TY - JOUR
T1 - Erratum
T2 - A Comparative Analysis of Emissions Trading Systems: Cost Efficiency and Environmental Jurisdictional (Authority Overlap Asian Journal of Law and Economics (2022) 13: 2 (173-193) DOI: 10.1515/ajle-2022-0058)
AU - Ji, Philip Inyeob
AU - Mulenga, Richard
AU - Bhandari, Seema Bogati
N1 - Publisher Copyright:
© 2021 by the Author(s).
PY - 2022/12/1
Y1 - 2022/12/1
N2 - The article by Ji, P. I., Mulenga R., and Bhandari, S. B, “A Comparative Analysis of Emissions Trading Systems: Cost Efficiency and Environmental Jurisdictional Authority Overlap” (Asian Journal of Law and Economics, 13, 2 (2022); 173-193; henceforth referred to as P22), conducts a comparative analysis of emissions trading systems (ETS) in terms of cost efficiency and jurisdictional authority overlap. In analyzing the cost efficiency, the study employs two models; coefficient of variation (CV) and variance ratio (VR) models. We point out that the estimates in the CV models are different from those stated in Table 2 of P22. A simple correction to the erroneous estimates is available which yields the new CV estimates. The corrections to the estimates do not affect or change the interpretation of the estimation, the conclusion, or the overall content of the paper. The notation is the same as in P22, taking into account the erroneous estimates in columns 2 to 7 of Table 2 on page 6 and the interpretation on pp 5 to 7 of P22. The CV estimates are based on the following estimator expressed as: (equation presented) where, CV is the coefficient of variation estimate, σ is the standard deviation, and x is the sample mean. The erroneous estimates were obtained from taking the wrong assumption of first standardizing the data and wrongly taking common summary statistics of ETS. This yielded erroneous estimates. We corrected the erroneous estimates in Table 2 of P22 using non-standardized data and individual ETS summary statistics. The results are reported in the corrected version of Table 2. Also, the estimates in the related paragraphs have been corrected. The paragraphs in P22 should now read as shown below the corrected version of Table 2. Table 2 reports the summary statistics and the respective ETS coefficient of variations (CVs). The Swiss ETS seems to exhibit higher price volatility relative to other ETS because it has the largest coefficient of variation of 0.823. The RGGI ETS price volatility is second at 0.629. New Zealand ETS ranks third with a coefficient of variation of 0.605. Korea ETS ranks fourth with a coefficient of variation of 0.348. The second lowest price volatility of 0.256 is reported in the linked California-Quebec ETS. The regionally integrated EU ETS has the lowest price volatility with a coefficient of variation of 0.185. Our literature review suggests that the price volatility in the ETS markets can be partially attributed to miscalculations of allowances largely due to insufficient historical emissions data. Additionally, the narrow ETS markets for most selected ETS surveyed (probably with the exception of the integrated EUETS and the linked California-Quebec ETS as these have relatively large ETS markets), the absence or underdeveloped ETS secondary1 and/or derivatives markets, and the free allocation of allowances to energy-intensive trade-exposed sectors also contribute to price volatility (ICAP 2017h; Narassimhan et al. 2018; World Bank; Ecofys; Vivid Economics, 2016). A pattern emerges from Figure 1 and Table 2 read together, which suggests that as the ETS market size increases, the coefficient of variation (CV) decreases. For example, the relatively large integrated regional EUETS and the state-linked California-Quebec ETS clearly show this pattern as they have relatively low coefficients of variations of 0.185 and 0.256, respectively. This implies that the larger the ETS market size, the lower the price volatility. This perhaps underscores the need for single ETS markets to be linked or regionally integrated. This erratum was prepared by Ji, Philip Inyeob, Mulenga, Richard and Bhandari, S. Bogati.
AB - The article by Ji, P. I., Mulenga R., and Bhandari, S. B, “A Comparative Analysis of Emissions Trading Systems: Cost Efficiency and Environmental Jurisdictional Authority Overlap” (Asian Journal of Law and Economics, 13, 2 (2022); 173-193; henceforth referred to as P22), conducts a comparative analysis of emissions trading systems (ETS) in terms of cost efficiency and jurisdictional authority overlap. In analyzing the cost efficiency, the study employs two models; coefficient of variation (CV) and variance ratio (VR) models. We point out that the estimates in the CV models are different from those stated in Table 2 of P22. A simple correction to the erroneous estimates is available which yields the new CV estimates. The corrections to the estimates do not affect or change the interpretation of the estimation, the conclusion, or the overall content of the paper. The notation is the same as in P22, taking into account the erroneous estimates in columns 2 to 7 of Table 2 on page 6 and the interpretation on pp 5 to 7 of P22. The CV estimates are based on the following estimator expressed as: (equation presented) where, CV is the coefficient of variation estimate, σ is the standard deviation, and x is the sample mean. The erroneous estimates were obtained from taking the wrong assumption of first standardizing the data and wrongly taking common summary statistics of ETS. This yielded erroneous estimates. We corrected the erroneous estimates in Table 2 of P22 using non-standardized data and individual ETS summary statistics. The results are reported in the corrected version of Table 2. Also, the estimates in the related paragraphs have been corrected. The paragraphs in P22 should now read as shown below the corrected version of Table 2. Table 2 reports the summary statistics and the respective ETS coefficient of variations (CVs). The Swiss ETS seems to exhibit higher price volatility relative to other ETS because it has the largest coefficient of variation of 0.823. The RGGI ETS price volatility is second at 0.629. New Zealand ETS ranks third with a coefficient of variation of 0.605. Korea ETS ranks fourth with a coefficient of variation of 0.348. The second lowest price volatility of 0.256 is reported in the linked California-Quebec ETS. The regionally integrated EU ETS has the lowest price volatility with a coefficient of variation of 0.185. Our literature review suggests that the price volatility in the ETS markets can be partially attributed to miscalculations of allowances largely due to insufficient historical emissions data. Additionally, the narrow ETS markets for most selected ETS surveyed (probably with the exception of the integrated EUETS and the linked California-Quebec ETS as these have relatively large ETS markets), the absence or underdeveloped ETS secondary1 and/or derivatives markets, and the free allocation of allowances to energy-intensive trade-exposed sectors also contribute to price volatility (ICAP 2017h; Narassimhan et al. 2018; World Bank; Ecofys; Vivid Economics, 2016). A pattern emerges from Figure 1 and Table 2 read together, which suggests that as the ETS market size increases, the coefficient of variation (CV) decreases. For example, the relatively large integrated regional EUETS and the state-linked California-Quebec ETS clearly show this pattern as they have relatively low coefficients of variations of 0.185 and 0.256, respectively. This implies that the larger the ETS market size, the lower the price volatility. This perhaps underscores the need for single ETS markets to be linked or regionally integrated. This erratum was prepared by Ji, Philip Inyeob, Mulenga, Richard and Bhandari, S. Bogati.
UR - http://www.scopus.com/inward/record.url?scp=85143541822&partnerID=8YFLogxK
U2 - 10.1515/ajle-2022-0114
DO - 10.1515/ajle-2022-0114
M3 - Comment/debate
AN - SCOPUS:85143541822
SN - 2154-4611
VL - 13
SP - 405
EP - 407
JO - Asian Journal of Law and Economics
JF - Asian Journal of Law and Economics
IS - 3
ER -