Advanced Research Methods in Regional Science

About

This course is designed for master nad Phd students, researchers, academics, and professionals eager to deepen their understanding of spatial data analysis and its applications in regional science. Throughout the program, participants will explore spatial econometrics in R, learn to identify and address spatial dependence in panel data, to apply cutting-edge techniques for more sophisticated data analysis, delve into the complexities of economic modeling across multiple sectors and regions and combine theoretical knowledge with practical application by engaging in empirical simulation models and testing complex causal relationships. Besides, the participants will broaden analytical skills with advanced spatial analysis techniques for comprehensive neighborhood and regional science studies.

Course leader

Vinko Muštra is the dean and associate professor at the Faculty of Economics, Business and Tourism, University of Split with a profound interest in regional and urban topics.

Target group

Graduate students in economics (or in social sciences, technical sciences or science related fields) who intend to round out their knowledge in the regional science and use it in the process of preparing dissertations.

Holders of undergraduate degrees or students on last year of their studies in economics or the social sciences who wish to study the field of regional economics.

Researchers and professionals working in the field.

Course aim

The course offers comprehensive learning outcomes, condensed into four key areas:

Mastery of spatial econometric tools in R and the ability to analyse spatial dependencies in economic data, with practical application to regional studies.
Expertise in multisectoral and multi-regional economic modelling
Introduction to innovative methodologies in regional science, such as spatial machine learning, agent-based modelling and Structural Equation Modelling, for robust economic and social simulations.
Practical experience with survey methods and spatial analysis, culminating in the ability to conduct empirical research and neighbourhood analysis within regional science.

Fee info