煤炭行业去产能、调整资产结构对煤炭经济的撬动效应

doi:10.18402/resci.2021.02.10

Abstract

Abstract:

De-capacity in the coal industry is an important measure for the transformation and development of coal enterprises. It promotes the development of energy resources in the direction of clean, low carbon, efficient, and high quality. At the same time, it forces coal enterprises to eliminate backward production capacity, improve the conversion rate of coal processing, rationally allocate capital investment, arrange asset structure in an orderly manner, and expand non-coal business. In this research we collected data on indicators related to coal industry capacity reduction in 2009-2018 and data on asset structure change of 34 listed coal companies in China during the same period, and used the entropy method to determine the entropy value of the asset structure change, and the regression analysis method to determine the effect of de-capacity in coal enterprises and adjust asset structure on the listed coal companies. The empirical research shows that: (1) Coal industry has achieved brilliant results in de-capacity and structural adjustment, but negatively correlated with earnings per share or return on equity of listed coal companies, and its implied prying effect lags behind release. (2) Listed coal companies actively adjust the direction of capital investment under the environmental pressure of de-capacity and structural adjustment, so that the asset structure changes in an orderly manner, and the entropy value of assets under orderly change is positively related to the prying effect of enterprises. (3) Rational arrangement of the proportion of current liabilities to current assets in listed coal companies and accelerating the turnover of current assets and fixed assets have played a positive role in promoting the prying effect of enterprises. The supply and demand balance of the coal industry has entered the normal track, consolidating the transformation results, controlling the orderly change of asset structure, and taking the road of green development and sustainable development is the future development direction that should be adhered to.

Key words: coal listed companies, de-capacity, adjustment structure, entropy value of asset structure evolution, economic prying effect, decision saliency method

ZHU Liangfeng, ZHU Xueyi. Economic prying effect of de-capacity and asset structure adjustment in the coal industry[J].Resources Science, 2021, 43(2): 316-327.

