【作者】 张福明；

【导师】 孟宪忠；

【作者基本信息】 上海交通大学 ， 企业管理， 2011， 博士

【摘要】 企业成长研究自亚当·斯密起至今已有二百多年的时间,但真正开展企业成长理论研究才不过几十年的时间,彭罗斯教授在1959年出版的《企业成长理论》,真正奠定了现代企业成长的理论基础。无论是经济学家、管理学家还是企业家们,从未间断对企业成长问题的探索。企业成长是一个复杂的动态过程,呈现丰富的动态特性。企业成长的动态特性是由企业所处的外界环境和内部因素综合作用的结果。因此,要对企业成长进行深入有效的分析,单凭定性分析的方法和手段已显得略为不足,选择合理的数学模型对企业成长过程进行量化的模拟,才能揭示企业成长的内在本质。本文在对已有企业成长理论进行文献梳理的基础上,通过对企业成长与规模、生产率和盈利能力之间的动态关系研究,把企业成长问题放在其所处的动态系统中进行分析,并且选择中国制造业企业作为研究样本,对企业成长理论在中国的适用性问题展开了深入的研究,从理论知识和实践应用上进一步完善了企业成长理论,具有重要的理论价值和实际意义。通过研读国内外企业成长理论的相关文献,笔者发现,已有文献的实证研究仅仅采用的是企业的静态面板数据,而利用企业层面的动态面板数据进行的实证研究则相对缺乏,这样的研究方法导致的直接后果则是从根本上忽视了企业成长的动态性问题;其次,大部分有关企业成长的研究都是通过全要素生产率分解来分析中国工业企业的生产率状况,较少地涉及在企业成长过程中分阶段研究生产率的作用;再次,国内的学者缺少用动态演化的方法分析企业成长与企业盈利能力之间的关系。在本篇论文中,笔者克服了前述研究的局限性,综合运用了管理学、经济学和自然科学的定量研究的理论与方法,坚持理论与实践相结合,充分发挥面板数据自身的动态特性,熟练应用回归分析、PVAR模型和系统广义矩估计等计量方法,着重从中国制造业企业生产率和盈利能力方面来研究与企业成长之间以及三者之间的动态关系问题。本论文的主要研究内容如下:第一,从中国制造业行业自身的特征入手,分析了目前我国制造业行业的几个特征。首先,分析了中国制造业上市公司行业规模特征,分别对资产总计和净利润进行统计分析,通过分析2007年、2008年和2009年我国制造业上市公司财务数据,结果发现,制造业类上市公司规模呈“幂曲线”形态,即只有少数企业规模较大或者占有绝大部分利润,然后曲线急剧下滑形成一个“长尾”,其余大部分企业都处在“尾部”。分析发现,这3年规模或利润排名前10位的多是国家垄断行业,行业分类为黑色金属冶炼及压延工业行业,部分为交通运输设备制造业;接着根据产业关联理论,利用2007年全国投入产出表,从宏观的视角分析了目前中国制造业各行业与其他各产业之间的感应度系数和影响力系数,综合分析各部门在国民经济中的地位和作用。结果表明,制造业行业中造纸印刷及文教体育用品制造业、化学工业、金属冶炼及压延加工业、金属制品业、通用、专用设备制造业、通信设备、计算机及其他电子设备制造业和仪器仪表及文化办公用机械制造业具有高影响力系数和感应度系数,煤炭开采和洗选业、石油和天然气开采业、金属矿采选业、非金属及其他采选业、石油加工、炼焦及核燃料加工业和废品废料具有高感应度系数和低影响力系数,这些产业对市场变化和其他产业发展具有较强的敏感性和影响能力。第三,对比分析了中国制造业行业生产率与美国制造业生产率,并给出了1999年到2005年中国制造业行业劳动生产率变化情况。尽管从国际比较看,我国制造业生产效率与世界先进水平存在较大差距,然而从历史的观点来看,我国制造业生产效率取得了长足的进步。中国制造业各行业质量竞争力逐年提高,2010年全球制造业竞争力指数排名第一。在经历了2008年11月中国制造业采购经理指数的最低点后,PMI指数稳步上升,2009年3月之后始终保持在50%以上。第二,以资产总计和营业收入作为衡量企业规模的代理变量,通过对中国制造业上市公司1999年到2009年财务数据进行统计分析,结果发现,中国制造业上市公司企业规模分布皆服从三参数的Log-Logistic分布。K-S检验结果表明,服从该分布,并给出Q-Q图检验。Gibrat首先探索分析了企业成长与企业规模之间的关系,本文根据Evans模型构建了企业成长与企业规模、企业年龄关系模型。对全样本进行单要素和回归分析,结果表明,企业成长与企业规模之间呈显著负相关关系,企业成长与企业年龄之间呈显著正相关关系。为了检验结果的稳健性,还进行了附加测试,结论基本不变。第三,研究了基于面板数据向量自回归(PVAR)模型的我国制造业上市公司企业成长与生产率关系,从动态的角度分析了各自变量的冲击对企业成长因变量的影响。首先运用Malmquist-DEA方法对我国制造业上市公司企业的生产率进行测算。全样本分解结果表明,2000年到2009年全要素生产率变动指数年均值小于1,技术效率和规模效率变动指数年均值大于1,纯技术效率变动指数年均值小于1,反映了我国制造业行业主要依靠规模增大来提高全要素生产率,依靠大量的物质和资金投入维持企业成长。其中C4和C6行业在制造业行业中具有较高的生产率水平,因此又对这两个行业进行细分行业的生产率测算。接着,建立了基于PVAR模型的企业成长与生产率关系模型,分析变量冲击对企业成长的影响。当在本期给企业规模一个正冲击后,当期企业成长未发生变化,在第2期有所下降,第3期之后迅速上升,之后第4、5期下降到最低点,而后又迅速上升。这说明企业规模增大在开始阶段对企业成长的负面影响较小,3期后才逐渐对企业成长产生较大的负向影响,5期后形成正向影响,有利于企业的后期成长。同样在当期给TFP一个正冲击后,企业成长始终在小幅度的上下波动,5期后迅速下降。反映出生产率对企业成长有一定的影响,但不能持续的促进企业成长,在经过了一定时期后需要提高生产率来获得企业的不断成长动力。在当期给PECH一个正冲击后,企业成长在前4期波动,在第4期后逐渐增大对企业成长的影响力。说明纯技术效率的提高在短时期内无法发挥对企业成长显著的促进作用,4期后会对企业成长产生明显的正向作用。技术提高,将促进企业持续成长。从预测方差分解表得到,经过20个预测期以后,系统基本稳定。20个预测期企业成长对其他三个变量的影响都很显著,相对来说,PECH对其他各变量的影响要大于企业规模和TFP对各变量的影响。第四,利用面板数据优良的动态优势,从动态的角度分析企业成长与盈利能力之间的关系。首先分析了目前我国工业行业盈利现状,1999年到2009年我国制造业行业上市公司盈利能力均值逐年上升,标准差增速不大,说明各企业盈利能力分化现象不严重。接着利用系统广义矩估计法构建了企业成长与盈利能力关系模型。为了对比分析,还给出了面板数据的静态分析结果,并且根据企业年龄分成4类分析了两者之间的关系。两步法系统矩估计结果表明,当从动态的角度分析企业成长与盈利能力、企业规模之间的关系时,结果不同于静态分析结果。企业规模对企业成长的影响在滞后1期后发生变化,而盈利能力则在滞后2期后发生变化,说明各自变量对因变量的影响是存在动态变化的。为了讨论结果的稳健性,进行了稳健性分析,基本结论不变。第五,从研究整体性和系统性角度,分析了企业生产率和盈利能力之间的关系,同时分析了企业成长、生产率和盈利能力之间三者之间的关系。首先,从统计学角度探索了生产率和盈利能力之间的联系。分别按盈利能力和生产率划分,利用统计学分析了各阶段两者之间的联系。另一方面利用第四章的研究方法,研究了基于PVAR模型的生产率和盈利能力之间的联系。结果发现,盈利能力不一定能促进生产率的提高,但生产率提高一定能促进企业盈利能力的提高。接着,按上市时间划分,研究了企业成长、生产率和盈利能力之间的联系。结果表明,生产率在促进企业成长的影响要大于盈利能力对企业成长的影响。另外,生产率和盈利能力的提高,将极大地促进企业成长。本文研究的创新点主要体现在以下几个方面:(1)在研究框架上,本文从中国制造业上市公司企业成长的实际出发,依次从生产率、盈利能力方面分析、探索了与企业成长之间存在的动态关系,首次从动态的角度的分析企业成长与生产率、盈利能力之间的动态关系,完整的分析了三者之间的联系,通过构建模型更丰富了企业成长理论,从而为深入理解和掌握企业成长规律提供了重要的理论依据。(2)样本数据时间跨度大,一方面实证分析部分应用了1999-2009年之间中国制造业上市公司数据,另一方面在论文描述性部分采用了2000年-2010年《中国统计年鉴》以及截至2010年的世界及美国等国家和行业统计年鉴;研究对象的选择,生产率、盈利能力和企业成长这三个方面是企业的核心,是制造业行业最关心的,同时将企业规模作为控制变量,使得研究更具稳定性。该研究对如何在新的背景下,开展制造业行业研究具有非常重要的理论和现实意义。(3)本文主要应用Malmquist-DEA方法测算的全要素生产率值来表征企业生产率,分解的纯技术效率变动指数作为衡量技术水平(或创新)的代理变量,本文首次建立基于面板数据向量自回归的企业成长与生产率关系模型,从动态的角度分析了企业成长与生产率、纯技术之间的关系。通过利用脉冲响应函数和方差分解,更直观地了解生产率与企业成长之间的互动关系。(4)在研究我国制造业上市公司企业成长与盈利能力之间关系时,首次利用系统广义矩估计方法研究两者之间的关系,该方法能更好地研究变量之间的动态关系,不同于以往简单、静态的分析企业成长与盈利能力之间的关系。(5)完整、系统的研究了企业成长与生产率、盈利能力之间的关系。(6)本文研究的样本取自中国上市公司财务数据,在文中做了相应的稳健性检验,保证结论的稳健性。充分发挥面板数据的优势,应用较新的关于面板数据的理论,如面板数据协整理论、面板数据单位根检验,更准确的分析各变量之间存在的关系情况。更多还原

