Factor allocation,economic growth and unbalanced regional development in China

On the basis of development accounting techniques and a factor misallocation framework, we use panel data of 30 Chinese provinces from 2000 to 2013 to assess how factor allocation affects economic growth and unbalanced regional development in China. In particular, we decompose economic growth into three parts, namely sector productivity (SP ), factor market efficiency (FME ) and factor endowment (FE ). We then conduct counterfactual analyses to investigate the short and long‐run roles of factor allocation in the income distribution across provinces. The results show that SP , FME and FE can explain 23%, 8.5% and 68.5% of economic growth, while labour, capital and energy reallocation account for aggregate productivity growth of about 47%, −4.8% and −0.1%. Furthermore, when the factors are efficiently allocated, transferring labour (capital, energy) from agriculture (service, industry) to the other sectors will increase the income per capita by 29.5% and 42.5% in the short and long term. Meanwhile, efficient factor allocation accounts for 32% and 29.7% of aggregate productivity and reduces the income variation across provinces by 25.5% and 23% in the short and long run, respectively.     

On the need to compensate the compensating variation in CGE modeling

The message of this research is that in the standard calibrated setting of Computational General Equilibrium (CGE) models, the welfare measures typically used to compare benchmark with counterfactuals are numéraire dependent. This evaluation bias affects the compensating variation and the Konüs index of cost of living. We show that the equivalent variation is neutral regarding the choice of value units in calibrated models but would be affected as well in uncalibrated CGE models. We illustrate with a simple example and propose an even simpler theoretical solution to overcome these biases; all that is required to have correct welfare estimates is to compensate normalizing with a suitable price index. This type of correction is necessary to overcome the sometimes blind implementation of welfare measures in numerical general equilibrium analysis. We show that the induced quantitative errors may be substantial providing biased welfare estimates and misleading results.     

Exploring Value‐Based Management Sophistication: The Role of Potential Economic Benefits and Institutional Influence

The complexity of value‐based management (VBM) is often not captured in empirical research. In particular, potential differences in the extent of VBM implementation are not considered. Firms are predominantly classified dichotomously into either VBM “adopters” or “non‐adopters.” In this study, we aim to fill this gap by introducing a framework to assess differences in the extent of VBM implementation (VBM‐sophistication) based on publicly available data. This approach enables us to study determinants of VBM‐sophistication based on a hand‐collected data set comprising 2,683 firm‐year observations from 16 European countries between 2005 and 2014. Specifically, we investigate (i) whether potential economic benefits associated with VBM implementation lead to a higher level of VBM‐sophistication, and (ii) if this relation is influenced by extra‐organizational institutions (e.g., industry norms). Our results indicate that companies exhibit higher VBM‐sophistication if certain firm characteristics that increase the potential economic benefits of VBM are present. Moreover, our study provides evidence that this effect is enhanced by extra‐organizational institutions that pressure and support firms in realizing the potential benefits of higher VBM‐sophistication.     

Operational risk quantified with spectral risk measures: a refined closed-form approximation

The quantification of operational risk has become an important issue as a result of the new capital charges required by the Basel Capital Accord (Basel II) to cover the potential losses of this type of risk. In this paper, we investigate second-order approximation of operational risk quantified with spectral risk measures (OpSRMs) within the theory of second-order regular variation (2RV) and second-order subexponentiality. The result shows that asymptotically two cases (the fast convergence case and the slow convergence) arise depending on the range of the second-order parameter. We also show that the second-order approximation under 2RV is asymptotically equivalent to the slow convergence case. A number of Monte Carlo simulations for a range of empirically relevant frequency and severity distributions are employed to illustrate the performance of our second-order results. The simulation results indicate that our second-order approximations tend to reduce the estimation errors to a great degree, especially for the fast convergence case, and are able to capture the sub-extremal behavior of OpSRMs better than the first-order approximation. Our asymptotic results have implications for the regulation of financial institutions, and may provide further insights into the measurement and management of operational risk.     

Conditional risk measures in a bipartite market structure

In this paper, we study the effect of network structure between agents and objects on measures for systemic risk. We model the influence of sharing large exogeneous losses to the financial or (re)insurance market by a bipartite graph. Using Pareto-tailed losses and multivariate regular variation, we obtain asymptotic results for conditional risk measures based on the Value-at-Risk and the Conditional Tail Expectation. These results allow us to assess the influence of an individual institution on the systemic or market risk and vice versa through a collection of conditional risk measures. For large markets, Poisson approximations of the relevant constants are provided. Differences of the conditional risk measures for an underlying homogeneous and inhomogeneous random graph are illustrated by simulations.     

