Spillover Effects of Carbon Emission Trading on the Green Supply-Chain Finance Network

Zhoufan Yu; Huijie Tang; Ningai Leng

doi:10.70393/6a6574626d.333033

Authors

Zhoufan Yu Cornell University
Huijie Tang University of Michigan
Ningai Leng JPMorgan Chase

DOI:

https://doi.org/10.70393/6a6574626d.333033

ARK:

https://n2t.net/ark:/40704/JETBM.v2n3a01

Disciplines:

Finance

Subjects:

Corporate Finance

References:

18

Keywords:

Carbon Emission Trading, Green Supply-Chain Finance, Technological Innovation, Financing Environment, Spillover Effects

Abstract

Against the backdrop of China’s deepening “dual-carbon” strategy, this paper systematically evaluates the spillover effects of Carbon Emission Trading (CET) on the Green Supply-Chain Finance Network (GSCFN). We first construct a three-tier transmission framework—“technological innovation → financing environment → chainwide collaboration”—to reveal, in theory, how CET price signals reallocate capital and diffuse across supply-chain nodes. Using a balanced panel of 420 listed manufacturing and power-sector firms from 2015–2023 and a fixed-effects model, we find: (i) a 0.1-unit increase in CET intensity raises green patent output by 0.8–1.0 items (p < 0.05); (ii) monetising carbon assets lowers green-loan interest rates by 38–45 basis points and boosts the supply-chain collaboration index by 2.4–3.1 percentage points; (iii) carbon-price stability significantly moderates firms’ green-investment willingness, and cross-regional tests confirm heterogeneous capital flows under different ETS designs. This study extends the literature at the intersection of carbon-market externalities and supply-chain finance, offering empirical support for carbon-market design and corporate practice under the dual-carbon goal. Policy recommendations include (a) a carbon-price corridor to stabilise expectations, (b) acceptance of carbon-asset income rights as collateral, and (c) leveraging leading firms’ contractual externalities to drive upstream- and downstream-level decarbonisation. Future work could employ spatial econometrics and network models, incorporating dynamic ESG scores and on-site verification data to depict cross-chain and cross-regional diffusion speed and intensity more precisely.

Author Biographies

Zhoufan Yu, Cornell University

Master's in Applied Economics and Management, Cornell University, Ithaca, New York, United States, 14850.

Huijie Tang, University of Michigan

Master of Supply Chain Management, 500 S. State St, Ann Arbor, MI 48109, USA.

Ningai Leng, JPMorgan Chase

Quality Sr. Specialist Ⅱ, 20855 Stone Oak Pkwy, San Antonio, TX, US, 78258.

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