*2017 Northwestern-Duke Main Causal Inference Workshop*
*[please recirculate to others who might be interested]*
Northwestern University and Duke University are holding our “main”
week-long workshop on Research Design for Causal Inference – our eighth
annual workshop -- at Northwestern Law School in downtown Chicago. We
invite you to attend. Our apologies for the length of this message.
*Workshop*: Monday – Friday, June 19-23, 2017
The workshop will be taught by world-class causal inference researchers.
See below for details. Registration is limited to around 100
participants. In the past we have filled the workshop quickly. Last year,
we filled especially quickly. So please register soon.
*For information and to register:*
www.law.northwestern.edu/research-faculty/conferences/
causalinference/frequentist/
Bernie Black [Northwestern University, Pritzker Law School, Institute for
Policy Research, and Kellogg School of Management, Department of Finance]
Mat McCubbins [Duke University, Department of Political Science and Law
School]
*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 natural or quasi
experiments and to pure observational studies, where part of the sample is
treated in some way, 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 causal inferences
one can draw from a research design, threats to valid inference, and
research designs that can mitigate those threats.
Most empirical methods courses survey a variety of methods. We will begin
instead with the goal of causal inference, and emphasize how to design
research to come closer to that goal. The methods are often adapted to a
particular study. Some of the methods are covered in PhD programs, but
rarely in depth, and rarely with a focus on causal inference and on which
methods to use with messy, real-world datasets and limited sample sizes.
Several workshop days will include a Stata “workshop” to 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), medicine, sociology, education, psychology, etc. –anywhere
that causal inference is important.
We will assume knowledge, at the level of an upper-level college
econometrics or similar course, of multivariate regression, including OLS,
logit, and probit; basic probability and statistics including conditional
and compound probabilities, confidence intervals, t-statistics, and
standard errors; and some understanding of instrumental variables. Despite
its modest prerequisites, this course should be suitable for most
researchers with PhD level training and for empirical legal scholars with
reasonable but more limited training. Even for recent PhD’s, there will be
much that you don’t know, or don’t know as well as you should.
*Workshop faculty (in order of appearance)*
Donald B. Rubin (Harvard University, Department of Statistics)
Donald Rubin is John L. Loeb Professor of Statistics, Harvard University.
His work on 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. Web page, with link to CV:
www.stat.harvard.edu/faculty_page.php?page=rubin.html
<https://urldefense.proofpoint.com/v2/url?u=http-3A__www.stat.harvard.edu_faculty-5Fpage.php-3Fpage-3Drubin.html&d=CwMFAg&c=yHlS04HhBraes5BQ9ueu5zKhE7rtNXt_d012z2PA6ws&r=UogPJ7VYoAeiC8NNwyY5AxLx8QgaRiMcicgAv7oi3tc&m=_8VwTWqWunmiMua_jjn4EFALP7WjPtEoGoGXRdtbf9g&s=ZD4Fz7abKxhxT2H5luEE1Rq87KlAumw4vZ_0KcowNAo&e=>;
Wikipedia: http://en.wikipedia.org/wiki/Donald_Rubin
<https://urldefense.proofpoint.com/v2/url?u=http-3A__en.wikipedia.org_wiki_Donald-5FRubin&d=CwMFAg&c=yHlS04HhBraes5BQ9ueu5zKhE7rtNXt_d012z2PA6ws&r=UogPJ7VYoAeiC8NNwyY5AxLx8QgaRiMcicgAv7oi3tc&m=_8VwTWqWunmiMua_jjn4EFALP7WjPtEoGoGXRdtbf9g&s=9DyY2nvDuXc1INLNeMtxWYvmaC46nuNl15t7onkyl5I&e=>
Alberto Abadie (Massachusetts Institute of Technology, Department of
Economics)
Alberto Abadie is Professor of Economics at the Massachusetts Institute of
Technology. Principal research interests: econometrics; program evaluation
*. *Web page with link to CV: http://economics.mit.edu/faculty/abadie
<https://urldefense.proofpoint.com/v2/url?u=http-3A__economics.mit.edu_faculty_abadie&d=CwMFAg&c=yHlS04HhBraes5BQ9ueu5zKhE7rtNXt_d012z2PA6ws&r=UogPJ7VYoAeiC8NNwyY5AxLx8QgaRiMcicgAv7oi3tc&m=_8VwTWqWunmiMua_jjn4EFALP7WjPtEoGoGXRdtbf9g&s=ru5lpmsw0dxWfIuQ0DaGHqZCo65FTGVNEYtI2sLR6ag&e=>.
