Debt versus tax financing in infrastructure: impact on employment

Debt versus tax financing in infrastructure: impact on employment

##article.authors##

  • Firdavs Raxmatov
  • Gulfayruz Kengesbaeva

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https://doi.org/10.5281/zenodo.16686068

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USA, infrastructure investment, tax financing, debt financing, econometrics, employment.

##article.abstract##

The study examines whether debt-financed or tax-financed infrastructure investments yield better employment
outcomes by analyzing U.S. macroeconomic data from 1989–2023. Using data from the IMF and World Bank, key variables
include the employment-to-population ratio, real GDP, gross fixed capital formation, inflation rates, interest rates, tax
revenue, and FDI. Two key indicators government borrowing for infrastructure (Infra_debt) and tax-funded infrastructure
spending (Infra_tax) are constructed to quantify financing methods. These are adjusted for GDP to ensure comparability
over time. Regression models with Newey-West standard errors address heteroskedasticity and autocorrelation, while
structural shifts are accounted for with lagged variables and dummy variables for events like the (2007) Financial Crisis
and (2021) COVID-19. The results indicate that GDP growth is a strong predictor of employment.
Debt-financed infrastructure investment has a modest positive effect on employment, suggesting that borrowing supports
job creation. In contrast, tax-financed infrastructure investment has little to no effect, potentially due to the economic
drag of increased taxation. These findings align with theories that borrowing can stimulate employment more effectively
in developed economies by avoiding distortions in consumer and business spending. In conclusion, debt-financed
infrastructure investment appears more favorable for employment growth than tax-based financing. While both methods
sustain public investment, policymakers should consider the potential drawbacks of higher taxation on labor markets.
Strategic debt financing can promote economic expansion while minimizing employment disruptions.

##submission.authorBiographies##

Firdavs Raxmatov

Tashkent Turin Polytechnic University researcher

Gulfayruz Kengesbaeva

Tashkent Turin Polytechnic University student
[email protected]

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2025-04-01
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