我国钢铁行业产能过剩研究
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摘要
产能过剩是我国长期面对的一个难题。自改革开放以来,我国逐步从计划经济体制向社会主义市场经济体制转变；在计划经济的体制下,物资十分匮乏,并不存在产能过剩的问题；而步入市场经济后,随着经济结构的调整和经济发展方式的转变,产能过剩的问题逐渐凸现出来。进入二十一世纪以来,我国进行了大规模的基础设施投资,每一轮经济过热过后,就会形成新一次的产能过剩。2008年,金融危机从美国爆发,并逐渐向全球蔓延。2010年欧洲主权债务危机爆发,各国央行相继出台经济刺激计划,我国政府也推出了4万亿的经济刺激计划以振兴市场。随着美联储连续推出的几轮货币量化宽松政策和欧元区债务危机的深入,以及国内原材料市场、特别是食品价格和住房价格上涨,输入型通货膨胀和国内通货膨胀共同推高了我国的通货膨胀水平。为了稳定物价,我国央行提高了银行的存款准备金率并提高了利率。这样做的结果,一方面是紧缩型货币政策造成众多中小型企业和民营企业的资金紧张,进而使企业生产受到很大影响,客观上造成一定产能的浪费；另一方面,基础设施建设的投资,使得大量资金投入水泥,钢铁等高耗能、高污染等行业,加剧了产能过剩的程度。产能过剩的研究有两个重要意义,一个是界定产能合理水平,为企业市场策略和国家制定政策提供政策基石,另一个是降低重复建设水平,提高资源配置效率。
本文回顾了国内外研究的现状。目前国内对于产能过剩问题的研究主要集中在产能过剩的成因解析及治理机制,或是对产能过剩的测度方法进行理论分析,并且大多集中于定性分析,鲜有从定量角度出发的实证研究。国务院相关文件中只指出产能过剩会“影响经济持续快速协调健康发展”,究竟这一现象会如何影响宏观经济的运行,影响程度又有多深,进而政府该采取何种应对措施,目前国内缺乏针对上述问题的理论研究。产能过剩作为一个宏观经济指标可以解释和说明很多经济现象,并起到对经济的前瞻性预测；同时,产能过剩作为一个微观的经济指标,可以为投资者和管理者提供关于企业生产的有效信息,从而制定更加合理的投资和战略决策。本文的主要研究内容,将基于效率分解的原理,以微观的22家钢铁企业上市公司为研究对象,来计算和说明产能利用水平,并明确产能过剩的标准。
本文的内容安排如下：
本文分为五个部分。第一部分,介绍了本文的选题背景、意义,梳理了相关的国内外研究文献和现状,提出了本文要解决的问题。第二部分为文章的理论部分,共分为五个小节,第一小节介绍了生产技术,包括投入集和产出集的定义和性质；第二小节介绍了距离函数的概念；第三小节介绍了距离函数与效率测量之间的关系；第四小节使用距离函数和效率分解的概念,提出了产能利用率的三种不同定义、测度和效率分解,第五小节为总结。第三部分介绍本文对产能利用率测度所使用的方法,包含两个部分,第一个部分是产能利用率的非参数数据包络分析方法,第二部分是产能利用率的参数随机生产前沿面方法。第四部分是本文的实证部分,包含四个部分,第一部分介绍了本文选取的指标和样本,第二部分使用数据包络分析方法对所选取的上市公司的产能利用效率进行计算和分解；第三部分,使用随机生产前沿面方法对所选上市公司的产能利用率进行估计和分解,并对两个方法估算的结果进行比较。第五部分,本文将对实证分析的结果进行总结,并提出政策和建议。
本文的结论表明,我国钢铁行业22家上市公司的平均径向产能利用率为61.2%,平均技术效率在90%以上,而最优产能利用率为69.0%,表明了企业在技术层面上的效率较高的同时,也形成了较为严重的产能过剩。本文的最后提出了政策建议和改进的方向。
Overcapacity is a problem which China faced for a long time. Since the reform and opening up. China has gradually changed from a planned economy to a socialist market economic system; in the planned economy system, the material is very scarce, there is the problem of excess capacity:and in the market economy, with the economic structure adjustment and economic development pattern, the problem of excess production capacity gradually exposed. In the twenty-first century. China carried out large-scale infrastructure investment, after each round of economic overheating, it will form a new round of overcapacity. In 2008. the U.S. financial crisis broke out, and gradually spread to the world.2010 European sovereign debt crisis, central banks have introduced economic stimulus plan, our government has launched a 4 trillion economic stimulus plan to revive the market. With the launch of several rounds of Fed quantitative easing monetary policy and the deepening of the euro zone debt crisis, and domestic raw material market, especially in food prices and housing prices, imported inflation and domestic inflation jointly push China's inflation level. In order to stabilize prices, China's central bank raised banks' deposit reserve ratio and increasing interest rates. As a result, by tight monetary policy many small and medium enterprises, private enterprises have very restricted funding, resulting capacity waste; on the other hand, investment in infrastructure funds a lot on cement, steel, etc. This high energy consumption, high pollution industries exacerbated the extent of excess capacity. Excess capacity study has two merits, one is to define a reasonable level of productivity for the enterprise market strategy and the cornerstone of national policy to provide policy, and the other is to reduce the level of duplication and improve efficiency of resource allocation.
