‘Globesity’? The effects of globalization on obesity and caloric intake

We examine the effect of globalization, in its economic and social dimensions, on obesity and caloric intake, namely the so –called ‘globesity’ hypothesis. Our results suggest a robust association between globalization and both obesity and caloric intake. A one standard deviation increase in globalization is associated with a 23.8 percent increase in obese population and a 4.3 percent rise in calorie intake. The effect remains statistically significant even after using an instrumental variable strategy to correct for some possible reverse causality and ommited variable bias, a lagged structure, and corrections for panel standard errors. However, we find that the primary driver (of the ‘globesity’ phenomenon) is the ‘social’ rather than the ‘economic’ dimension of globalization, and specifically the effect of changes in ‘information flows’ and ‘social proximity’ on obesity. A one standard deviation increase in social globalization increased the percentage of obese population by 13.7 percent.     

The local impact of typhoons on economic activity in China: A view from outer space

We examine the impact of typhoons on local economic activity in coastal China. To capture potential damages from an individual typhoon we use historical typhoon track data in conjunction with a detailed wind-field model. We then combine our damage proxy with satellite derived nightlight intensity data to construct a panel data set that allows us to estimate the impact of typhoons at a spatially highly disaggregated level (approx. 1 km). Our results show that typhoons have a negative and significant, but short-term, impact on local activity – a typhoon that is estimated to destroy 50% of the property reduces local economic activity by 20% for that year. Over our period of analysis (1992–2010) total net economic losses are estimated to be in the region of $US 28.34 billion. To assess the damage risk from future typhoons we use simulated probability distributions of typhoon occurrence and intensity and combine these with our estimated effects. Results suggest that expected annual losses are likely to be around $US 0.54 billion.     

应用型大学数学课程的研究与实践

数学是人类生活,劳动和学习中不可缺少的工具,但是我国高校的半数毕业生弄不清自己在大学中学习些高等数学课程到底有什么用,也不认为自己在将来的工作和生活中能够用到这些数学知识,而教育部在2012版课程目录指明了大学数学各个课程的开展最终是要达到能“实际应用”的这一目标,所以建设应用型大学数学课程体系就非常紧迫和必要了.本文结合在应用型人才培养这个核心目标就大学数学课程体系、教学方法、教学质量管理、实践环节建设等等进行了一些实践探索和小结.     

Upzoning and value capture: How U.S. local governments use land use regulation power to create and capture value from real estate developments

The public sector can harness its authority to control land uses to secure valuable public benefits from real estate developments. This paper investigates how five major U.S. cities—Boston, Chicago, New York, San Francisco, and Seattle—are using their land use regulation powers to create and capture value for the public benefit. An analysis of the zoning and entitlement processes of the 20 largest real estate development projects in each city reveals that value has been captured from all 100 projects. Furthermore, these cities implicitly differentiated value capture into two distinct components: value creation and value capture. Among the 100 projects, cities created value for 90 projects by allowing greater density and height—a practice often referred to as “upzoning.” Distinguishing such upzoning incidences from traditional land use exaction tools is important because the added value gives local governments greater legitimacy in asking for public benefits. The experience of the five cities further revealed that value capture strategies can be customized to adapt to unique regulatory, political, and cultural contexts. Lastly, despite the fact that the majority of the upzoned projects increased density and height through project-specific negotiations, none of the cities had clear standards or evaluation frameworks for determining: how much value was created, what can be asked for in return, and who should benefit from the value captured. Cross-national scholarship on value capture can be leveraged to address these important questions.     

Economic policy uncertainty and imitation behaviors of corporate social responsibility practices: Evidence from China

In this paper, we examine whether firms facing higher economic policy uncertainty (EPU) are more likely to show similar corporate social responsibility (CSR) practices compared with their peer firms. Drawing upon institutional theory, in response to uncertainty under complex circumstances, managers tend to imitate peer firms' strategic actions to acquire legitimacy. Consistent with our theoretical expectations, we find that EPU increases the likelihood that a focal firm will show CSR practices similar to its peer firms. Such a likelihood is amplified for firms that (1) bear more negative media coverage, (2) have higher industry competition intensity, (3) belong to heavy-polluting industries, and (4) for the first-time disclosures. Our results hold when we employ a series of endogeneity tests and robustness checks.     

