Predicting the geo-temporal variations of crime and disorder

Traditional police boundaries—precincts, patrol districts, etc.—often fail to reflect the true distribution of criminal activity and thus do little to assist in the optimal allocation of police resources. This paper introduces methods for crime incident forecasting by focusing upon geographical areas of concern that transcend traditional policing boundaries. The computerised procedure utilises a geographical crime incidence-scanning algorithm to identify clusters with relatively high levels of crime (hot spots). These clusters provide sufficient data for training artificial neural networks (ANNs) capable of modelling trends within them. The approach to ANN specification and estimation is enhanced by application of a novel and noteworthy approach, the Gamma test (GT).     

Analysing Materials and Energy Flows in an Industrial District using an Enterprise Input–Output Model

Recent approaches to sustainable development leave much room for policies at a local level. In fact, it is becoming evident that targets such as increasing resource productivity, preserving natural cycles, or extending the present level of welfare, are best pursued within the confines of a local area. In particular, environmental changes are best brought about by considering local systems of firms as cornerstones of cooperative strategies and using data on materials and energy use in physical terms. In this paper, an enterprise input–output model is developed for an industrial district, i.e. a local group of firms specialized in the production of a single final output. The model allows for a detailed quantitative analysis of materials and energy flows and the consequent generation of waste and pollution. As a planning tool, the model may be used to evaluate alternative scenarios, such as the possibility of re- using waste taking account of sustainability requirements. An empirical case study applies the model to an industrial district in Southern Italy producing leather sofas.     

The Multilevel Approach to Repeated Measures for Complete and Incomplete Data

Repeated measurements often are analyzed by multivariate analysis of variance (MANOVA). An alternative approach is provided by multilevel analysis, also called the hierarchical linear model (HLM), which makes use of random coefficient models. This paper is a tutorial which indicates that the HLM can be specified in many different ways, corresponding to different sets of assumptions about the covariance matrix of the repeated measurements. The possible assumptions range from the very restrictive compound symmetry model to the unrestricted multivariate model. Thus, the HLM can be used to steer a useful middle road between the two traditional methods for analyzing repeated measurements. Another important advantage of the multilevel approach to analyzing repeated measures is the fact that it can be easily used also if the data are incomplete. Thus it provides a way to achieve a fully multivariate analysis of repeated measures with incomplete data. This revised version was published online in June 2006 with corrections to the Cover Date.     

A comparative site evaluation study for relocating Japanese government agencies out of Tokyo

As a national project of Japan, plans for the relocation of several government agencies out of Tokyo have been ongoing. This paper is concerned with the problem of site selection for this project. The National Land Agency, the agency responsible for this project, has declared that the process of site selection should be rational, open to the public and easily understandable. In an effort to meet these requirements, we propose a consensus-making method for reaching a group decision, based on a combination of the analytic hierarchy process (AHP) and the Assurance Region model of data envelopment analysis (DEA). Several strategic uses of these methodologies, e.g., Delphi procedures, are also discussed. Based on these analyses, the “Wise Men” Committee for deciding the best site has chosen two from among ten contenders, one from the North-East and the other from the Central part of Japan, as candidates for the best relocation site. We could not discriminate between the two with respect to the multiple criteria chosen for evaluating sites. The Committee recommended the two sites to the Prime Minister at the end of December 1999. The Prime Minister reported this conclusion to the Diet. This topic is currently the focus of political discussions in the Diet. In this report, the authors summarize the decision-making processes that the Wise Men Committee followed, putting emphasis on the methodological aspects.     

IP电话系统中SNMP代理的实现

结合对简单网络管理协议（SNMP）的研究，分析了Agent 网管代理开发包，并介绍了利用Agnet 实现IP电话系统中SNMP代理的过程。     

Initial Public Offerings: CFO Perceptions

We examine four issues pertaining to initial public offerings (IPOs) using a survey of 438 chief financial officers (CFOs). First, why do firms go public? Second, is CFO sentiment stationary across bear and bull markets? Third, what concerns CFOs about going public? Fourth, do CFO perceptions correlate with returns? Results support funding for growth and liquidity as the primary reasons for IPOs. CFO sentiment is generally stationary in pre‐ and post‐bubble years. Managers are concerned with the direct costs of going public, such as underwriting fees, as well as indirect costs. We find a negative relation between a focus on immediate growth and long‐term abnormal returns.     

中国和新加坡产业内贸易与规模经济关系的协整分析

中国和新加坡产业内贸易与规模经济存在着一种长期的均衡关系,新加坡生产企业的规模经济对产业内贸易的推动作用大于中国,中国和新加坡生产企业的规模经济与产业内贸易存在单向因果关系,即规模经济促进产业内贸易.     

中国进口与经济增长关系的区域差异分析

利用面板数据对中国东、中、西部的进口额和GDP增长关系进行的实证研究。在短期内，GDP增长对进口额影响最小是中部地区，在长期，西部GDP增长对进口额影响最大。中国经济增长对拉动世界经济增长起了十分重要的作用，中国经济增长减速也会影响全球经济。     

试论我国证券投资基金稳定市场的功能

本文采用博弈分析方法 ,通过博弈模型 ,对虚假会计信息产生的条件、机制和影响因素等作了探讨。     

Environmental Valuation with Imperfect Information The Case of the Random Utility Model

This paper considers welfare analysis with therandom utility model (RUM) when perceptions ofenvironmental quality differ from objectivemeasures of environmental quality. Environmental quality is assumed to be anexperience good, so that while perceptions ofquality determine choices, ex postutility is determined by objective quality. Given this assumption, I derive a measure ofthe welfare impact of changes in environmentalquality, and I show how this new welfaremeasure differs from the traditional welfaremeasure developed by Hanemann (1982). This newwelfare measure provides an approach tomeasuring the value of information aboutenvironmental quality within the framework ofthe random utility model.