Structural Modeling of Equity Outcomes with Research Funding Rules in National Innovation Systems

Abstract

The distribution of research funding within National Innovation Systems represents a critical determinant of scientific output, technological advancement, and long-term economic growth. Historically, resource allocation mechanisms have prioritized perceived meritocratic efficiency, often unintentionally exacerbating structural disparities across institutions, disciplines, and demographic groups. This paper investigates the equity outcomes of diverse research funding rules by employing a comprehensive structural modeling approach. By simulating the long-term dynamics of grant allocations under various policy configurations, the study elucidates the complex feedback loops that drive the accumulation of scientific advantage and resource concentration. The structural model captures the interplay between researcher productivity, institutional capacity, and funding agency algorithms, providing a robust framework for evaluating policy interventions such as funding caps, stratified peer review, and lottery-based distribution thresholds. The findings demonstrate that strictly performance-based funding rules systematically diminish systemic equity, thereby reducing the diversity of the research ecosystem over time. Conversely, the introduction of equity-weighted allocation constraints significantly mitigates institutional monopolization without proportionally degrading aggregate scientific productivity. Ultimately, this research offers evidence-based insights for policymakers seeking to design more equitable and sustainable National Innovation Systems, emphasizing the necessity of balancing merit-driven excellence with structural fairness.