A Feminist Policy Analysis Framework

ABSTRACT

Most policy analysis models, both inside and outside of social work, approach policy in a gender-neutral manner. This fact belies the many ways our society is organized around gender, which is often regulated through policy. This article outlines a model for looking at policies through a gendered lens by framing a set of questions to be asked in a feminist policy analysis. The complexities and underlying issues inherent in such a model are discussed, as well as the model's implicit goals and values. The model provides an important framework for policy analysts and teaching students about policy.     

R–estimation of normed bivariate density functions

Normed bivariate density funtions were introduced by HOEFFDING (1940/41). In the present paper estimators for normed bivariate ranks and on a FOURIER series expansion in LEGENDRE polynomials. The estimation of normed bivarate density functions under positive dependence is also described     

A Comparison of Hierarchical Methods for Clustering Functional Data

Functional data analysis (FDA)—the analysis of data that can be considered a set of observed continuous functions—is an increasingly common class of statistical analysis. One of the most widely used FDA methods is the cluster analysis of functional data; however, little work has been done to compare the performance of clustering methods on functional data. In this article, a simulation study compares the performance of four major hierarchical methods for clustering functional data. The simulated data varied in three ways: the nature of the signal functions (periodic, non periodic, or mixed), the amount of noise added to the signal functions, and the pattern of the true cluster sizes. The Rand index was used to compare the performance of each clustering method. As a secondary goal, clustering methods were also compared when the number of clusters has been misspecified. To illustrate the results, a real set of functional data was clustered where the true clustering structure is believed to be known. Comparing the clustering methods for the real data set confirmed the findings of the simulation. This study yields concrete suggestions to future researchers to determine the best method for clustering their functional data.     

云南企业参与越南项目的SWOT分析和PROT研究

近年来,云南企业参与越南项目越来越多,但均未达到预期目标,其潜力有待发掘。通过探讨越南本地情况以及云南企业情况,进行SWOT分析,对云南企业和越南的投资环境进行四方面的分析,并根据分析结果,提出云南企业参与越南项目的对策,包括潜在投资领域、参与项目融资方式及参与项目方式,尤其推荐采用PROT模式参与越南投资。     

Effects of Alternative Policies on Income Redistribution: Evidence from Brazil

Despite recent successes, Brazilian income (cash) transfer policies remain controversial, and alternative approaches to income redistribution are being actively considered. This article contributes to this debate, analysing the effects of several alternative policies for income redistribution in the Brazilian economy using a computable general equilibrium model. Simulations were conducted consistent with the following policies: direct transfer of income, reduction of taxes, and incentives to agricultural exports. The results suggest that transfer of income is the most effective in promoting redistribution of income, with a positive impact on the level of welfare of the poorest households.     

Decomposing the predictive performance of the moving average trading rule of technical analysis: the contribution of linear and non-linear dependencies in stock returns

The main purpose of this work is to decompose the predictive performance of the moving average (MA) trading rule and find out the portion that could be attributed to the possible exploitation of linear and non-linear dependencies in stock returns. Data from the General Index of the Athens Stock Exchange, from the Standard and Poor-500 Index of the New York Stock Exchange and from the Austrian Traded Index of the Vienna Stock Exchange are filtered by linear filters so as the resulting simulated ‘returns’ exhibit no serial correlation. Applying MA trading rules to both the original and the simulated indices and using a new statistical testing procedure that takes into account the sensitivity of the performance of the trading rule as a function of the length of the MA it is found that the predictive performance of the trading rule is clearly weakened when applied to the simulated indices indicating that a substantial part of the rule's predictive performance is due to the exploitation of linear dependencies in stock returns. This weakening is uneven; in general the shorter the MA length the more pronounced the attenuation.     

的士司机撞击抢劫犯司法适用之我见

本文对的士司机撞击抢劫犯司法适用的相关问题加以论述。     

A robustness framework for monitoring real options under uncertainty

This paper presents a problem structuring methodology to assess real option decisions in the face of unpredictability. Based on principles of robustness analysis and scenario planning, we demonstrate how decision-aiding can facilitate participation in projects setting and achieve effective decision making through the use of real options reasoning. We argue that robustness heuristics developed in earlier studies can be practical proxies for real options performance, hence indicators of efficient flexible planning. The developed framework also highlights how to integrate real options solutions in firms’ strategic plans and operating actions. The use of the methodology in a location decision application is provided for illustration.     

An alternative approach to variable selection for prediction

A procedure for selecting a subset of predictor variables in regression analysis is suggested. The procedure is so designed that it leads to the selection of a subset of variables having an adequate degree of informativeness with a directly specified confidence coefficient. Some examples are considered to illustrate the application of the procedure.     

A Conditional Approach for Regression Analysis of Longitudinal Data with Informative Observation Time and Non-negligible Observation Duration

Recently, there has been a great interest in the analysis of longitudinal data in which the observation process is related to the longitudinal process. In literature, the observation process was commonly regarded as a recurrent event process. Sometimes some observation duration may occur and this process is referred to as a recurrent episode process. The medical cost related to hospitalization is an example. We propose a conditional modeling approach that takes into account both informative observation process and observation duration. We conducted simulation studies to assess the performance of the method and applied it to a dataset of medical costs.