This paper reviews literature both in and abroad. Present studies for domestic overcapacity focuses on overcapacity causes and governance mechanisms, or on overcapacity's theoretical analysis, and most of them focused on the qualitative analysis, rarely from a quantitative point of view. Documents from State Council only shows that overcapacity will affect the sustain, rapidness and health development of the economy. There lacks the theoretical analysis of how overcapacity would affect the economy, what is the degree and what solution the government should execute to deal with this problem. As a macroeconomic index, overcapacity can predict the development of economy; as a micro-indicator, it can provide useful information for both managers and investors to make better decisions.
The main content of this article, based on the principle of decomposition efficiency, uses 22 listed steel companies to calculate and illustrate the level of capacity utilization, and tries to give a standard for overcapacity.
This paper is structured as follows:
This paper is divided into five parts. The first part introduces the background, significance of this paper, together with the relevant domestic and abroad literatures, raises the problem to be solved. The second part--the theoretical part is divided into five sections, the first section describes the production technology, including the input sets and output sets; the second section introduces the concept of distance function:the third section introduces the relation between distance function and efficiency measurement:the fourth section raises three different definitions and their measurement and decomposition. The fifth part is summary of part 2. The third part describes methods used to identify capacity utilization. This part consists two sections; the first section is a non-parametric measurement of capacity utilization--data envelopment analysis; the second section is the parametric method--stochastic production frontier approach. The fourth part is the empirical part of this article, consists of four sections, the first section describes the selection of indicators and sample, the second section uses data envelopment analysis to calculate the efficiency of capacity utilization and its decomposition of 22 listed steel companies; the third section uses stochastic frontier model to calculate the 22 companies' capacity utilizations and their decomposition, thereby compare the differences of SFA and DEA. PartⅤ, this article will summarize and propose suggestions on policies and decision making.
The paper concludes that average radial capacity utilization of 22 listed companies was 61.2%, the average technical efficiency of 90%, while the optimal capacity utilization was 69.0%, indicating that while enterprises were operating at a higher technical efficiency level, there also exists a serious overcapacity. This article proposes policy recommendations together with directions of improvement for this article.
