IRVAPP WINTER SCHOOL 2018 – Advanced Methods for Impact Evaluation
The school is designed to be particularly beneficial to graduate students and researchers with a high level of proficiency in applied policy evaluation and quantitative micro-econometrics. It will run over three consecutive days, from January 10 to January 12 2018, covering methods for the estimation of policy effects with endogenous participation. Different solutions to the identification problem will be considered, resulting in three thematic one-day sessions.
This is an advanced/graduate course on quantitative empirical methods for policy evaluation. As such, knowledge of methods for treatment effects and quantitative micro-econometrics equivalent to Ph.D. or Doctorate level coursework is a prerequisite.
Erich Battistin, FBK-IRVAPP and Queen Mary University of London
Guido Imbens, Stanford University
Enrico Rettore, FBK-IRVAPP and University of Trento
10/01/2018 to 12/01/2018
January 10, 2018: Discontinuities (Enrico Rettore)
This part will address identification of policy effects when the probability of participation changes discontinuously or has kinks along observable dimensions. Starting with the basic methodology and implementation, the module will discuss extensions ranging from multiple cut-offs, to extrapolation and external validity, and randomization-inference methods.
January 11, 2018: Causality and Machine Learning (Guido Imbens)
This part will discuss the recent literature on machine learning methods for causal effects. It will start with a discussion of the basics of causal inference, including the analysis of observational studies under the assumption of unconfoundedness. Then it will discuss modern methods for experimentation including multiarmed bandits, and methods for estimating heterogeneous treatment effects. Next it will review the literature on observational studies with many covariates. It will also discuss the connection with synthetic control methods and the matrix completion literature.
January 12, 2018: Instrumental Variables (Erich Battistin)
This part will present solutions when (quasi-)experimental sources of exogenous variability for treatment participation become available. Identification of “local average” and “marginal” treatment effects will be discussed, offering a broad overview of ex-ante and ex-post evaluation methods when effects are heterogeneous across the statistical units.
The course will be taught in English.
This course has the patronage of the Centro Interuniversitario di Econometria (CIdE) & of the Società Italiana di Econometria (SIdE) & of ECSR (European Consortium for Sociological Research)
Department of Sociology and Social Research, via Verdi 26, Trento (Italy).
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The registration fee includes workshop materials, as well as coffee and lunch breaks; it does not include dinners, accommodation, transport or any other services. We are not in the position to offer any scholarship.
Students: EUR 400
HE delegates and Government: EUR 700
Others: EUR 1000
The course is limited to 30 participants, with constrained accessibility of space.
Candidates can enroll at the following link, and will be asked to complete a short application form.
Online application and payment are due by December 10, 2017. It is advisable that, conditional to the offer of place, payment is made at the earliest to secure your place on the program. Enrollment will be secured only after receipt of the payment notification.
Payment shall be done by bank transfer. Details will be provided in the notification of acceptance, conditional to the offer of place.
Cancellation of registration requests must be notified to [email protected]
Refund of registration fee will be as follows:
Cancellation requests received by September 30: full refund.
Cancellation requests received by November 10: 50% refund.
Cancellation requests received from November 10 and no-shows: no refund.
Refunds will be made via bank transfer, and all bank charges will be for the registrants account.
Participants are responsible for cancelling their own hotel and travel reservations.