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International Environmental Agreement and Trade in Environmental Goods: The Case of Kyoto Protocol

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Abstract

The Kyoto Protocol has received much criticism for its effectiveness as well as the spillover effect (i.e. carbon leakage and competitiveness loss). This paper provides the first evidence for the effect of the Kyoto Protocol on the bilateral trade in environmental goods, which can mitigate and prevent environmental damage. Using the generalized synthetic control method, I construct the counterfactual of trading pairs with Kyoto commitment and show that the export of environmental goods by Kyoto countries increases by 29–30% after the protocol enters into force. The paper further examines the top exporters (Germany and Japan) individually and also reports positive effects. Technology transfer induced by project-based mechanisms under the Kyoto Protocol, in particular Clean Development Mechanism, is found to be the potential driving force.

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Notes

  1. The specific sub-categories in the pollution management group are (1) air pollution control, (2) wastewater management, (3) solid waste management, (4) remediation and cleanup, (5) noise and vibration abatement, and (6) environmental monitoring, analysis and assessment.

  2. Air pollution control and environmental monitoring belong to the pollution management group, while renewable energy is in the resource management group. Together, they comprised approximately 25% of EG trade value in 2011. Details of the six-digit HS product code in the analysis can be found in Table A2 of Sugathan (2013).

  3. From now on, EGs are used to imply only products in the analysis, unless otherwise indicated.

  4. The synthetic method relies on placebo tests to gauge the uncertainty of the estimated treatment effect. A detailed comparison of the two approaches can be found in Sect. 3.

  5. Details of the emission limitation or reduction commitment can be found at https://unfccc.int/kyoto_protocol.

  6. See https://unfccc.int/kyoto-protocol-html-version.

  7. From now, the terms “Annex B countries" and “Kyoto countries" are used interchangeably to indicate countries that have commitments in the KP.

  8. See https://unfccc.int/process/the-kyoto-protocol/the-doha-amendment.

  9. The products in the analysis were from the two subcategories of the resources management group of EGs: (i) renewable energy plant and (ii) heat energy savings and management.

  10. The proxies are carbon dioxide emissions, current environmental protection expenditures by both the public and private sectors, the percentage of revenues from environmental taxes in total revenues, and the public investment in environmental protection.

  11. Costantini and Crespi (2008) argue that carbon dioxide emissions is a proxy variable that partially represents countries’ efforts to respect Kyoto abatement targets; however, the coefficient estimation shows no statistical significance.

  12. It is assumed that the factor component \(\lambda _{p}' f_{t} = \lambda _{p1} f_{1t} + \lambda _{p2} f_{2t} + ... + \lambda _{pr} f_{rt}\) takes a linear and additive form

  13. Australia and Croatia ratified in 2007, so the enforcement year for these two countries is also 2007.

  14. Ratification is used as a treatment period in the majority of Kyoto studies, such as Grunewald and Martinez-Zarzoso (2016); Almer and Winkler (2017).

  15. Aichele and Felbermayr (2013b) restrict their analysis period to 2007 and consider Australia an “untreated" country.

  16. The placebo studies are conducted by assigning one unit in the control group as “treated" and analyzing its effect with the remaining units in the control group. Theoretically, there should be no treatment effect found in these control units. Therefore, the treatment effect found in the actual “treated" unit is considered significant when it is larger than that of all control units.

  17. Further details can be found in Xu (2017).

  18. Trade value is expressed in current USD, so it is deflated using the United States Consumer Price Index.

  19. Source: https://treaties.un.org/Pages/ViewDetails.aspx?src=TREATY&mtdsg_no=XXVII-7-a&chapter=27&clang=_en.

  20. This restriction will help speed up the analysis, as a larger unbalanced panel will significantly slow the process. Note that the method cannot execute if there are observations with missing values in the covariates, so the sample is also restricted to all observations with no missing values in the covariates.

  21. The total nominal trade value of the original data in the same period is 4,270 billion USD.

  22. The export value from Annex B countries in the raw data is about 2,450 billion USD.

  23. In the robustness check, I extend the analysis to 2015, as some might argue that the Doha Amendment has not yet been effective. It is possible that the Doha Amendment has little effect on the original Kyoto commitments. While the data are now available until 2017, I again restrict the analysis until 2015, as the Paris Agreement was adopted in 2015. The agreement could be regarded a structural break, so the method cannot accommodate the DGP in this case.

  24. Similar to Aichele and Felbermayr (2013b), the energy intensity of the pair is the difference between the energy intensity of the exporter and importer.

  25. Note that for all analyses in this paper, the last year for Romania is dropped. The reason for this exclusion lies in the fact that Romania was the first country to ratify the KP in 2001, while the ratification year for most remaining countries was 2002. Given that the method scales the ratification year as 0 for all countries, only Romania has the longest post-treatment period. Hence, Romania is the only treated country in the final period, which might result in exaggerating the estimation of the counterfactual average at this period.

