From assimilation to innovation: A Bayesian Nelson–Phelps model of China’s technological catch-up with the United States

Abstract

Over the past half-century, China has been evolving into the second-largest economic system, which creates endogenous innovation as a key driver of growth. Yet, a scientific inquiry into whether or not this nation can technologically keep pace with the United States (U.S.) remains unexplored. The purpose of this research is to explore China’s possibilities for technological convergence with the frontier, evaluating the logistic against exponential variants within the neo-Schumpeterian diffusion paradigm. The study also assesses how education and other structural capacities—including governance quality, financial capacity, openness policies, and digital infrastructure—condition China’s standing vis-à-vis the frontier. To this end, Bayesian mixed regressions are applied to the Chinese and U.S. time-series data spanning 1996–2022. The research findings indicate that this country’s technological convergence predominantly occurs through implementation rather than innovation. An increasing contribution from innovation-oriented human capital and R&D activities signals China’s steady evolution toward innovation-driven expansion. Policy implications include enhancing the quality of education, strengthening institutional, innovation, and financial capacities, and promoting a balanced combination of technology absorption and generation for China and other emerging economies.