Author Description

This paper explores Asia-Pacific's medium-term growth prospects using two approaches. First, growth accounting analysis and machine-learning estimation reveal how demographics, capital deepening, productivity, and human capital shaped Asia's growth. Second, an innovative algorithm forecasts growth by matching countries' current conditions with historically analogous periods using Dynamic Time Warping (DTW). Comparing pattern-based forecasts with traditional projections highlights economic convergence and demographic headwinds. Results show that without ambitious reforms, Asia's growth will likely moderate, though remaining the world's fastest growing region. The paper offers data-driven tools for policymakers to identify growth drivers and generate robust forecasts.