Dependent relationships between Chinese commodity markets and the international financial market: Evidence from quantile time-frequency analysis

In this article, the quantile time–frequency method is utilized to study the dependence of Chinese commodities on the international financial market. The impacts of risk management and diversification benefits of different portfolios are examined by calculating the reduction in downside risk. Moreover, we estimate and compare Sharpe Ratios (SRs) and Generalized Sharpe Ratios (GSRs) based on the frequencies of the investigated portfolios. Our empirical results reveal a strong asymmetric response from Chinese commodity markets. Specifically, we find that gold is a safe-haven asset, and due to negative correlations found at lower quantiles in medium and long term, an increase in the USD index damages bull commodity markets but boosts bear conditions under long-term investments, and negative (positive) tail correlations with interest rates (IRs) in bull (bear) markets are observed. It is proven that WTI can decrease short-run risks while USD and GOLD are more efficient in the diversification of downside risk. Adding international commodities may not improve the returns of Chinese commodities at given risk levels in the short and medium term through SRs and GSRs. In brief, investors should consider these dependence structures and modes of risk management in terms of time and frequency.     

高速铁路站台雨棚运维管理系统可视化监测E-BIM应用研究

高速铁路站台雨棚结构监测是保证列车行车与旅客候车安全的重要环节。为提高站台雨棚的运维管理与监测效率,针对高速铁路站台雨棚运维管理系统可视化监测进行设计,建立高速铁路站台雨棚运维管理系统可视化监测实施流程。以广州局集团公司海南环岛高速铁路海口东站站台钢结构雨棚为依托,引入基于BIM技术的E-BIM结构进行可视化监测,开发适用于大跨度空站台雨棚运维管理系统的可视化监测模块,实现高速铁路站台雨棚的结构风险管控,确保高速铁路列车与旅客的安全。     

Price competition between green and non green products under corporate social responsible firm

This article deals with a newsvendor inventory model in light of green product marketing of corporate social responsible firms. In this model, comparison between green and non green marketing is analyzed including subsidy and tax implementation by Government where the Government offers higher subsidy and lower tax to the green producer unlike the lower subsidy and higher tax to the non green producer. There is also price contest between green and non green producer as the demands of the products are dependent on sales price, carbon emission and corporate social responsibility index. Assuming the cost and profit parameters, an expected profit function of the systems is formulated and maximized analytically. Finally, numerical examples are illustrated to justify the proposed model.     

劳动异质情况下的产业结构偏离及其影响因素分析——基于2006～2013年全国产业行业数据

本文充分考虑劳动异质性，利用产业人力资本结构，重新核算三次产业结构偏离度，发现第一产业和第三产业结构偏离程度均被高估，第二产业结构偏离被低估，进而指出“民工荒”、大学生就业难等现象产生的原因是第一产业可转出人力资本减少，第二产业需求旺盛，而第三产业由于发展不足陷入低水平均衡状态。最后通过系统的影响因素分析发现，解决我国结构偏离和就业问题的重点在于优化需求结构、合理规划产业发展路径以及全面推进城镇化和市场化进程，关键更在于释放农村消费市场巨大潜力和全面加快第三产业发展。     

Analysis of global marine oil trade based on automatic identification system (AIS) data

A fine-grained analysis framework of global marine oil trade based on AIS data is developed to address the existing problems of using statistical data to analyze oil trade without sufficient temporal and spatial resolution. The framework includes three modules: traffic route analysis, trade volume analysis, and trade network analysis. A ship cargo payload calculation (SCPC) model is proposed to take the draught, shape, and size of the vessel and seawater density into consideration. It calculates the oil trade volume of each oil tanker voyage as a unit. More than 3.4 billion global automatic identification system (AIS) records in 2017 are utilized to verify the proposed framework and achieve the following findings. The Middle East-Strait of Malacca-East Asia oil transport route is the busiest and largest trade volume route in the global marine oil trade. The oil trade volume of the world's top 20 oil-importing and oil-exporting countries calculated based on AIS data is strongly correlated to the Joint Organizations Data Initiative (JODI) statistics with the determination coefficient (R²) of 0.8798. More than 90% of the world's top 20 oil-importing and oil-exporting countries have more than five oil trading partners. The experimental results show that the proposed analysis framework has utilized the most minimal research object, every oil tanker's trajectory, to realize the fine-grained research of marine oil trade based on oil tanker flows analysis. The derived oil flows with directions and trade volumes provide the basis for constructing a directed weighted oil trade network.