【Abstract】 Since Adam Smith, the study of the growth of the firm has been two hundred years from the time, but really to carry out theoretical research of the growth of the firm was only a few decades. Professor Penrose, published "the Theory of the Growth of the Firm" in 1959, really laid the theoretical basis of modern theory of the growth of the firm. Economists, management scientists or entrepreneurs, who have never stopped thinking about the problem of the growth of the firm, The growth of firm is a dynamic process, and shows various dynamic characteristics, which is the integrated effect of surroundings and inter structure of the system. Therefore, to probe in-depth the growth of firm, we must take into account the dynamic nature of firm growth, with the mathematical model, building a dynamic process of firm growth.In this paper, our study based on the theory of the growth of the firm with lots of literature research, through research the dynamic relationship of firm growth and firm size, productivity and profitability, we put the company’s problems on its own dynamic system to analysis, and further improve the growth of the firm of the Chinese manufacturing enterprises.Through researching the domestic and international literatures of the theory of the growth of the firm, we can see, the use of firm level panel data analysis is relatively scarce and only the use of static analysis of panel data, ignoring the problem of the dynamic firm growth. Secondly, most of these studies to analyze the productivity of China’s industrial enterprises state through the decomposition of total factor productivity, less involved in the firm growth stages of the process the role of productivity. Thirdly, domestic researches lack of the study of the relationship between the firm growth and profitability. Therefore, this study combines the use of management, economics and natural science theories and methods, adhere to the theory and practice, give full play to the dynamic nature of panel data itself, skillfully applied regression analysis, PVAR model and system GMM estimation of measurement approach, focusing on the Chinese manufacturing enterprises firm size, productivity and profitability and the three aspects of the dynamic relationship between the growth of the firm issues.Following is the main contents and viewpoints:Firstly, from the characteristics of Chinese manufacturing industry to start our studies, we analyze the current number of China’s manufacturing industry characteristics. (1), analysis the firm size of characteristics of listed companies of Chinese manufacturing industry, namely, total assets and net profit of statistical analysis, by analyzing the 2007, 2008 and 2009 financial data of listed manufacturing companies, we found that listed companies manufacturing firm size was "power curve", which unlike normal distributions, implies that most companies are below average, such a curve is characterized by a short "head", comprising a small set of companies with extremely large total assets or net profit, and drops off quickly to a long "tail". We also found that the firm size or profits of top 10 multi-national monopolies in three