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Home Research PhD programme and research grants PhD in QUANTITATIVE METHODS FOR ECONOMIC POLICY


Quantitative Methods for Economic Policy is an interdisciplinary Ph.D. Program at the crossroads of Economics, Economic Policy and Mathematical and Statistical Sciences, at a time when quantitative methods are fundamental in the economic policy analysis. Moreover, the Ph.D. program aims at facing subject at the economic science frontier and interconnected to other sciences (for instance physics and computer science), such as network analysis and data mining methods. The Ph.D. program merges theoretical aspects with empirical applications developed using technical software.

The courses are taught by high quality professors, including outstanding guests lecturers from major international universities. Moreover, the Ph.D. students join an active research community and participate in regular seminars, hosted by academics of international reputation, and workshops.

Our doctoral program

The Ph.D. is structured in three curricula:

  • Multisectoral and Computational Methods of Analysis for Economic Policy
  • Mathematical and Statistical Methods for Economic Policy
  • Network Analysis and Online Data Mining Methods for Economic Policy


The Ph.D. program is developed over three years:

  • a first year of courses, seminars and exams common to all curricula and aimed at teaching advanced topics in economics and quantitative subjects. Strong emphasis is on methods, on applications to different economic policy context – from the local to the international – and on the replication of well known contributions in the scientific literature on economic policy analysis. In particular, the courses will start with a series of tutorials on Data analysis and visualization with R; introduction to Stata; programming with Matlab.
  • a second and a third year of research activity for completing the Ph.D. thesis, with the possibility to spend a period in international universities (with an increase of 30% for the research scholarship amount).


The Ph.D. professors offer supervision on a wide range of topics, with particular strengths in:

  • graph theory and network analysis
  • sparse graphical models
  • input-output analysis
  • computable general equilibrium models
  • computational methods for macro and microeconomics
  • agent-based economic modeling
  • dynamic systems  in economics and finance
  • mixture regression models and hidden Markov models
  • statistical methods for policy evaluation and causal inference in observational studies