Financial components of FDI and choice of capital structure: an analysis for 30 OECD countries

Even though the choice of capital structure depends on the three different financial components of foreign direct investment (FDI), previous research has regarded FDI as unidimensional rather than multidimensional. This study addresses new findings in the FDI area and investigates the relevant determinants of capital structure in 30 OECD countries from 2006 to 2014 within the framework of a simultaneous equation model. Our primary findings reveal that each component has its own deterministic features driven by relevant policy variables and risks in the market. While an increase or decrease in equity capital shows the ability of the host country to attract new investments, the subsequent components are mostly used to adjust the equity capital investment exposure.     

How to overcome the implementation gap in ecosystem services? A user-friendly and inclusive tool for improved urban management

One of the main issues with the concept of ecosystem services is its absence on the ground in concrete operational decision-making contexts; that is, an implementation gap. In this study, we investigated if this gap could be overcome through the use of open-source data and free tools, and the adoption of a short-term participatory process. We tested these methods in the context of a project in the urban metropolitan area of Bordeaux (Communauté urbaine de Bordeaux: CUB) in France. The ecosystem services were defined using a participatory approach involving local stakeholders, and then selected scenarios were simulated to test the impact of various development or conservation plans. The study addressed three main questions: (1) Is it possible to adopt a simple methodological approach that overcomes the implementation gap through the development of a user-friendly and inclusive method? (2) What is the added value of a participatory approach? (3) With regards to four scenarios in this territory, what are the ES trends in the selected biophysical and monetary indicators, and will knowledge of these trends help planners to shape a sustainable trajectory for the territory?     

Deciphering big data in consumer credit evaluation

This paper examines the impact of large-scale alternative data on predicting consumer delinquency. Using a proprietary double-blinded test from a traditional lender, we find that the big data credit score predicts an individual’s likelihood of defaulting on a loan with 18.4% greater accuracy than the lender’s internal score. Moreover, the impact of the big data credit score is more significant when evaluating borrowers without public credit records. We also provide evidence that big data have the potential to correct financial misreporting.     

Performance assessment of ensemble learning systems in financial data classification

Financial data classification plays an important role in investment and banking industry with the purpose to control default risk, improve cash and select the best customers. Ensemble learning and classification systems are becoming gradually more applied to classify financial data where outputs from different classification systems are combined. The objective of this research is to assess the relative performance of existing state‐of‐the‐art ensemble learning and classification systems with applications to corporate bankruptcy prediction and credit scoring. The considered ensemble systems include AdaBoost, LogitBoost, RUSBoost, subspace, and bagging ensemble system. The experimental results from three datasets: one is composed of quantitative attributes, one encompasses qualitative data, and another one combines both quantitative and qualitative attributes. By using ten‐fold cross‐validation method, the experimental results show that AdaBoost is effective in terms of low classification error, limited complexity, and short time processing of the data. In addition, the experimental results show that ensemble classification systems outperform existing models that were recently validated on the same databases. Therefore, ensemble classification system can be employed to increase the reliability and consistency of financial data classification task.     

Food scandals,media attention and habit persistence among desensitised meat consumers

Consumer reactions to food scandals and their resulting economic implication are well documented. However, studies have typically neglected the roles that consumption habits and media usage behaviours may play in explaining household’s response to food safety incidences. In this study we develop a model of heterogeneous media usage intensity, information impacts and decay over time to estimate household’s behavioural responses to the 2011 German Dioxin scandal. We are specifically interested in determining the degree of heterogeneity in household’s short-term adjustments demand patterns versus persisting long-term consumption habits of meat products (chicken and pork) directly affected by the incident. The empirical analysis employs detailed household-level retail scanner and media usage data collected by the GfK Consumer Scan panel for a total of 16,023 households over a period of 104 calendar weeks. Results of dynamic correlated random effect Tobit models indicate an important role of unobserved heterogeneity in explaining household responses during the food scandal. We find strong empirical evidence supporting our hypothesis that short-term marginal adjustments in demand and propensity to buy affected products triggered by the negative impact of household media exposure were over-compensated by habit persistence. The question of how consumption patterns evolve over time in the presence of food scandals is expected to be of interest for both policy makers and the food industry. The potential biases in the projection of economic impacts resulting from simplifying assumptions of household’s response patterns to a proliferating numbers of food safety incidences has implications for risk management and public policy.     