years, the industry is classified as black metal smelting and pressing industry sectors, some of the transportation equipment manufacturing; (2), then based industry association theory, from a macro perspective we use the national investment output tables in 2007, calculate the sensitivity coefficient and influence coefficient between the current Chinese manufacturing industries and other industries, and also a comprehensive analysis of various departments in the national economy status and role. The results show that the printing and paper manufacturing industry, educational and sports goods, chemical industry, metal smelting and rolling processing industry, fabricated metal products, general, special equipment manufacturing, communications equipment, computers and other electronic equipment and instruments meters, cultural and office machinery with high impact coefficients and sensitivity coefficients, coal mining and dressing industry, oil and gas industry, mining industry, metal and other mining industry, petroleum processing, coking and waste nuclear fuel and waste processing industry with high sensitivity coefficients and low influence coefficients, these industries have strong sensitivity and influencing skills to market changes and other industries. (3), the comparative analysis of productivity in Chinese manufacturing industry and U.S. manufacturing productivity, and gives labor productivity in Chinese manufacturing industry changes from 1999 to 2005. While international comparison, China’s manufacturing efficiency has a wide gap between the advanced world’s levels, but from a historical point of view, China’s manufacturing productivity has made considerable progress. The quality of Chinese manufacturing competitiveness increased year by year, in 2010 global manufacturing competitiveness index ranked first. After the lowest point in the November 2008 of China Manufacturing Purchasing Managers Index (PMI), PMI index rose steadily, after March 2009 PMI index has been in more than 50%.Secondly, we use the total assets and operating income as a proxy variable to measure the firm size, by statistical analysis of China’s listed manufacturing companies financial data from 1999 to 2009, found that the firm size of Chinese manufacturing enterprises listed companies are subject to the three-parameter Log-Logistic distribution. K-S test results show that, subject to the distribution, and gives Q-Q figure test. Gibrat first exploration the relationship between the growth of firm and firm size, we constructed the relationship model of the growth of firm and firm size, firm age model, according to Evans. We analysis from single element of the whole sample to regression analysis, the results show that, the relationship between the growth of firm and firm size was a significant negative correlation, the relationship between the growth of firm and firm age was a significant positive correlation. To test the robustness of the results, also carried out additional testing, conclusions remain basically unchanged.Thirdly, from the dynamic point of view we analysis the relationship between the growth of firm and productivity of China’s listed manufacturing companies, which based on the panel data vector autoregressive (PVAR) model, also studied the variables impact on the growth of firm variable. (1), we use the Malmquist-DEA method to measure the productivity of China’s manufacturing listed companies. Full sample decomposition results show that, from 2000 to 2009, annual average total factor productivity change index is less than 1, technical efficiency and scale efficiency change index