[Eeglablist] Registration open: 2022 Northwestern Causal Inference Workshops
Scott Makeig
smakeig at gmail.com
Fri Apr 15 09:21:41 PDT 2022
Dear Dr. Scott Makeig: I am writing on behalf of Prof. Bernie Black. We
would be grateful if you could circulate the announcement below to your
faculty and researchers.
Bernie
*************************************************************
Bernard S. Black
Chabraja Professor, Northwestern University
Pritzker Law School and Kellogg School of Management
375 East Chicago Ave., Chicago IL 60611
bblack at northwestern.edu
tel: law: 312-503-2784; Kellogg 847-491-5049; cell: 847-807-9599
papers on SSRN at: https://urldefense.proofpoint.com/v2/url?u=http-3A__ssrn.com_author-3D16042&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=DpI5MLF4unz1u_bt8FCAPoVY1g6v-AXQnHPTWhHMqJ7iZFsvDSstJ_fAsd5_q4rr&s=llZFV6TmInzEzxQXUMR3fBrQQzSuIVapb5g_lmRs1Co&e=
<https://urldefense.proofpoint.com/v2/url?u=http-3A__ssrn.com_author-3D16042&d=DwMFAw&c=-35OiAkTchMrZOngvJPOeA&r=KEnFjcsfiKF_BPOsgvPP912y1yQ0q05CJ14uAvMNdNQ&m=IKdtFkr2lwEliZwH7roaxkL0BIy5WRo-tpGFg7bsP22hSIeKar-kvPKECtqXXYMr&s=dbcO1EV15x-Qo8cN3hnQo2HYPjmim6f5mctxq3SEctY&e=>
************************************************************
2022 Northwestern Main and Advanced Causal Inference Workshops
*[please recirculate to others who might be interested]*
*After a COVID break during 2020 and 2021, we are excited to be holding our
11th annual workshop on Research Design for Causal Inference at *
*Northwestern* *Law School** in Chicago, IL. We invite you to attend. Our
apologies for the length of this message.*
*Main Workshop**: Monday – Friday, August 8-12, 2022*
*Advanced Workshop**: Monday – Wednesday, August 15-17, 2022*
*What’s special about these workshops are the speakers. They will be
taught by world-class causal inference researchers. See below for
details. *Registration is limited to 125 participants for each workshop.
There will also be a Zoom option, but please come in person if you can.
The online experience is not the same.
*For information and to register:*
https://urldefense.proofpoint.com/v2/url?u=https-3A__www.law.northwestern.edu_research-2Dfaculty_events_conferences_causalinference_&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=DpI5MLF4unz1u_bt8FCAPoVY1g6v-AXQnHPTWhHMqJ7iZFsvDSstJ_fAsd5_q4rr&s=FdwaVtQMicfXZQd1GEb5_8-X_HvhF_ZZmLEK2LNB8Pc&e=
<https://urldefense.proofpoint.com/v2/url?u=https-3A__www.law.northwestern.edu_research-2Dfaculty_events_conferences_causalinference_&d=DwMFAw&c=-35OiAkTchMrZOngvJPOeA&r=KEnFjcsfiKF_BPOsgvPP912y1yQ0q05CJ14uAvMNdNQ&m=IKdtFkr2lwEliZwH7roaxkL0BIy5WRo-tpGFg7bsP22hSIeKar-kvPKECtqXXYMr&s=8E1Ch0hEQF8_eoeFAfQGkByQ03zUEMcRACLqEB_IIgU&e=>
*Bernie Black [Northwestern University, Pritzker Law School, Institute for
Policy Research, and Kellogg School of Management, Department of Finance]*
*Scott Cunningham [Baylor University, Department of Economics]*
*Main Workshop Overview: *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 which
units are treated vs. control, nor administration of the treatment. We
will assess the causal inferences one can draw from specific “causal”
research designs, threats to valid causal 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 how to design a research
plan to come closer to that goal, using messy, real-world datasets with
limited sample sizes. The methods are often adapted to a particular study.
