Program Description

The PhD program integrates the typical competencies in economics and business with mathematical, statistical and econometric tools, to offer a training program that will enable students to carry out high-quality research, as well as work in consultancy and business.

The PhD program consists of three complementary curricula :

A) Economics and Institutions (E&I)

This curriculum aims at providing advanced theoretical knowledge in economic disciplines, focusing on the role of institutional factors is shaping development and growth dynamics, labour and product markets, firms behaviour and performance. In particular, the following topics will be covered:

  1. Growth and development (institutions and economic change, comparative economic systems, social/political instability and development, theory and empirics of growth, inequality)
  2. Labour Economics (theory and empirics of imperfect markets, macroeconomic shocks and policy responses)
  3. Corporate governance and firm organization (theories of the firm, economics of transaction costs)
  4. International economics (Firms in international trade)
  5. Energy and Environmental Economics

The theoretical analysis of these topics will be supported by a rigorous application of qualitative and quantitative methods of analysis.


B) Economics and Business (E&B)

This curriculum will help you sharpening your research skills for a broad range of management studies. Lectures during the first year will provide you with sound theoretical and methodological bases.
You will learn how to design and implement researches in different disciplines ranging from accounting to innovation management, from marketing to organization and strategy.
During the second and third year, our faculty will connect you to cutting-edge research opportunities on relevant and timely topics like sustainability, internationalization, digitalization and servitization in large and small and medium enterprises, managerial and family firms, state-owned and no-profit organizations.
Finding your passion will make it easier to learn how to master quantitative and qualitative research methods to deepen your knowledge of the macro, meso and micro conditions underlying firms’ competitiveness.
Finally, you will be trained to develop and deliver your theoretical, policy and managerial implications to the most prestigious communities of management researchers and practitioners.

C) Quantitative Methods for Economics (QME)

This curriculum is designed to provide students with advanced education in statistics and quantitive methods for the study of socio-economic and financial phenomena. First-year courses focus on statistical inference, statistical models for multivariate and for longitudinal data, graphical models, survey sampling design and analysis, small area estimation, optimization tools, financial mathematics, computational statistics. The program and the Mathematics and Statistics faculty have several, well established, scientific connections with universities and research centers in many countries of the world: this enhances research opportunities and the connection with cutting-edge and relevant topics.

Research topics include graphical and latent variable models; official statistics and analysis of data from complex survey designs; small area estimation; causal inference; financial econometrics, time series analysis and volatility modeling; measures of risk and sustainable finance. The application of quantitative methods to socio-economic, financial, health and official data is of central importance and a core aspect of the curriculum. This will enable our Doctors to apply for positions in universities and public research institutions, as well as in the public administration and in industries where advanced data analysis skills are increasingly required.


The call for applications and all information related to this PhD program are available at:  http://dottorato.ec.unipg.it/apply-now/.  The deadline for applications is scheduled on the 31 July 2019. For more information, please contact Prof. Francesco Rizzi (francesco.rizzi@unipg.it)