annual average greater than 1, the pure technical efficiency change index annual average of less than 1, which reflecting China’s manufacturing industry mainly depends on the scale of the industry to increase total factor productivity increases, that is relying on a lot of material and capital investment to maintain the growth of firm. In the manufacturing industry sector, C4 and C6 has a high productivity level, we also carried out these two sub-sectors of industry productivity measure. (2), we create a business model based on PVAR to analyze the relationship between the growth of firm and productivity, also study the impact of variables on the growth of firm. When give a positive impact to the current firm size, the current growth of firm did not change, a decline in the 2 period, after has a rapid increase period in the 3 period, followed drop to the lowest point of 4 period and 5 period, and then rose rapidly. This shows that firm size increases has a small negative impact on the growth of firm at the beginning, after three periods have a greater negative impact on the growth of firm, after five periods form a positive influence and help the latter part of growth of firm. Also give a positive impact to the current TFP, the growth of firm has fluctuated in a small range, decreased rapidly after five periods. That reflects the productivity have a certain impact on the growth of firm, but can not continue to promote the growth of firm, after a certain period of time, we should improve the productivity of firm momentum. Given a positive shock to the PECH in the current, the growth of firm volatility in the first four periods, after fourth period PECH has gradually increase the impact of the growth of firm. That reflect pure technical efficiency can not play a significant role in promoting growth of firm in the short term, after four periods will have the obvious positive effect. Improvement of technology will facilitate sustainable the growth of firm. Variance decomposition obtained from the table after 20 forecast periods, the system was stable. The growth of firm has significant influence to the other three variables after 20 forecast periods, relatively speaking, PECH effects of other variables is greater than firm size and TFP on the impact of each variable.Fourth, we use the quality dynamic advantages of panel data, from the dynamic point of view, analysis the relationship between the growth of firm and profitability. (1), analysis the current status of China’s industrial profits from 1999 to 2009, China’s listed companies of manufacturing industry average profitability increased year by year, the growth of standard deviation is not, indicating that differentiation of the profitability of the business is not serious. (2), we use the System-GMM method to construct the relationship model between the growth of firm and profitability. For comparative analysis, we also give the results of static analysis of panel data. We divided the firm age into four categories, to analysis the relationship between the two. Two-step system GMM estimation results show that, from the dynamic point of view the relationship in growth of firm, firm size profitability is different from the static analysis results. Firm size on the impact of growth of firm, has a change after 1 lag, and profitability has change after2 lags, these indicate that the independent variables on the dependent variable have the dynamic change. In order to discuss the robustness of the results, we carried out a robust analysis; the results reflect the basic conclusion unchanged.Fifth, we analysis the relationship among the firm