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References 30

[1]	朱亮峰. 煤炭资源资本化支撑理论及运作效率研究[M]. 北京: 中国经济出版社, 2017.
	[Zhu L F. Study on the Support Theory and Operation Efficiency about Capitalization of Coal Resource[M]. Beijing: China Economic Publishing House, 2017.]
[2]	朱亮峰, 朱学义. 煤炭去产能转机情况分析与对策[J]. 财务与会计, 2018, (6):67-69.
	[Zhu L F, Zhu X Y. Analysis and countermeasures of coal de-capacity and a favourable turn[J]. Finance & Accounting, 2018, (6):67-69.]
[3]	Zhu L F, Zhu X Y. Study on the “Bottoming Out” recovery of coal capacity in China[J]. International Journal of Economic Perspectives, 2017,11(3):1355-1361.
[4]	李刚, 田越. 煤炭去产能形势下煤层气产量与价格演变趋势研究[J]. 价格理论与实践, 2017, (10):60-63.
	[Li G, Tian Y. A study on the trend of the output and price of CBM under coal capacity-cutting[J]. Price, Theory & Practice, 2017, (10):60-63.]
[5]	任继球. 我国钢铁和煤炭去产能对就业的影响: 基于投入产出表的实证分析[J]. 宏观经济研究, 2017, (10):83-91.
	[Ren J Q. The impact of China’s steel and coal de-capacity on employment: An empirical analysis based on the input output table[J]. Macroeconomics, 2017, (10):83-91.]
[6]	王德鲁, 赵成. 中国煤炭去产能省区分配研究[J]. 经济问题, 2018, (4):77-82.
	[Wang D L, Zhao C. Study on coal de-capacity allocation among provinces in China[J]. On Economic Problems, 2018, (4):77-82.]
[7]	曾湘泉, 杨涛, 刘华. 兼并重组、所有制与产能过剩: 基于山西省煤炭去产能困境的案例分析[J]. 山东大学学报(哲学社会科学版), 2016, (5):24-31.
	[Zeng X Q, Yang T, Liu H. Merging and reorganization, ownership and coal overcapacity: A case study based on the dilemma of cutting excessive coal capacity in Shanxi Province[J]. Journal of Shandong University (Philosophy and Social Sciences), 2016, (5):24-31.]
[8]	马忠德. 煤炭企业调结构转方式促转型发展的路径选择[J]. 中国能源, 2010,32(8):25-28.
	[Ma Z D. Path choice of the coal enterprises in structure adjustment and restructuring development process[J]. Energy of China, 2010,32(8):25-28.]
[9]	鲁玉栋, 张升壹. 国有大型煤炭企业转方式调结构的路径[J]. 中国煤炭工业, 2011, (10):56-57.
	[Lu Y D, Zhang S Y. The path of transforming the mode and adjusting the structure of large state owned coal enterprises[J]. China Coal Industry, 2011, (10):56-57.]
[10]	李永东. 关于煤炭资源型企业调结构转方式的几点思考[J]. 中国煤炭, 2012, (4):21-23.
	[Li Y D. Reflections on structure adjustment and mode transformation in coal resource-based enterprises[J]. China Coal, 2014, (4):21-23.]
[11]	巩翠海. 关于煤炭企业“转方式调结构”的几点思考[J]. 中国能源, 2011, (7):18-20.
	[Gong C H. Considerations of the way to “adjust and transform the pattern of economic development” for coal enterprises[J]. Energy of China, 2011, (7):18-20.]
[12]	马俊华. 2017煤炭行业: 去产能、调结构、降成本、防风险[J]. 能源, 2017, (1):45-48.
	[Ma J H. 2017 coal industry: De-capacity, structure adjustment, cost reduction and risk prevention[J]. Energy, 2017, (1):45-48.]
[13]	李成先. 调结构促整合实现煤炭工业又好又快发展[J]. 品牌, 2010, (4):15-16.
	[Li C X. Adjusting structure and promoting integration to realize sound and rapid development of coal industry[J]. Brand, 2010, (4):15-16.]
[14]	马翠梅, 戴尔阜, 刘乙辰, 等. 中国煤炭开采和矿后活动甲烷逃逸排放研究[J]. 资源科学, 2020,42(2):311-322.
	[Ma C M, Dai E F, Liu Y C, et al. Methane fugitive emissions from coal mining and post-mining activities in China[J]. Resources Science, 2020,42(2):311-322.]
[15]	耿爱欣, 潘文琦, 杨红强. 中国林木生物质能源替代煤炭的减排效益评估[J]. 资源科学, 2020,42(3):536-547.
	[Geng A X, Pan W Q, Yang H Q. Quantifying the mitigating effects and benefits from substituting wood biomass for coal in energy production in China[J]. Resources Science, 2020,42(3):536-547.]
