Two-step multi-criteria model for selecting optimal portfolio

In spite of a large number of multi-criteria models applied to solve the problem of optimal portfolio selection and a large number of market criteria and accounting criteria proposed for these models, the problem of portfolio containing securities from different industries has not yet been adequately solved. Namely, neither can stocks of companies from different industries be compared using the same criteria nor can the weight of a particular criteria be equal for them all. Therefore this paper develops a new two-step model that will overcome the shortcomings of the previously used models. The model is divided into two different but related pillars: the choice of different industries to form the overall portfolio and the choice of portfolio for each industry. The multi-criteria model used in this paper is a modified multi-criteria programming model based on the PROMETHEE II approach. The selected model has been applied at the Zagreb Stock Exchange (ZSE) as a real case.     

农村零售区域评价、商店态度与消费者购物地选择

以山东省农村居民为调查对象,探讨了零售区域评价、商店态度与消费者购物地选择之间的关系。通过问卷调查,利用因子分析及多元线性回归分析验证了研究假设。实证分析结果表明,零售区域评价对商店态度产生显著影响,而商店态度是影响农村居民购物地选择决策的关键因素。     

Enhance the evaluation quality of project performance based on fuzzy aggregation weight effect

The small and medium enterprises had played an important role during the economy development at Taiwan. Under the competitive environment, the managers or the decision-makers will frequently meet a scenario with the complicate decision-making problems, e.g. the importance tradeoffs between the multiple criteria or the multiple attributes. That is, the consensus and differences among evaluation-makers will be frequently met for most practitioners in multiple criterions decision-making (MCDM) consideration. How to incorporate those characteristics into analysis to enhance the evaluation quality of performance will be a meaningful issue to be addressed. In this study, a case about performance evaluation of the multiple projects owing to a small and medium enterprise at Taiwan will be applied to demonstrating the rationality and feasibility of proposed approach based on the fuzzy aggregation weight effect incorporating the consensus and differences among evaluation-makers.     

Efficient estimation for error component seemingly unrelated nonparametric regression models

Multivariate panel data provides a unique opportunity in studying the joint evolution of multiple response variables over time. In this paper, we propose an error component seemingly unrelated nonparametric regression model to fit the multivariate panel data, which is more flexible than the traditional error component seemingly unrelated parametric regression. By applying the undersmoothing technique and taking both of the correlations within and among responses into account, we propose an efficient two-stage local polynomial estimation for the unknown functions. It is shown that the resulting estimators are asymptotically normal, and have the same biases as the standard local polynomial estimators, which are only based on the individual response, and smaller asymptotic variances. The performance of the proposed procedure is evaluated through a simulation study and a real data set.     

Estimation of poverty measures with auxiliary information in sample surveys

The analysis of poverty measures has been receiving increased attention in recent years. This paper contributes to the literature by developing percentile ratio estimators based on the pseudo empirical likelihood method. In practice, variances of poverty measures could be not expressible by simple formulae and consequently other techniques should be used in the variance estimation stage. Assuming percentile ratios, resampling techniques are investigated in this paper. A numerical example based on data from the Spanish Household Panel Survey is taken up to illustrate how suggested procedures can perform better than existing ones. The effect of a model-misspecification on the proposed estimators is also evaluated by using simulated populations.     

Elasticities of substitution and complementarity

This paper develops a classification scheme of the many different definitions of elasticities of substitution and complementarity in the production case based on primal and dual representations of technology and their related direct and inverse demand functions, gross and net substitution, elasticity type, and three different basic concepts of substitution and complementarity. The ten elasticities of substitution are derived from the cost, profit, input distance, and revenue functions. All the elasticities are equally valid for single and multi-output technologies. The classic Berndt-Wood dataset is used to show the considerable variation across the elasticities.     

The measurement of pay discrimination between job assignments

The traditional Becker/Arrow model of taste discrimination in pay depicts majority and minority labour as perfectly substitutable, implying that all workers perform precisely the same job assignment and have the same qualifications. The model is thus only appropriate for determining whether ceteris paribus pay differences between white workers and non-white workers, for example, performing job assignment A are attributable to prejudice (‘within-assignment discrimination’). The model is inappropriate for determining whether ceteris paribus pay differences between white workers in assignment A and non-white workers in assignment B reflect prejudice (‘cross-assignment discrimination’). We extend the traditional model to allow for cross-assignment discrimination and we propose an empirical methodology for its estimation. In so doing we address two broad questions: (1) Do predictions about cross-assignment discrimination vary with the form of the production function?; and (2) How can one estimate such discrimination when there is no common measure of productivity? We address the first question by deriving a measure of cross-assignment discrimination for four different production functions—Generalized Leontief, Quadratic, CES, and Cobb-Douglas. The Generalized Leontief provides the most general results, although closed form solutions are not possible. Closed form solutions are obtainable from the other three functions, but only under restrictive assumptions. There are two main findings. First, most predictions are generally robust across functional forms. Second, cross-assignment discrimination depends upon productivity and labour supply differences between the two worker groups, labour market structure, and the interaction between relative group productivity and prejudice. We address the second question by outlining, for future exploration, a two-stage regression methodology in which a standardised (i.e. common) measure of productivity is estimated separately for each occupation. This measure is then incorporated as a right-hand-side explanatory variable in a second-stage, all-occupation regression designed to estimate cross-assignment discrimination. We discuss the proposed methodology with reference to a valuable and interesting test case: The market for professional sports players.     

住房流动性对房价指数的影响及其定量分析

目前中国城市住房市场不稳定程度较高,这不仅体现为房价的迅速变化,而且反映在交易量的大幅波动上,后者就是住房流动性的变化。有学者研究指出,以实际交易价格为基础的房价指数可能会低估住房市场的波动程度。为了更准确地把握住房市场的运行状态,本文借鉴美国MIT的相关技术,分析了住房流动性（交易活跃程度）对房价指数的影响,并尝试将流动性信息引入房价指数当中。我们发现,住房流动性对于房价指数有较大影响,且符合人们对于市场走势的直观判断,能够较好地反映市场转折点。     

防止利益冲突：治理房地产腐败的有效途径

当前,中国正处在发展的“黄金期”、“关键期”和“敏感期”,经济发展的“高速”、腐败现象的“高频”,以及由此引发的各类矛盾“高显”是其突出表征。我国房地产业在迅猛发展、对国计民生影响愈来愈深远、并成为国民经济发展支柱产业的同时,却也因房地产领域腐败案件频发给其发展带来极大困扰。应当充分认识利益冲突是房地产领域腐败的第一诱因和根源;多管齐下,建立健全防止利益冲突机制是从源头上治理房地产腐败的必然选择。