Diagnosing Barriers to Technological Catch-Up: Evidence from a Hierarchical Bayesian Model of OECD Economies

Abstract

This thesis develops a hierarchical Bayesian model to estimate technological absorption across 37 OECD countries (2000–2021) along two dimensions: exposure to frontier knowledge (Direct Absorption Index, DAI) and internal conversion frictions (Catch-Up Friction Index, CUFI). The model nests countries within regional–income groupings and embeds a translog production system with feedback between output and human capital. The empirical estimates reveal striking cross-country contrasts. Switzerland, the United States, and the United Kingdom lead in both absorption and friction reduction. On the other hand, Japan and South Korea lag due to factors such as domestic technological resistance despite their technological reputation. Latvia, Lithuania, and Costa Rica rank lowest and face deficits across both indices. These patterns suggest that absorptive capacity is shaped not merely by technological potential but by institutional and structural characteristics. The framework offers a policy-relevant diagnostic tool for identifying bottlenecks and designing targeted interventions to support sustained productivity convergence.