*Advanced Workshop **Overview: **The advanced workshop provides in-depth
discussion of selected topics that are beyond what we can cover in the main
workshop.* The principal topics for 2022 quantile and nonlinear
difference-in-differences, doubly robust estimation of causal effects; DiD
methods that address staggered treatments (applied to different units at
different times); and the application of machine learning methods to causal
inference.
*Target audience for main workshop: *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 confidence
intervals, *t*-statistics, and standard errors; and some understanding of
instrumental variables. This course should be suitable both for
researchers with recent PhD-level training in econometrics and for
empirical scholars with reasonable but more limited training.
*Target Audience for Advanced Workshop:* Empirical researchers who are
familiar with the basics of causal inference (from our main workshop or
otherwise), and want to extend their knowledge. We will assume
familiarity, but not expertise, with potential outcomes,
difference-in-differences, and panel data methods.
*Main Workshop Faculty (in order of appearance)*
Donald B. Rubin (Harvard University)
Donald Rubin is John L. Loeb Professor of Statistics Emeritus, at Harvard.
His work on the “Rubin Causal Model” is central to modern understanding of
causal inference with observational data. Principal research interests:
statistical methods for causal inference; Bayesian statistics; analysis of
incomplete data. Website:
https://urldefense.proofpoint.com/v2/url?u=https-3A__statistics.fas.harvard.edu_people_donald-2Db-2Drubin&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=DpI5MLF4unz1u_bt8FCAPoVY1g6v-AXQnHPTWhHMqJ7iZFsvDSstJ_fAsd5_q4rr&s=lEBn27XeQUI7TDTkyrqyflegdmXXBmCVZKC7kFn0RNg&e=
<https://urldefense.proofpoint.com/v2/url?u=https-3A__statistics.fas.harvard.edu_people_donald-2Db-2Drubin&d=DwMFAw&c=-35OiAkTchMrZOngvJPOeA&r=KEnFjcsfiKF_BPOsgvPP912y1yQ0q05CJ14uAvMNdNQ&m=IKdtFkr2lwEliZwH7roaxkL0BIy5WRo-tpGFg7bsP22hSIeKar-kvPKECtqXXYMr&s=finKh3l1BtC2pv_ncK7CSOfUmkfe3X8zygTR3EJRkM0&e=>.
Wikipedia: https://urldefense.proofpoint.com/v2/url?u=http-3A__en.wikipedia.org_wiki_Donald-5FRubin&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=DpI5MLF4unz1u_bt8FCAPoVY1g6v-AXQnHPTWhHMqJ7iZFsvDSstJ_fAsd5_q4rr&s=CaTwAs25FHtZQFl3klmpHynOX2NNhc--2Xo7bcXa5Qk&e=
<https://urldefense.proofpoint.com/v2/url?u=http-3A__en.wikipedia.org_wiki_Donald-5FRubin&d=DwMFAw&c=-35OiAkTchMrZOngvJPOeA&r=KEnFjcsfiKF_BPOsgvPP912y1yQ0q05CJ14uAvMNdNQ&m=IKdtFkr2lwEliZwH7roaxkL0BIy5WRo-tpGFg7bsP22hSIeKar-kvPKECtqXXYMr&s=V3tnhOS_zaKTD3WmMpQTNbzHFj-UORvTuKjoLngw5zQ&e=>
Pedro Sant’Anna (Vanderbilt University and Microsoft)
Pedro SantAnna is Assistant Professor of Economics at Vanderbilt
University. His research focus is on microeconometrics, including causal
inference methods and program evaluation. Website:
https://urldefense.proofpoint.com/v2/url?u=https-3A__as.vanderbilt.edu_economics_bio_pedro-2Dsantanna_-3Fwho-3Dpedro-2Dsantanna&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=DpI5MLF4unz1u_bt8FCAPoVY1g6v-AXQnHPTWhHMqJ7iZFsvDSstJ_fAsd5_q4rr&s=bphe-mzc9-RGLMRsvW_VwRzRs-h-4uWV5ZDd_K1b-xI&e=
<https://urldefense.proofpoint.com/v2/url?u=https-3A__as.vanderbilt.edu_economics_bio_pedro-2Dsantanna_-3Fwho-3Dpedro-2Dsantanna&d=DwMFAw&c=-35OiAkTchMrZOngvJPOeA&r=KEnFjcsfiKF_BPOsgvPP912y1yQ0q05CJ14uAvMNdNQ&m=IKdtFkr2lwEliZwH7roaxkL0BIy5WRo-tpGFg7bsP22hSIeKar-kvPKECtqXXYMr&s=wA8JwrtIP7H7I80qdZcLpDaEXGj6Rg0SyqkVgE9syfU&e=>
.