  26. Given that the exact number of factors to be included in the model is unknown, the cross-validation procedure is designed to select the number of factors before the causal effect estimation. Basically, the procedure chooses the number of factors that minimizes the mean square prediction error (MSPE) from a given set of numbers (i.e. 0 to 5 in this case).

  27. https://www.wto.org/english/tratop_e/envir_e/ega_e.htm

  28. Details of the ratification year can be found in Table 8.

  29. The covariate, \(Currency_{pt}\), is not included in the analysis due to almost no variation.

  30. See https://ec.europa.eu/eurostat/databrowser/view/ENV_AC_AINAH_R2__custom_1234643/default/table?lang=en

  31. Trade data (in HS code 85 and 90) come from UN Comtrade. Trade values recorded in HS code 85 (i.e. Electrical machinery and equipment and parts thereof) and 90 (i.e. Optical, photographic, cinematographic, measuring, checking, precision, medical or surgical instruments and apparatus; clocks and watches; musical instruments; parts and accessories thereof) match the definition of this industry best. Note that EGs in this study that fall in category of HS 85 and 90 are excluded from the data.

  32. See https://www.unep.org/news-and-stories/story/air-pollution-and-climate-change-two-sides-same-coin

  33. See https://unfccc.int/files/kyoto_protocol/compliance/enforcement_branch/application/pdf/cc-eb-25-2014-2_canada_withdrawal_from_kp.pdf.

  34. Almer and Winkler (2017) use Canada as a treated country in their analysis of the KP’s effectiveness.

  35. GDP, GDP per capita and population are used as predictors in the SCM in Verevis and Üngör (2021), which is also a trade-related paper

  36. More details about this method could be referred to Ben-Michael et al. (2021).

  37. See https://unfccc.int/process/the-kyoto-protocol/mechanisms

  38. It is important to note that the literature on evaluation of JI and CDM is controversial, as some other studies show skepticism on the role of these mechanisms. For instance, Cames et al. (2016) conclude that most of energy-related projects within CDM are not additional (i.e. the emission reductions would not have occurred in the absence of the mechanism). Besides, Wara (2007) and Kollmuss et al. (2015) revealed no or even negative effects of these mechanisms on emissions reductions.

  39. Statistics on JI and CDM projects are available at https://ji.unfccc.int/JI_Projects/DeterAndVerif/Verification/PDD/index.html and https://cdm.unfccc.int/Projects/projsearch.html

  40. The reduction in the number of available countries in the donor pool results from the fact that not all countries export to China. As there are only 17 countries left in the sample restricted to the export flow to China, I use all of them in the donor pool.

  41. Data is available for download at https://worldmrio.com/eora26/

  42. The sectors in this analysis are agriculture, fishing, metal products, transport equipment, electrical and machinery, food & beverages, textiles & wearing apparel, petroleum, chemical and non-metallic mineral products, and wood & paper.

  43. In addition, running the full sample of 821,583 observations (189 exporters x 189 importers x 23 years) requires extremely high-power computers that my current laptop could not handle.

  44. \(\hbox {CO}_{{2}}\) rates are measured in metric tons of \(\hbox {CO}_{{2}}\) per thousand dollars of output. The higher the rate is, the dirtier the industry is. Information on the \(\hbox {CO}_{{2}}\) rate for each industry is available from the replication files of Shapiro (2020).

  45. In the aggregate analysis, emission intensity is calculated by taking the ratio of carbon emission in all industries over output values in all industries.

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  1. Department of Economics, School of Bussiness, Monash University Malaysia, Bandar Sunway, 47500, Subang Jaya, Selangor, Malaysia

    Trang My Tran

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I wish to thank the editor, Sergio Vergalli, and two anonymous referees for helpful and constructive comments. I am grateful for the advice and metorship of Pasquale Sgro, Cong Pham and Xuan Nguyen. I thank Bo Yu, Kenji Takeuchi and Laura Puzzello for helpful discussion and suggestions. I am also thankful for constructive comments from participants in the Association of Environmental and Resource Economist 2020 Virtual Conference, the 23rd Annual Conference on Global Economic Analysis, the Brown Bag Seminar at Deakin University and Queensland University of Technology.

Appendices

A - Additional Figures

See Figs. 10, 11, 12 and 13.

Fig. 10
figure 10

Factor loading

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Fig. 11
figure 11

Robustness check: Exclusion of big exporters. Notes. USA as an exporter is dropped from the analysis sample. Treatment period is the ratification year

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Fig. 12
figure 12

Treated and counterfactual averages of export value (left) and carbon content of export (right) by sector

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Fig. 13
figure 13

Treated and counterfactual averages of export value (left) and carbon content of export (right) by sector (continued)

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B - Additional Tables

See Tables 8, 9, 10, 11.

Table 8 Annex B countries in the analysis sample and ratification year
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Table 9 Definition of variables
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Table 10 List of countries in the analysis
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Table 11 Summary Statistics of EORA26 dataset
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Tran, T.M. International Environmental Agreement and Trade in Environmental Goods: The Case of Kyoto Protocol. Environ Resource Econ 83, 341–379 (2022). https://doi.org/10.1007/s10640-021-00625-2

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