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.     

Inferential Causal Models: Integrating Quality & Quantity

In-depth data analysis plus statistical modeling can produce inferentialcausal models. Their creation thus combines aspects of analysis by close inspection,that is, reason analysis and cross-tabular analysis, with statistical analysis procedures,especially those that are special cases of the generalized linear model (McCullaghand Nelder, 1989; Agresti, 1996; Lindsey, 1997). This paper explores some of the roots of this combined method and suggests some new directions. An exercise clarifies some limitations of classic reason analysis by showing how the cross tabulation of variables with controls for test factors may produce better inferences. Then, given the cross tabulation of several variables, by explicating Coleman effect parameters, logistic regressions, and Poisson log-linear models, it shows how generalized linear models provide appropriate measures of effects and tests of statistical significance. Finally, to address a weakness of reason analysis, a case-control design is proposed and an example is developed.     

COMPUTABLE GENERAL EQUILIBRIUM MODELS FOR DEVELOPMENT POLICY ANALYSIS IN LDCs

Abstract. The use of CGE models has gained much popularity among policy analysts in LDCs and there is a fast growing body of literature on this area of economics. In this survey, the advantages of general equilibrium approach over partial equilibrium approach in analysing a wide range of policy issues are highlighted. The evolution of CGE modelling is discussed and more than 60 CGE applications related to different policy issues in LDCs are surveyed. This comprehensive survey shows that the CGE models have become quite popular analytical tools among policy analysts in LDCs over the last decade or so. The debate in the economic profession regarding the value and appropriateness of using CGE models for policy analysis is examined in the final section of this paper. Some of the criticisms levelled at CGE models are discussed and it is argued that despite this criticism such models are capable of providing insight into important policy problems.     

A Nonstandard Approach to Option Pricing

Nonstandard probability theory and stochastic analysis, as developed by Loeb, Anderson, and Keisler, has the attractive feature that it allows one to exploit combinatorial aspects of a well-understood discrete theory in a continuous setting. We illustrate this with an example taken from financial economics: a nonstandard construction of the well-known Black-Scholes option pricing model allows us to view the resulting object at the same time as both (the hyperfinite version of) the binomial Cox-Ross-Rubinstein model (that is, a hyperfinite geometric random walk) and the continuous model introduced by Black and Scholes (a geometric Brownian motion). Nonstandard methods provide a means of moving freely back and forth between the discrete and continuous points of view. This enables us to give an elementary derivation of the Black-Scholes option pricing formula from the corresponding formula for the binomial model. We also devise an intuitive but rigorous method for constructing self-financing hedge portfolios for various contingent claims, again using the explicit constructions available in the hyperfinite binomial model, to give the portfolio appropriate to the Black-Scholes model. Thus, nonstandard analysis provides a rigorous basis for the economists' intuitive notion that the Black-Scholes model contains a built-in version of the Cox-Ross-Rubinstein model.     

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.     

仓储诊断分析研究

通过对仓储运作的调查诊断，来定义仓储操作中拥有广泛基础的可持续发展的优先管理权。以让每个企业能更方便的发现自身仓储操作中的问题，重新检查自身的库存系统，建设一套符合企业自身特点的仓储管理系统。     

Got milk? The rapid rise of China’s dairy sector and its future prospects

This paper synthesizes recent research and new empirical findings to build a more comprehensive understanding of developments in China’s dairy sector. China’s tremendous rise in dairy demand has been driven by several mutually reinforcing factors: including rapid income growth, promotion by the government and dairy industry, changes in urban lifestyles, and the development of new, more sophisticated marketing channels. Domestic milk output has grown to satisfy rising demand largely by increasing the dairy herd. Substantial increases in productivity have been achieved through technology adoption, but there is evidence that the torrid growth has created inefficiencies because adaptations to marketing rules, infrastructure, and institutions have not kept pace with the changing environment. These results suggest there is ample room for future growth in both domestic milk production and dairy demand, but multinational firms and imported products will likely play and increasing role as China’s dairy market continues to develop.     

用普遍的人性来解释艺术—浅谈荣格的美学思想

荣格将人的心理结构分为意识、个人无意识和集体无意识三个层次，通过对集体无意识与创作过程、艺术作品、艺术家的关系的分析，以及对里比多理论在艺术创作中的阐述等，确立其美学理论的基本构架。他创立的精神分析学说对现代西方美学和文艺理论发展产生了巨大而又深远的影响。