PhD Program in Economics, Analytics and Decision Sciences
PhD Coordinator: Ennio Bilancini
PhD Program Overview
The Doctoral Program in Economics, Analytics and Decision Sciences is based on the development of skills that underlie the quantitative and qualitative analysis of the phenomena observed in economic and social systems. The Program aims at providing participants with a solid knowledge of modern analytical methods, following a multidisciplinary approach. The Program develops a strong integration of concepts, analytical methods and practical skills, to train the new generation of economists, social scientists, managers and professionals with specific competences in the analysis, interpretation and management of the complexity of economic, firm, and social systems.
Students are trained to become researchers and decision-makers in academia, politics, administration and business, through the integration of knowledge that lies at the borders between economics, management and the other social sciences, while maintaining the unifying language of mathematics and statistics and borrowing the tools necessary for specific applications from computer science and psychology.
The close connection with a selected group of companies and institutions offers the opportunity to adopt new perspectives of analysis and interpretation of phenomena through the use of innovative quantitative and qualitative research methodologies for solving the problems of the real economy and society. Students are therefore involved in the collection and analysis of high-dimensional real-world data.
The Program is characterized by the interdisciplinary nature of its approach. The obstacles that traditionally divide the different domains of knowledge are overcome by addressing the problems that arise in the various application fields - industrial, institutional, health, environmental, technological, social, ethical, etc. - through a variety of scientific methodologies derived from probability theory, theory of the firm, mathematical statistics, econometrics, machine learning, experimental methods, cognitive science, computer science and computational methods.
The Program is characterized by the presence of three major areas of knowledge and application that can be traced back in a broad sense to economics, management and decision sciences. These areas are characterized by a common training in the analysis of behavior of economic decision-makers and in the statistical-econometric analysis of data and evidence, but can then be modulated and combined towards the individual specific needs of the candidate. Ideally, there will be three prototypical outgoing profiles: one encompassing economics and management, one encompassing management and decision sciences, and one encompassing economics and decision sciences.
In particular, Program offers training in the use of tools and methods such as: statistical learning, networks analysis (physical and virtual), analysis of business dynamics, strategy evolution and dynamic capabilities, analysis of dynamic systems (stochastic and deterministic), analysis of firm performance, analysis of Environmental Social Governance (ESG), high-dimensional econometrics (characterized by significant and highly innovative computational components), experimental methods (in the field, in the laboratory and online), simulations of interactive systems made of interactive decision-makers (agent-based models). These tools allow the study of economic and social systems that are typically difficult to analyze due to the size and complexity of the mechanisms underlying their evolution and, at the same time, they make it possible to acquire and effectively analyze large datasets. These methodological skills, which are both quantitative and qualitative, provide students with a wide applicative versatility and a shared vocabulary to deal with a wide spectrum of phenomena which are typical of economic, firm, and social systems.
Input and output profiles
The EADS program welcomes candidates with training in one of the following subject areas: economics, management, statistics, law, physics, computer science, engineering, logic and philosophy of science, mathematics, cognitive and behavioral sciences, or in contiguous areas. The ideal candidate is interested in acquiring distinctive competencies in economics, statistics, management and neuroscience, but does not necessarily need to have previous training in these areas. However, it is crucial that the candidate demonstrates solid quantitative skills, comparable with those typically acquired in economics-managerial degrees.
The Program prepares to face, analyze and solve a wide spectrum of complex and interdisciplinary problems of relevance at the institutional, social and industrial level, with the primary objective of identifying sustainable solutions and designing effective intervention policies in the economic and social spheres, as well as in business life, understood in a broad sense.
Outgoing profiles share a characterizing common part of training on the behavior of economic decision-makers and on the statistical-econometric analysis of data and evidence, plus dedicated specialization along the lines of economics and management, management and decision sciences, or economics and decision sciences.
Job placement opportunities range from academia, in the various disciplines of the CUN 13 macro-area (economic sciences and statistics) and in contiguous areas, to the public sector, international institutions, research laboratories, study centers, and regulatory authorities, as well as the private sector (services, industry and professional advice).
Research Units contributing to the Program
Students also have the opportunity of completing their research projects under the joint supervision (double-degree) with partner universities, including KU Leuven and the University of Alicante. All students are encouraged to spend periods abroad, both within the Erasmus+ framework and through ad-hoc mobility agreements, taking advantage of strong ties with selected companies and international institutions.
- Prof. Ennio Bilancini (Full Professor of Political Economy, IMT School)
- Dr. Andrea Averardi (Assistant Professor in Administrative Law, IMT School)
- Prof. Alberto Bemporad (Full Professor of Control Systems, IMT School)
- Prof. Valerio Capraro (Senior Lecturer of Economics, Middlesex University London)
- Prof. Jose. R. Carvalho (Professor of Econometrics, Universidade Federal do Ceará)
- Prof. Gustavo Cevolani (Associate Professor in Logic and Philosophy of Science, IMT School)
- Prof. Irene Crimaldi (Associate Professor of Statistics, IMT School)
- Prof. Marco Giarratana (Professor of Strategy, IE Business School Madrid)
- Prof. Giorgio Stefano Gnecco (Associate Professor in Operations Research, IMT School)
- Prof. Inigo Iturbe-Ormaetxe (Professor of Economics, Universidad de Alicante)
- Prof. Nicola Lattanzi (Full Professor of Business Administration, IMT School)
- Prof. Alessia Paccagnini (Assistant Professor of Econometrics, University College Dublin)
- Prof. Pietro Panzarasa (Reader in Organisational Theory and Behaviour, Queen Mary College London)
- Dr. Luca Polonio (Researcher in Political Economy, Università degli Studi di Milano-Bicocca)
- Prof. Massimo Riccaboni (Full Professor of Economics and Management, IMT School)
- Prof. Emiliano Ricciardi (Full Professor in Psychobiology and Psychophysiology, IMT School)
- Prof. Armando Rungi (Associate Professor in Industrial Organization and International Trade, IMT School)
- Prof. Francesco Serti (Associate Professor in Economics, IMT School)
- Prof. Tiziano Squartini (Associate Professor in Theoretical Physics of Matter, IMT School)
- Prof. Erik Stam (Professor of Strategy, Organization & Entrepreneurship, Utrecht University School of Economics)
- Prof. Mirco Tribastone (Full Professor of Computer Science, IMT School)