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).     

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.     

Asymmetric performance: the market share impact of scale and link alliances in the global auto industry

This study investigates how participating in strategic alliances with rivals affects the relative competitive positions of the partner firms. The paper builds on studies that show significant differences in the outcomes of scale and link alliances. The study argues that the more asymmetric outcomes of link alliances translate into greater changes in the relative market shares of the partner firms, due to unbalanced opportunities for inter‐partner learning and learning by doing. We find support for this argument by examining 135 alliances among competing firms in the global automobile industry, from 1966 to 1995. Copyright © 2004 John Wiley & Sons, Ltd.     

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.     

中小企业成长的理论

概根据相关文献资料对中小企业成长的理论观点,本文作了归纳、整理,目的在于识别影响和决定其成长的关键因素,理解和把握其生存发展的规律,以有助于从事创业的企业家和中小企业经营管理者借鉴,为政府制订面向中小企业的支持体系建设提供理论依据。     

土工实验中的液、塑限测定浅议

文章分析了当前土工实验中的液、塑限测定过程中应当注意的问题及其存在的问题,并论述了如何对其实验数据进行处理和分析的方法。     

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.     

A Pricing and Hedging Comparison of Parametric and Nonparametric Approaches for American Index Options

This article investigates the extent to which options on theAustralian Stock Price Index can be explained by parametricand nonparametric option pricing techniques. In particular,comparisons are made of out-of-sample option pricing performanceand hedging performance. The dataset differs from many of thoseused previously in the empirical options pricing literaturein that it consists of American options. In addition, a broaderspectrum of techniques are considered: a spline-based nonparametrictechnique is considered in addition to the standard kernel techniques,while the performance of a Heston stochastic volatility modelis also considered. Although some evidence is found of superiorperformance by nonparametric techniques for in-sample pricing,the parametric methods exhibit a markedly better ability toexplain future prices and show superior hedging performance.