Short-term forecasting of crime

The major question investigated is whether it is possible to accurately forecast selected crimes 1 month ahead in small areas, such as police precincts. In a case study of Pittsburgh, PA, we contrast the forecast accuracy of univariate time series models with naïve methods commonly used by police. A major result, expected for the small-scale data of this problem, is that average crime count by precinct is the major determinant of forecast accuracy. A fixed-effects regression model of absolute percent forecast error shows that such counts need to be on the order of 30 or more to achieve accuracy of 20% absolute forecast error or less. A second major result is that practically any model-based forecasting approach is vastly more accurate than current police practices. Holt exponential smoothing with monthly seasonality estimated using city-wide data is the most accurate forecast model for precinct-level crime series.     

Modelling and predicting recorded property crime trends in England and Wales—a retrospective

In 1999 the Home Office published, for the first time ever, 3-year ahead projections of property crime in England and Wales. The projections covered the period 1999–2001 and indicated strong upward pressure after five full years of falling crime. This pressure was generated by three factors: the number of young men in the general population, the state of the economy and the fact that property crime appeared to be well below its underlying trend level. The projections received a mixed response, with some agreeing that crime was set to rise while questioning the scale of any increase, to others who doubted the value of this type of econometric modelling. In fact, property crime did increase in 1999, although not at the rate suggested by the models—and indeed levels of burglary continued to fall. This paper addresses some of the reasons for this disparity as well as considering various criticisms of the Home Office approach.     

Criminal incident prediction using a point-pattern-based density model

Law enforcement agencies need crime forecasts to support their tactical operations; namely, predicted crime locations for next week based on data from the previous week. Current practice simply assumes that spatial clusters of crimes or “hot spots” observed in the previous week will persist to the next week. This paper introduces a multivariate prediction model for hot spots that relates the features in an area to the predicted occurrence of crimes through the preference structure of criminals. We use a point-pattern-based transition density model for space–time event prediction that relies on criminal preference discovery as observed in the features chosen for past crimes. The resultant model outperforms the current practices, as demonstrated statistically by an application to breaking and entering incidents in Richmond, VA.     

基于灰色神经网络的咸宁市财政收入预测研究

在介绍灰色神经网络模型原理的基础上,以湖北省咸宁市为例,利用灰色神经网络模型预测出2011-2014年咸宁市财政收入,由于灰色神经网络模型考虑了多指标的共同作用,具有更好的预测效果。     

The effect of home-ownership on labor mobility in the Netherlands

In various macro-studies, home-ownership is found to hamper job mobility and to increase unemployment. This paper addresses similar issues, but uses a micro-econometric framework where both individual job mobility, as well as the probability of being homeowner are modeled simultaneously. Using a panel of individual labor and housing market histories for the period 1989–1998, we estimate a nonparametric model of both job durations and home-ownership. We do not find homeowners to change less from jobs than tenants. Instead, our results suggest that the housing decision is driven by job commitment, and not the reverse. We do however find homeowners to be less vulnerable to unemployment.     

Just-in-time inventory systems innovation and the predictability of earnings

Firms that adopt just-in-time (JIT) inventory practices do so in order to realize cost savings and improve product quality, but an unexpected benefit to such firms could be a more predictable earnings stream. We examine the relationship between implementation of just-in-time inventory practices and the predictability of future quarterly earnings for a matched-pair sample of 82 firms, half of which have publicly announced that they have adopted JIT inventory practices. We find that one- and four-step-ahead forecasts of quarterly earnings, using either a Brown–Rozeff [Journal of Accounting Research (1979) 179–189] ARIMA or a seasonal random walk expectation model, are more accurate for the firms that have adopted JIT.     

Diagnostics for evaluating the value and rationality of economic forecasts

A number of studies have sought to determine whether economic forecasts had predictive value. These analyses used a single statistical methodology based on the independence of the actual and predicted changes. This paper questions whether the observed results are robust if alternative statistical methodologies are used to analyze this question. Procedures suggested by Cumby and Modest as well as rationality tests were applied to two data sets. Sometimes the conclusions differ depending on the procedures that are used. The results yield a guideline for the diagnostics that should be employed in testing for the value of economic forecasts.     

Airport expansions and property values: the case of Chicago O'Hare Airport

The paper adds to the empirical literature by providing up-to-date estimates of the effect of airport noise on property values around one of the world's busiest airports, Chicago O'Hare. The results indicate that home values were about 9% lower within a 65 dB noise contour band of O'Hare in 1997. Opponents of airport expansions argue that increased noise will reduce property values and lower tax bases. The results of this paper suggest that aircraft are becoming so much quieter that the airport can be expanded without causing a drop in local property values or tax bases. Estimates suggest that house prices may rise by as much as $284.6 million in the densely populated area around O'Hare after a new runway is added to the airport.     

Forecasting the New York State economy: The coincident and leading indicators approach

Currently there are no reliable summary indicators of the economic and fiscal condition of states and localities. This deficiency has hampered the efforts of policy makers at the sub-national level to monitor changes in the economic environment and predict how those changes will impact the fiscal health of governments. This paper attempts to fill this analytical vacuum by providing summary indicators of economic and fiscal health for New York State. The models developed are based on the single-index methodology developed by Stock and Watson [(1991). A probability model of the coincident economic indicators. In K. Lahiri and G. H. Moore (eds.), Leading economic indicators: new approaches and forecasting records (pp. 63–85). New York: Cambridge University Press]. This approach allows us to date New York business cycles and compare local cyclical behavior with the nation as a whole. We develop a leading index of economic indicators which predicts future movements in the coincident indicator. The Stock and Watson approach is used to create a fiscal indicator which acts as a summary indicator of revenue performance for New York. In addition, we explore the ability of our economic indicator series to predict future changes in state revenues. We find that changes in the leading indicator series have significant predictive power in forecasting changes in our revenue index.     

