<![CDATA[Regional economic inequality remains a major challenge in many countries, particularly in the context of rapid technological disruption and digital transformation. The concept of regional economic convergence suggests that less developed regions may grow faster than advanced regions, thereby reducing disparities in income and productivity. However, recent evidence indicates that convergence processes are increasingly influenced by technological innovation, spatial spillovers, and structural regional differences. This study aims to analyze regional economic convergence in the era of technological disruption by applying dynamic panel and spatial econometric approaches to capture both temporal dynamics and spatial interactions among regions. This research employs a quantitative approach using secondary panel data on regional economic indicators, including gross regional domestic product per capita, digital economy development, infrastructure, and human capital. The analysis applies dynamic panel estimation using the Generalized Method of Moments (GMM) to identify β-convergence, followed by spatial econometric modeling to examine spatial spillover effects between regions. The results indicate that regional convergence occurs conditionally rather than absolutely, with technological innovation and digital economy development playing important roles in shaping regional growth dynamics. Spatial econometric results reveal significant spillover effects, indicating that technological development in one region can positively influence economic growth in neighboring regions. In conclusion, regional convergence in the era of technological disruption is strongly influenced by innovation spillovers and spatial interactions, highlighting the importance of dynamic panel and spatial econometric models in analyzing regional economic development patterns.]]>
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