本文回顾了国内外研究的现状。目前国内对于产能过剩问题的研究主要集中在产能过剩的成因解析及治理机制,或是对产能过剩的测度方法进行理论分析,并且大多集中于定性分析,鲜有从定量角度出发的实证研究。国务院相关文件中只指出产能过剩会“影响经济持续快速协调健康发展”,究竟这一现象会如何影响宏观经济的运行,影响程度又有多深,进而政府该采取何种应对措施,目前国内缺乏针对上述问题的理论研究。产能过剩作为一个宏观经济指标可以解释和说明很多经济现象,并起到对经济的前瞻性预测；同时,产能过剩作为一个微观的经济指标,可以为投资者和管理者提供关于企业生产的有效信息,从而制定更加合理的投资和战略决策。本文的主要研究内容,将基于效率分解的原理,以微观的22家钢铁企业上市公司为研究对象,来计算和说明产能利用水平,并明确产能过剩的标准。
本文的内容安排如下：
本文分为五个部分。第一部分,介绍了本文的选题背景、意义,梳理了相关的国内外研究文献和现状,提出了本文要解决的问题。第二部分为文章的理论部分,共分为五个小节,第一小节介绍了生产技术,包括投入集和产出集的定义和性质；第二小节介绍了距离函数的概念；第三小节介绍了距离函数与效率测量之间的关系；第四小节使用距离函数和效率分解的概念,提出了产能利用率的三种不同定义、测度和效率分解,第五小节为总结。第三部分介绍本文对产能利用率测度所使用的方法,包含两个部分,第一个部分是产能利用率的非参数数据包络分析方法,第二部分是产能利用率的参数随机生产前沿面方法。第四部分是本文的实证部分,包含四个部分,第一部分介绍了本文选取的指标和样本,第二部分使用数据包络分析方法对所选取的上市公司的产能利用效率进行计算和分解；第三部分,使用随机生产前沿面方法对所选上市公司的产能利用率进行估计和分解,并对两个方法估算的结果进行比较。第五部分,本文将对实证分析的结果进行总结,并提出政策和建议。
本文的结论表明,我国钢铁行业22家上市公司的平均径向产能利用率为61.2%,平均技术效率在90%以上,而最优产能利用率为69.0%,表明了企业在技术层面上的效率较高的同时,也形成了较为严重的产能过剩。本文的最后提出了政策建议和改进的方向。
Overcapacity is a problem which China faced for a long time. Since the reform and opening up. China has gradually changed from a planned economy to a socialist market economic system; in the planned economy system, the material is very scarce, there is the problem of excess capacity:and in the market economy, with the economic structure adjustment and economic development pattern, the problem of excess production capacity gradually exposed. In the twenty-first century. China carried out large-scale infrastructure investment, after each round of economic overheating, it will form a new round of overcapacity. In 2008. the U.S. financial crisis broke out, and gradually spread to the world.2010 European sovereign debt crisis, central banks have introduced economic stimulus plan, our government has launched a 4 trillion economic stimulus plan to revive the market. With the launch of several rounds of Fed quantitative easing monetary policy and the deepening of the euro zone debt crisis, and domestic raw material market, especially in food prices and housing prices, imported inflation and domestic inflation jointly push China's inflation level. In order to stabilize prices, China's central bank raised banks' deposit reserve ratio and increasing interest rates. As a result, by tight monetary policy many small and medium enterprises, private enterprises have very restricted funding, resulting capacity waste; on the other hand, investment in infrastructure funds a lot on cement, steel, etc. This high energy consumption, high pollution industries exacerbated the extent of excess capacity. Excess capacity study has two merits, one is to define a reasonable level of productivity for the enterprise market strategy and the cornerstone of national policy to provide policy, and the other is to reduce the level of duplication and improve efficiency of resource allocation.
This paper reviews literature both in and abroad. Present studies for domestic overcapacity focuses on overcapacity causes and governance mechanisms, or on overcapacity's theoretical analysis, and most of them focused on the qualitative analysis, rarely from a quantitative point of view. Documents from State Council only shows that overcapacity will affect the sustain, rapidness and health development of the economy. There lacks the theoretical analysis of how overcapacity would affect the economy, what is the degree and what solution the government should execute to deal with this problem. As a macroeconomic index, overcapacity can predict the development of economy; as a micro-indicator, it can provide useful information for both managers and investors to make better decisions.
The main content of this article, based on the principle of decomposition efficiency, uses 22 listed steel companies to calculate and illustrate the level of capacity utilization, and tries to give a standard for overcapacity.
This paper is structured as follows:
This paper is divided into five parts. The first part introduces the background, significance of this paper, together with the relevant domestic and abroad literatures, raises the problem to be solved. The second part--the theoretical part is divided into five sections, the first section describes the production technology, including the input sets and output sets; the second section introduces the concept of distance function:the third section introduces the relation between distance function and efficiency measurement:the fourth section raises three different definitions and their measurement and decomposition. The fifth part is summary of part 2. The third part describes methods used to identify capacity utilization. This part consists two sections; the first section is a non-parametric measurement of capacity utilization--data envelopment analysis; the second section is the parametric method--stochastic production frontier approach. The fourth part is the empirical part of this article, consists of four sections, the first section describes the selection of indicators and sample, the second section uses data envelopment analysis to calculate the efficiency of capacity utilization and its decomposition of 22 listed steel companies; the third section uses stochastic frontier model to calculate the 22 companies' capacity utilizations and their decomposition, thereby compare the differences of SFA and DEA. PartⅤ, this article will summarize and propose suggestions on policies and decision making.