The competitiveness of nations and implications for human development

Human development should be the ultimate objective of human activity, its aim being healthier, longer, and fuller lives. Thus, if the competitiveness of a nation is properly managed, enhanced human welfare should be the key expected consequence. The research described here explores the relationship between the competitiveness of a nation and its implications for human development. For this purpose, 45 countries were evaluated initially using data envelopment analysis. In this stage, global competitiveness indicators were taken as input variables with human development index indicators as output variables. Subsequently, an artificial neural network analysis was conducted to identify those factors having the greatest impact on efficiency scores.     

Predicting economic contractions and expansions with the aid of professional forecasts

Traditional econometric models of economic contractions typically perform poorly in forecasting exercises. This criticism is also frequently levelled at professional forecast probabilities of contractions. This paper addresses the problem of incorporating the entire distribution of professional forecasts into an econometric model for forecasting contractions and expansions. A new augmented probit approach is proposed, involving the transformation of the distribution of professional forecasts into a ‘professional forecast’ prior for the economic data underlying the probit model. Since the object of interest is the relationship between the distribution of professional forecasts and the probit model’s economic-data dependent parameters, the solution avoids criticisms levelled at the accuracy of professional forecast based point estimates of contractions. An application to US real GDP data shows that the model yields significant forecast improvements relative to alternative approaches.     

2001-2011年江西省生态足迹分析及预测

本文利用生态足迹模型、相关分析以及灰色预测模型对江西省的生态足迹进行分析。结果表明:2011年江西省的人均生态足迹比2001年增加了68.05%,为2.2366hm2/人;生态足迹与GDP、城镇化、居民消费水平及人口的相关系数均在0.94以上;预测得2012年江西人均GDP生态足迹为3659.247hm2,2019年为1798.4273hm2,即未来江西发展的不可持续状态将逐步得到改善。     

Mixture of MLP-experts for trend forecasting of time series: A case study of the Tehran stock exchange

A new method for forecasting the trend of time series, based on mixture of MLP experts, is presented. In this paper, three neural network combining methods and an Adaptive Network-Based Fuzzy Inference System (ANFIS) are applied to trend forecasting in the Tehran stock exchange. There are two experiments in this study. In experiment I, the time series data are the Kharg petrochemical company’s daily closing prices on the Tehran stock exchange. In this case study, which considers different schemes for forecasting the trend of the time series, the recognition rates are 75.97%, 77.13% and 81.64% for stacked generalization, modified stacked generalization and ANFIS, respectively. Using the mixture of MLP experts (ME) scheme, the recognition rate is strongly increased to 86.35%. A gain and loss analysis is also used, showing the relative forecasting success of the ME method with and without rejection criteria, compared to a simple buy and hold approach. In experiment II, the time series data are the daily closing prices of 37 companies on the Tehran stock exchange. This experiment is conducted to verify the results of experiment I and to show the efficiency of the ME method compared to stacked generalization, modified stacked generalization and ANFIS.     

HIS系统药品动态流动和结构的研究

药品动态流动是医院计算机管理中的一个重要组成部分,合理设置药品流动的动态管理既可以方便医院的自主使用．又可以避免软件开发人员频繁地改动程序。针对医院管理系统中药品动态流动的问题,应用集中参数表方式设定药品动态流动结构的思想和基表结构．解决了药品动态流动中的问题,效果良好。     

城市物流需求供给研究

对物流需求进行分析的同时,构建了较为全面的物流需求指标体系,同时利用多种预测方法对各个指标进行了动态预测,最后建立了物流需求供给匹配模型。     

Intra-metropolitan shifts in labor demand and the adjustment of local markets

I offer new evidence on the adjustment of local labor markets to geographic shifts in labor demand within US metropolitan areas using a unique data set in which metropolitan subregions are geographically matched across the 1970–1980 and 1980–1990 decades. The evidence uncovered paints the following picture. Workers, especially those with less education, make incomplete adjustments within metropolitan areas in response to intra-metropolitan demand shifts. Although blacks may not make especially limited adjustments, they have disproportionately suffered deleterious effects from job movements because the demand shifts have tended to be away from their places of residence.     

市级工业与信息化委员会政务信息系统总体分析

建立政务信息系统、推行电子政务是市级工业与信息化委员会改善服务企业质量、提高行政效率的必然选择。文章从系统用户、网络结构、业务需求、非性能需求和性能需求等方面对市级工业与信息化委员会政务信息系统作了总体分析。     

一种汽车坐椅试验分析系统的研制

文章结合国家的强制性标准、国家的产业政策及广西汽车坐椅工业的现状,研制出一种较为完善、较为先进的汽车坐椅试验分析系统。该系统由机械台架、液压加载系统、测量控制系统和计算机监控系统等组成,将坐椅强度、头枕冲击、安全带固定点强度等试验功能有机结合。     

《管理信息系统》课程教学问题探讨与对策

对《管理信息系统》课程教学问题进行了探讨,鉴于案例分析教学法能普遍提升教学的效果,特提出加强案例分析教学法来进行授课,并据此提出了相应的对策。