Rocio Titiunik (Princeton University)
Rocío Titiunik is Professor of Politics at Princeton University. She
specializes in quantitative methodology for the social sciences, with
emphasis on quasi-experimental methods for causal inference. Personal
Website: https://urldefense.proofpoint.com/v2/url?u=https-3A__scholar.princeton.edu_titiunik&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=DpI5MLF4unz1u_bt8FCAPoVY1g6v-AXQnHPTWhHMqJ7iZFsvDSstJ_fAsd5_q4rr&s=ySjIpVnCX0ZZhf-bbPW1yagkncYp6rty-NPJq6HE9NI&e=
<https://urldefense.proofpoint.com/v2/url?u=https-3A__scholar.princeton.edu_titiunik&d=DwMFaQ&c=yHlS04HhBraes5BQ9ueu5zKhE7rtNXt_d012z2PA6ws&r=UogPJ7VYoAeiC8NNwyY5AxLx8QgaRiMcicgAv7oi3tc&m=g-_a1ZP6SVVOGh0ByfSalzE_6f5YTvFiL680jgP-mG8&s=6_PF8jksGYX0eR9mFvdGNpffUzqqu8fPtI8jJOjKIfc&e=>
.
Matias Cattaneo (Princeton University)
Matias Cattaneo is Professor in the Department of Operations Research and
Financial Engineering at Princeton University, with positions in
Princeton’s Department of Economics, Center for Statistics and Machine
Learning, and Program in Latin American Studies. His research focus is *[*to
come]*. Website: https://urldefense.proofpoint.com/v2/url?u=https-3A__cattaneo.princeton.edu_home&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=DpI5MLF4unz1u_bt8FCAPoVY1g6v-AXQnHPTWhHMqJ7iZFsvDSstJ_fAsd5_q4rr&s=i_BvpHlc8isKKxf910DCsiEtgozd-aEb9BrFLQ-fM_g&e=
<https://urldefense.proofpoint.com/v2/url?u=https-3A__cattaneo.princeton.edu_home&d=DwMFAw&c=-35OiAkTchMrZOngvJPOeA&r=KEnFjcsfiKF_BPOsgvPP912y1yQ0q05CJ14uAvMNdNQ&m=IKdtFkr2lwEliZwH7roaxkL0BIy5WRo-tpGFg7bsP22hSIeKar-kvPKECtqXXYMr&s=l5D0twTVr-XdHENQpNdvi9DA1jvLG5_S9lNtBXqUvLk&e=>
*Advanced Workshop Faculty*
Jeffrey Wooldridge (Michigan State University)
Jeffrey Wooldridge is University Distinguished Professor at Michigan State
University and the author of leading undergraduate and graduate textbooks
on econometrics. His research interests include causal inference and the
econometrics of panel data, including nonlinear models in
difference-in-differences and general policy analysis settings. Website:
https://urldefense.proofpoint.com/v2/url?u=http-3A__econ.msu.edu_faculty_wooldridge_&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=DpI5MLF4unz1u_bt8FCAPoVY1g6v-AXQnHPTWhHMqJ7iZFsvDSstJ_fAsd5_q4rr&s=F3-3ka-n2I1m2EfgRG1z2dzZSUH-qll0btU7HMV-GMo&e=
<https://urldefense.proofpoint.com/v2/url?u=http-3A__econ.msu.edu_faculty_wooldridge_&d=DwMFAw&c=-35OiAkTchMrZOngvJPOeA&r=KEnFjcsfiKF_BPOsgvPP912y1yQ0q05CJ14uAvMNdNQ&m=IKdtFkr2lwEliZwH7roaxkL0BIy5WRo-tpGFg7bsP22hSIeKar-kvPKECtqXXYMr&s=wNrl81G27_LzMH9ZFbE7033Rbr7PilsLEe3MAWiIEdU&e=>
.