Papers on SSRN: http://ssrn.com/author=198468
<https://urldefense.proofpoint.com/v2/url?u=http-3A__ssrn.com_author-3D198468&d=CwMFAg&c=yHlS04HhBraes5BQ9ueu5zKhE7rtNXt_d012z2PA6ws&r=UogPJ7VYoAeiC8NNwyY5AxLx8QgaRiMcicgAv7oi3tc&m=_8VwTWqWunmiMua_jjn4EFALP7WjPtEoGoGXRdtbf9g&s=BMhsyV57dEfULFYv9JFLACd1vMKLd5muHr0aKj-ox4Y&e=>
.
Jens Hainmueller (Stanford University, Department of Political Science)
Jens Hainmueller is Associate Professor in the Stanford Political Science
Department. He also holds a courtesy appointment in the Stanford Graduate
School of Business. His research interests include statistical methods,
political economy, and political behavior. Web page with link to CV:
http://www.stanford.edu/~jhain//
<https://urldefense.proofpoint.com/v2/url?u=http-3A__www.stanford.edu_-257Ejhain_&d=CwMFAg&c=yHlS04HhBraes5BQ9ueu5zKhE7rtNXt_d012z2PA6ws&r=UogPJ7VYoAeiC8NNwyY5AxLx8QgaRiMcicgAv7oi3tc&m=_8VwTWqWunmiMua_jjn4EFALP7WjPtEoGoGXRdtbf9g&s=K0NwWy219fabZd7a_o42Fs9XwvXd4GZn3sUqOqrLqG4&e=>*.
Papers on SSRN: https://ssrn.com/author=739013
<https://ssrn.com/author=739013>.*
*Workshop outline*
*Monday June 19 (Don Rubin)*
*Introduction to Modern Methods for Causal Inference*
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. Causal inference as a missing data problem, and imputation of
missing potential outcomes. Rerandomization. One-sided and two-sided
noncompliance.
*Tuesday June 20 (Alberto Abadie)*
*Designs for “Pure” Observational Studies*
The core, untestable requirement of selection [only] on observables.
Ensuring covariate balance and common support. Subclassification,
matching, reweighting, and regression estimators of average treatment
effects. Propensity score methods.
*Wednesday June 21 (Alberto Abadie)*
*Instrumental variable methods*
Causal inference with instrumental variables (IV), including (i) the core,
untestable need to satisfy the “only through” exclusion restriction; (ii)
heterogeneous treatment effects; and (iii) intent-to-treat designs for
randomized trials (or quasi-experiments) with noncompliance.
*Thursday June 22 (Jens Hainmueller)*
*Panel Data and Difference-in-Differences*
Panel data methods: pooled OLS, random effects, correlated random effects,
and fixed effects. Simple two-period DiD. The core “parallel changes”
assumption. Testing this assumption. Leads and lags and distributed lag
models. When does a design with unit fixed effects become DiD?
Accommodating covariates. Triple differences. Robust and clustered
standard errors.
*Friday morning June 23 (Jens Hainmueller)*
*Regression Discontinuity*
(Regression) discontinuity (RD) research designs: sharp and fuzzy designs;
bandwidth choice; testing for covariate balance and manipulation of the
threshold; discontinuities as substitutes for true randomization and
sources of convincing instruments.
*Friday afternoon: Feedback on your own research*
Attendees will present their own research design questions from current
work in breakout sessions and receive feedback on research design. Session
leaders: Bernie Black, Mat McCubbins, Jens Hainmueller. Additional
parallel sessions if needed to meet demand.