[16]	朱学义. 中级财务会计(第4版)[M]. 北京: 机械工业出版社, 2011.
	[Zhu X Y. Intermediate Financial Accounting (4th Edition)[M]. Beijing: China Machine Press, 2011.]
[17]	Ahmed R. 会计理论(第4版)[M]. 钱逢胜, 译. 上海: 上海财经大学出版社, 2004.
	[Ahmed R. Accounting Theory (4th Edition)[M]. Qian F S, Trans. Shanghai: Shanghai University of Finance & Economics Press, 2004.]
[18]	姜宁, 胡翊肱. 我国企业资产结构变化及其分析[J]. 管理世界, 2000, (6):188-189.
	[Jiang N, Hu Y G. Change and analysis of assets structure of Chinese enterprises[J]. Management World, 2000, (6):188-189.]
[19]	邓伟. 产权交易成本、债务成本的均衡与企业资产结构的优化[J]. 管理现代化, 2001, (6):53-54.
	[Deng W. Balance of property right transaction cost and debt cost and optimization of enterprise asset structure[J]. Modernization of Management, 2001, (6):53-54.]
[20]	赵卫斌. 传媒企业资产结构和质量的优化: 基于新华传媒定向增发的分析[J]. 中国出版, 2007, (11):23-25.
	[Zhao W B. Optimization of asset structure and quality of media enterprises: Based on the analysis of Xinhua Media’s private placement[J]. China Publishing Journal, 2007, (11):23-25.]
[21]	张永冀, 孟庆斌. 预期通货膨胀与企业资产结构[J]. 会计研究, 2016, (7):27-34.
	[Zhang Y J, Meng Q B. Expected inflation and corporate assets structure[J]. Accounting Research, 2016, (7):27-34.]
[22]	张宁辉, 韩家闯. 影响企业资产结构的因素[J]. 技术与创新管理, 2009,30(4):462-464.
	[Zhang N H, Han J C. Factors influencing the structure of the business assets[J]. Technology and Innovation Management, 2009,30(4):462-464.]
[23]	方明月. 中国地区制度质量对企业资产结构的影响[J]. 经济社会体制比较, 2018, (4):156-165.
	[Fang M Y. The impact of regional institutional quality on firms’ asset structure in China[J]. Comparative Economic & Social Systems, 2018, (4):156-165.]
[24]	雷新途, 徐青原. 区域金融生态环境对企业资产结构的影响: 来自制造业的证据[J]. 经济地理, 2018,38(6):102-108.
	[Lei X T, Xu Q Y. The impact of regional financial eco-environment on the enterprises asset structure: Theoretical analysis and positive examination[J]. Economic Geography, 2018,38(6):102-108.]
[25]	谢君萍. 利益相关者的产权与控制权配置: 企业资产结构的视角[J]. 江西社会科学, 2015,35(6):61-65.
	[Xie J P. Allocation of stakeholders about property rights and control rights: From the perspective of enterprise asset structure[J]. Jiangxi Social Sciences, 2015,35(6):61-65.]
[26]	邓伟根, 薛莲, 潘捷. 中国民营上市企业资产结构调整速度研究[J]. 现代管理科学, 2016, (5):64-66.
	[Deng W G, Xue L, Pan J. Research on the speed of asset structure adjustment of private listed enterprises in China[J]. Modern Management Science, 2016, (5):64-66.]
[27]	隋立秋, 刘百芳. 基于面板模型的企业资产结构优化引致效应研究[J]. 商业研究, 2010, (8):10-15.
	[Sui L Q, Liu B F. Study on incurrence-effect of firm asset structure optimization based on panel model[J]. Commercial Research, 2010, (8):10-15.]
[28]	朱亮峰. 煤炭企业经济效益与外部倒逼和内部资金营运的关系分析[J]. 资源科学, 2015,37(12):2414-2420.
	[Zhu L F. Analysis of the relationship between the economic benefits of coal enterprises and external force and internal funds operation[J]. Resources Science, 2015,37(12):2414-2420.]
[29]	胡振兴, 王阿娇. 创业投资对新能源技术创新效率的撬动效应研究[J]. 科技进步与对策, 2018,35(23):82-91.
	[Hu Z X, Wang A J. Research on the stimulating effect of venture capital on the innovation efficiency of new energy technology[J]. Science & Technology Progress and Policy, 2018,35(23):82-91.]
[30]	艾思奇. 辩证唯物主义历史唯物主义[M]. 北京: 人民出版社, 1978.
	[Ai S Q. Dialectical Materialism Historical Materialism[M]. Beijing: People’s Publishing House, 1978.]