Yiqing Xu (Stanford University)
Yiqing Xu is Assistant Professor of Political Science at University of
California, San Diego. His main methods research involves causal inference
with panel data. Website: https://urldefense.proofpoint.com/v2/url?u=https-3A__yiqingxu.org_&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=DpI5MLF4unz1u_bt8FCAPoVY1g6v-AXQnHPTWhHMqJ7iZFsvDSstJ_fAsd5_q4rr&s=qz-DSIQvnega8iwL0wldtO9K3uMJ1ssZbrz5e7APpmI&e=
<https://urldefense.proofpoint.com/v2/url?u=https-3A__yiqingxu.org_&d=DwMFAw&c=-35OiAkTchMrZOngvJPOeA&r=KEnFjcsfiKF_BPOsgvPP912y1yQ0q05CJ14uAvMNdNQ&m=IKdtFkr2lwEliZwH7roaxkL0BIy5WRo-tpGFg7bsP22hSIeKar-kvPKECtqXXYMr&s=Fc1mwxxY4urDNk2qp90kuV5cBxyuVj2x4KA3ChBdy4g&e=>
.
Christian Hansen (University of Chicago)
Christian Hansen is Wallace W. Booth Professor of Econometrics and
Statistics at the University of Chicago, Booth School of Business. His
research has chiefly been in the areas of the use of machine learning
methods in estimation of causal and policy effects, estimation of panel
data models, inference using clustered standard errors, quantile
regression, and weak instruments. Website:
https://urldefense.proofpoint.com/v2/url?u=https-3A__voices.uchicago.edu_christianhansen_&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=DpI5MLF4unz1u_bt8FCAPoVY1g6v-AXQnHPTWhHMqJ7iZFsvDSstJ_fAsd5_q4rr&s=qywwMFHbWNOIYmoXQXSZ_1gk7V3cf-3pN238Jw-RwSY&e=
<https://urldefense.proofpoint.com/v2/url?u=https-3A__voices.uchicago.edu_christianhansen_&d=DwQFAw&c=-35OiAkTchMrZOngvJPOeA&r=KEnFjcsfiKF_BPOsgvPP912y1yQ0q05CJ14uAvMNdNQ&m=IKdtFkr2lwEliZwH7roaxkL0BIy5WRo-tpGFg7bsP22hSIeKar-kvPKECtqXXYMr&s=sAM9_pXKyE4OJVjtqjnLLJ268CTbMFTP1t_k56Rtjz8&e=>
.
*Main Workshop Outline*
*Monday, August 8 (Donald 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, August 9 (Pedro Sant’Anna)*
*Matching and Reweighting Designs for “Pure” Observational Studies*
The core, untestable requirement of selection [only] on observables.
Ensuring covariate balance and common support. Matching, reweighting, and
regression estimators of average treatment effects. Propensity score
methods.
*Wednesday, August 10 (Pedro Sant’Anna)*
*Panel Data and Difference-in-Differences*
Panel data methods: pooled OLS, random effects, and fixed effects. Simple
two-period DiD and panel data extensions. The core “parallel trends”
assumption. Testing this assumption. Event study (leads and lags) and
distributed lag models. Accommodating covariates. Triple differences.
Robust and clustered standard errors.
