The integrity of greenhouse gas emissions data is essential to assess progress towards countries’ pledges under the Paris Agreement on climate change. Building credible systems for emissions measurement, reporting and verification is challenging, especially in developing countries. Using a unique dataset from two of China’s pilot emissions trading systems (Beijing and Hubei), we compare firms’ self-reported CO2 emissions with emissions verified by third parties (‘verifiers’). In Beijing, we find that the average discrepancy fell by statistically significant levels (from 17% in 2012 to 4% in 2014 and 2015), while in Hubei it started lower and showed a statistically insignificant decrease (from 6% in 2014 to 5% in 2015). We observe no evidence of deliberate misreporting in these two pilots, and show that improvements in firms’ reporting capacity are associated with discrepancies of decreasing magnitude in Beijing. The results suggest that the administrative and firm capabilities required to support emissions trading systems in developing countries will require substantial time and effort to build.
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The original self-reported and verified emissions datasets were developed and are maintained by offices within the Chinese government, and can be accessed only with official permission. We make available all scripts that replicate the results presented in this study at https://github.com/zhangda1021/ChinaMRV. Additional data that support the findings of this study are available from the corresponding authors upon request.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
We acknowledge the support of the National Science Foundation of China (project number 71690244) and Ministry of Science and Technology, China (grant number 2017YFA0605304). We further thank the Energy Information Administration of the US Department of Energy for supporting this work under a cooperative agreement (grant number DE-EI0003030). This research received further support from an MIT Energy Initiative Seed Fund Grant and the MIT Joint Program on the Science and Policy of Global Change, which is funded through a consortium of industrial sponsors and federal grants, including the US Department of Energy (grant number DE-FG02-94ER61937). We are grateful to J. Caron (HEC Montreal), J. Jacoby (MIT), S. Li (Cornell University), B. Pizer (Duke University), R. Schmalensee (MIT), R. Stavins (Harvard University), S. Tanaka (Tufts University), D. Victor (UCSD) and X. Zhou (Harvard University) for helpful comments, and to L. Sun (McGill University) for advice on data visualization.