Assessing the impact of science and education on GDP: Evidence from Armenia

Yuri Suvaryan (), Meri Manucharyan (), Liana Khachatryan (), Manush Minasyan () and Yevgenya Hakobyan ()

International Journal of Innovative Research and Scientific Studies, 2025, vol. 8, issue 6, 1358-1366

Abstract: This study aims to assess the methodological challenges and quantify the impact of scientific research and education on the volume and growth rates of GDP, with a specific focus on the case of Armenia. The analysis employs correlation and regression models to explore the relationships between GDP, scientific research expenditures, and educational services. Drawing on monthly macroeconomic data from Armenia for the period 1995–2023, the methodological framework includes trend analysis, Pearson correlation, and Granger causality tests to determine both the strength and the direction of predictive relationships between these variables. The results reveal strong positive correlations: between GDP and science (0.97), GDP and education (0.99), and between science and education (0.98). Regression analyses indicate that a one-unit increase in scientific output raises GDP by 564.3 billion drams, while a one-unit increase in educational output contributes 28.9 billion drams. Critically, Granger causality tests show that education and science outputs are significant predictors of future GDP growth, whereas GDP growth does not have a statistically significant predictive effect on future outputs in education or science. The study concludes that science and education are fundamental drivers of economic growth in Armenia, demonstrating a consistent and direct relationship with GDP despite geopolitical fluctuations. The findings suggest a unidirectional causality where investments in these sectors stimulate economic expansion, not vice versa. For policymakers in resource-limited economies like Armenia, the study underscores the critical importance of strategic, sustained investment in science and education as a primary engine for sustainable development. The methodological insights highlight the need for nuanced, long-term approaches to effectively capture the full economic return of investments in human capital and innovation.

Keywords: Analyses; Economic development; GDP; Granger Causality; Growth rate; Science and education. (search for similar items in EconPapers)
Date: 2025
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