Impact of Environmental Policies on the Stock Prices of Energy Companies Xiaoli Zhao Ye Fan Xueying Yu Ming Fang Oct. 24. 2015 Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Outline Introduction Hypothesis Data Methodology Empirical results Conclusions Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Introduction In traditional corporate management, less attention has been paid to the environmental performance of firms because of profit maximization. However, stricter environmental policies and a growing concern from consumers have triggered a change from a simple corporate management to an environmentally conscious one. Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Environmental Policies the Stock Prices of Energy Companies Introduction Affect? Environmental Policies the Stock Prices of Energy Companies Not Affect? The reaction of Capital Market and Energy Companies Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Hypothesis Generally，environmental control policies have negative impact on stock price of listed energy companies in the short term. Because, when dealing with environmental policies, companies have to pay extra money on them, and the corporate earnings are reduced (Yanying Chen, 2009). Samiah (2013) has the idea that environmental control policies will increase company cost. Hypothesis 1: Environmental control policies have negative impact on stock price of listed energy companies in the short term. Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Hypothesis In China, traditional energy industries are mainly thermal power generation, coal and oil & gas, they also play important parts in listed energy companies. Coal companies can adjust the selling price according to the market. However, companies of thermal power generation and oil & gas are limited. Hypothesis 2: In the short term, environmental policies has a greater negative impact on the stock prices of the electric industry and the oil industry rather than the coal industry. Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Hypothesis Plumlee (2009) found companies of a high level of disclosure were welcomed by the capital market, because their expected cash flows would increase. Wang and Choi (2010),Yang Tang(2013) hold the same idea. Hypothesis 3: In the short term , the negative impact of environmental policies is relatively low for the listed energy companies who possess a higher level of disclosure. Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Hypothesis China has vast country lands, population density and unbalanced economic development. So the sense of protecting environment is different in the same way. The level of industrialization of listed energy companies in eastern and central regions of China is higher than the western companies, they need more money to deal with the new coming policies which will surely influence their economic development. Hypothesis 4: Environmental control policies have greater negative effect on Listed Energy Companies in eastern and central regions of China than the western ones. Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Hypothesis Cowen (1987) point out energy companies of large scale will be paid more attention by the public, so they deal with environmental issues actively. However, companies of small size are limited by financial strength, political and social pressure, their ability to deal with environmental issues is always challenged. Hypothesis 5: The negative impact of environmental regulation policies on the listed energy companies of large scale is smaller than the companies of small size. Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Hypothesis Our classification of environmental policies are Market stimulation, Administrative control, Legislative control and Disclosure. Administrative control, Legislative control are more powerful than Market stimulation and Disclosure (John J.Binder, 1985). Hypothesis 6: The negative impact of environmental regulation policies of Market Stimulation and Disclosure is less than the policies of Administrative control and Legislative control. Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Data Environmental control policies over the years No. Enacted Time Enacting Department Environmental Policy Policy Type 1 Jun.7.2007 National Development and Reform Commission Long-term development plan for renewable energy Market stimulation 2 Nov.17.2007 State council Energy conservation and emissions reduction statistical monitoring and assessment of implementation plan and method Administrative control 3 Jan.15.2008 State Environmental Protection Department, NDRC Pollution prevention of acid rain and carbon dioxide in the eleventh five-year plan 4 Aug.29.2008 National People's Congress People's Republic of China Circular Economy Promotion Law Legislative control 5 Aug.25.2009 Resolution on tackling climate change 6 Jan.19.2010 Ministry of Environmental Protection Publish environmental administrative penalties 7 May.4.2010 Notification of "Further intensify efforts to ensure the realization of the emission reduction targets in the eleventh five-year plan" 8 Aug.29.2011 Publish Main pollutants emission in China, 2011 Disclosure 9 Feb.29.2012 Clean Production Promotion Law of People's Republic of China 10 Sep.10.2013 Air Pollution Control Action Plan Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Statistics of listed energy companies 表3-1 能源上市公司市值统计 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, heat production 33 38% 82.4 Coal Mining 15 71% 292.5 Oil, gas exploration 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 ($ hundred million) V<50 22 29.70% 26.4 50≤V<100 11 25.60% 69.6 V≤100 85.20% 1225.1 Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Data No. Code 27 600188 Yanzhou Coal Mining Company Limited 28 600348 000027 Shenzhen Energy Group Co., Ltd. 2 000037 Shenzhen Nanshan Power Co.,Ltd. 3 000531 Guangzhou Hengyun Enterprises Holding Ltd. 4 000539 Guangdong Electric Power Development Co.,Ltd. 5 000543 Anhui Wenergy Company,Limited 6 000552 Gansu Jingyuan Coal Industry and Electricity Power Co.,Ltd 7 000600 Jointo Energy Investment Co.,Ltd. Hebei 8 000601 Guangdong Shaoneng Group Co.,Ltd. 9 000690 Guangdong Baolihua New Energy Stock Co.,Ltd. 10 000692 Shenyang Huitian Thermal Power Co.,Ltd. 11 000695 Tianjin Binhai Energy & Development Co.,Ltd 12 000780 Inner Mongolia Pingzhuang Energy Resources Co.,Ltd. 13 000937 Jizhong Energy Resources Co., Ltd. 14 000966 Guodian Changyuan Electric Power Co.,Ltd. 15 000983 Shanxi Xishan Coal and Electricity Power Co.,Ltd 16 000993 Fujian Mindong Electric Power Limited Company 17 001896 Henan Yuneng Holdings Co.,Ltd. 18 002039 Guizhou Qianyuan Power Co.,Ltd. 19 600011 Huaneng Power International,Inc. 20 600021 Shanghai Electric Power Company Limited 21 600027 Huadian Power International Corporation Limited 22 600028 China Petroleum & Chemical Corporation 23 600098 Guangzhou Development Group Incorporated 24 600101 Sichuan Mingxing Electric Power Co.,Ltd. 25 600123 Shanxi Lanhua Sci-Tech Venture Co.,Ltd 26 600167 Luenmei Holding Co.,Ltd No. Code 27 600188 Yanzhou Coal Mining Company Limited 28 600348 Yang Quan Coal Industry （Group） Co., Ltd. 29 600395 Guizhou Panjiang Refined Coal Co.,Ltd. 30 600396 Shenyang Jinshan Energy Co.,Ltd. 31 600397 Anyuan Coal Industry Group Co., Ltd. 32 600508 Shanghai Datun Energy Resources Co.,Ltd. 33 600509 Xinjiang Tianfu Thermoelectric Co.,Ltd. 34 600578 Beijing Jingneng Thermal Power Co.,Ltd. 35 600583 Offshore Oil Engineering Co.,Ltd. 36 600719 Dalian Thermal Power Co.,Ltd. 37 600726 Huadian Energy Company Limited 38 600744 Datang Huayin Electric Power Co.,Ltd 39 600758 Liaoning Hongyang Energy Yesource Invest Co.,Ltd 40 600780 Top Energy Company Ltd.Shanxi 41 600795 GD Power Development Co.,Ltd. 42 600863 Inner Mongolia Mengdian Huaneng Thermal Power Corporatio 43 600864 Harbin Hatou Investment Co.,Ltd. 44 600971 Anhui Hengyuan Coal Industry and Electricity Power Co.,Ltd 45 600982 Ningbo Thermal Power Co., Ltd. 46 601001 Datong Coal Industry Co.,Ltd. 47 601088 China Shenhua Energy Company Limited 48 601666 Pingdingshan Tianan Coal. Mining Co.,Ltd. 49 601699 Shanxi Lu'An Environmental Energy Development Co.,Ltd. 50 601808 China Oilfield Services Limited 51 601857 Petrochina Company Limited 52 601991 Datang International Power Generation Co.,Ltd. Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