*Thursday, August 11 (either Rocio Titiunik or Matias Cattaneo)*
*Regression Discontinuity*
Regression discontinuity (RD) designs: sharp and fuzzy designs;
continuity-based methods and bandwidth selection; local randomization
methods and window selection; empirical falsification of RD assumptions;
extensions and generalizations of canonical RD setup: discrete running
variable, multi-cutoff, multi-score, and geographic designs. RD software
website: https://urldefense.proofpoint.com/v2/url?u=https-3A__sites.google.com_site_rdpackages_&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=DpI5MLF4unz1u_bt8FCAPoVY1g6v-AXQnHPTWhHMqJ7iZFsvDSstJ_fAsd5_q4rr&s=dBh3tXhuJT3Zz00Ntctf9K_bJHsp8zL-nSMd8ryrqAY&e=
<https://urldefense.proofpoint.com/v2/url?u=https-3A__sites.google.com_site_rdpackages_&d=DwMFaQ&c=yHlS04HhBraes5BQ9ueu5zKhE7rtNXt_d012z2PA6ws&r=UogPJ7VYoAeiC8NNwyY5AxLx8QgaRiMcicgAv7oi3tc&m=g-_a1ZP6SVVOGh0ByfSalzE_6f5YTvFiL680jgP-mG8&s=CM0m9c8i5SuSTFEiLBNY3pnzWEbi-2gsSzYIflpwjhI&e=>
*Friday, August 12: Morning **(either Matias Cattaneo or Rocio Titiunik)*
*Instrumental variable methods*
Causal inference with instrumental variables (IV): the role of the
exclusion restriction and first stage assumption; the monotonicity
assumption and local average treatment effect (LATE) interpretation;
applications
to randomized experiments with imperfect compliance, including
intent-to-treat designs and two-stage estimation. Connections between IV
and fuzzy RD designs.
*Friday, August 12: 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, Scott Cunningham, Rocio Titiunik or Matias
Cattaneo). Additional parallel sessions if needed to meet demand.
*Stata and R code*
*On selected days, we will run parallel Stata and R sessions to illustrate
code for the research designs discussed in the lectures, or the speakers
will build Stata code into their lecture slides. Presenters: Bernard
Black (Stata) and Joshua Lerner (R).*
*Advanced Workshop Outline*
*Monday, August 15: Jeffrey Wooldridge*
*Advanced matching and balancing methods*
*Choosing among the many available matching and balancing methods.
Estimators that aim directly at covariate balance. Combining balancing
with regression and doubly robust estimators in cross-sectional and panel
data settings. Synthetic controls. *
*Tuesday, August 16: Yiqing Xu*
*Advanced panel data methods*
Causal inference with panel data using parametric, semi-parametric,
non-parametric methods for addressing imbalance between treated and control
units. Bias in classic DiD models using two-way fixed effects. Topics
include interactive fixed effects and matrix completion methods, as well as
reweighting approaches such as panel matching, trajectory balancing and
augmented synthetic control. *Relative strengths and weaknesses of
different methods will be discussed.*
*Wednesday, August 17: Christian Hansen*
*Introduction to machine learning (predictive inference) *
*Introduction to “machine-learning” approaches to prediction algorithms.
High-dimensional model selection (function classes, regularization,
tuning), model combination (ensemble models, bagging, boosting), model
evaluation, and implementation.*
*Applications of machine learning to causal inference*
*When and how can machine learning methods be applied to causal inference
questions. Limitations (prediction vs estimation) and opportunities (data
pre-processing, prediction as quantity of interest, high-dimensional
nuisance parameters), with examples from an emerging empirical literature.*
*Registration and Workshop Cost*
*Vaccination required: *All in-person enrollees should be vaccinated
against COVID-19 (2 doses), and have received a booster shot if the second
dose was more than 6 months before the start of the workshop. Contact us
if you need an exception to this policy. You will be asked for vaccine
details when you register.
*Main Workshop:* tuition is $900 ($600 for post-docs and graduate students;
$500 if you are Northwestern-affiliated). The workshop fee includes all
materials, temporary Stata license, breakfast, lunch, snacks, and an
evening reception on the first workshop day.
*Advanced Workshop: *tuition is $600 ($400 for post-docs and graduate
students; $300 if you are Northwestern affiliated).
There is a $200 discount for non-Northwestern persons attending both
workshops ($100 for Northwestern affiliates).
*Zoom option: *We’ve decided to charge the same amount for in-person and
virtual attendance. Partly, we want to encourage in-person attendance. We
also want to allow attendees to switch from one format to the other,
depending on how travel and COVID-19 risk looks by mid-summer.
You can cancel either workshop five weeks in advance, for a 75% refund –
July 1, 2020 for the Main Workshop and July 8, 2022 for the Advanced
Workshop – or carry over your registration to next year for full credit.