利用相位差变化趋势的多源信号关联

针对多源信号关联难度大、关联准确率低的问题，利用同一目标平台上搭载的多个辐射源信号具有一致的动态变化趋势这一特点，提出一种利用相位差特征的多源信号关联方法。已知阵列形式和侦测点位置，通过对侦收到的多个辐射源信号进行处理，获取相位差信息并累积形成相位差变化趋势；对比提取疑似相似段，根据相似性判决策略进行有效关联。该方法能有效避免不同传感器对位置测量的误差影响，相比传统基于位置信息关联的方法，能有效提升关联准确率。仿真和实测数据分析证明了该方法的有效性，在阵列形式和侦测点位置已知的条件下该方法具有重要工程意义。     

四川省水稻产投特征变迁及技术进步对单产的影响

[目的]了解四川水稻产投特征和技术进步对单产的影响,促进水稻可持续生产。[方法]分析了改革开放以来四川省水稻产投特征和技术特征变动,并基于索洛余值法测算了1980~2015年四川省科技进步对水稻单产的贡献情况。[结果](1)全省水稻单产水平及物质与服务费用投入均呈现波动增长趋势,人工投入逐年递减,但人工成本在生产成本中的比重较大;(2)四川省水稻品种选育、栽培管理技术、推广技术、稻作经营方式和农业政策不断变迁,更适应当前以普通家庭生产和新型经营主体共同发展的局面对技术的需求;(3)整体来看,近36年技术进步对四川省水稻单产水平提高的贡献率较低,生产经营较为粗放;(4)分时期看,2005年前,技术进步对全省水稻单产水平提高的贡献率较高,但之后尤其是近5年,技术进步并未对水稻单产水平提高产生影响,要素投入是水稻单产水平提升的主要因素。[结论]提出了加强科技研发及投入水平、"一主多元"联合推广、生产管理技术培训和丘区节本增效生产的政策建议。     

山东省耕地后备资源变化及驱动因素分析

[目的]揭示耕地后备资源变化规律及其驱动因素是进行耕地后备资源合理保护、开发利用的重要基础,但目前对于耕地后备资源变化及驱动因素的研究较为匮乏。[方法]文章以山东省为例,基于2003年和2015年两期耕地后备资源数据库,在分析耕地后备资源时空变化的基础上,采用空间回归模型分析了其变化的驱动因素。[结果]2003~2015年期间,山东省集中连片耕地后备资源减少了30.81万hm~2,其中可开垦土地减少24.97万hm~2,可复垦土地减少5.84万hm~2。[结论]总人口、文盲率、农民人均纯收入、建设用地扩张速度、第一产业产值占总产值比重等是山东省耕地后备资源变化的显著性驱动因素,并且总人口和建设用地扩张的驱动作用最大,受教育程度和产业结构调整的作用次之,农民人均纯收入变化对耕地后备资源变化的影响最小。"宏观统筹协调,异地代补"是解决"耕地后备资源空间分布不均衡、供需不匹配",实现耕地占补平衡、高效合理的开发利用耕地后备资源的必经之路。但异地代补的数量比例和质量应严格控制,并注重对补充耕地地区的经济补偿和政策倾斜,逐步缩小与发达地区之间的差距。     

时间压力对网络冲动性购买的影响研究：交易效用和感知风险的调节

以往关于时间压力对冲动性购买影响的研究结论具有两面性，即促进或抑制。文章引入交易效用和感知风险两个调节变量，通过两个实验探讨了时间压力对网络冲动性购买倾向影响的边界条件。首先，当交易效用较高时，时间压力的增加会导致其网络冲动性购买倾向的提高；而当交易效用较低时，时间压力的增加会导致其网络冲动性购买倾向的降低（实验一）。其次，当人们感知风险较低时，时间压力的增加会导致其网络冲动性购买倾向的提高；而当人们感知风险较高时，时间压力的增加会导致其网络冲动性购买倾向的降低（实验二）。研究结论可以帮助电商企业进一步了解消费者的冲动性购买行为，充分利用时间压力的影响，制定更灵活有效的促销策略。