DIGITAL TRANSFORMATION AND ECONOMIC GROWTH: A PREDICTIVE PANEL DATA ANALYSIS FOR REIMAGINING SUSTAINABLE LOCAL ECONOMIES IN DEVELOPING COUNTRIES

Abstract

This study aims to analyze the impact of digital transformation on economic growth, to forecast future economic growth in developing countries, and to provide policy recommendations for reimagining local economies in developing countries across the Asian region. The method employed is a quantitative approach using panel data analysis of nine countries over the period 2015–2022. The best model obtained is the Random Effects Model (REM), estimated using a robust approach to ensure the validity of the results. The variables used include internet, mobile, broadband, education, and energy as determinants of Gross Domestic Product (GDP). The results indicate that digital transformation variables broadband, internet, mobile, energy consumption, have a positive and significant effect on economic growth. Meanwhile, education shows a negative effect in the model. Predictive analysis suggests that continuous improvements in digital transformation will drive a positive economic growth trend during the 2023–2030 period. This study contributes by integrating explanatory and predictive analysis within a panel data framework and provides policy recommendations. The importance of strengthening digital infrastructure, energy, and improving human capital quality to support 
sustainable local economic transformation in developing countries.