Investigating the Impact of Income on Savings Using a Chinese Household Level Dataset

This article uses the China Household Financial Survey (CHFS) to examine the savings behavior of Chinese Households. Using a standard cross-sectional empirical approach to modeling permanent and transitory income, we show that one way of explaining the relative high savings rate in China is by recognizing that in fast growing economies, individuals may have higher transitory income from which they save a large proportion. The estimation also contains a range of household specific variables which can be used to understand the impact of socio-economic characteristics such as urban vs rural dwelling, age, and the educational level.     

试论大数据技术在生态环境保护领域的应用架构及相关技术

促进大数据在生态环境保护领域的深化应用,可以提高生态环境监管能力,并实现环境管理工作精细化。实践中需要把握生态环境信息化的大数据需求,对其应用架构及相关技术进行深入探究,以从多维度出发挖掘有价值的信息,更好地服务生态环境保护工作。     

Trade-off relationship between modern agriculture and biodiversity: Heavy consolidation work has a long-term negative impact on plant species diversity

Human-driven land-use changes often cause a decline in biodiversity. Although traditional agricultural practices maintained biodiversity at high levels, recent land-use changes may have negative consequences on species composition. In this study, we examined the hypothesis that land consolidation, which is a major recent land-use change in agricultural areas, decreases plant species diversity over the long term (the so-called negative legacy). To test this hypothesis, we examined the relationships between consolidated areas and the occurrence of threatened plant species across Japan and at the prefecture scale. Twenty-three threatened plant species were selected, all of which were formerly common. Our results show that areas containing records of threatened plant species rarely experienced consolidation at whole-country and prefectural scales. Breakdown analysis showed that unconsolidated agricultural areas contained significantly more threatened species than consolidated agricultural areas. These results suggest that threatened plant species require unconsolidated agricultural areas (i.e., these species could not grow in consolidated areas). Thus, we propose that consolidation history could be used as an indicator of the potential for biodiversity recovery. We also suggest that consolidated agricultural areas should be used for food production rather than for the restoration of biodiversity, for reasons of cost efficiency.     

工程资料在工程建设中的重要性研究

企业如果想要在质量上"更上一层楼",就必须对于工程资料予以足够重视。本文以工程资料的作用为切入点,详细论述了其在信息查询、项目监管、项目信息、项目成果以及项目后期建设的作用和意义。     

The significance of digital data systems for smart city policy

Our planet is gradually moving towards an urbanized world. Modern urban agglomerations tend to turn nowadays into advanced information hubs supporting a smart management of dynamic urban systems. The currently popular notion of ‘smart cities’ aims to provide a new perspective for sustainable and high-performance strategies of city stakeholders in our ‘urban century’. In this context, digital information technology provides a new tool for efficient and effective management and planning of urban space, inter alia in the field of transportation, environment, public facilities or advanced service provision to citizens. This paper aims to offer, first, a concise overview of the emerging opportunities of information and communication technology (ICT) for smart urban policy; digital technology in particular, appears to provide novel pathways for modern planning strategies in smart cities. Against this background, the paper sketches out the complex force field of global urbanisation phenomena and highlights the data and information needs for strategic planning of cities (using inter alia as a framework the so-called ‘urban piazza’ strategy framework). Secondly, various new decision support tools that are currently emerging and that offer a new promising scope for handling complex urban management issues (for instance, on accessibility, congestion, safety or sustainability) are briefly presented. And finally, the potential of such digital data systems for urban management and policy is concisely illustrated by means of some recent applications in the area of smartphone data systems. The paper concludes with a discussion of the challenges ahead for urban policy, inter alia by paying attention to institutional and governance aspects of ‘big digital data’ management in urban systems.