China Policy Journal Volume 1, Number 1, Fall 2018 | Page 38

Assessing the Implementation of Local Emission Trading Schemes in China
T when the regulated firms actively
manage their compliance after the disclosure
of verified emission and before
the submission deadline of allowances
valid for year T-1 (Alberola, Chevallier,
and Chèze 2008).
There are limited empirical studies
on the price dynamics of the piloting
ETSs in China. Among a few recent
empirical studies that did focus on CO 2
emission allowance (CEA), Zeng et al.
(2017), Zhang and Zhang (2016), and
Fan and Todorova (2017) examined
the relationships between CEA price
and energy prices. Zeng et al. (2017)
employed a structural VAR approach
showing that during April 2014–November
2015, coal price had a significant
and positive impact on Beijing
CEA price within a short period, but it
became negative after two days when
firms started to substitute coal with less
carbon-intensive energy sources or use
carbon-reduction measures. Based on a
quantile regression method, Zhang and
Zhang (2016) argued that oil price had
a slight positive impact on the Shanghai
CEA price, consistent with the substitution
effect theory. Fan and Todorova
(2017) investigated into the response
of emission allowance price to energy
prices and macroeconomic indicators
in Beijing, Shenzhen, Guangdong and
Hubei from the launching dates to December
2016. The results showed that
Hubei CEA price was weakly related
to natural gas price, while Guangdong
CEA price had a significant positive relation
with oil price. However, overall,
the empirical studies on the influence
from energy prices to CEA prices have
been scarce and scattered.
Given that there are still few empirical
studies on the prices of China’s
CEA and considering that ETS will
continue to play an important role in
reducing CO 2
emissions in China, this
study aims at examining the price dynamics
of CEA, with a focus on the
relations between energy markets and
ETS markets. The rest of the article is
organized as follows. Section 2 details
the data and method. Section 3 starts
with the descriptive analysis of the
CEA price and trading volume data,
following by co-integration tests and
multivariate regressions to examine the
relationship between energy prices and
CEA price. Section 4 presents concluding
remarks and policy implications of
the findings.
2. Data and Method
2.1. Data
We collected the daily CEA
price data and daily transaction
volume data from
the website (www.tanpaifang.com) that
compiles the market data published
by Emission Exchanges of the seven
ETS pilots. The website was created in
2012, organized by the Zhongke Carbon
Information Technology Research
Institute, providing data, regulatory information
and consultancy about ETS.
As Chinese ETS allows for only spot
trading, all price data collected are closing
spot trading price data. The market
data of China’s seven piloting ETSs can
also be found from the website (www.
chinacarbon.net.cn) organized by Climate
Limited, which is a UN-accredited
online media company. Data from the
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