Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/305750 
Erscheinungsjahr: 
2024
Schriftenreihe/Nr.: 
IZA Discussion Papers No. 17308
Verlag: 
Institute of Labor Economics (IZA), Bonn
Zusammenfassung: 
This paper provides insights into the design of effective location-based policies. In the context of European regional policy, we use algorithms to predict regions that are likely to underutilize funding and identify the key determinants of their low absorptive capacity. We then use a regression discontinuity design (RDD) to document that EU funds are ineffective in recipients predicted to have low absorptive capacity while increasing output and employment in high-capacity regions. Our approach allows early identification and targeting of interventions to increase regional spending capacity based on publicly available data and standard algorithms, thereby facilitating implementation by policymakers.
Schlagwörter: 
machine learning
location-based policies
program design
JEL: 
C21
F35
H77
R11
Dokumentart: 
Working Paper

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