中小高技术上市公司成长因素财务识别的实证研究

中小高新技术企业作为当今全球经济发展的一个重要组成部分,其迅速崛起引起了各国管理学者的高度重视.本文以深圳证券交易所中小企业板的上市公司为样本,采用多元线性回归的方法,识别出能够比较确切反映中小高新技术企业成长因素的指标.研究发现中小高新技术企业所提供的现金流量信息中,能够反映各方面因素对其影响的信息比较少;无形资产、薪酬指标不能充分体现技术和人力资源因素对中小高新技术企业成长的影响;管理活动和充足的资金保障对中小高新技术企业的成长有比较重要的影响.     

关系型融资对中小高新技术企业成长能力的影响

基于上市公司的截面数据和面板数据,通过运用Heckman选择模型和条件Logit模型,对银企关系长度等指标进行了测量,采用两阶段估计法对企业成长能力进行了分析,将传统中小企业与中小高新技术企业进行了对比,探讨了关系型融资对中小高新技术企业成长能力的影响。研究结果表明,对于传统中小企业,关系型融资对其成长能力的影响不大;而关系型融资对于中小高新技术企业成长能力的提高发挥了重要作用。此外,对于中小高新技术企业,主银行贷款份额、贷款银行数量、银企关系长度等指标与企业成长能力正相关,而对于传统中小企业,只有关系长度的影响较为显著。最后,为促进银行更好地开展关系型融资,提出了相关建议。     

组织印记、生态位与新创企业成长——基于组织生态学视角的质性研究

基于组织生态学理论,本文对中国农村电商创业生态系统中的新创企业成长过程进行了质性研究,提出了新创企业生成的印记因素及生态位对企业成长的影响过程模型,揭示了在初始条件约束和自然选择压力下新创企业的成长机理。研究发现:诱发创业者创建企业及持续影响其成长的印记因素包括市场空间的成长性、自身资源禀赋以及创业者特性;这些初始印记因素影响新创企业的战略偏向,包括目标定位,经营结构与盈利模式,并在很大程度上决定了企业所处的生态位;在面对生态位选择机制时,先进入的新创企业囿于初始印记效应不愿改变其生态位,更倾向于采用制度化策略维护既有生态位,后发企业则会通过差异化策略寻求生态位分离。研究结论明晰了在一个创业生态系统中,带有不同阶段初始印记的新创企业在相互竞争生态位过程中的不同成长路径,并引致企业整体(种群)层面的演化。     

高新技术企业技术自主创新的影响因素分析

通过对高新技术企业技术自主创新的内部条件——企业高管决策层的素质、企业资本因素、企业R&D状况和企业外部环境——地域因素、政策环境、联系效应、合作协议等影响因素进行分析,揭示了其对技术自主创新的影响情况,为实现高新技术企业技术自主创新提供了理论依据。     

民营高新技术企业成长性协同研究

本文结合高新技术产业的特点,针对民营高新技术企业的实际,首先明确了高新技术企业、成长性等基本概念的内涵,阐述了高新技术企业成长性的特点,指出成长性问题是民营高新技术企业成长的关键性问题;其次,对民营高新企业的成长阶段理论和成长性决定因素理论进行回顾,总结了面临的主要障碍,提出创新是企业成长的动力;最后,在深入分析企业成长性所面临的挑战和当前所存在的问题之后,提出企业必须实现技术创新、市场创新的协同。     

高新技术企业内部控制探析

高新技术企业是高风险、高收益的企业,资金、人力和技术是影响高新技术企业内部控制的重要因素,高新技术企业要面对复杂的外部环境,应对激烈的市场竞争,防范经营风险和财务风险,必须加强内部控制。本文讨论了高新技术企业内部控制的重要因素,分析了高新技术企业内部控制的主要特点,并就如何加强高新技术企业内部控制进行了探讨。     

