1. Xiaoli Zhao， Ye Fan， Ming Fang
Impact of Environmental Policies on the Stock Prices of Energy Companies
Xiaoli Zhao， Ye Fan， Ming Fang
赵晓丽 范烨 方明
Oct
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

2. 2. Description of Environmental Regulation 3. Hypothesis 4. Data
1. Introduction
2. Description of Environmental Regulation
3. Hypothesis
4. Data
5. Methodology
6. Empirical results
7. Conclusions
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

3. 1. Introduction
China is facing burdens of environmental pollution and carbon emission
Government environmental regulations are counted as an important and effective strategy
Environmental regulations alter the corporate’s inner organization and influence outside investors’ perception
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

4. 1. Introduction
Environmental regulations are assumed as a burden which effect productivity and competitiveness (Palmer et al., 1995)
Break the optimized allocation of resources
Nonprofit activities
(Gray and Shadbegian, 1995; Haveman and Christiansen, 1981)
Environmental fines and lawsuits
(Stewart, 1993; Gray and Shadbegian, 1995; Haveman and Christiansen, 1981；Thomas and Zhao, 2009)
Crowd out potential investment or innovation
(Jaffe and Palmer, 1997; Thomas, 2009)
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

5. 1. Introduction (Motoko and Yang, 2010; Liu et al, 2007)
Environmental regulations represent unique opportunities for enterprise competitiveness
Popular in green consumers and green markets
(Huang and Kung 2010; Jose and Lee 2007)
Pollution is wrong placed resources
(Porter & van der Linde, 1995)
Green mutual funds and green credits
(Motoko and Yang, 2010; Liu et al, 2007)
Avoid conflicts with local communities, government agencies and public media；
(Porter & van der Linde, 1995; Gorski ,1986; Zhang, B. et al.,2011)
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

6. 1. Introduction Market value of listed energy companies
Environmental regulations
Market value of listed energy companies
Affect?
Not Affect?
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

7. 2. Description of Environmental Regulation
China’s government has gradually established an integrated policy system including
Command-and-control regulation (CCR)
Legal based policy and administrative based policy
Market based regulation (MBR)
Environmental information disclosure (EID)
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

8. 2. Description of Environmental Regulation
We selected 14 significant environmental policies from 2007 to 2015 in China and 6 important time points
MBR:
Long-term development plan for renewable energy in Jun
CCR: Administrative 5
Legislative
Publish environmental administrative penalties in Jan Air pollution Law in Aug
EID: Main pollutants emission in China, 2011
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

9. 3. Hypothesis
H1: Environmental regulation has a negative impact on energy companies.
H2: The negative impact of MBR and EID is less than that of CCR.
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

10. 3. Hypothesis
H3: Environmental regulation has greater negative impacts electricity and coal companies than oil and gas.
H4: Environmental regulations have weaker negative influence on companies of higher EID level.
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

11. 3. Hypothesis
H5: The higher proportion of state owned, the less negative impacts of environmental regulation are.
H6: Environmental regulation has a greater negative impact on energy companies in eastern and middle regions than that in western regions of China.
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

12. 3. Hypothesis
H7: The negative impact of environmental regulation on the stock price of small-scale and large-scale companies is weaker than that of middle-scale.
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

13. 4. Data Electricity companies, coal companies, oil & gas companies
52 companies are selected from the total 93 listed companies
The data is collected from China Stock Market Accounting Research (CSMAR) database
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

14. Statistics of listed energy companies
4. Data
Statistics of listed energy companies
Classification
Number
The proportion of top 20 percent market capitalization companies
The average market capitalization($ hundred million)
Listed Energy Companies 52
89.10%
473.5
Industry
Electricity 33
38%
82.4
Coal Mining 15
71%
292.5
Oil, gas 4
4378.6
The level of disclosure
High 19
90%
114.6
Low
61%
87.2
Area
East 30
764.2
Middle
48%
88.7
West 7
33%
52.2
Market capitalization ($ Billion)
V<5 22
29.70%
26.4
5≤V<10 11
25.60%
69.6
V≤10
85.20%
1225.1
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

15. 4. Data
The distribution of shareholding proportion of the listed energy companies owned by governments.
Figure 1: Distribution of shareholding proportion of governments in listed energy companies
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

16. 5. Methodology
Event study is a research methodology designed to measure the impact of an event of interest on stock returns. Dolley (1933), Fama (1969), Mackinlay (1997) explains this method in detail. To date using a market model, several researchers have performed event studies on the day of the announcement pertaining to environmental information — Arora (2001), Gupta and Goldar (2005), and Klassen and McLaughlin (1996).
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

17. 5. Methodology Event study contains six steps.
1. Define event and time window
2. Identify research samples
Estimation
period
Event
day
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

18. 5. Methodology
3. Determine share returns model. From the raw daily data, share returns were calculated according to the formula:
where is the share return for firm i on day t and
is the share price for day t.
(1)
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

19. 5. Methodology 4. Estimate the abnormal returns.
The expected returns is obtained from the market model and EGARCH model (Nelson,1991). The abnormal returns ARi,t is obtained from the formula 4.
(2)
(3)
(4)
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

