Impacts on CO2 Emission Allowance Prices in China: A Quantile Regression Analysis of the Shanghai Emission Trading Scheme

Abstract

A pilot regional carbon emission trading scheme (ETS) has been implemented in China for more than two years. An investigation into the impacts of different factors on carbon dioxide (CO 2 ) emission allowance prices provides guidance for price-making in 2017 when the nation-wide ETS of China will be established. This paper adopts a quantile regression approach to estimate the impacts of different factors in Shanghai emission trading scheme (SH-ETS), namely, economic growth, energy prices and temperature. The empirical analysis shows that: (i) the economic growth in Shanghai leads to a drop in the carbon allowance prices; (ii) the oil price has a slightly positive effect on the allowance prices regardless of the ordinary least squares (OLS) or quantile regression method; (iii) a long-run negative relationship exists between the coal price and the Shanghai emission allowances (SHEA) prices, but a positive interaction under different quantiles, especially the 25%-50% quantiles; (iv) temperature has a significantly positive effect at the 20%-30% quantiles and a conspicuous negative impact at the right tail of the allowances prices.

How Do Verified Emissions Announcements Affect the Comoves between Trading Behaviors and Carbon Prices? Evidence from EU ETS

“…Since the buying behaviors for compliance (i.e., CB) are much more intensive in the announcement period of Phase I, NB is suppressed while NS is triggered, consequently introducing more volatility into the carbon price returns. In Phase II, the significance of the values of ARCH and GARCH variables proves the validity of this variance model, that is, Equation (6). According to the testing results of Equation 6, "trading with non-compliance purpose" of the complete period of Phase II (γ 1 II,A and γ 2 II,A ) seems to have no significant impacts on the volatility of carbon price returns.…”

“…For the announcement period in Phase I, the testing results of Equation (6) demonstrate that the variance is modeled validly, because both the ARCH and GARCH variables are highly significant.…”

“…Emissions trading schemes for CO 2 have been established across the globe in response to the commitment to an 8% reduction in greenhouse gases (GHG) in the Kyoto Protocol [1,2]: the European Union Emission Trading Scheme (EU ETS) in Europe [3], the Regional Greenhouse Gas Initiative in the United States [4], the New South Wales Greenhouse Gas Abatement Scheme in Australia [5], Pilot Carbon Trading Markets in selected provinces and cities in China [6][7][8], and the Korean Emissions Trading Scheme in the Republic of Korea [9]. Since new emissions trading schemes are continuously being designed and implemented, such as a national-scale carbon market of China that launched at the end of 2017 [10], it is highly desirable to investigate the operations of the extant ones for providing a better understanding of this important climate change mitigation strategy.…”

A Feedback Control Method for Addressing the Production Scheduling Problem by Considering Energy Consumption and Makespan

“…Moreover, the proposed method adopts control strategies from a temporal perspective by adjusting short-term schedules according to comparison results of actual shop floor data and planned KPIs to make the schedule implementation coincide with the production plan. This will be more important than ever as the emission trading scheme prevails at the company level [23][24][25][26][27].…”

Comparison of Carbon Emission Trading Schemes in the European Union and China

“…Some scholars have explored the effects of the EU ETS [23][24][25]. On the other hand, the literature provides an overview of China's ETS [1,3,26], particularly allowance allocation [27,28], MRV [29], carbon price [30], and carbon credit [31] in the context of China's pilot ETS. Studies have also been conducted on the effects of China's ETS on emission reduction [32].…”