Impulse Response Function Analysis of the Long-Term Effects of Knowledge-Based Economy Indicators on the Economic Growth of Selected Persian Gulf Countries

Abstract

Objective: This study aims to analyze the impulse response of the long-run effects of knowledge-based economy indicators on the economic growth of selected Persian Gulf countries during the period 2010 to 2022. Methods and Materials: The study employed a Panel Vector Autoregression (PVAR) model along with the Impulse Response Function (IRF) technique. Variables included institutional quality, innovation (R&D), human capital and active labor force, ICT infrastructure, and personal internet usage. Data were sourced from the World Bank, and optimal lag lengths were determined prior to analysis. Findings: Results revealed that institutional quality, innovation, human capital and labor force, ICT, and internet usage—each representing one of the four key pillars of the knowledge-based economy—have statistically significant and positive effects on economic growth in both the short, medium, and long run across the selected Persian Gulf countries. Conclusion: The findings affirm the strategic importance of knowledge-based economy components in fostering sustainable economic growth in the region. Policymakers are advised to strengthen institutional frameworks, enhance digital infrastructure, invest in human capital, and support innovation systems and intellectual property protection to fully leverage the growth potential of knowledge-based development.