20. 5. Methodology
(5)
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

21. 5. Methodology
5. Inspection of significant abnormal returns. To test the null hypothesis that the event does not affect the returns, we use the following J-statistics:
(7)
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

22. Table 4: CAAR differences (%) and absolute J-statistics
6. Empirical results
Table 4: CAAR differences (%) and absolute J-statistics
All the companies
Environmental Policies
Industry
The level of disclosure
estimation window
event window
CAAR/J-ratio
Market based regulation
Administrative Control
Legislative control
Information disclosure
Electricity, heat production
Coal Mining
Oil, gas exploration
High
Low
240
[-2,2]
CAAR
-0.005***
0.013*
0.007*
-0.013***
-0.011**
-0.008**
-0.003
-0.002
-0.008***
-0.004
J-ratio
(-2.694)
(1.777)
(1.703)
(-4.113)
(-2.060)
(-2.435)
(-1.591)
(0.401)
(-2.647)
(-1.360)
[-4,4]
-0.010***
0.006
-0.022***
0.005
-0.015***
-0.012
(-3.652)
(-0.252)
(0.692)
(-4.885)
(0.485)
(-3.553)
(-1.029)
(-0.932)
(-3.253)
(-2.093)
[-6,6]
-0.019***
-0.044***
-0.005
-0.034***
0.053***
-0.029***
-0.006*
0.003
-0.024***
-0.016***
(-5.367)
(-3.247)
(-1.370)
(-6.616)
(5.170)
(-5.542)
(-1.739)
(0.160)
(-4.187)
(-3.552)
[-8,8]
-0.012***
-0.028*
0.010
-0.028***
0.042***
-0.010*
-0.020***
-0.007
(-2.992)
(-1.869)
(1.166)
(-4.965)
(3.687)
(-2.642)
(-1.939)
(0.768)
(-3.127)
(-1.383)
[-10,10]
-0.006
-0.042***
0.018**
0.049***
-0.008
-0.012*
(-1.403)
(-2.730)
(2.130)
(-3.267)
(3.910)
(-1.074)
(-0.923)
(-0.150)
(-1.707)
(-0.466)
[-20,20]
-0.045*
0.016
0.042**
0.033
-0.019**
(-0.549)
(-1.888)
(1.491)
(-1.712)
(2.387)
(-0.543)
(-0.894)
(1.622)
(-2.008)
(0.807)
200
-0.005**
0.015**
0.009**
-0.012**
-0.007**
-0.001
(-2.350)
(2.015)
(2.263)
(-4.017)
(-2.214)
(-2.203)
(0.555)
(-2.530)
(-1.021)
0.008
-0.021***
0.002
-0.007*
(-3.466)
(-0.262)
(1.126)
(-4.776)
(0.149)
(-3.512)
(-0.761)
(-0.911)
(-3.184)
(-1.911)
-0.018***
-0.046***
-0.032***
0.050***
-0.027***
(-5.025)
(-3.365)
(-0.878)
(-6.277)
(4.843)
(-5.310)
(-1.471)
(0.195)
(-3.926)
(-3.323)
-0.011***
-0.027*
0.011
0.038***
-0.017***
-0.008*
(-2.960)
(-1.785)
(1.287)
(-4.892)
(3.333)
(-2.770)
(-1.703)
(0.797)
(-3.155)
(-1.321)
0.021**
0.043***
(-1.418)
(-2.724)
(2.469)
(-3.313)
(3.471)
(-1.105)
(-0.893)
(-0.175)
(-1.689)
(-0.500)
-0.043*
0.014
0.038*
-0.018*
0.007
(-0.455)
(-1.843)
(1.331)
(-1.672)
(2.816)
(-0.280)
(-1.234)
(1.931)
(-1.897)
(0.845)
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