企业自主创新的融资行为及其对成长的影响:来自中国A股市场的经验证据

在"创新型国家"建设的背景下,资金瓶颈被认为是企业自主创新的一个主要影响因素,相应资本结构的变化也可能影响了企业的成长。以592家中国A股上市公司为样本,以2001-2010年共10年为时间窗,利用独立混合横截面回归方法研究了自主创新能力对融资行为的影响,以及财务杠杆对企业成长的影响。结果发现:无论是用专利授权数还是专利申请数作为创新能力的替代变量,创新能力对内源融资都具有显著的促进作用,用专利申请数作为创新能力的替代变量时,创新能力对股权融资也具有显著促进作用。进而,创新能力对杠杆具有显著的抑制作用。但并未发现杠杆影响成长的证据。     

人力资源管理系统影响企业绩效的复杂性机理——基于高新技术企业的实证研究

破解人力资源管理系统影响企业绩效的机理是战略人力资源管理研究领域的核心问题。基于164家高新技术企业的调查数据,采用层级回归模型检验了人力资源管理系统与企业绩效间的复杂性机理。结果显示,人力资源管理系统对企业绩效的正向直接效应显著,影响二者关系的外生变量是创新战略非高管价值观;人力资本在二者关系间的中介效应不显著,但以组织氛围为控制变量时中介效应有了显著提高;"组织氛围调节下的人力资本中介作用模型"很好地刻画人力资本发挥中介效应的机理。研究结果强化了我们对人力资源管理系统与企业绩效关系机理的认知,同时为高新技术企业管理者在实践中管理员工提供了有益启示。     

高技术企业创业早期成长阶段的管理问题

对高技术企业创业早期成长阶段的管理问题进行了理论上的分析,指出了高技术企业创业早期的动因和管理中存在的问题,并通过早期成长阶段管理因素的统计分析得出对影响早期创业成功的三大类因素,指出了高技术企业创业早期成长阶段的重要影响因素排序,运用统计分析手段得出影响高技术企业创业失败的5个因素,进而提出了早期创业的管理系统及其管理的一般特点和相应的管理原则.     

公司治理机制对企业成长发展影响的实证分析——以河南省A股上市公司为例

本文以河南省A股上市公司1997-2007年间202个样本为例,研究了公司治理机制对企业成长发展的影响问题。回归结果显示,企业成长性与审计师的外部评价结果呈正相关关系,第一大股东如果属于国有性质将会对企业成长起到积极的正面作用,管理层持有公司股票和独立董事比例也将会对企业成长起到积极作用。但是,如果董事长（或副董事长）兼任总经理将会对企业成长起到负面作用。研究还发现上市公司的股权集中度和股权制衡状况对企业成长性的影响并不显著。     

IV Quantile Regression for Group‐Level Treatments,With an Application to the Distributional Effects of Trade

We present a methodology for estimating the distributional effects of an endogenous treatment that varies at the group level when there are group‐level unobservables, a quantile extension of Hausman and Taylor, 1981. Because of the presence of group‐level unobservables, standard quantile regression techniques are inconsistent in our setting even if the treatment is independent of unobservables. In contrast, our estimation technique is consistent as well as computationally simple, consisting of group‐by‐group quantile regression followed by two‐stage least squares. Using the Bahadur representation of quantile estimators, we derive weak conditions on the growth of the number of observations per group that are sufficient for consistency and asymptotic zero‐mean normality of our estimator. As in Hausman and Taylor, 1981, micro‐level covariates can be used as internal instruments for the endogenous group‐level treatment if they satisfy relevance and exogeneity conditions. Our approach applies to a broad range of settings including labor, public finance, industrial organization, urban economics, and development; we illustrate its usefulness with several such examples. Finally, an empirical application of our estimator finds that low‐wage earners in the United States from 1990 to 2007 were significantly more affected by increased Chinese import competition than high‐wage earners.     

