Instrumental Variables

A 2-Day Seminar Taught by Felix Elwert, Ph.D.

Read reviews of this seminar 


This course offers an in-depth survey of modern instrumental variables (IV) analysis. IV analysis is an important quasi-experimental technique with numerous applications in economics, the social and biomedical sciences, business, marketing, and education. 

IVs allow us to get unbiased estimates of causal effects even when there is selection bias, unobserved confounding, or imperfect compliance. The technique applies equally to randomized trials and observational studies. IV analysis is a very powerful tool—as long as the underlying assumptions are met.

This seminar will take students from the basic Wald estimator up to powerful recent developments, including non-parametric tests of the exclusion assumption. Students will get extensive hands-on experience by analyzing real world examples across the social sciences. We will carefully dissect key technical and substantive assumptions to empower students to recognize, understand, and empirically test these assumptions in practice.

This seminar puts a premium on a practical understanding. We will capitalize on three complementary perspectives: modern potential-outcomes notation, visually intuitive directed acyclic graphs (DAGs), and the traditional algebraic approach. This will enable students to recognize IVs in their own studies, understand assumptions thoroughly, and read the specialist literatures in different fields.

Topics include single instruments, multiple instruments, weak instruments, first-stage diagnostics, over-identification tests, exclusion tests, two-stage least squares (2SLS), natural experiments, encouragement trials, Mendelian randomization, continuous and categorical outcomes, compliance classes, local average treatment effects (LATE), and Balke-Pearl bounds.

We will use the latest commands in Stata and learn theoretical and practical insights that transfer across software packages.


Who should attend?

If you want to understand how and when you use instrumental variables analysis in practice, this course is for you. The material is equally applicable to experimental and non-experimental data. Participants should have a good working knowledge of multiple regression and basic knowledge of Stata (point-and-click graphical user interface or basic command line operation). This course is appropriate for researchers (in industry or at universities, faculty, doctoral students, and advanced masters students) with a solid applied background in multiple regression analysis. This course does not require calculus (Differentialrechnung). Students will be given fully executable do-files, so no prior programming experience is necessary.  


Computing

This seminar will use Stata for the examples. Although not required, participants are welcome to bring their own laptop computers with version 14 of Stata installed. Power outlets will be available at each seat.


Schedule and materials

The class will meet from 9 am to 4 pm each day with a 1-hour lunch break from 12 pm to 1 pm.

The course will be taught in English.

Participants receive a bound manual containing detailed lecture notes (with equations and graphics), examples of computer printout, and many other useful features. This book frees participants from the distracting task of note taking. 


Registration and Lodging

The fee of €895 includes all course materials. 

Lodging Reservation Instructions

A block of rooms has been reserved at the Berlin Marriott Hotel, Inge-Beisheim-Platz 1, Berlin 10785 Germany, where the seminar is located, at a nightly rate of €205 for a room. It is advisable to check online for a lower rate, before booking with the group rate. 

To make a reservation, you must call 0049 30 22 000 6300 or toll free 0049 800 18 54422 during business hours and identify yourself by part of the “Statistical Horizons” group. The room block will expire when it is full or on May 13, 2015. Availability is limited to please book your reservation at your earliest convenience.  

The city of Berlin levies a city tax of 5% on the room rate that is collected by the hotel. This tax does NOT apply to business related travel. To be exempt from the tax you must provide proof of business reason for the stay. This can be in several forms: Billing address is the customer’s company name and address, the invoice is settled through the customer company, or a set form.  


Seminar outline

  1.  Causal effects
        a. ATE: Average treatment effects
        b. LATE: Local average treatment effects
        c. Identification in randomized trials and observational studies
        d. Problems: Confounding, selection, and attrition bias
  2.  Approaches to IV analysis
        a. Potential outcomes
        b. Directed acyclic graphs
        c. Algebraic
  3.  Estimation
        a. Wald estimator (IV)
        b. Two-stage least squares (TSLS)
        c.  Generalized methods of moments (GMM)
        d.  Limited information maximum likelihood (LIML)
        e.  Linear and nonlinear outcome models
         f.  Standard errors
        g.  Why one should never control for an IV in OLS  
  4.  Understanding assumptions and their consequences 
        a. Weak instruments
        b. Instrument ignorability
        c. Instrument exclusion 
  5.  Testing assumptions
        a. Endogeneity tests
        b. Over-identification tests
        c. Balke-Pearl check


Comments by recent participants

“This course was exceptional. Dr. Felix was engaged with the seminar participants. His ability to breakdown the complex topic, both theoretically and through applications and exercises, was very helpful in learning (and hopefully retaining) what was presented over the past 2 days.”
  Mary Kelly, Villanova University 

“The instructor skillfully combines the theory and the applicable examples, and walked us from the past, current and the instrument aspect of IV approach. Very applicable. Highly recommended.”
  Shaowei Wan,University of Charleston School of Pharmacy

“This course very clearly outlines how to think in a practical and applied way about IV regression. Specifically, it provides excellent understanding of IV’s assumptions and limitations, to ensure that you use it responsibly.”
  Zach McDade, Urban Institute

“This is a wonderful two-day course that provides the basic foundation of IV and its application. Illuminating and well presented.”
  Madhu S. Mohanty, California Stata University

“Extremely useful course. As a non-statistical person it helped me understand the concept of IV without getting lost.”
  Amol Karmarkar, University of Texas Medical Branch

“Great style of going through the different methods. Felix makes everything easy to understand and engages you in discussion to make sure the material is clear.”
  Razvan Lungeanu, Penn State University