The Spanish Economic Association and its Education Committee are happy to introduce the 1st SAEe PhD School in Economics. The School, a one-day event, will take place on the day before the start of the Simposio de la Asociación Española de Economía (SAEe) in Alicante (Wednesday, December 11th).

The School will consist of a full day of lectures with prominent speakers who will offer a broad perspective of their research areas. The School will also feature a session on early career advice for PhD students; on topics such as surviving the PhD, research presentations, choice of research topics, and the like.

We are very excited to announce that the 1st SAEe PhD School in Economics will be given by Manuel Arellano (CEMFI) and Dmitry Arkhangelsky (CEMFI) on

“Advances in the Econometrics of Program Evaluation and Inequality”

The number of available places is limited. Applicants must submit their academic CV (which should include contact details of academic advisors or sponsors) by September 6th to

Admission to the school will be based on academic merit. Applicants with a paper accepted to be presented at SAEe will be given priority. Participants in the School must register to the SAEe conference. The Spanish Economic Association will award 20 fellowships for students participating in the school. The fellowships will cover the registration fees for the selected candidates. Admission to the school and awarded fellowships will be announced on September 15th, at the same time as decisions on submissions to the Simposio are made public.

For the participants in the School there are rooms available on the Student Residence in the campus at reduced prices. The list of prices, location and the booking of these rooms will be available through the website of SAEe:

A short description of the program follows:

The first session will deal with the estimation of average treatment effects and potential outcome distributions. Topics covered will include linear and nonlinear difference-in-difference models, synthetic control methods, regression discontinuity, and standard error issues. This session will also discuss the application of machine learning and Lasso methods to program evaluation with high-dimensional data.

The second session will deal with nonlinear panel data methods with an emphasis on static and dynamic quantile models. Topics covered will include quantile regression, latent variables, and estimation by simulation based on the EM algorithm and Markov chain Monte Carlo samplers. The session will discuss applications to the study of inequality of income, consumption and wealth at the intersection of micro and macroeconomics.


Participants should have taken first-year master level courses in mathematical statistics and econometrics at a minimum. Familiarity with the basic concepts of probability theory, statistical inference, and least squares methods will be required.