国际化背景下的中国本土企业战略:一个理论框架与应用分析

发展中经济体内的本土企业,在面对全球竞争环境时如何形成有效的战略,是尚未受到充分研究的战略管理领域。本文以中国为对象,通过三个相关论题来探究这个有意义的问题。首先,我们评估了中国这样的转型发展经济体内的外部环境条件。在此基础上,我们确定了4个关键战略要素——本土化、资源拓展性成长、战略差异化和竞争性协作,从而形成成功的本土企业战略。然后,我们用这个四元模型来分析中国高新技术公司这类面临竞争挑战的特殊的公司群体。最后,我们提出了战略复杂性的概念以开拓未来的研究。除了理论贡献之外,我们还提供了管理建议和政策指向。     

基于非线性分位数回归模型的多期VaR风险测度

多期VaR主要受到持有期及波动率两个变量的影响,并且其影响模式(线性或非线性)的确定对于准确地进行VaR风险测度至关重要。非线性分位数回归模型,能够克服线性分位数回归模型只能揭示多期VaR及其影响因素之间线性依赖关系的局限,从而提高多期VaR风险测度的准确性。结合波动模型与两个非线性分位数回归方法:QRNN和SVQR,给出了多期VaR风险测度的三类方案:波动模型法、QRNN+波动模型法、SVQR+波动模型法。选取3个股票价格指数作为研究对象,考虑了6种不同形式的波动模型,得到了18个多期VaR风险测度方法进行实证比较,结果表明:波动模型选择影响到多期VaR风险测度效果;SVQR+波动模型法略优于QRNN+波动模型法,并且两者显著优于波动模型法。     

An IV Model of Quantile Treatment Effects

The ability of quantile regression models to characterize the heterogeneous impact of variables on different points of an outcome distribution makes them appealing in many economic applications. However, in observational studies, the variables of interest (e.g., education, prices) are often endogenous, making conventional quantile regression inconsistent and hence inappropriate for recovering the causal effects of these variables on the quantiles of economic outcomes. In order to address this problem, we develop a model of quantile treatment effects (QTE) in the presence of endogeneity and obtain conditions for identification of the QTE without functional form assumptions. The principal feature of the model is the imposition of conditions that restrict the evolution of ranks across treatment states. This feature allows us to overcome the endogeneity problem and recover the true QTE through the use of instrumental variables. The proposed model can also be equivalently viewed as a structural simultaneous equation model with nonadditive errors, where QTE can be interpreted as the structural quantile effects (SQE).     

企业效益评价因子分析模型及应用

本文将因子分析方法应用于社会科学领域的经济评价系统。从一些错综复杂的经济现象中找出少数几个主因子,每一个主因子代表经济变量之间相互依赖的一种经济作用,抓住这些主因子就可以帮助我们对复杂的经济问题进行分析和解释。在简要介绍因子模型以后,从实证分析的角度,选取深沪股市高科技板块 2 0家上市公司1998年中期的一系列经济评价指标,采用因子分析方法,并借助社会科学统计软件SPSS,进行企业的综合经济效益分析评价,得出因子分析是一种进行企业综合效益评价的有效方法。     

Quantile Regression under Misspecification,with an Application to the U.S. Wage Structure

Quantile regression (QR) fits a linear model for conditional quantiles just as ordinary least squares (OLS) fits a linear model for conditional means. An attractive feature of OLS is that it gives the minimum mean‐squared error linear approximation to the conditional expectation function even when the linear model is misspecified. Empirical research using quantile regression with discrete covariates suggests that QR may have a similar property, but the exact nature of the linear approximation has remained elusive. In this paper, we show that QR minimizes a weighted mean‐squared error loss function for specification error. The weighting function is an average density of the dependent variable near the true conditional quantile. The weighted least squares interpretation of QR is used to derive an omitted variables bias formula and a partial quantile regression concept, similar to the relationship between partial regression and OLS. We also present asymptotic theory for the QR process under misspecification of the conditional quantile function. The approximation properties of QR are illustrated using wage data from the U.S. census. These results point to major changes in inequality from 1990 to 2000.     

