Forecasting U.S. money growth using economic uncertainty measures and regularisation techniques

This paper examines the out-of-sample forecasting properties of six different economic uncertainty variables for the growth of the real M2 and real M4 Divisia money series for the U.S. using monthly data. The core contention is that information on economic uncertainty improves the forecasting accuracy. We estimate vector autoregressive models using the iterated rolling-window forecasting scheme, in combination with modern regularisation techniques from the field of machine learning. Applying the Hansen-Lunde-Nason model confidence set approach under two different loss functions reveals strong evidence that uncertainty variables that are related to financial markets, the state of the macroeconomy or economic policy provide additional informational content when forecasting monetary dynamics. The use of regularisation techniques improves the forecast accuracy substantially.     

中国货币国际化的趋势预测与人民币的范式选择

货币国际化是一个动态的历史过程。通过对其历史进程的考察,可以清晰地对未来货币国际化进程加以预测。文章认为,中国的人民币国际化进程刚刚起步,但却面临与以往世界货币迥异的道路、环境和结构,迫切需要走出一条符合中国国情的货币国际化道路。     

广西中期工业化纵深发展的战略思考

2011年,广西经济总量突破万亿,进入中期工业化阶段。接下来广西应该走怎样的工业化道路,是需要认真思考的问题。文章通过构建TCI指数,指出广西目前的重型化工业道路是一条不能实现经济可持续发展的道路。广西的工业发展需要走一条最优工业化道路,即按照广西的要素禀赋结构,选择最优工业技术水平,使企业具有自生能力,以最快的速度实现资本积累、技术进步和产业升级。     

Perceptions of determinants of job selection in the hospitality and tourism industry: The case of Korean university students

ABSTRACT

This study explores the key factors influencing potential employees in the hospitality and tourism industry and examines whether causal relationships between behavioral attitudes, subjective norms, and perceived behavioral control influence students' job selection. The study suggests that the career decision-making process is related to job selection. A total of 307 responses were analyzed. The results explain individual students' attitudes toward a behavior and perceived behavioral control in the context of their job selection. Attitudes toward a behavior and job selection had significant effects on career decisions. On the other hand, opinions of significant others had no significant effect. Perceived behaviors required to decide on jobs had a significant effect on job selection intentions. Students with internship experience were likely to form positive attitudes toward the hospitality and tourism industry, suggesting internships to be a useful source of a stronger relationship between the industry and job aptitudes of students in hospitality and tourism programs. The results have important implications.     

GIS as a tool for selection of sample areas in a travel behaviour survey

Whilst Geographical Information Systems (GIS) are now used more commonly in transport research and modelling, GIS techniques were used in this study to select similar sample areas (in terms of geography and census attributes) for data collection. For this purpose, a GIS mapping system for Tyne and Wear, UK, was built. The system included topographic maps of the area, boundary maps of Lower Super Output Areas (LSOA), and aggregated census statistics datasets for LSOAs. Criteria relating to census attributes and the nature of transport were employed to identify ‘hotspots’ by GIS enquiry to provide suitably matching areas, which then formed the basis of the sampling frame.The research project was concerned with commuters’ travel choices and so the study needed to identify commuters. In this case-study context, it is not possible to select fully homogeneous areas, so the GIS ‘hotspots’ approach allowed the identification of areas where there were a high concentration of commuters with multiple alternatives for travel to work. A pilot study showed that the GIS origin-based approach was good in collecting a balanced sample, as compared to an employment-based destination survey. This paper explores the benefits and costs of these origin- and destination-based approaches. In the origin-based home sample, households with paper-based surveys were targeted after identification by GIS. This origin approach requires more data preparation compared to the alternative of an employer-based, destination-based sample that could use online survey methodologies.The paper concludes by identifying GIS as an important tool in selecting a sample area for data collection using multiple criteria, but argues that plans for data collection need to be flexibly constructed to overcome unexpected challenges. Although this paper focuses on a transport research case study, the methodology presented can be applied to survey design and selection of sample areas in other disciplines.     

IT外包的投资、再谈判机制分析

本文从IT承包商(vendor)和客户(client)的角度考虑去设计最优契约。由于客户方的需要,或者是由于契约的不完全性导致契约经常需要再谈判,而且由于契约修改后的执行问题也可能引起法律诉讼,因此对于如何决定事前的投资、谈判利润分配和契约诉讼的赔偿都是一系列要解决的问题,本文正是根据这些问题的提出而逐步展开的。     

A decision method for supplier selection in multi-service outsourcing

Although supplier selection in multi-service outsourcing is a very important decision problem, research concerning this issue is still relatively scarce. This paper proposes a decision method for selecting a pool of suppliers for the provision of different service process/product elements. It pioneers the use of collaborative utility between partner firms for supplier selection. A multi-objective model is built to select desired suppliers. This model is proved to be NP-hard, so we develop a multi-objective algorithm based on Tabu search for solving it. We then use an example to show the applicability of the proposed model and algorithm. Extensive computational experiments are also conducted to further test the performance of the proposed algorithm.     

A weighted max-min model for fuzzy multi-objective supplier selection in a supply chain

Supplier selection is one of the most important activities of purchasing departments. This importance is increased even more by new strategies in a supply chain. Supplier selection is a multi-criteria decision making problem in which criteria have different relative importance. In practice, for supplier selection problems, many input information are not known precisely. The fuzzy set theories can be employed due to the presence of vagueness and imprecision of information. A weighted max-min fuzzy model is developed to handle effectively the vagueness of input data and different weights of criteria in this problem. Due to this model, the achievement level of objective functions matches the relative importance of the objective functions. In this paper, an analytic hierarchy process (AHP) is used to determine the weights of criteria. The proposed model can help the decision maker (DM) to find out the appropriate order to each supplier, and allows the purchasing manager(s) to manage supply chain performance on cost, quality and service. The model is explained by an illustrative example.