Targeting and Effectiveness of Location-Based Policies

Vincenzo Carrieri (vincenzo.carrieri@unical.it), Guido de Blasio, Antonella Ferrara and Rosanna Nisticò
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Vincenzo Carrieri: University of Calabria
Rosanna Nisticò: University of Calabria

No 17308, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: 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.

Keywords: machine learning; location-based policies; program design (search for similar items in EconPapers)
JEL-codes: C21 F35 H77 R11 (search for similar items in EconPapers)
Pages: 23 pages
Date: 2024-09
New Economics Papers: this item is included in nep-big, nep-geo, nep-ipr and nep-ure
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