Strategic Internet application trends in supply chain management

The Internet is evolving as a powerful force in the new marketplace where the nexus of competition has changed from individual firms to efficient supply chain networks both between firms and within industries. This study explores Internet adoption patterns and operational applications in US supply chain networks. The data reveal that the integration of the Internet into supply chain management applications has increased and has moved away from indiscriminate application of novel Internet technologies towards becoming a focused endeavor with precise expectations and measurable goals. Specifically, the study finds that Internet usage within supply chains is maturing as evidenced by enhanced and increased productivity, reduced costs and increased profit for participating firms.     

Efficiency in the provision of social care for older people. A three-stage Data Envelopment Analysis using self-reported quality of life

Using a three-stage data envelopment analysis approach, this paper explores efficiency in the provision of social care for older people in 148 English Councils in 2009/10. Departing from D'Amico and Fernández (2012) [31] our measure of efficiency is inscribed within the production of welfare framework and based on self-reported quality of life of recipients of the services. Our results indicate a high level of efficiency, but once we control for the effects of a number of environmental variables, we found that more stringent eligibility criteria and higher assessment costs are negatively associated with the efficiency in the provision of social services.     

我国居民杠杆率现状及影响因素研究

近年来,我国居民部门杠杆率的快速上升引起社会各界关注。本文使用货币信贷和城镇储户调查数据,对我国居民部门杠杆率和偿债能力现状进行了分析,并运用各省住户贷款数据计算各省的居民杠杆率,使用面板数据模型对居民杠杆率上升的原因进行了实证分析。结果表明,房价的快速上涨和住房销售的增长都对居民部门杠杆率的上升有显著正向影响,其中房价上涨的影响程度更大。此外,金融发展水平和老年人抚养比对居民杠杆率有正向影响,少年人抚养比对居民杠杆率有负向影响。     

数据的要素化过程及其与传统产业数字化的融合机制研究

从生产过程和价值创造来看,数据具备了传统生产要素所具备的功能,但又具有区别于传统生产要素的新特征。数据作为一种新型生产要素,对于数字产业化的高速发展和传统产业数字化进程的深入推进,具有关键作用。数据要素的形成和发展一方面需要与数字产业化、产业数字化融合发展进程相适应;另一方面,数据要素的形成过程本身又是与传统产业数字化进程的一个深度技术融合过程。因而,多样化和异质性的数据要素,其实质乃是数字技术与传统产业专用性技术融合的结果,其间的融合机制表现为深化、促进和多元性。     

Determinants of time varying co-movements among international stock markets during crisis and non-crisis periods

In this paper, we use the DCC MIDAS approach to assess the validity of the wake-up call hypothesis for developed and emerging markets during the global financial crisis (GFC). We use this approach to decompose the total correlations into short- (daily) and long-run (quarterly) correlations for the period from 1999 to 2011. We then examine the transmission mechanisms by regressing the quarterly economic, financial, and behavioral variables on the quarterly DCC–MIDAS correlations. We find that country specific factors are crisis contingent transmission mechanisms for the co-movements of emerging country pairs and mixed pairs of advanced and emerging countries during the global financial crisis. However, we do not observe wake-up calls in the transmission of the crisis among advanced country pairs. The classification of the transmission mechanisms for crisis and non-crisis periods with the different country pairs has important implications for crisis management as well as for portfolio investment strategies. Thus, our findings contribute to the discussion on the role and effectiveness of the international financial architecture.     

Why you should care about the Target data breach

Data breaches are becoming more frequent and more damaging to the bottom line of many businesses. The Target data breach marked the beginning of increased scrutiny of cybersecurity practices. In the past, data breaches were seen as a cost of doing business, but Target's negligence and the scale of the data loss forced businesses and the courts to reevaluate current practices and regulatory frameworks. Businesses must make strategic use of their chief information officers, adopt cybersecurity best practices, and effectively train their employees to respond to growing security threats. They must also shape the cybersecurity narrative to influence regulatory responses to these threats.     

农村减贫效率及其空间差异研究——基于DEA-ESDA模型的分析

[目的]通过对2011~2015年间全国以及各区域层面的农村减贫效率进行测度,探讨其空间差异及变化特征。[方法]文章采用投入导向的DEA-BCC模型测算农村减贫效率值,并借助探索性数据分析法(ESDA)对农村减贫效率的空间差异和变化展开分析。[结果](1)我国农村减贫综合技术效率相对较低,未能充分挖掘现有资源投入的潜力,纯技术效率整体偏小是造成综合技术效率较低的重要原因;(2)省际农村减贫效率在2011~2015年整体呈现出先减后增的趋势,并表现出西高东低的阶梯形空间布局;(3)农村减贫的综合技术效率存在正自相关性,高高聚集的区域主要集中在西部地区,低低聚集区域呈现由东北向京津都市区移转的趋势;(4)减贫综合技术效率的热点区域主要集中在西北与西南两大区域,且具有较强的稳定性;冷点区域主要分布在江西、安徽及东部沿海地区,较为稳定的冷点区域主要集中在东北及环渤海地区。[结论]我国农村减贫效率存在显著的空间异质性的特征,需要精准地识别出局部性致贫因素,因地制宜地制定出具有区域联动特点的空间扶贫开发策略。     

The impacts of risk-taking behaviour and competition on technical efficiency: Evidence from the Chinese banking industry

This paper tests the impact of risk and competition on efficiency in the Chinese banking industry over the period 2003–2013. Comprehensive types of risk-taking behaviour are considered including credit risk, liquidity risk, capital risk, and insolvency risk. Competition is measured by the Lerner index. The results are cross-checked using an alternative econometric technique as well as an alternative competition indicator. The findings show that the technical and pure technical efficiencies of Chinese commercial banks are significantly and negatively affected by liquidity risk. They further show that greater competition precedes declines in technical and pure technical efficiencies of Chinese commercial banks. The results suggest that Chinese bank efficiency is significantly affected by bank diversification, banking sector development, stock market development, inflation and GDP growth rate. The findings also indicate that, compared to state-owned commercial banks, joint-stock commercial banks and city commercial banks have lower technical and pure technical efficiencies.     

On estimating long-run effects in models with lagged dependent variables

A common procedure in economics is to estimate long-run effects from models with lagged dependent variables. For example, macro panel studies frequently are concerned with estimating the long-run impacts of fiscal policy, international aid, or foreign investment.Our analysis points out the hazards of this practice. We use Monte Carlo experiments to demonstrate that estimating long-run impacts from dynamic models produces unreliable results.Biases can be substantial, sample ranges very wide, and hypothesis tests can be rendered useless in realistic data environments. There are three reasons for this poor performance. First, OLS estimates of the coefficient of a lagged dependent variable are downwardly biased in finite samples. Second, small biases in the estimate of the lagged, dependent variable coefficient are magnified in the calculation of long-run effects. And third, and perhaps most importantly, the statistical distribution associated with estimates of the LRP is complicated, heavy-tailed, and difficult to use for hypothesis testing. While many of the underlying problems have been long-known in the literature, the continued widespread use of the associated empirical procedures suggests that researchers are unaware of the extent and severity of the estimation problems. This study aims to illustrate their practical importance for applied research.