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

Methodology Event study contains six steps. 1. Define event and time window 2. Identify research samples To examine the effect on share prices, daily data was obtained from CCER for each of the 10 events of the 52 companies. Estimation period Event day Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

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

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

Methodology stands for the cumulative abnormal returns from t1 to t2 . is abnormal returns. Also take weight of companies into consideration. (5) Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

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: 6. Conclusion. (6) Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

CAR(cumulative abnormal returns ) of all the listed energy companies Empirical results CAR(cumulative abnormal returns ) of all the listed energy companies Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Empirical results Significance Testing – Summary classification J-5 J-15 J-30 Industry Electricity, heat production -4.7392*** -4.34643*** -4.13913*** Coal Mining -3.6064*** -3.05046*** -3.38866*** Oil, gas exploration -1.81541* -1.81* -1.37717 The level of disclosure High -7.2142*** -6.5493*** -8.08129*** Low -4.1082*** -3.83078*** -3.40319*** Area East -2.6159*** -2.38299** -2.07045** Middle -3.6955*** -2.95739*** -3.64876*** West -3.3530*** -3.42822*** -2.91289*** Market capitalization ($ hundred million) V<50 -8.4609*** -6.34731*** -7.21016*** 50≤V<100 -2.8969*** -3.10612*** -2.60577*** V≤100 -2.9239*** -2.65771*** -2.46021** J-5，J-15，J-30 stand for the J number in significance test in date [-5，5]，[-15，15]，[-30，30] * = significant at the 1% level. ** = significant at the 5% level. *** = significant at the 10% level. CAR(cumulative abnormal returns ) of all the listed energy companies Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Summary figure of CAR in different industries Empirical results Summary figure of CAR in different industries Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Summary figure of CAR in different level of disclouse Empirical results Summary figure of CAR in different level of disclouse Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Summary figure of CAR in different area Empirical results Summary figure of CAR in different area Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Summary figure of CAR in different size of companies Empirical results Summary figure of CAR in different size of companies Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Empirical results Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Empirical results Significance Testing - Market Incentive classification J-5 J-15 J-30 Industry Electricity, heat production 0.101264 -0.18972 -0.23708 Coal Mining 0.211032 0.277802 -0.52537 Oil, gas exploration 0.887438 1.248778 1.270919 The level of disclosure High 1.235832 1.299757 1.610628 Low 0.028934 -0.24304 -0.4519 Area East -0.84041 -0.69616 0.847545 Middle -0.3216 0.24934 0.330447 West 0.308252 -0.00593 -0.39841 Market capitalization ($ hundred million) V<50 -0.70856 -0.69839 -0.21344 50≤V<100 0.35693 0.036393 -0.17388 V≤100 -0.42723 0.075633 -0.01723 J-5，J-15，J-30 stand for the J number in significance test in date [-5，5]，[-15，15]，[-30，30] * = significant at the 1% level. ** = significant at the 5% level. *** = significant at the 10% level. Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Empirical results Significance Testing - Legislative Control classification J-5 J-15 J-30 Industry Electricity, heat production -1.72323* -1.22966 -0.57234 Coal Mining -1.74197* -1.03526 -1.14763 Oil, gas exploration -1.16916 -1.10324 -0.65301 The level of disclosure High -3.6052*** -2.5409** -3.01438*** Low -1.85866* -1.5261 -0.89177 Area East -1.44535 -1.2672 -0.82015 Middle -1.76639* -0.86281 -1.12221 West -1.01413 -0.94143 -0.19934 Market capitalization ($ hundred million) V<50 -4.1229*** -2.69795*** -2.4107** 50≤V<100 -0.7688 -0.77798 -0.12205 V≤100 -1.65051* -1.31573 -0.94566 J-5，J-15，J-30 stand for the J number in significance test in date [-5，5]，[-15，15]，[-30，30] * = significant at the 1% level. ** = significant at the 5% level. *** = significant at the 10% level. Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Empirical results Significance Testing - Administrative Control classification J-5 J-15 J-30 Industry Electricity, heat production -5.2624*** -4.58828*** -4.38003*** Coal Mining -3.8027*** -3.25569*** -3.39645*** Oil, gas exploration -1.32898 -1.39485 -1.0848 The level of disclosure High -6.9990*** -6.49939*** -8.12779*** Low -4.2143*** -4.01357*** -3.61414*** Area East -2.22396** -2.10509** -2.05519** Middle -3.7622*** -3.25761*** -4.03785*** West -4.09135** -3.81062*** -3.21057*** Market capitalization ($ hundred million) V<50 -7.8764*** -5.56717*** -7.03522*** 50≤V<100 -3.6532*** -3.53138*** -2.96162*** V≤100 -2.4947** -2.42764** -2.33196** J-5，J-15，J-30 stand for the J number in significance test in date [-5，5]，[-15，15]，[-30，30] * = significant at the 1% level. ** = significant at the 5% level. *** = significant at the 10% level. Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Empirical results Significance Testing - Disclosure classification J-5 Industry Electricity, heat production -0.35188 -1.79045* -3.29633*** Coal Mining -0.51064 -2.13746** -2.65554*** Oil, gas exploration -0.60449 -1.10419 -1.37839 The level of disclosure High -1.1594 -2.94225*** -3.73166*** Low -0.7422 -2.07078** -2.86595*** Area East -0.72488 -1.42232 -1.82555* Middle -0.65264 -2.26227** -2.79278*** West 0.079854 -0.91877 -2.00844** Market capitalization ($ hundred million) V<50 -1.52566 -3.12124*** -4.05581*** 50≤V<100 0.046181 -0.82751 -1.93598 V≤100 -0.75155 -1.86563* -2.31135** J-5，J-15，J-30 stand for the J number in significance test in date [-5，5]，[-15，15]，[-30，30] * = significant at the 1% level. ** = significant at the 5% level. *** = significant at the 10% level. Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

Empirical results 0.172228 -0.07932 -0.21596 -4.96891*** -4.72453*** 不同类型政策影响的显著性检验 Empirical results Significance Testing Environmental Policies J-5 J-15 J-30 Market Incentive 0.172228 -0.07932 -0.21596 Administrative Control -4.96891*** -4.72453*** -4.52595*** Legislative Control -2.13493** -1.68937* -1.10578 Disclosure -0.82069 -2.3379** -3.20149*** J-5，J-15，J-30 stand for the J number in significance test in date [-5，5]，[-15，15]，[-30，30] * = significant at the 1% level. ** = significant at the 5% level. *** = significant at the 10% level. Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing

End Thank you all Developed by: © Ye Fan, School of Business Administration, China University of Petroleum, Beijing