There is a 50% refund after these dates but before three weeks in advance,
July 15, 2022 for the Main Workshop and July 22, 2020 for the Advanced
Workshop. After these dates no refund will be given, because we cant
realistically replace you. If the workshop is canceled, we will offer a
full refund.
We know the workshop is not cheap. We use the funds to pay our speakers
and 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: https://urldefense.proofpoint.com/v2/url?u=http-3A__www.law.northwestern.edu_faculty_profiles_BernardBlack_&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=DpI5MLF4unz1u_bt8FCAPoVY1g6v-AXQnHPTWhHMqJ7iZFsvDSstJ_fAsd5_q4rr&s=unrh1z0JQfG8fWtUZ53ZcCoZJfB4S1hqCoyIqpll9KE&e=
<https://urldefense.proofpoint.com/v2/url?u=http-3A__www.law.northwestern.edu_faculty_profiles_BernardBlack_&d=DwMFAw&c=-35OiAkTchMrZOngvJPOeA&r=KEnFjcsfiKF_BPOsgvPP912y1yQ0q05CJ14uAvMNdNQ&m=IKdtFkr2lwEliZwH7roaxkL0BIy5WRo-tpGFg7bsP22hSIeKar-kvPKECtqXXYMr&s=mnvdlQtl8pdbbkES-97pmrPt3F-Z3ajaS1ne_LVfeIQ&e=>
. Papers on SSRN: https://urldefense.proofpoint.com/v2/url?u=http-3A__ssrn.com_author-3D16042&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=DpI5MLF4unz1u_bt8FCAPoVY1g6v-AXQnHPTWhHMqJ7iZFsvDSstJ_fAsd5_q4rr&s=llZFV6TmInzEzxQXUMR3fBrQQzSuIVapb5g_lmRs1Co&e=
<https://urldefense.proofpoint.com/v2/url?u=http-3A__ssrn.com_author-3D16042&d=DwMFAw&c=-35OiAkTchMrZOngvJPOeA&r=KEnFjcsfiKF_BPOsgvPP912y1yQ0q05CJ14uAvMNdNQ&m=IKdtFkr2lwEliZwH7roaxkL0BIy5WRo-tpGFg7bsP22hSIeKar-kvPKECtqXXYMr&s=dbcO1EV15x-Qo8cN3hnQo2HYPjmim6f5mctxq3SEctY&e=>
.
Scott Cunningham (Baylor University)
Scott Cunningham is Professor of Economics at Baylor University. Principal
research interests: mental healthcare; suicide; corrections; sex work;
abortion policy; drug policy. Web page with link to CV:
https://urldefense.proofpoint.com/v2/url?u=https-3A__www.scunning.com&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=DpI5MLF4unz1u_bt8FCAPoVY1g6v-AXQnHPTWhHMqJ7iZFsvDSstJ_fAsd5_q4rr&s=uczbUKAyX71F8Ds79pgccbbSKWhvkyqIL6DdlGpesxU&e=
<https://urldefense.proofpoint.com/v2/url?u=https-3A__www.scunning.com&d=DwMFAw&c=-35OiAkTchMrZOngvJPOeA&r=KEnFjcsfiKF_BPOsgvPP912y1yQ0q05CJ14uAvMNdNQ&m=IKdtFkr2lwEliZwH7roaxkL0BIy5WRo-tpGFg7bsP22hSIeKar-kvPKECtqXXYMr&s=kEHBVY-TgjEMhqCGEvwi9kMfBxLDZda-uiTgYobQIWU&e=>
.
*Questions about the workshops: *Please email Bernie Black (
bblack at northwestern.edu) or Scott Cunningham (scunning at gmail.com) for
substantive questions or fee waiver requests, and Sarah Jane King Shoemaker
(sarah.shoemaker at law.northwestern.edu) for logistics and registration.
--
Scott Makeig, Research Scientist and Director, Swartz Center for
Computational Neuroscience, Institute for Neural Computation, University of
California San Diego, La Jolla CA 92093-0559, http://sccn.ucsd.edu/~scott
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