Sustainable economic convergence in emerging markets now hinges on a structural break from the historical fossil‑fuel‑intensive development model. As the document states, “achieving sustainable economic convergence requires nothing less than a fundamental structural decoupling of economic growth from carbon intensity.” This monograph argues that clean technology diffusion—through FDI spillovers, global value chain integration, patent licensing, South‑South cooperation, and AI‑enabled grid modernization—has become the central engine of productivity growth and industrial upgrading across the Global South. Empirical evidence shows that clean capital inflows generate significant Total Factor Productivity (TFP) gains, with green FDI and capital‑goods imports producing elasticities of +0.32% to +0.38% per 10% increase, while domestic absorptive capacity yields the highest long‑run multiplier. The study identifies a persistent cost‑of‑capital divide—where emerging economies face WACCs 2–4× higher than advanced economies—as the largest barrier to clean diffusion, despite dramatic global cost declines in solar, wind, and battery storage. It also highlights systemic risks including transmission grid deficits, CBAM‑driven trade vulnerabilities, and critical mineral refining concentration. To overcome these constraints, the monograph proposes a three‑pillar policy architecture: (1) financial de‑risking via MDB guarantees and FX‑risk mitigation; (2) targeted green industrial policy to build domestic manufacturing and absorptive capacity; and (3) open technology transfer through patent pools, TRIPS flexibilities, and interconnected regional supergrids. Ultimately, the document outlines a phased roadmap (2026–2050) in which emerging economies can achieve full structural convergence—defined as high‑productivity, low‑carbon industrialization—by scaling clean energy, modernizing grids, deploying green hydrogen and advanced manufacturing, and establishing equitable global technology‑transfer systems.
Hunter Hughes, H Heuristics· Zenodo (CERN European Organi...· 0 citations
Sustainable economic convergence in emerging markets now hinges on a structural break from the historical fossil‑fuel‑intensive development model. As the document states, “achieving sustainable economic convergence requires nothing less than a fundamental structural decoupling of economic growth from carbon intensity.” This monograph argues that clean technology diffusion—through FDI spillovers, global value chain integration, patent licensing, South‑South cooperation, and AI‑enabled grid modernization—has become the central engine of productivity growth and industrial upgrading across the Global South. Empirical evidence shows that clean capital inflows generate significant Total Factor Productivity (TFP) gains, with green FDI and capital‑goods imports producing elasticities of +0.32% to +0.38% per 10% increase, while domestic absorptive capacity yields the highest long‑run multiplier. The study identifies a persistent cost‑of‑capital divide—where emerging economies face WACCs 2–4× higher than advanced economies—as the largest barrier to clean diffusion, despite dramatic global cost declines in solar, wind, and battery storage. It also highlights systemic risks including transmission grid deficits, CBAM‑driven trade vulnerabilities, and critical mineral refining concentration. To overcome these constraints, the monograph proposes a three‑pillar policy architecture: (1) financial de‑risking via MDB guarantees and FX‑risk mitigation; (2) targeted green industrial policy to build domestic manufacturing and absorptive capacity; and (3) open technology transfer through patent pools, TRIPS flexibilities, and interconnected regional supergrids. Ultimately, the document outlines a phased roadmap (2026–2050) in which emerging economies can achieve full structural convergence—defined as high‑productivity, low‑carbon industrialization—by scaling clean energy, modernizing grids, deploying green hydrogen and advanced manufacturing, and establishing equitable global technology‑transfer systems.
Hunter Hughes, H Heuristics· Zenodo (CERN European Organi...· 0 citations