基于AHP-TOPSIS模型的京津冀家政服务人力资源供给质量评价研究

依托已有的研究成果构建了家政服务人力资源供给质量评价指标体系,利用AHP-TOPSIS模型对京津冀家政服务人力资源供给质量进行了评价和排名,并使用障碍度模型分析了员工制、准员工制、培训学校、中介制四种类型家政机构人力资源供给质量的关键制约因素,在此基础上,给出了不同类型家政机构人力资源供给质量改善的针对性建议,为家政服务人力资源供给质量的改善提供参考依据。     

Does local government competition aggravate haze pollution? A new perspective of factor market distortion

Haze pollution has become a new threat to China's sustainable development, but it may be that local government behaviour can play an important role in the prevention and control of pollutants. A dynamic spatial autoregressive (SAR) model is used to study the relationship between local government competition and haze pollution. To further explore the indirect impact of factor market distortion on haze pollution and control potential endogeneity problems, a newly developed intermediary effect model that incorporates the characteristics of the generalized method of moments (GMM) is utilized to explore how factor market distortion indirectly affects haze pollution. The research results show that regional haze pollution in China is characterized by significant spatial correlation, and local government competition has a positive impact on haze pollution; that is, local government competition exacerbates haze pollution. In general, local government competition not only directly leads to an increase in haze pollution but also further intensifies it by distorting the local factor market, and the intermediary role of factor market distortion is approximately 7.04%. The results of the regional inspection found that competition among local governments in the eastern region did not lead to haze pollution, and distortion of the factor market did not exist as an intermediary effect. However, both direct and intermediary effects are significant in the central and western regions. Therefore, an official performance appraisal system that includes ecological constraints should be established to guide the benign transformation of local government competition, and an environmental management mechanism must be developed for joint prevention and control to reduce haze pollution. In addition, the free flow of factors and marketization are equally important.     

The impacts of value chain upgrading on the export of processed food

Upgrading in global value chains (GVCs) is an important path for developing countries to move along to capture higher benefits. Several qualitative studies of GVCs have identified two main upgrading types: economic (product, process, functional, and inter-sectoral) and social upgrading. The upgrading concept is widespread in productive sectors such as processed food, which has become a key export for developing countries. However, they have confronted multiple product standards required by global buyers. This study uses a case study of Thailand’s processed food exports (TPFEs). Although Thailand is a leading exporter of processed food, the country needs to upgrade in many areas related to production to meet global product standards and requirements. If Thailand fails to comply with global product standards, it will lose its export competitiveness. This study uses a gravity model to evaluate the impact of economic and social upgrading (EUP and SUP) on TPFEs. Our results show that upgrading types are significant in TPFEs, particularly for exports to developed countries. Process upgrading has a negative impact on TPFEs because of increased production costs to comply with product standards. However, process upgrading can lead to increased producers’ and exporters’ knowledge about how to comply with international standards. Consequently, process upgrading exhibits a lagged positive effect on TPFEs.     

老龄化与碳排放：消费效应还是生产效应？——基于2002-2017年中国省级面板数据的实证研究

人口老龄化是经济增长的一大阻碍,它对碳排放的影响是做出环境政策抉择的关键因素.以中国2002—2017年的省级面板数据为研究样本,从理论与实证两个层面分析人口老龄化与碳排放的关系及影响机制.一方面,构建包含碳排放的世代交叠模型(overlapping generations,OLG),发现老龄化主要通过消费效应和生产效应两个路径对碳排放产生影响;另一方面,从实证层面发现老龄化与碳排放之间存在倒"U"形关系,而且消费效应在人口老龄化与碳排放的关系中起到部分中介作用,生产效应的影响则不显著.     

Bitcoin price and its marginal cost of production: support for a fundamental value

This study back-tests a marginal cost of production model proposed to value the digital currency Bitcoin. Results from both conventional regression and vector autoregression (VAR) models show that the marginal cost of production plays an important role in explaining Bitcoin prices, challenging recent allegations that Bitcoins are essentially worthless. Even with markets pricing Bitcoin in the thousands of dollars each, the valuation model seems robust. The data show that a price bubble that began in the Fall of 2017 resolved itself in early 2018, converging with the marginal cost model. This suggests that while bubbles may appear in the Bitcoin market, prices will tend to this bound and not collapse to zero.     