年份	煤炭去产能比值/%	煤炭加工转换率/%	清洁能源消费占比/%	煤炭消费占比/%	非煤业务收入占比/%
2009	80.00	71.71	12.00	71.60	43.67
2010	87.95	63.88	13.40	69.20	42.80
2011	96.41	74.80	13.00	70.20	40.08
2012	101.28	64.61	14.50	68.50	39.73
2013	101.79	66.53	15.50	67.40	39.28
2014	99.23	65.81	17.00	65.60	40.89
2015	96.15	66.65	18.00	63.70	37.64
2016	87.44	70.09	19.50	62.00	45.59
2017	90.26	72.90	20.80	60.40	47.41
2018	91.03	76.48	22.10	59.00	44.79
平均数	93.15	69.34	16.58	65.76	42.19

	N	最小值	最大值	平均数	标准偏差
流动资产熵值	332	0.0334	0.2653	0.2160	0.0274
非流动资产投资熵值	332	0.0000	0.2286	0.0582	0.0525
固定资产熵值	332	0.0586	0.3343	0.2085	0.0356
无形资产熵值	332	0.0000	0.2651	0.1368	0.0603
其他长期资产熵值	332	0.0006	0.2282	0.0594	0.0403
资产结构演变熵值合计	332	0.1721	0.9294	0.6793	0.1198
非煤业务占比	332	0.0040	1.0000	0.4108	0.3599
煤炭去产能比值	332	0.8000	1.0179	0.9324	0.0658
煤炭加工转换率	332	0.6388	0.7480	0.6890	0.0349
煤炭消费占比	332	0.5900	0.7160	0.6565	0.0411
清洁能源消费占比	332	0.1200	0.2220	0.1667	0.0331
流动比率	332	0.0134	14.1078	1.1175	0.9622
流动资产周转次数	332	0.2581	12.8563	1.8841	1.2032
固定资产周转次数	332	0.1906	26.0288	2.2808	2.8817
净资产收益率	332	-2.1278	2.2194	0.0688	0.2031
每股（本）收益	332	-3.0482	2.9108	0.4609	0.7053
经营资产收入率	332	0.1240	3.5237	0.7505	0.4601
经营资产利润率	332	-0.3141	0.3630	0.0700	0.0832
煤炭与清洁能源消费交互系数	332	0.0859	0.1310	0.1081	0.0146

解释变量、控制变量	模型1回归结果	模型3回归结果
解释变量、控制变量	被解释变量：每股收益	被解释变量：净资产收益率
（常数）	-1.5243	-1.9596**
流动资产熵值	4.1736***	3.7488***
固定资产熵值	-0.5201	0.1233
无形资产熵值	1.8796*	1.4541
非煤业务占比	-2.2962**	0.3842
煤炭去产能比值	-2.1440**	-1.7844*
煤炭加工转换率	2.8635***	2.1618**
清洁能源消费占比	-3.4988***	-0.9873
流动比率	2.8271**	2.3584**
流动资产周转次数	3.7759***	4.0314***
固定资产周转次数	0.5839	1.1450
年度（2009—2018）	哑变量	哑变量

解释变量、控制变量	模型2回归结果	模型4回归结果	模型5回归结果
解释变量、控制变量	被解释变量：经营资产收入率	被解释变量：经营资产利润率	被解释变量：资产结构演变熵值合计
（常数）	-7.1101***	-1.3935**	-1.0957
流动资产熵值	9.3244***	4.1124***
固定资产熵值	10.7015***	-0.0182
无形资产熵值	-0.8944	2.4361
非煤业务占比	0.0409	-3.3104	-8.5626***
煤炭去产能比值	1.3342	-2.8292*	0.3795
煤炭加工转换率	2.3329**	3.4246**	0.3729
清洁能源消费占比	-1.5431	-5.1307	0.1636
煤炭消费占比			1.1485
煤炭消费与清洁能源消费交互系数			0.8224
流动比率	-0.2553	4.6121**
流动资产周转次数	28.5593***	5.4683***
固定资产周转次数	24.8863***	0.2192
年度（2009—2018）	哑变量	哑变量	哑变量

Economic prying effect of de-capacity and asset structure adjustment in the coal industry

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