Megachurch involvement at the local level: Examining conditions for church action in economic development

The roles of small congregations and their social impacts are well known, but few theoretical studies investigate megachurch congregations. These mammoth organizations have the potential for advancing social good, but minimal research specifically focuses on the activities of these congregations in economic development (ED). This study addresses this dearth of information by answering the following research questions: (a) In what ways are megachurches involved in ED activities? (b) Who benefits from these programs and how are the programs offered? and (c) What factors influence megachurches to offer ED activities? We frame our investigation using both demand‐ and supply‐side arguments from Frumkin's (2002) model of nonprofit and voluntary action. Online survey data and follow‐up interviews with 42 megachurch leaders in the Dallas/Fort Worth and greater Houston areas show that megachurches are implementing ED activities in alignment with demand‐side explanations, especially when advancing opportunities for the unemployed and underemployed. However, supply‐side arguments provide more explanatory power, indicating that volunteer engagement with ED activities plays a significant role in the provision of ED services through megachurches. Our study offers a better understanding of why megachurches carry out ED activities with considerable attention devoted to how megachurches partner with other congregations, nonprofits, and government entities to encourage economic growth and improve the economic well‐being of community members.     

复杂性科学及其在经济领域中的资助和研究进展

统计和分析了国家自然科学基金委员会(以下简称基金委) 管理科学部自 1986 年以来对复杂性科学及其在经济领域中相关研究的资助情况，同时，对复杂性科学及其与经济科学融合所产生的复杂经济学等研究进行了梳理，系统总结和分析了国内外相关研究的进展和发展趋势，以期为该领域的研究者提供参考和启示，促进复杂系统管理的研究，进而为管理科学部的十四五学科战略规划提供参考，为国家经济治理体系的完善等提供理论储备．     

Estimation of system reliability for exponential distributions based on L ranked set sampling

Abstract

In the case where strength and stress both follow exponential distributions, this paper considers the maximum likelihood estimator (MLE) of the system reliability based on L ranked set sampling (LRSS). The proposed MLE is shown to have existence, uniqueness and asymptotic normality, and its asymptotic variance is obtained by the Fisher information matrix of LRSS. The values of asymptotic relative efficiencies show that the proposed MLE is always more efficient than the MLE using simple random sampling (SRS). However, the MLE using LRSS cannot be written in closed form. Therefore, the modified MLE is proposed using the technique replaced some terms in the maximum likelihood equations by their expectations. The newly modified MLE using LRSS is shown to be superior to the MLE using SRS. Finally, the proposed method is applied to a real data set on metastatic renal carcinoma study.     

京津冀人口集聚对能源消费的影响

京津冀作为我国重要的人口集聚区,其区域发展面临严重的能源和环境问题。首先,基于STIRPAT模型构建京津冀面板数据模型,研究1990—2017年京津冀人口密度、经济增长、产业结构和环境规制对能源消费的影响。其次,采用SVAR模型通过脉冲响应函数和方差分解,研究京津冀人口密度变动对能源消费的作用机理和动态影响关系。结果显示,京津冀三地的人口密度、人均实际GDP与能源消费之间存在正向影响关系,其中河北省影响系数最大;北京和天津第三产业占比与能源消费之间存在反向影响关系,河北省第三产业占比对能源消费的影响不显著;北京和天津的环境规制对能源消费影响不显著,河北省环境规制对能源消费具有正向影响;京津冀地区和京冀两地人口密度变动对能源消费的影响在短期呈现负向效应,但是在中长期京津冀地区和三地人口密度变动对能源消费的影响均先上升然后缓慢下降,人口集聚具有集约用能效应。相对于能源消费自身影响而言,京津冀人口密度变动对能源消费的贡献相对较小,其影响效应有限。最后,对京津冀人口流动和能源消费一体化协同发展提出对策建议。     

Social investment effects of public education,health care,and welfare service expenditures on economic growth

The purpose of this study is to theoretically and empirically examine whether public spending in education, health care, and welfare service operates as a fruitful investment in welfare states, which has been implied in the literature of social investment arguments. Based on comprehensive review of existing literature, this study suggested a tripartite mechanism of social investment effect of such spending, that is “enhancement of human capital,” “support for labor force participation,” and “job creation.” To find the empirical evidence, a pooled time‐series cross‐section analysis was conducted with the data of 15 advanced welfare states from 1980 to 2015 using estimation technique of fixed‐effect model. The results confirmed that public spending in education, health care, and welfare service had a positive medium‐term as well as long‐term effect on economic performance, while cash‐type welfare spending had an obscure or no visible effect on economy. Government consumption that is a proxy and control variable of size of the welfare state showed a positive effect on real GDP in the medium term but a negative effect in the long run. In conclusion, this study suggests that reinforcing social services should be recognized and dealt with as essence of social investment strategy.     