A multi-criteria approach for managing inter-enterprise collaborative relationships

Collaboration amongst enterprises is a common strategy used to increase competitiveness. Thus, enterprises that are collaborating need to define and use performance measurement/management frameworks composed of performance elements (objectives, performance indicators, etc.) that facilitate the management of their activity, as well as monitor their strategy and processes. There are many factors, e.g. trust, interoperability of Information Systems, etc. that need to be managed properly in order to support collaborative success. However, such factors and performance are not usually managed together. Furthermore, these factors and performance elements are interrelated but these influences are commonly overlooked. This paper aims to present an approach based on the Analytic Network Process (ANP) to manage collaborative relationships under an integrated approach by considering not only the inter-enterprise performance elements, but also the factors that influence collaboration. The approach is then applied to a collaborative enterprise network belonging to the renewable energy sector. With this innovative approach, enterprises will obtain significant information for the decision-making process, regarding which are the factors and performance elements that have the greatest impact on their competitiveness, and therefore should be prioritized.     

Identification in Nonseparable Models

Weak nonparametric restrictions are developed, sufficient to identify the values of derivatives of structural functions in which latent random variables are nonseparable. These derivatives can exhibit stochastic variation. In a microeconometric context this allows the impact of a policy intervention, as measured by the value of a structural derivative, to vary across people who are identical as measured by covariates. When the restrictions are satisfied quantiles of the distribution of a policy impact across people can be identified. The identification restrictions are local in the sense that they are specific to the values of the covariates and the specific quantiles of latent variables at which identification is sought. The conditions do not include the commonly required independence of latent variables and covariates. They include local versions of the classical rank and order conditions and local quantile insensitivity conditions. Values of structural derivatives are identified by functionals of quantile regression functions and can be estimated using the same functionals applied to estimated quantile regression functions.     

节能信息曝光度对绿色消费行为影响的实证分析——来自电商数据平台大规模文本数据的判据

随着中国绿色消费群体快速增长,绿色消费在拉动消费升级的同时体现出巨大的环境价值,节能信息曝光度对绿色消费行为的影响也引起学者关注。本文将数据驱动与模型驱动方法相结合,采用自然语言处理技术构建节能信息曝光度指标,采用倾向得分匹配与分位数回归对我国电商平台5,889种节能家电消费数据与评论数据进行实证研究。结果发现,我国现阶段电商平台整体节能信息曝光度不高,节能信息曝光度对节能家电销量的边际效应呈现单调上升趋势,信息冗余拐点尚未出现;同时,节能信息曝光度对不同销量规模节能家电产品的影响呈倒"U"型变化,其对中等销售规模的节能家电产品具有更大影响;最后,本文进一步验证了"平台效应"对于节能信息曝光度的调节作用,为基于大规模多源异构数据的绿色消费行为研究提供借鉴。     

Bayesian Quantile Impairment Threshold Benchmark Dose Estimation for Continuous Endpoints

Quantitative risk assessment often begins with an estimate of the exposure or dose associated with a particular risk level from which exposure levels posing low risk to populations can be extrapolated. For continuous exposures, this value, the benchmark dose, is often defined by a specified increase (or decrease) from the median or mean response at no exposure. This method of calculating the benchmark dose does not take into account the response distribution and, consequently, cannot be interpreted based upon probability statements of the target population. We investigate quantile regression as an alternative to the use of the median or mean regression. By defining the dose–response quantile relationship and an impairment threshold, we specify a benchmark dose as the dose associated with a specified probability that the population will have a response equal to or more extreme than the specified impairment threshold. In addition, in an effort to minimize model uncertainty, we use Bayesian monotonic semiparametric regression to define the exposure–response quantile relationship, which gives the model flexibility to estimate the quantal dose–response function. We describe this methodology and apply it to both epidemiology and toxicology data.