“Absorption capacity of regions in terms of supporting entrepreneurship under the EU Cohesion Policy. New evidence” – 27th seminar online by QFRG and DSLab [19.11.2022]
We kindly invite to join the 27th seminar organised jointly by the Quantitative Finance Research Group and Data Science Lab.
During the meeting “Absorption capacity of regions in terms of supporting entrepreneurship under the EU Cohesion Policy. New evidence” Marcin Wajda, Ph.D. (Warsaw School of Economics) and prof. Piotr Wójcik from the Department of Quantitative Finance at the Faculty will present their research.
The meeting will take place on December 19th, 2022 (Monday) at 17:00 via Zoom platform.
Link to the meeting:
https://uw-edu-pl.zoom.us/j/94029787811?pwd=dytEUHF5Zi9OZWhUWERtMkszM1kwUT09
Meeting ID: 940 2978 7811
Passcode: 233525
The meeting will be conducted in English. The presentation is scheduled for about 45 minutes, and after that we invite you to a discussion.
Please log in the latest at 4:50 PM. The presentation will start at 5:00 PM.
Joining a meeting implies consent to recording. Please turn off cameras and microphones during the presentation and send the questions to the speaker in the chat.
Presentation abstract:
A good understanding of the mechanism of absorption of funds under the Cohesion Policy is essential from the point of view of poorly developed regions, but also for the EU as a whole. The aim of the paper is to analyse the expenditures of funds from the Cohesion Policy in the 2007–2013 perspective in the area of support for entrepreneurs on NUTS2 level. Previous studies demonstrated that the econometric methods that have been used so far might prove insufficient. That is why we apply non-linear machine learning algorithms (LASSO, support vector regression and random forest) which have a great advantage of presenting the real influence of individual predictors on absorption. To better understand the results we apply selected explainable artificial intelligence (XAI) tools – permutated feature importance and partial dependency profiles. The results confirm that non-linear approach is more effective and allows for the identification of break points, at which the amount of financing received by a particular region changes significantly.
