Predicting Delays in Cohesion Infrastructure Projects

Giuseppe Coco (), Gianluca Monturano () and Giuliano Resce ()

Economics & Statistics Discussion Papers from University of Molise, Department of Economics

Abstract: Public investment in infrastructure is essential for economic growth, but delays in project implementation can undermine its benefits. This paper examines the determinants of such delays using data from cohesion projects in Italy. We predict which projects are likely to experience delays and identify the key contributing factors by means of machine learning (ML) techniques. To avoid endogeneity, we use only (lagged) features observed at the start of the project as predictors. Our findings show that socioeconomic factors and institutional weaknesses in various regions play a significant role in these delays. The discipline imposed by rules and strict implementation timing on EU funds seems to work, lending credibility to the hypothesis of the benefit of an external commitment. Results underscore the potential of ML in designing appropriate implementation policies, enhancing project management, and improving the outcomes of public investments.

Keywords: Territorial cohesion; Administrative efficiency; Machine learning; Project Delays. (search for similar items in EconPapers)
JEL-codes: C55 H77 O18 R58 (search for similar items in EconPapers)
Pages: 52
Date: 2025-01-08
New Economics Papers: this item is included in nep-big and nep-ppm
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://web.unimol.it/progetti/repec/mol/ecsdps/ESDP25099.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:mol:ecsdps:esdp25099

Access Statistics for this paper

More papers in Economics & Statistics Discussion Papers from University of Molise, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Claudio Lupi ().