Paper: arXiv 2504.01964

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.

Complexity vs Empirical Score

  • Math Complexity: 3.5/10
  • Empirical Rigor: 8.0/10
  • Quadrant: Street Traders — practical and empirical, lighter on theory

Why this score: The paper employs a standard econometric model (Local Projections) with moderate mathematical complexity, focusing on estimation rather than theoretical derivations, but demonstrates high empirical rigor through a novel, large-scale dataset (240,000 credit transactions) integrated with procurement records, detailed backtesting, and robustness checks.

Research Flowchart

  flowchart TD
  A["Research Question<br>Impact of NGEU<br>Procurement on Credit?"] --> B["Methodology<br>Panel Data & Local Projections"]
  
  B --> C["Data Inputs"]
  subgraph C [" "]
      C1["240K Credit Transactions"]
      C2["Procurement Records"]
      C3["Firm Characteristics"]
      C4["Macroeconomic Data"]
  end

  C --> D["Computational Process<br>Estimate Dynamic Effects"]
  
  D --> E{"Key Findings"}
  
  E --> F["Procurement Awards<br>Significantly Increase<br>New Lending"]
  E --> G["NGEU Contracts<br>Generate Stronger<br>Credit Expansion"]
  E --> H["Impact Alignment<br>Differences Driven by<br>Lower Utilization Rates"]