During June and July 2026, Institute researchers Luka Draganić, Romario Marijanović, Branko Stanić, and Anja Špoljarić participated in the summer school organized by the Barcelona School of Economics. The summer school aims to advance professional development of economists, doctoral students, and researchers in the field of economics.

Luka Draganić attended the Bayesian Estimation of RANK and HANK Business Cycle Models course which encompassed RANK and HANK models, Bayesian RANK solvers and the innovative HANK solver method which applies the Jacobian matrices in the sequence space. Through the theoretical and practical classes in MATLAB, he gained insight into different New Keynesian models and solver methods.

Romario Marijanović participated in the Dynamic and Non-linear Panel Data Models program, which focused on advanced dynamic panel models, discrete and censored panel models, and the estimation of dynamic panel models in the presence of sample selection. Through a combination of theoretical lectures and practical workshops using the STATA software package, he gained knowledge regarding the specification, estimation, and interpretation of modern panel models, as well as their application in empirical economic research.

Branko Stanić attended the Quantitative Methods for Spatial Economics programme, which covered contemporary quantitative approaches to spatial economics, with a focus on the spatial distribution of economic activity, interregional linkages, and the role of geographical and economic factors in shaping spatial patterns. The programme enabled him to deepen his understanding of spatial economic relationships and of the ways in which the effects of different economic policies on cities and regions can be analysed.

Anja Špoljarić participated in the Statistical Machine Learning for Large and Unstructured Data course, focusing on contemporary statistical methods for analysing large and unstructured data. The topics covered in the course included probabilistic modelling, high dimensional linear regression models, causal inference, and text data analysis. Through theoretical lectures and practical labs using R, she gained expertise in advanced computational data analysis methods, as well as the application of contemporary statistical and Bayesian approaches to research in economics.

The summer school was funded by the National Recovery and Resilience Plan 2021-2026 (NextGenerationEU) under the projects Strategic networking and innovation as determinants of the business performance of small and medium-sized enterprises: possibilities of applying the experiences of private enterprises in the public sector economics and Efficiency of public services at local government levels – definitions, measurements and analyses, as well as the Croatian Science Foundation installation research project Fiscal decentralization in Croatia – current state, challenges, and potential solutions.