Bayesian hierarchical modeling reveals how Schumpeterian technology diffusion drives BRICS convergence toward the United States frontier

Since the mid-1800s, global development has exhibited greater divergence than convergence, with only a select group of economies forming so-called “convergence clubs.” In the context of sustainability research, the ability of large emerging groups to close technology gaps is critical, as it influences SDG-compatible development trajectories. This study assesses whether BRICS economies are technologically converging with the U.S. frontier by employing a neo-Schumpeterian diffusion framework that integrates both technology adoption and domestic innovation. Exponential and logistic catch-up dynamics are estimated for BRICS-5 (Brazil, Russia, India, China, South Africa) over 1996–2022, with the analysis extended to the expanded BRICS using Bayesian hierarchical methods that enhance inference stability under multicollinearity and parameter uncertainty. The findings reveal steady convergence of both BRICS-5 and BRICS+ toward the frontier, with the BRICS-5 demonstrating stronger absorptive and innovation capacities. Innovative human capital facilitates both imitation and domestic innovation, while institutional quality, tacit knowledge transfer, FDI attraction, and ICT diffusion are significant drivers of technological growth. Conversely, the impacts of R&D intensity, digital investment, financial development, and education investment are contingent upon governance quality and absorptive capacity, indicating that financial inputs alone are insufficient without supportive institutions and capabilities. Methodologically, this paper presents the first Bayesian hierarchical application of the neo-Schumpeterian diffusion model and offers actionable, SDG-aligned policy recommendations for emerging economies.