集群企业资源获取、吸收能力与技术创新绩效——珠三角传统产业集群中的企业研究

以珠三角传统产业集群中的企业为研究对象,从资源依赖理论出发,探索集群企业技术创新的影响因素和路径。构建了资源获取、吸收能力与技术创新绩效的概念模型,编制问卷,并使用结构方程模型对其进行检验。结果表明,企业的"软资源的获取"(信息、技术、人才)能够积极提高企业的潜在吸收能力,进而促进企业的模仿创新和率先创新。企业的"硬资源的获取"(资金)虽然可以提高企业的现实吸收能力,但对两种技术创新的作用都不显著。根据所得结论,从企业、政府、行业协会3个方面提出要构建良好的外部网络和发展环境,促进其资源获取从而提高企业的技术创新绩效。     

Optimal dynamic scale and structure of a multi-pollution economy

We analyze the optimal dynamic scale and structure of a two-sector-economy, where each sector produces one consumption good and one specific pollutant. Both pollutants accumulate at different rates to stocks which damage the natural environment. This acts as a dynamic driving force for the economy. Our analysis shows that along the optimal time path (i) the time scale of economic dynamics is mainly determined by the lifetime of pollutants, their instantaneous harmfulness and the discount rate; (ii) economic scale and structure, as well as resulting welfare, may be non-monotonic, and (iii) environmental damage may exhibit an inverted U-shape form. These results raise important questions about the optimal design of environmental policies in a multi-pollution economy. We suggest a system of dynamic Pigouvian emission taxes, each of which should be levied specifically on one particular pollutant. We show that the optimal time path of each tax level is determined by the characteristics not only of that particular pollutant but also of all other pollutants.     

Understanding supplier structural embeddedness: A social network perspective

Despite a significant amount of attention, the potential of supplier structural embeddedness (i.e., the value of the structural position in an extended network) to improve the performance of a buying firm remains poorly understood. This study drew on the social network theory to empirically examine a conceptual framework specifying a relationship between the efforts of a buying firm to understand supplier structural configuration and operational and financial performance. This study also examines how the comprehension of structural embeddedness is transformed into performance for a buying firm through relational embeddedness (i.e., the strength of a dyadic relationship). Survey data collected from companies in the U.S. were analyzed using hierarchical regression analysis. The results indicate that the understanding of the structural dimension does help to enhance operational performance of a buying firm, but it does not lead to better financial performance. Empirical evidence shows that a buying firm does improve the quality of a dyadic relationship between the buying firm and a supplier by understanding how the supplier is connected to other firms and what positional values are produced. Further, relational embeddedness is found to mediate the influence of the enhanced understanding of the structural configuration on operational performance.     

审视新结构经济学:一个多维视角

要素禀赋论又被称为要素比例理论,被誉为国际贸易理论的一大柱石. 新结构经济学以要素禀赋理论为基础,将一国的产业结构变迁归因于要素禀赋结构的变化.本文的分析表明:新结构经济学忽视了某些重要的历史因素和现实因素;如果按照新结构经济学的建议来制定一国的发展战略,企业在要素使用结构上将会高度一致,从而可能导致一国经济在面临外部冲击时产生巨大波动.     

Kernel-type estimators for the distortion risk premiums of heavy-tailed distributions

A new kernel-type estimator for the distortion risk premiums of heavy-tailed losses is introduced. Using a least-squares approach, a bias-reduced version of this estimator is proposed. Under suitable assumptions, the asymptotic normality of the given estimators is established. A small simulation study, to illustrate the performance of our method, is carried out.     

建立我国贸易调整援助制度的构想

随着我国加快融入全球贸易自由化的进程,日趋激烈的进口竞争致使国内相关产业的安全问题越来越突出,所以我国需要制定新的贸易制度以有效应对因进口贸易自由化而产生的产业损害和结构调整问题。作为制度选择之一,美国贸易调整援助制度给我国带来了重要的经验启示,某些具体规则对构建符合国情的TAA制度具有重要的借鉴价值。在当下加快产业结构调整的背景下,构建我国TAA制度不仅是必要的,而且是可行的。因此,必须对该制度的几个基础性、根本性的问题进行深入研究,从立法定位、立法目标、基本原则与立法模式的角度提出制度设计的基本设想。     

自适应约束下的双边全变差正则化超分辨率重建

在经典的双边全变差(BTV)超分辨率重建中,加权系数和正则化参数的恒定性导致重建结果边缘保持能力受限。为此,提出了一种自适应约束的BTV正则化先验模型。算法首先定义了图像的局部邻域残差均值以区分当前像素属于平坦区域还是边缘区域;然后针对加权系数的不变性导致边缘削弱的问题,利用边缘方向和垂直边缘方向扩散性的不同,设计自适应权重矩阵;最后根据代价函数的极值问题推导出迭代公式,从而进行图像的超分辨率重建,重建过程中采用自适应的方法确定正则化参数,以便求得代价函数的全局最优解,提高了算法的鲁棒性。实验结果表明：与双三次线性插值法和经典BTV算法相比,该算法取得了更好的视觉效果和更高的峰值信噪比,更多地保留了图像的边缘细节信息。     

We share; we connect: how shared brand consumption influences relational brand connections

This research examines how married consumers form relational brand connections. Findings from two studies contribute to research on identity‐related brand consumption by showcasing how shared brand consumption and marital satisfaction influence relational brand connections and the perceived importance of the brand to the marital relationship. This research has important theoretical contributions and managerial implications. From a theoretical perspective, the authors show how consumers incorporate brands into their interpersonal relationships through shared brand consumption and that relational brand connections influence brand‐related outcomes, such as brand attitudes, purchase intentions, brand affect, and brand separation distress. From a managerial perspective, the findings highlight the importance of considering relational aspects of brand consumption when designing branding strategy and advertising appeals.     

Playing the synthesizer with Canadian data: Adding polls to a structural forecasting model

Election forecasting has become a fixture of election campaigns in a number of democracies. Structural modeling, the major approach to forecasting election results, relies on ‘fundamental’ economic and political variables to predict the incumbent’s vote share usually a few months in advance. Some political scientists contend that adding vote intention polls to these models—i.e., synthesizing ‘fundamental’ variables and polling information—can lead to important accuracy gains. In this paper, we look at the efficiency of different model specifications in predicting the Canadian federal elections from 1953 to 2015. We find that vote intention polls only allow modest accuracy gains late in the campaign. With this backdrop in mind, we then use different model specifications to make ex ante forecasts of the 2019 federal election. Our findings have a number of important implications for the forecasting discipline in Canada as they address the benefits of combining polls and ‘fundamental’ variables to predict election results; the efficiency of varying lag structures; and the issue of translating votes into seats.     

Do monetary subjective well-being evaluations vary across space? Comparing continuous and discrete spatial heterogeneity

Using subjective well-being estimations, this study analyzes whether compensating variations vary across space using a cross-sectional data set from Chile. To achieve this goal, it describes and compares two econometric ways of modelling unobserved spatial heterogeneity. Both approaches allow compensating variations to vary across spatial units by assuming some distribution a priori. One method assumes that the spatial heterogeneity can be represented by a discrete distribution (a group of regions that share the same coefficient) and the other that the preferences can be represented by a continuous distribution (each region has a different coefficient). The results show that focusing just on the average estimates of compensating variations, as the applied studies have done so far, masks useful local variation. More empirical studies are needed to assess the advantages and disadvantages of both econometric approaches and how their results compare across a wide range of conditions and samples.