Balancing Infrastructure and Human Capital: Optimal Fiscal Composition for Sustainable Growth

Octavio Martínez-Baltodano & María Haydée Fonseca‐Mairena

Economia2025https://doi.org/10.18800/economia.202501.002article
ABDC C
Weight
0.50

What the paper says

This paper investigates the relationship between fiscal policy composition and long-run economic growth by extending the classic Alesina–Rodrik framework. We develop a dynamic model that distinguishes between capital-augmenting public investments (such as infrastructure) and labor-enhancing expenditures (including human capital development), both financed through a wealth tax. Our central hypothesis is that an optimal allocation of public spending exists which maximizes the net return on capital and thereby supports sustained growth. However, political pressures—stemming from heterogeneous factor endowments and median voter preferences—can drive fiscal policies away from this efficiency benchmark, leading to suboptimal tax rates and spending compositions that may even trigger growth traps. By employing comparative statics and equilibrium analysis, we demonstrate how redistributive forces influence the choice of fiscal instruments, ultimately affecting aggregate productivity and capital accumulation. The findings offer novel theoretical insights into the trade-offs between redistribution and growth, underscoring the critical importance of aligning fiscal composition with underlying production technologies to achieve both efficient and politically feasible outcomes.

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https://doi.org/https://doi.org/10.18800/economia.202501.002

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@article{octavio2025,
  title        = {{Balancing Infrastructure and Human Capital: Optimal Fiscal Composition for Sustainable Growth}},
  author       = {Octavio Martínez-Baltodano & María Haydée Fonseca‐Mairena},
  journal      = {Economia},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.18800/economia.202501.002},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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