23. Table 4 (continue): CAR differences(%) and absolute J-statistics
6. Empirical results
Table 4 (continue): CAR differences(%) and absolute J-statistics
State-owned proportion
Area
Market capitalization (hundred million of RMB ￥)
estimation window
event window
CAAR/J-ratio
10%-30%
30%-50%
50%-70%
70%-90%
East
Middle
West
V<5
50≤V<100
V>100
240
[-2,2]
CAAR
-0.011*
-0.007
-0.004
-0.003
-0.007***
-0.000
-0.005
-0.013***
-0.001
J-ratio
(-1.812)
(-1.631)
(-1.491)
(-0.260)
(-2.621)
(-1.171)
(-0.254)
(-1.450)
(-2.598)
(-0.870)
[-4,4]
-0.022**
-0.012**
-0.008**
-0.012***
-0.008*
-0.011**
-0.020***
(-2.496)
(-2.088)
(-2.032)
(0.090)
(-3.262)
(-1.699)
(-0.731)
(-2.465)
(-2.695)
(-1.290)
[-6,6]
-0.037***
-0.023***
-0.015***
0.005
-0.024***
-0.015**
-0.002
-0.019***
-0.028***
-0.014**
(-3.375)
(-3.504)
(-3.092)
(0.787)
(-5.186)
(-2.546)
(-0.220)
(-3.585)
(-3.216)
(-2.534)
[-8,8]
-0.025*
-0.012
0.014
-0.008
-0.010*
-0.023**
(-1.929)
(-1.640)
(-2.447)
(1.328)
(-3.699)
(-1.362)
(1.444)
(-1.846)
(-2.175)
(-1.273)
[-10,10]
-0.017
0.008
0.022**
(-0.460)
(-1.091)
(0.627)
(-2.489)
(-0.486)
(2.018)
(-0.851)
(-1.048)
(-0.586)
[-20,20]
-0.015
0.003
0.023*
-0.010
-0.009
(-0.784)
(-0.267)
(-0.427)
(0.929)
(-1.467)
(-0.200)
(1.843)
(0.379)
(-0.711)
(-0.788)
200
-0.006
-0.006**
(-1.651)
(-1.548)
(-1.186)
(-0.107)
(-2.329)
(-0.942)
(-0.248)
(-1.337)
(-2.310)
(-0.645)
-0.007*
-0.010**
-0.019**
(-2.461)
(-2.207)
(-1.703)
(0.069)
(-3.072)
(-1.542)
(-0.848)
(-2.340)
(-2.568)
(-1.218)
-0.035***
-0.022***
-0.014***
0.004
-0.018***
-0.026***
(-3.153)
(-3.407)
(-2.888)
(0.748)
(-4.716)
(-2.542)
(-0.258)
(-3.358)
(-2.982)
(-2.399)
-0.024*
-0.012*
0.012
-0.009*
-0.021**
(-1.896)
(-2.426)
(1.411)
(-3.612)
(-1.298)
(1.264)
(-1.748)
(-2.056)
(-1.427)
-0.016
0.006
0.021*
-0.011
(-1.214)
(-0.598)
(-0.975)
(0.593)
(-0.500)
(1.917)
(-0.941)
(-0.950)
(-0.590)
0.015
0.024*
(-0.513)
(0.025)
(-0.726)
(1.043)
(-1.488)
(0.048)
(1.767)
(0.353)
(-0.245)
(-0.981)
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

24. 6. Empirical results
H1 is supported.
Figure 2 Impact of total environmental policies on the stock price of listed energy companies
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

25. 6. Empirical results H2 is rejected
Figure 3: Impact of different environmental policies on the stock price of listed energy companies
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

26. 6. Empirical results H3 is supported.
Figure 4: Impact of environmental regulation on the stock price of different kinds of energy companies
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

27. 6. Empirical results
H4 is rejected.
Figure 5: Impact of environmental regulation on the stock price of energy companies with different EID
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

28. 6. Empirical results
H5 is supported.
Figure 6: Impact of environmental regulation on the stock price of energy companies with different state share
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

29. 6. Empirical results
H6 is supported.
Figure 7: Impact of environmental regulation on the stock price of energy companies in different regions
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

30. 6. Empirical results
H7 is supported.
Figure 8: Impact of environmental regulation on the stock price of energy companies with different scales
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

31. 6. Empirical results Robustness Checks of Abnormal Daily Volume
Event window
AADV
Market Based Regulation
Administrative Regulation
Legislative Regulation
Information Disclosure
All policies
Panel A: Average abnormal daily volume (AADV)
[-2,2]
0.678***
-0.033
0.404***
-0.291***
0.253***
(7.202)
(-1.035)
(9.426)
(-8.602)
(8.930)
[-4,4]
0.810***
-0.100***
0.390***
-0.343***
0.236***
(10.507)
(-5.520)
(12.508)
( )
(11.072)
[-6,6]
0.866***
-0.121***
0.374***
-0.334***
0.229***
(11.722)
(-8.149)
(14.296)
( )
(12.345)
[-8,8]
0.936***
-0.136***
0.402***
-0.356***
0.245***
(13.156)
( )
(17.304)
( )
(14.770)
Panel B: Average daily volume shifts(ADVS)
0.963
0.126***
0.064***
0.071**
0.170**
(1.118)
(6.790)
(5.376)
(2.156)
(2.280)
0.626
0.054***
0.093***
0.079***
0.135***
(1.392)
(4.131)
(8.359)
(3.224)
(3.355)
0.409
0.063***
0.095***
0.092***
0.118***
(1.312)
(5.701)
(8.176)
(4.795)
(4.253)
0.351
0.086***
0.123***
0.068***
0.131***
(1.489)
(8.443)
(7.585)
(4.359)
(5.841)
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

32. 7. Conclusions
Environmental regulation has a negative impact on energy companies.
The negative effect of MBR and EID is not less than that of CCR.
Environmental regulation has greater negative effects on electricity and coal than oil and gas.
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

33. 7. Conclusions
Environmental regulations don’t have weaker negative influence on the companies that have higher EID levels.
The higher proportion of state owned, the less negative effects of environmental regulation.
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

34. 7. Conclusions
Environmental regulation has a greater negative effect on the companies in eastern and middle regions than that in western regions in China.
The negative impact of environmental regulations on the stock price of small-scale and large-scale companies is weaker than that of middle-scale.
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

35. Ye Fan 范烨 E-mail: Fanyecup@foxmail.com
Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing