal inference is important.

Minimum prior knowledge
We will assume knowledge, at the level of an upper-level college econometrics or applied statistics course, of how to run multivariate regressions, including OLS, logit, and probit; familiarity with basic probability and statistics including conditional and compound probabilities, confidence intervals, t-statistics, and standard errors; and some understanding of instrumental variables are and how they are used.

Despite its modest prerequisites, this course should be suitable for most researchers with PhD level training and for empirical legal scholars with reasonable even if more limited training. Especially for recent PhD's, there will be overlap with what you already know, but much that you don't know, or don't know as well as you should.

Teaching Faculty

We are fortunate to have recruited outstanding experts in causal research design to teach the workshop sessions. Click on the links below and see for yourself.

  • Donald B. Rubin (Harvard University) is John L. Loeb Professor of Statistics, Harvard University. His work on what today is often called the "Rubin Causal Model" is central to modern understanding of when one can and cannot infer causation from regression. Principal research interests: statistical methods for causal inference; Bayesian statistics; analysis of incomplete data. Wikipedia

  • Justin McCrary (University of California, Berkeley) is Professor of Law, University of California, Berkeley. Principal research interests: crime and urban problems, law and economics, corporations, employment discrimination, and empirical legal studies.

  • Alberto Abadie (Harvard University) is Professor of Public Policy at the Kennedy School of Government at Harvard University. Principal research interests: econometrics; program evaluation. Papers on SSRN

  • Jens Hainmueller (MIT, Political Science) is Associate Professor at the Massachusetts Institute of Technology. Principal research interests: applied statistics, immigration, political economy, program evaluation. Web page with link to CV and synthetic controls software.

Conference Organizers

  • Bernard Black (Northwestern University, Law and Kellogg School of Management) is Nicholas J. Chabraja Professor at Northwestern University, with positions in the Law School and Kellogg School of Management. Principal research interests: law and finance, international corporate governance, health law and policy; empirical legal studies. Papers on SSRN

  • Mathew McCubbins (University of Southern California) is Provost Professor of Business, Law and Political Economy at University of Southern California, with positions in the Marshall School of Business, the Gould School of Law, and the Department of Political Science. Principal research interests: legislative organization; communication, learning and decisionmaking; research design; network economics. Papers on SSRN

Registration and Workshop Cost

Registration is limited to 100 participants.We are very close to full (as of April 13), so please register soon.

Tuition is $850; with a discounted rate of $500 for graduate students (PhD, SJD, or law) and post-doctoral fellows. The workshop fee includes all materials, a temporary Stata license, breakfast, lunch, snacks, and Monday evening reception. All amounts will increase by $50 on July 2, 2012 (but we're likely to fill up well before then).

Registration deadline: July 20, 2012. You can cancel by July 2 for a 75% refund and by July 20 for a 50% refund (in each case, less credit card processing fee), but there are no refunds after that.

For Northwestern or USC-affiliated attendees, we will charge only $300 (basically our marginal cost for meals and incidental expenses) if you in fact attend, but will charge the regular rate if you register and then don't come, because you occupied a spot we could have provided to someone else.

Register

For questions about the workshop please email Bernie Black bblack@northwestern.edu or Mat McCubbins mmccubbins@law.usc.edu for substantive questions or fee waiver requests, and Michael Cooper causalinference@law.northwestern.edu for logistics and registration.

Workshop Schedule

Monday, August 6 (Don Rubin)
Overview of causal inference and the Rubin "potential outcomes" causal model. The "gold standard" of a randomized experiment. Treatment and control groups, and the core role of the assignment (to treatment) mechanism. Multiple imputation of missing potential outcomes.

Reading: Imbens and Rubin, Causal Inference in Statistics and Social Sciences, chapters 1-3 (chapter 2 is background and can be skipped).
Stata examples: [to come]

Tuesday, August 7 (Justin McCrary)
Instrumental variables (IV), including (i) the core (untestable) need to satisfy the "only through" exclusion restriction, (ii) heterogeneous treatment effects; (iii) randomized trials or quasi-experiments with noncompliance.

Reading: Angrist and Pischke, Mostly Harmless Econometrics, chaps. 2,4
(Regression) discontinuity (RD) research designs: sharp and fuzzy designs; bandwidth choice; need to test (not just assume) covariate balance; discontinuities as substitutes for true randomization and as sources of convincing instruments.
A gentle introduction to GMM (generalized method of moments)

Stata examples: IV (good and bad instruments); sharp and fuzzy RD

Wednesday, August 8 (Alberto Abadie)
Selection (only) on observables
Matching and subclassification
Comparing matching to regression
Propensity score methods

Reading: [to come]
Stata examples: estimating and using propensity scores; nnmatch.ado

Thursday, August 9 (Alberto Abadie)
Handling poorly matched observations
Introduction to difference-in-differences
Standard error issues (robust and clustered standard errors, bootstrapping)

Reading: [to come]
Stata examples: DiD and DiDiD examples; assessing covariate balance, standard errors

Thursday post-lunch talk (Bernie Black): Bloopers
Examples drawn from different areas of how to get causal inference wrong.

Friday morning, August 10 (Jens Hainmueller)
Panel data: Fixed and random effects, and the choice between then.
Synthetic controls and other advanced DiD topics.

Reading: [to come]

Friday afternoon: Feedback on your own research
Attendees will have an opportunity to present their own research questions from current work in breakout sessions (session leaders: Bernie Black, Mat McCubbins, Jens Hainmueller)
present your own research design issues; get group feedback (parallel sessions as needed to meet demand) (15 min to present, 15 min discussion)

Hotels

Chicago offers many options, but here are three good ones, all an easy walk to Northwestern and reasonably priced. All rates are before taxes.

  • Affinia Chicago Hotel, 166 East Superior Street, Chicago IL, (312) 787-6000. Closest to Northwestern, a bit nicer than the Allerton. Email: Chelsea Wagenblast. $175 plus tax for a standard room and $219 for a suite.
  • Allerton Hotel, 701 North Michigan Avenue Chicago IL, (312) 440-1500. $118 for Queen bed (Northwestern rate). $135 for a standard room or $155 plus tax for a standard one-bedroom suite. Older but nice hotel, smaller rooms.
  • Omni Chicago Hotel, 676 North Michigan Avenue, Chicago IL, (312) 944-6664. King or queen suite, $179 (Northwestern rate, all rooms non-smoking).

Chicago has some quite low-priced options. You might check online services, such as www.cheaphotels.com and www.hotwire.com. Hotwire can have especially good deals, but you won’t know what hotel you are at until the last minute.

Attendees have also suggested the following nearby options:

A number of other hotels in the area also offer discounts to Northwestern guests, visit our hotel information page for additional options.

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