Macroeconomic consequences of state fragility in sub‐Saharan Africa

Are poor macroeconomic outcomes primarily the result of economic policies, or of deeper underlying state fragility problems in sub‐Saharan Africa? We attempt to answer this question by using carefully specified dynamic panel regression techniques to show how state fragility conditions help to explain the differences in the macroeconomic performance of sub‐Saharan African economies, and to identify the most plausible mechanisms of transmission. We find that countries with greater fragility suffer higher macroeconomic volatility and crisis; they also experience weaker growth. When we disaggregate state fragility into its various components, we find that it is the security and social components that have the strongest causal impact on macroeconomic outcomes, while the political component is, at best, weak. Therefore, we conclude that it is state fragility conditions, and not necessarily macroeconomic policies, that are of first‐order importance in explaining the differences in macroeconomic performance for African countries. The knock‐on effects are mostly mediated through the fiscal channel, the aid channel, and the finance channel. Accordingly, we recommend that interventions in fragile states should best focus on exploiting the potential for using fiscal policy, aid, and finance as instruments to improve macroeconomic outcomes in sub‐Saharan Africa.     

互联网下高校外卖物流配送的现状与发展

随着互联网的快速发展,我国的手机愈发成为一部掌上电脑,通过手机进行外卖订餐已经成为现代高校大学生的日常状态,外卖的物流配送大大改变了学生的生活饮食方式。但是高校周围的外卖物流配送也容易导致很多问题,影响大学生的生活。针对高校外卖的特殊性,文章以互联网下逐渐形成的O2O模式来研究高校外卖物流配送的现状与发展,并且针对存在的问题提出相关建议。     

A truly global crisis? Evidence from contagion dependence across international REIT markets

This study examines the global nature of the recent crisis under bivariate Markov-switching models for pre- and post-crisis periods using the breakpoint of August 9, 2007. It quantifies international synchronization of boom-bust regime switches to investigate contagion-type dynamic comovements of Real Estate Investment Trusts (REITs). Global REIT markets display persistent bust regimes from September 2008 to May 2009, whereas the regime-switching patterns are not significant in the pre-crisis period. The results provide new evidence for global REIT contagion phenomena and suggest greater difficulties in diversifying risks across global REIT markets during the post-crisis period.     

EMPIRICAL PERFORMANCE OF GARCH MODELS WITH HEAVY‐TAILED INNOVATIONS

We introduce a new type of heavy‐tailed distribution, the normal reciprocal inverse Gaussian distribution (NRIG), to the GARCH and Glosten‐Jagannathan‐Runkle (1993) GARCH models, and compare its empirical performance with two other popular types of heavy‐tailed distribution, the Student's t distribution and the normal inverse Gaussian distribution (NIG), using a variety of asset return series. Our results illustrate that there is no overwhelmingly dominant distribution in fitting the data under the GARCH framework, although the NRIG distribution performs slightly better than the other two types of distribution. For market indexes series, it is important to introduce both GJR‐terms and the NRIG distribution to improve the models’ performance, but it is ambiguous for individual stock prices series. Our results also show the GJR‐GARCH NRIG model has practical advantages in quantitative risk management. Finally, the convergence of numerical solutions in maximum‐likelihood estimation of GARCH and GJR‐GARCH models with the three types of heavy‐tailed distribution is investigated.     

Covariance breakdowns and connectedness of crude oil futures markets with non-synchronous data

ABSTRACT

This article identifies the breakdowns in the covariance of three benchmark crude oil futures markets (WTI, Brent and Dubai) and investigates the changes of market connectedness across the breakdown periods. As the crude oil futures are traded in different regions, this article eliminates the non-synchronous trading data by employing the Vector Moving Average structure and the Bayesian data augmentation approach, which keeps the integrity of original data without changing its properties. The results show that there are significant breaks in the covariance structure of crude oil futures markets. The breakdown periods are consistent with the periods when the market volatilities are at high level and the returns are volatile. The changes of market connectedness are independent of the covariance states, which supports the globalization hypothesis for the crude oil market. The results also suggest that there is more information flow out of the WTI than to the WTI during the sample period, particularly during the breakdown periods in 2008–2009.