IRVAPP ADVANCED SCHOOL 2023 - Advanced Methods for Impact Evaluation (Online)
The school is designed to be particularly beneficial to graduate students and researchers with intermediate proficiency in applied policy evaluation and quantitative micro-econometrics. It will run over six days, from January 30, 2022, from 2.00 pm (CET) to 5.30 pm (CET) (30mins break at 3.30 pm).
The school consists of 3 different modules. Each module includes 4 slots (3 theoretical sessions and 1 basic training session); each slot lasts 90 minutes. The training sessions will illustrate the basic implementation in Stata of a selection of approaches discussed in the theoretical sessions; a temporary Stata license will be released on demand.
The school will be held on-line.
This is an intermediate/advanced course on quantitative empirical methods for policy evaluation. Knowledge of methods for treatment effects and quantitative micro-econometrics equivalent to Ph.D. or Doctorate level coursework is required. Although the exercises will be guided, basic familiarity with Stata is strongly recommended.
- January 30-31, 2023: 1 st module [Bayesian causal inference]
- February 6-7, 2023: 2nd module [Difference-in-Differences]
- February 13-14, 2023: 3 rd module [Empirical Bayes methods]
Bayesian causal inference
This part will introduce the fundamental concepts and the state-of-the-art methods for causal inference under the potential outcomes framework, with an emphasis on the Bayesian inferential paradigm. Topics will cover randomized experiments, common methods for observational studies, such as propensity score, matching, weighting and doubly-robust estimation, heterogeneous treatment effects, instrumental variables. Recent advances related to high-dimensional analysis and machine learning will be naturally incorporated into the discussion. All methods will be illustrated via real-world case studies and labs.
This part will discuss several empirical strategies at the research frontier of modern difference-in-differences research designs. Our agenda includes discussions on the role of covariates, research designs with variation in the timing of treatment, and treatment effect dynamics and heterogeneity through the lens of event studies.
Empirical Bayes methods
This part reviews econometric methods to analyze the case in which there are J groups, n(j) units available in group j, Y(i,j) the outcome on unit i, group j, e.g. J school, n(j) students in school j, Y(i,j) performance of student i in school j. We analyze methods to deal with the following problems:
- How to estimate the distribution across schools of the school fixed effect, G(.)
- How to improve the estimation of each school fixed effect using G(.)
- How to use G(.) to select schools above/below a specific cutoff value for the fixed effect
- How to classify schools as good/bad using G(.)
The course will be taught in English.
All the slides used by instructors will be sent to participants prior to the beginning of the school. All lectures link will be sent some days before the lecture.
The registration fee includes workshop materials. We are not in a position to offer any scholarship.
It is possible to register for individual modules or for the entire training.
|Single module||All modules|
|Students||150 €||350 €|
|Others||200 €||450 €|
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Candidates can enroll using this link (for any preferences click on “select a time” to register) where they will be asked to complete a short application form.
Enrollment and proof of completed payments are due by January 20, 2023.
It is advisable that conditional on admission, payment is made at the earliest to secure your place in the program. Enrollment will be secured only after receipt of the payment notification.
Payment must be done by bank transfer. Details will be provided in the notification of acceptance, conditional to the offer of a place.