3rd Giovanni Anania Summer School on Evidence-Based Policy Making
On July 15th 2015 Giovanni Anania suddenly passed away. Giovanni was a pillar in the profession and a natural academic leader for young agricultural and international economics scholars. He also was an institutional leader, serving as president of the European Association of Agricultural Economists (EAAE), and at the University of Calabria, where he served as Head of the Department of Economics as well as a member of the University Executive Board.
To honor Giovanni, the Italian Association of Agricultural and Applied Economics (AIEAA), the Rossi-Doria Center, the Research Centre for Agricultural Policies and Bioeconomy of the Council for Agricultural Research and Economics (CREA) and the University of Calabria have organized the 3rd edition of the Summer School for PhD students and young researchers, a constant focus in Giovanni’s mentoring role.
Machine learning (ML) now offers great potential for expanding the applied economist’s toolbox. Data availability has dramatically increased and ML methods are well equipped to exploit large volumes of data more efficiently than traditional statistical methods. Researchers have developed and improved algorithms that push the boundaries of ML. The community has a strong open source tradition, including powerful DL libraries (e.g. tensorflow.org, pytorch.org) and pretrained models (e.g. VVGNet, ResNet), increasing the potential for adoption. In the past few years, economists have begun to realize that the predictive power of ML methods may not only be used as such, but can also improve causal identification. In this course, we introduce ML to applied economists by placing it in the context of standard econometric and simulation methods. We identify shortcomings of current methods used in agricultural and applied economics, and discuss both the opportunities and challenges afforded by ML to supplement our existing approaches.
The 3rd Giovanni Anania Summer School on Evidence-based policy making provides an introduction to the use of machine learning techniques and introduces students to their use in agricultural, food and environmental policy analysis.
The overall objective of the Summer School is to train young applied economists in the field of policy analysis. The approach is based on a close interaction between participants and senior economists.
The Summer School is organized as a series of theoretical lectures focused on methodological issues coupled with up-to-date empirical sessions focused on the computer-based applications of the same techniques.
Both young scholars and lecturers will be hosted and live together at the University of Calabria, in an informal environment, facilitating the sharing of experiences and expertise.
The Summer School welcomes applications by PhD students at any stage of their PhD as well as young researchers who have completed their PhD. Applicants are welcome from any areas of applied economics, with a preference for those specializing in agricultural, food, environmental, trade, and development economics. Given the highly interactive activities planned at the School, the number of participants is limited to 50. Admission priority will be given to students of the AFEPA Consortium, of the University of Calabria and of the University Roma Tre.
For more information click "LINK TO ORIGINAL" below.