China Policy Journal Volume 1, Number 1, Fall 2018 | Page 46

Assessing the Implementation of Local Emission Trading Schemes in China
in order to see whether they have longrun
equilibrium relationships. However,
we can see from Table 7 that there
is no significant long-run equilibrium
relationships between the variables.
Table 5. Descriptive Statistics of Energy Prices and Stock Index
Var.
Coal Price
(Coal t
)
Brent Oil Price
(Brent t
)
LNG Price
(LNG t
)
Shanghai Shenzhen 300
Stock Index (Stock t
)
Full
sample
Table 6. Test for Unit Roots
Price
Returns
From 2013 Week 25 2013 Week 25 2014 Week 1 2013 Week 25
To 2017 Week 26 2017 Week 26 2017 Week 26 2017 Week 26
Unit $/ton $/barrel $/ton Dimensionless
Obs. 210 210 182 210
Mean 78.123 69.378 586.724 3096.085
Std. Dev. 12.421 28.166 129.759 704.039
Min. 55.840 27.760 428.959 2116.750
Max. 101.840 116.030 804.167 5324.406
Skewness −0.380 0.493 0.215 0.508
Kurtosis 1.791 1.550 1.474 3.111
Stationary?
Obs.
ADF,
Simple
PP, Simple
ADF, with
Trend
PP, with
Trend
ADF, with
Drift
Z(t) Z(t) Z(t) Z(t) Z(t)
Integ.
Order
BJ: CEA Yes 183 −9.249*** −14.191*** −9.224*** −14.151*** −9.249*** I(0)
CQ: CEA Yes 154 −7.366*** −7.660*** −7.421*** −7.677*** −7.366*** I(1)
GD: CEA Yes 179 −9.554*** −12.210*** −9.616*** −12.218*** −9.554*** I(0)
HB: CEA Yes 165 −10.173*** −13.940*** −10.174*** −13.928*** −10.173*** I(1)
SH: CEA Yes 179 −4.577*** −10.568*** −4.680*** −10.604*** −4.577*** I(1)
SZ: CEA Yes 205 −9.581*** −19.583*** −9.667*** −19.647*** −9.581*** I(0)
TJ: CEA Yes 178 −8.455*** −9.646*** −8.444*** −9.632*** −8.455*** I(0)
Coal Yes 205 −4.610*** −7.406*** −4.729*** −7.625*** −4.610*** I(0)
Brent Oil Yes 205 −7.433*** −10.641*** −7.436*** −10.621*** −7.433*** I(1)
LNG Yes 177 −5.450*** −13.144*** −5.432*** −13.120*** −5.450*** I(1)
shsz300 Yes 205 −5.682*** −11.200*** −5.670*** −11.184*** −5.682*** I(0)
Note: “Z(t)” refers to the statistic of ADF or PP unit root test. ***, ** and * denote significance at
1%, 5% and 10% levels. “Integ. Order” refers to order of integration.
3.3. Multivariate Regressions
for Provincial ETSs
Table 8 displays the regression results
for the two provincial level ETSs,
Guangdong ETS and Hubei ETS. The
dependent variables are the CEA price
returns (lnReturn t
) of Guangdong and
Hubei respectively, while the independent
variables are the logarithmic dif-
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