房地产股权投资信托当事人的利益均衡研究

简要介绍了房地产信托,对房地产股权投资型信托的委托人、受托人利受益人三方当事人的利益均衡进行分析讨论,建立了相应的数学模型,并通过将持股比例引入模型,使三方构成一个有机的整体,然后对模型进行比较详尽的分析研究,找出影响最优持股比例的因素并分析,得出一些有意义的结论。     

Symmetry and order in the portfolio allocation problem

Summary. This research studies the role of multivariate distribution structures on random asset returns in determining the optimal allocation vector for an expected utility maximizer. All our conclusions pertain for the set of risk averters. By carefully disturbing symmetry in the distribution of the, possibly covarying, returns, we ascertain the ordinal structure of the optimized allocation vector. Rank order of allocations is also established when a permutation symmetric random vector is mapped into the returns vector through location and scale shifts. It is shown that increased dispersion in the vectors of location and scale parameters benefit, ex-ante, investors as does a decrease in the rank correlation coefficient between the location and scale parameter vectors. Revealed preference comparative static results are identified for the location and scale vectors of asset returns. For most issues addressed, we arrive at much stronger inferences when a safe asset is available. Received: August 8, 2000; revised version: January 8, 2001     

浅析石油化工项目产品市场分析

市场分析是项目前期的重要工作之一，目前尚未赢得人们足够的重视。国外的投资咨询公司对石油化工项目的产品市场分析有其一套比较完整的操作程序和评估体系，以BOPP为案例介绍了市场分析的思路和方法，并且指出市场分析作为一种新的理念，必须进一步深化和细化，逐步加以完善。     

标准化在油藏监测工作中的作用

以油藏监测工作中的油藏压力监测为例，介绍了标准化工作在压力资料录取及解释分析中的作用。并用实例说明了标准化作业在油田开发方案的制定及油藏压力监测中的应用。     

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.     

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.