Conditional time-dependent nonparametric estimators with an application to healthcare production function

ABSTRACT

By using the probabilistic framework of production efficiency, the paper develops time-dependent conditional efficiency estimators performing a non-parametric frontier analysis. Specifically, by applying both full and quantile (robust) time-dependent conditional estimators, it models the dynamic effect of health expenditure on countries’ technological change and technological catch-up levels. The results from the application reveal that the effect of per capita health expenditure on countries’ technological change and technological catch-up is nonlinear and is subject to countries’ specific income levels.     

基于效率视角的上市公司股权激励工具选择研究

本文运用2011-2016年发布股权激励计划的我国A股上市公司数据，从激励效率的角度，探讨公司规模、成长性及产权性质等异质性要素如何影响公司股权激励工具的选择。研究发现，公司规模能够显著影响股权激励工具的效率，大型上市公司更适合使用股票期权，而小型上市公司更适合使用限制性股票；且公司成长性越高，上述匹配关系对股权激励效率的影响越显著。对于国有上市公司，选择股票期权作为股权激励工具比限制性股票更具有激励效率。     

Considering economic stress and empathic traits in predicting prosocial behaviors among U.S. Latino adolescents

The goal of the current study was to examine two competing models focusing on the roles of empathy‐related traits in the relation between economic stress and prosocial behaviors. First, we examined the mediating roles of perspective taking and empathic concern in the association between economic stress and adolescents’ prosocial behaviors. Second, we examined the moderating role of perspective taking in the association between economic stress and empathic concern, as well as the links between empathic concern and prosocial behaviors. Participants consisted of 307 (46.2% girls; M age = 15.05) U.S. Latino adolescents (77.5% U.S. Mexicans) and their primary caregivers (87.9% mothers). Primary caregivers reported on family‐level economic stress, and adolescents reported on their own perspective taking, empathic concern, and their tendency to engage in six forms of prosocial behaviors. Results demonstrated support for the moderating role of perspective taking on the link between economic stress and empathic concern, which in turn, was associated with multiple forms of helping behaviors. Economic stress was also directly associated with selfless and selfish helping behaviors. The discussion focuses on the multiple roles of empathic traits in understanding the links between economic stress and prosocial outcomes in U.S. Latino youth.     

Development of an Asset Value Map for Disaster Risk Assessment in China by Spatial Disaggregation Using Ancillary Remote Sensing Data

The extent of economic losses due to a natural hazard and disaster depends largely on the spatial distribution of asset values in relation to the hazard intensity distribution within the affected area. Given that statistical data on asset value are collected by administrative units in China, generating spatially explicit asset exposure maps remains a key challenge for rapid postdisaster economic loss assessment. The goal of this study is to introduce a top‐down (or downscaling) approach to disaggregate administrative‐unit level asset value to grid‐cell level. To do so, finding the highly correlated “surrogate” indicators is the key. A combination of three data sets—nighttime light grid, LandScan population grid, and road density grid, is used as ancillary asset density distribution information for spatializing the asset value. As a result, a high spatial resolution asset value map of China for 2015 is generated. The spatial data set contains aggregated economic value at risk at 30 arc‐second spatial resolution. Accuracy of the spatial disaggregation reflects redistribution errors introduced by the disaggregation process as well as errors from the original ancillary data sets. The overall accuracy of the results proves to be promising. The example of using the developed disaggregated asset value map in exposure assessment of watersheds demonstrates that the data set offers immense analytical flexibility for overlay analysis according to the hazard extent. This product will help current efforts to analyze spatial characteristics of exposure and to uncover the contributions of both physical and social drivers of natural hazard and disaster across space and time.     

Evaluating and Visualizing the Economic Impact of Commercial Districts Due to an Electric Power Network Disruption

Critical infrastructure networks enable social behavior, economic productivity, and the way of life of communities. Disruptions to these cyber–physical–social networks highlight their importance. Recent disruptions caused by natural phenomena, including Hurricanes Harvey and Irma in 2017, have particularly demonstrated the importance of functioning electric power networks. Assessing the economic impact (EI) of electricity outages after a service disruption is a challenging task, particularly when interruption costs vary by the type of electric power use (e.g., residential, commercial, industrial). In contrast with most of the literature, this work proposes an approach to spatially evaluate EIs of disruptions to particular components of the electric power network, thus enabling resilience‐based preparedness planning from economic and community perspectives. Our contribution is a mix‐method approach that combines EI evaluation, component importance analysis, and GIS visualization for decision making. We integrate geographic information systems and an economic evaluation of sporadic electric power outages to provide a tool to assist with prioritizing restoration of power in commercial areas that have the largest impact. By making use of public data describing commercial market value, gross domestic product, and electric area distribution, this article proposes a method to evaluate the EI experienced by commercial districts. A geospatial visualization is presented to observe and compare the areas that are more vulnerable in terms of EI based on the areas covered by each distribution substation. Additionally, a heat map is developed to observe the behavior of disrupted substations to determine the important component exhibiting the highest EI. The proposed resilience analytics approach is applied to analyze outages of substations in the boroughs of New York City.