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).     

Estimating the Size of a Criminal Population from Police Records Using the Truncated Poisson Regression Model

The truncated Poisson regression model is used to arrive at point and interval estimates of the size of two offender populations, i.e. drunk drivers and persons who illegally possess firearms. The dependent capture–recapture variables are constructed from Dutch police records and are counts of individual arrests for both violations. The population size estimates are derived assuming that each count is a realization of a Poisson distribution, and that the Poisson parameters are related to covariates through the truncated Poisson regression model. These assumptions are discussed in detail, and the tenability of the second assumption is assessed by evaluating the marginal residuals and performing tests on overdispersion. For the firearms example, the second assumption seems to hold well, but for the drunk drivers example there is some overdispersion. It is concluded that the method is useful, provided it is used with care.     

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.     

Multiple Imputation in Multivariate Problems When the Imputation and Analysis Models Differ

Bayesian multiple imputation (MI) has become a highly useful paradigm for handling missing values in many settings. In this paper, I compare Bayesian MI with other methods – maximum likelihood, in particular—and point out some of its unique features. One key aspect of MI, the separation of the imputation phase from the analysis phase, can be advantageous in settings where the models underlying the two phases do not agree.     

Measurement error and panel data1

The underidentification of linear models with measurement error does not necessarily extend to panel data models, as has been shown by GAiliches and Hausman (1986). We discuss and extend some of their results for a simple case and address particular issues concerning identification and asymptotic variances.     

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.     

Trades and Quotes: A Bivariate Point Process

This article formulates a bivariate point process to jointlyanalyze trade and quote arrivals. In microstructure models,trades may reveal private information that is then incorporatedinto new price quotes. This article examines the speed of thisinformation flow and the circumstances that govern it. A jointlikelihood function for trade and quote arrivals is specifiedin a way that recognizes that an intervening trade sometimescensors the time between a trade and the subsequent quote. Modelsof trades and quotes are estimated for eight stocks using Tradeand Quote database (TAQ) data. The essential finding for thearrival of price quotes is that information flow variables,such as high trade arrival rates, large volume per trade, andwide bid–ask spreads, all predict more rapid price revisions.This means prices respond more quickly to trades when informationis flowing so that the price impacts of trades and ultimatelythe volatility of prices are high in such circumstances.     

Costs of financial instability, household-sector balance sheets and consumption

Extant work on costs of financial instability focuses on fiscal costs and declines in aggregate GDP following banking crises. We estimate effects of banking and currency crises on consumption in 19 OECD countries, showing consumption plays an important role in the adjustment following a crisis, and effects are not captured solely by the impact of crises on standard consumption determinants, income and wealth. Additional effects, attributable to factors such as time-varying confidence, uncertainty and credit rationing, are aggravated by high and rising leverage, despite financial liberalisation easing liquidity constraints. High leverage implies that banking crises taking place now could have greater incidence than in the past.     

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。