Empirical Results and Analysis

Sheng Liu (), Xiuying Chen and Rui Wang
Additional contact information
Sheng Liu: Guangdong University of Foreign Studies
Xiuying Chen: Guangdong University of Finance
Rui Wang: Guangdong University of Foreign Studies

Chapter 6 in Green Trade Barriers and the Green Transformation of China's Manufacturing Industry, 2026, pp 47-71 from Springer

Abstract: Abstract This chapter presents empirical results on the impact of green trade barriers on pollution emission intensity in Chinese firms. Using methods like Propensity Score Matching (PSM) and Difference-in-Differences (DID), the study finds that green trade barriers significantly reduce chemical oxygen demand (COD) and sulfur dioxide (SO₂) emissions. The results hold after robustness checks and additional tests such as parallel trend and placebo tests. Further analysis reveals that the effectiveness of these barriers varies by firm characteristics (e.g., trade mode, ownership structure), regional regulatory intensity, and industry pollution levels. Mechanisms such as reduced production scale, technological innovation, and resource reallocation are identified as key drivers of emission reductions. The study concludes that green trade barriers can incentivize green innovation and promote sustainable practices in firms, offering valuable insights for developing countries looking to balance economic growth and environmental protection.

Date: 2026
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-95-5433-1_6

Ordering information: This item can be ordered from
http://www.springer.com/9789819554331

DOI: 10.1007/978-981-95-5433-1_6

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().