Data-based mechanistic modelling and forecasting globally averaged surface temperature

The main objective of this paper it to model the dynamic relationship between global averaged measures of Total Radiative Forcing (RTF) and surface temperature, measured by the Global Temperature Anomaly (GTA), and then use this model to forecast the GTA. The analysis utilizes the Data-Based Mechanistic (DBM) approach to the modelling and forecasting where, in this application, the unobserved component model includes a novel hybrid Box-Jenkins stochastic model in which the relationship between RTF and GTA is based on a continuous time transfer function (differential equation) model. This model then provides the basis for short term, inter-annual to decadal, forecasting of the GTA, using a transfer function form of the Kalman Filter, which produces a good prediction of the ‘pause’ or ‘levelling’ in the temperature rise over the period 2000 to 2011. This derives in part from the effects of a quasi-periodic component that is modelled and forecast by a Dynamic Harmonic Regression (DHR) relationship and is shown to be correlated with the Atlantic Multidecadal Oscillation (AMO) index.     

Does the presence of professional football cause crime in a city? Evidence from Pontiac,Michigan

Using daily panel data from Detroit, we empirically explore the relationship between the National Football League (NFL) and crime in a city. We exploit the natural experiment of the Detroit Lions’ move from Pontiac, Michigan, to downtown Detroit in 2002. Pontiac is used as the treatment city and non-game day crime, other suburban cities, and other cities outside Detroit MSA are used as the comparison groups. Employing a difference-in-difference approach, we find decreases in assaults and vandalism on home game days in Pontiac relative to the control cities after the Lions’ move. We find weak evidence of a net decrease in larceny and vandalism in Pontiac on home game days following the loss of professional football. No changes in assaults and auto theft are reported. While not conclusive, our results suggest that professional football leads to additional larceny and vandalism incidents but no effects on assaults and auto theft.     

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.     

Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities

Artificial intelligence (AI) has captured substantial interest from a wide array of marketing scholars in recent years. Our research contributes to this emerging domain by examining AI technologies in marketing via a global lens. Specifically, our lens focuses on three levels of analysis: country, company, and consumer. Our country-level analysis emphasizes the heterogeneity in economic inequality across countries due to the considerable economic resources necessary for AI adoption. Our company-level analysis focuses on glocalization because while the hardware that underlies these technologies may be global in nature, their application necessitates adaptation to local cultures. Our consumer-level analysis examines consumer ethics and privacy concerns, as AI technologies often collect, store and process a cornucopia of personal data across our globe. Through the prism of these three lenses, we focus on two important dimensions of AI technologies in marketing: (1) human–machine interaction and (2) automated analysis of text, audio, images, and video. We then explore the interaction between these two key dimensions of AI across our three-part global lens to develop a set of research questions for future marketing scholarship in this increasingly important domain.     

我国“一带一路”沿线地区风险投资时空分布及影响因素研究

深入分析我国“一带一路”沿线地区风险投资时空格局及影响因素，有助于促进创新创业与企业发展、提高区域科技创新水平。运用空间分析方法和空间计量模型，对2003-2018年我国“一带一路”沿线139个城市风险投资的时空分布特征及影响因素进行分析，结果表明：①沿线地区的风险投资发展具有不均衡性，呈现为沿海高、西部低的分异格局；②风险投资的全局自相关系数均为正，呈现出明显的空间集聚特征；③风险投资机构数、国家高新区数量、风险投资退出、政府引导基金发展、财政科技支出对区域风险投资具有显著促进作用，环境污染对风险投资有一定抑制作用。随着ESG投资理念逐渐获得认可，沿线地区可以通过提升绿色发展水平促进风险投资发展。     

跨越竞争丛林与范式重构：全球治理改革进程中的疫苗产业创新治理

疫苗作为新冠疫情防控的最关键手段之一，已在各国抗疫中发挥积极影响。疫苗研发、生产、注射意愿以及全球分配的公平性与可及性等一系列问题日益受到世界关注。分析全球治理改革中，疫苗作为一种全球公共产品的创新治理问题，讨论疫苗产业发展特征与创新规律演化，剖析西方国家疫苗产业创新治理困境以及“竞争丛林”逻辑，阐释中国行动方案及对全球治理改革的贡献。最终提出疫苗产业创新治理机制对推动全球治理改革的政策含义。     

Cross-border exchanges and volatility forecasting

We test for the performance of a series of volatility forecasting models (GARCH 1,1; EGARCH 1,1; CGARCH) in the context of several indices from the two oldest cross-border exchanges (Euronext; OMX). Our findings overall indicate that the EGARCH (1,1) model outperforms the other two, both before and after the outbreak of the global financial crisis. Controlling for the presence of feedback traders, the accuracy of the EGARCH (1,1) model is not affected, something further confirmed for both the pre and post crisis periods. Overall, ARCH effects can be found in the Euronext and OMX indices, with our results further indicating the presence of significant positive feedback trading in several of our tests.     

The saving–investment correlation puzzle is still a puzzle

A number of simulation studies claim to have solved the Feldstein–Horioka puzzle by demonstrating that a high time-series correlation between saving and investment naturally arises from business cycle shocks. This paper uses panel data of saving and investment controlled for business cycle shocks to empirically test the significance of cyclical shocks — productivity, fiscal and the terms of trade shocks — in explaining a high saving–investment correlation. The estimation results reveal that conventional aggregate shocks only partially explain the high saving–investment correlation. Moreover, country differences in the size of the GNP and the non-traded sector do not significantly affect the saving–investment correlation. The saving–investment correlation puzzle remains a puzzle after all.     

“一带一路”框架下的中拉绿色产品贸易:特征、比较优势与出口潜力

在“双循环”背景下,加强“一带一路”建设对中国深化对外开放意义重大,促进中拉绿色贸易符合双方利益,可为“一带一路”延伸至拉美创造新的合作增长点。本文使用2002年至2018年的货物贸易数据,分析了中拉共建“一带一路”过程中中拉绿色产品贸易的特征和趋势,并重点研究了中国绿色产品对拉美的出口潜力。通过使用双边显示性比较优势指数和出口潜力矩阵,文章发现,在现有的中拉货物贸易结构中,绿色产品贸易所占比重较低,贸易对象高度集中,但随着双方经贸合作的全面深化、特别是“一带一路”延伸至拉美,双边绿色产品贸易金额和种类都在稳定上升。尽管中国绿色产品在拉美市场面临着地理距离遥远、市场竞争激烈等客观困难,但中国的优势产品已成功出口到拉美。中国的出口潜力更多地取决于拉美地区的市场需求,一旦拉美对绿色产品的需求提升,那么中国就具备进一步扩大向拉美出口该类产品的潜力。此外,出口潜力矩阵也找出了部分对拉美市场而言具备不可替代性的中国产品,这也将成为中国潜在的对拉出口重点绿色产品。     

现行财务会计报告模式改进的探讨

随着信息技术的发展,现行财务会计报告模式正面临严峻挑战。如何建立适应经济发展和时代要求的财务会计报告模式已成为会计探讨的热点问题。本文从通用财务会计报告模式的分析入手,探讨了理想财务会计报告模式的设想和网络环境下以通用财务会计报告模式为基础,建立交互式按需报告模式的思路和联合按需报告模式的发展方向,旨在通过网络手段改进现行的财务会计报告模式,不断适应和满足信息使用者的需求。