Crossing the decarbonization threshold: A sectoral endogenous growth model of U-shaped transport carbon efficiency

Yan and Li (2023) find a U-shaped link between transport carbon emissions reduction efficiency (TCERE) and economic growth, using per-capita nighttime lights as a novel growth indicator. This project embeds that empirical regularity in a Romer-style, sectoral model with learning-by-doing and knowledge spillovers in clean transport technologies. Early-stage growth can temporarily reduce TCERE due to scale-up frictions, but beyond a threshold, innovation and network effects make decarbonization more efficient with further growth. Moving beyond static EKC-style correlations, this provides an explicit micro-founded mechanism for a U-shape in a key sector, integrated with remote sensing-based measurement. It connects to the semi- vs fully-endogenous growth debate by asking whether transport innovation is scale-driven or idea-driven. The project calibrates sectoral learning curves with panel data on transport investments, mode share, and TCERE across regions, using nighttime lights as a harmonized proxy where GDP data are weak. It stress tests under climate-induced volatility in fuel and infrastructure costs. This identifies concrete policy levers—pushing economies past the TCERE turning point via demand aggregation (public procurement), mode shift infrastructure, and R&D subsidies—and quantifies growth and emissions co-benefits of crossing that threshold earlier. The impact is a tractable tool for green industrial policy sequencing, highlighting when “grow to green faster” is optimal and how to avoid getting stuck on the inefficient side of the U.

References:

1. Semi-Endogenous or Fully Endogenous Growth? A Uni(cid:133)ed Theory (cid:3). Guido Cozzi, Faruk Gul, Chad Jones, Pietro Peretto, S. Smulders (2023).
2. Transport carbon emissions reduction efficiency and economic growth: a perspective from nighttime lights remote sensing. Yuxiang Yan, Jianing Li (2023). Archives of Transport.