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https://doi.org/10.2139/ssrn.5...
Article . 2025 . Peer-reviewed
Data sources: Crossref
https://doi.org/10.2139/ssrn.5...
Article . 2025 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2025
License: CC BY
Data sources: Datacite
DBLP
Preprint . 2025
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What Can 240,000 New Credit Transactions Tell Us About the Impact of Ngeu Funds?

Authors: Alvaro Ortiz; Tomasa Rodrigo; David Sarasa; Sirenia Vazquez;

What Can 240,000 New Credit Transactions Tell Us About the Impact of Ngeu Funds?

Abstract

Using a panel data local projections model and controlling for firm characteristics, procurement bid attributes, and macroeconomic conditions, the study estimates the dynamic effects of procurement awards on new lending, a more precise measure than the change in the stock of credit. The analysis further examines heterogeneity in credit responses based on firm size, industry, credit maturity, and value chain position of the firms. The empirical evidence confirms that public procurement awards significantly increase new lending, with NGEU-funded contracts generating stronger credit expansion than traditional procurement during the recent period. The results show that the impact of NGEU procurement programs aligns closely with historical procurement impacts, with differences driven mainly by lower utilization rates. Moreover, integrating high-frequency financial data with procurement records highlights the potential of Big Data in refining public policy design.

Keywords

FOS: Economics and business, FOS: Computer and information sciences, Computer Science - Machine Learning, Statistical Finance (q-fin.ST), Quantitative Finance - Statistical Finance, Machine Learning (cs.LG)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green