growth, productivity and profitability, from the perspective of systematic view. First, from a statistical point of view, we explore the linkages between the productivity and profitability. We classified the data respectively according to the profitability and productivity, using statistical analysis the linkages between the two vaiables in various stages. On the other hand, we use the research methods of Chapter IV to study the relationship of the productivity and profitability. It was found that profitability may not be able to promote productivity, but productivity will be able to promote the improvement of profitability. Then, by time-division study on the firm growth data, we study the linkages between the productivity and profitability. The results show that the productivity growth impact in promoting enterprise profitability is greater than the impact on firm growth. In addition, both the improvement of productivity and profitability will greatly facilitate firm growth.The innovation of this paper is mainly reflected in the following areas:(1)In the research framework aspect, the paper analysis from the reality of growth of firm of China’s listed manufacturing companies, followed by the firm size, productivity and profitability, the relationship between the three aspects and the growth of firm. And we take the lead from the dynamic perspective analysis the relationship between the growth of firm and the productivity, the profitability, by building models richer the theory of the growth of firm, so provides an important theoretical basis as to understand and master the law of the growth of firm.(2)The sample data time is span, on the one hand the application of empirical analysis of Chinese manufacturing listed company data between 1999-2009, on the other hand in the descriptive part of the paper used "China Statistical Yearbook" between 2000 -2010 and the world and the United States and other countries and industries Statistical Yearbook as of 2010; choose the firm size, productivity and profitability, which three aspects the dynamic relationship between the growth of firm, these aspects are most concerned about the manufacturing industry, we think that carry out the study is very important in theoretical and practical for the manufacturing industry.(3)This paper mainly use the Malmquist-DEA method estimated total factor productivity to characterize corporate productivity, decomposition of the pure technical efficiency change index as a proxy for measuring technological level, first establish the panel data VAR model, from the dynamic point of view analysis the relationship between the growth of firm and productivity, pure technology. Through using the impulse response functions and variance decomposition, we more intuitive understand the dynamic influence of productivity to the growth of firm.(4)We first use the system GMM estimation method to analysis the relationship between the growth of firm and profitability of the China’s manufacturing listed companies, which is different from the previous simple, static analysis the relationships between the two aspects.(5) From complete and systematic point, study the relationship between firm growth, productivity, and profitability.(6)We studied a sample of financial data from Chinese listed companies, in the text made the corresponding robustness checks to ensure the conclusions robustness. Give full play to the advantages of panel data, a relatively new application of the theory on the panel data, such as the panel data cointegration, panel data unit root test, a more accurate analysis the relationship between the variables.更多还原