*Stata and R sessions*
On Tuesday, Wednesday, and Thursday, we will either run parallel Stata and
R sessions to illustrate actual code to implement the designs discussed in
the lectures, or build Stata code into the lecture slides.
*Registration and Workshop Cost*
tuition is $850 ($500 for graduate students (PhD, SJD, or law) and
post-docs; $350 for Northwestern or Duke-affiliated attendees). The
workshop fee include all materials, temporary Stata 14 license, breakfast,
lunch, snacks, and an evening reception on the first workshop day.
Amounts will increase by $50 on May 1, 2016 (but the workshop is likely to
fill up before then). You can cancel byMay 16, 2017 for a 75% refund and
by June 1, 2017 for a 50% refund (in each case, less credit card processing
fee), but there are no refunds after that.
We know the workshop is not cheap. We use the funds to pay our speakers
and for meals and other expenses; we don’t pay ourselves.
*Workshop Schedule*
You should plan on full days, roughly 9:00-5:00. Breakfast will be
available at 8:30.
*Workshop Organizers*
Bernard Black (Northwestern University)
Bernie Black is Nicholas J. Chabraja Professor at Northwestern University,
with positions in the Pritzker School of Law, the Institute for Policy
Research, and the Kellogg School of Management, Finance Department.
Principal research interests: health law and policy; empirical legal
studies, law and finance, international corporate governance. Web page
with link to CV:
www.law.northwestern.edu/faculty/profiles/BernardBlack/. Papers
on SSRN: http://ssrn.com/author=16042
<https://urldefense.proofpoint.com/v2/url?u=http-3A__ssrn.com_author-3D16042&d=CwMFAg&c=yHlS04HhBraes5BQ9ueu5zKhE7rtNXt_d012z2PA6ws&r=UogPJ7VYoAeiC8NNwyY5AxLx8QgaRiMcicgAv7oi3tc&m=_8VwTWqWunmiMua_jjn4EFALP7WjPtEoGoGXRdtbf9g&s=s2INxVNcHFV9TZiUG3pn-V_p0cPLAVWqif0nMb4MLyg&e=>
.
Mathew McCubbins (Duke University)
Professor of Political Science and Law at Duke University, with positions
in the Political Science Department and the Law School, and director of the
Center for Law and Democracy. Principal research interests: democratic
institutions, legislative organization; behavioral experiments*,
*communication,
learning and decisionmaking; statutory interpretation, administrative
procedure, research design; network economics. Web page with link to CV:
www.mccubbins.us
<https://urldefense.proofpoint.com/v2/url?u=http-3A__www.mccubbins.us&d=CwMFAg&c=yHlS04HhBraes5BQ9ueu5zKhE7rtNXt_d012z2PA6ws&r=UogPJ7VYoAeiC8NNwyY5AxLx8QgaRiMcicgAv7oi3tc&m=_8VwTWqWunmiMua_jjn4EFALP7WjPtEoGoGXRdtbf9g&s=i8LaCzedl11IZVOvi9_6ovdSEqAI2Up0OISQKn9NwxQ&e=>
. Papers on SSRN: http://ssrn.com/author=17402
<https://urldefense.proofpoint.com/v2/url?u=http-3A__ssrn.com_author-3D17402&d=CwMFAg&c=yHlS04HhBraes5BQ9ueu5zKhE7rtNXt_d012z2PA6ws&r=UogPJ7VYoAeiC8NNwyY5AxLx8QgaRiMcicgAv7oi3tc&m=_8VwTWqWunmiMua_jjn4EFALP7WjPtEoGoGXRdtbf9g&s=YRhVej_ocJJsmwY1VHVhhgcEMyvabWHBX7pBEW9CG1s&e=>
.
*Questions about the workshops: *Please email Bernie Black (
[log in to unmask]) or Mat McCubbins ([log in to unmask]) for
substantive questions or fee waiver requests, and Michael Cooper (
[log in to unmask] for logistics and registration.
--
Ryan M. Welch, Ph.D.
Postdoctoral Associate
School of Politics and Global Studies
Arizona State University
http://rmerrillwelch.wix.com/ryan-welch
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