Adding Institutional Metrics to Economic Complexity Models Improves Growth Forecasting

Researchers have integrated institutional indicators directly into Economic Complexity forecasting models for the first time, demonstrating that governance metrics improve the accuracy of economic growth projections across distinct stages of development. The investigation, published in Humanities and Social Sciences Communications, expanded traditional Velocity Bootstrapped Selective Predictability Scheme models by incorporating Polity alongside established measures of export sophistication and innovation capacity.

The traditional framework incorporates metrics such as Fitness to capture export sophistication and Technological Fitness to represent innovation capacity. In the new study, the authors systematically evaluated how adding Polity, an index capturing institutional structures, alters gross domestic product growth forecasting across different national settings, testing model configurations to determine how each indicator influences predictive performance.

The comparative analysis revealed that no single variable governs economic forecasts uniformly across the globe. Instead, individual metrics proved most effective at specific development phases: Polity yielded the highest predictive accuracy for early-stage developing countries, traditional Fitness served best for middle-stage developing economies, and Technological Fitness proved most decisive for advanced economies.

The study also identified a clearly-defined cohort of nations where incorporating more than two metrics notably enhanced prediction accuracy, indicating that the conventional two-dimensional approach of Economic Complexity models is insufficient for specific country groups. In addition, the authors identified China and India as distinct outliers within the global dataset, requiring separate evaluation outside standard modeling configurations.

These findings suggest that robust forecasting of economic development requires higher-dimensional analytical frameworks tailored to specific developmental trajectories. By systematically demonstrating where governance metrics enhance growth projections, the study provides a methodological foundation for expanding Economic Complexity theory and refining macroeconomic forecasting models.

Subject of Research: Economic growth forecasting using institutional metrics in economic complexity models

Article Title: Institutions in economic complexity: enhancing growth predictions and theoretical understanding

Article References: Angelini, O., Tacchella, A., Pietronero, L., & Di Matteo, T. (2026). Institutions in economic complexity: enhancing growth predictions and theoretical understanding. Humanities and Social Sciences Communications. https://doi.org/10.1057/s41599-026-09377-0

Image Credits: AI Generated

DOI: 10.1057/s41599-026-09377-0

Keywords: Economic Complexity, Growth Forecasting, Institutional Economics, Polity Metric, Fitness Metric, Technological Fitness, GDP Predictions, Macroeconomic Modeling, Predictive Accuracy, Economic Development, Developing Economies, Advanced Economies, Innovation Capacity, Export Sophistication, Selective Predictability Scheme