The paper concludes that average radial capacity utilization of 22 listed companies was 61.2%, the average technical efficiency of 90%, while the optimal capacity utilization was 69.0%, indicating that while enterprises were operating at a higher technical efficiency level, there also exists a serious overcapacity. This article proposes policy recommendations together with directions of improvement for this article.
引文
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[2]周业樑、盛文军转轨时期我国产能过剩的成因解析及政策选择金融研究,2007年第2期
[3]张军,中国国有部门的利润率变动模式：1978-1997[J],经济研究,2001年3月：19-28.
[4]徐铭蔚、张明,产能过剩埋下隐患：结构调整势在必行[J],西部论丛,2010年2月：56-57
[5]王兴艳,产能过剩评价指标体系研究初探[J], 技术经济与管理研究,2007(04)：12-13
[6]王立国,重复建设与产能过剩的双向交互机制研究.企业经济,2010年第6期
[7]王关义,现代生产管理[M]，第一版，北京,经济管理出版社.2005
[8]汪同三宏观经济出现不良循环链[N].国际金融报,2006年12月12日
[9]孙巍、何彬、武治国, 现阶段工业产能过剩“窖藏效应”的数理分析及其实证检验[J]，吉林大学社会科学学报，2008,48(1)：68-75
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[11]孙巍,产能过剩与市场结构的相关性研究.吉林大学,2007.4
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[14]罗毅丹,徐俊武.过剩产能与通货膨胀的关系分析——基于包含随机波动的TVP模型考察[J],中南财经政法大学学报，2010.179(2)：15-20
[15]卢峰,天则经济研究所399次学术报告会：治理产能过剩,http://www.docin.com/p-78668792.html,2010年2月.
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[2]周业樑、盛文军转轨时期我国产能过剩的成因解析及政策选择金融研究,2007年第2期
[3]张军,中国国有部门的利润率变动模式：1978-1997[J],经济研究,2001年3月：19-28.
[4]徐铭蔚、张明,产能过剩埋下隐患：结构调整势在必行[J],西部论丛,2010年2月：56-57
[5]王兴艳,产能过剩评价指标体系研究初探[J], 技术经济与管理研究,2007(04)：12-13
[6]王立国,重复建设与产能过剩的双向交互机制研究.企业经济,2010年第6期
[7]王关义,现代生产管理[M]，第一版，北京,经济管理出版社.2005
[8]汪同三宏观经济出现不良循环链[N].国际金融报,2006年12月12日
[9]孙巍、何彬、武治国, 现阶段工业产能过剩“窖藏效应”的数理分析及其实证检验[J]，吉林大学社会科学学报，2008,48(1)：68-75
[10]孙巍,尚阳.工业过剩生产能力与经济波动之间的相关性研究[J].工业技经济,2008,27(6)：117-121.
[11]孙巍,产能过剩与市场结构的相关性研究.吉林大学,2007.4
[12]苏剑,产能过剩背景下的中国宏观调控[J],经济学动态,2010年10期：47-51
[13]米黎钟、曹建海,我国工业生产能力过剩的现状、原因及政策建议[J],经济管理,2006,(07)
[14]罗毅丹,徐俊武.过剩产能与通货膨胀的关系分析——基于包含随机波动的TVP模型考察[J],中南财经政法大学学报，2010.179(2)：15-20
[15]卢峰,天则经济研究所399次学术报告会：治理产能过剩,http://www.docin.com/p-78668792.html,2010年2月.
[16]刘西顺,产能过剩、企业共生与信贷配给[J],金融研究,2006,309(3)：166-173.
[17]林毅夫, 潮涌现象与产能过剩的形成机制,经济研究,2010年第10期
[18]李江涛,产能过剩”及其治理机制[J],国家行政学院学报,2006(05)
[19]江源 钢铁等行业产能利用评价.统计研究、2006(12)
[20]何彬, 基于窖藏行为的产能过剩形成机理及其波动性特征研究[D],吉林大学,2008年.
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