APPROACHES TO INEQUALITY OF OPPORTUNITY: PRINCIPLES,MEASURES AND EVIDENCE

We put together the different conceptual issues involved in measuring inequality of opportunity, discuss how these concepts have been translated into computable measures, and point out the problems and choices researchers face when implementing these measures. Our analysis identifies and suggests several new possibilities to measure inequality of opportunity. The relevance of the conceptual issues and modelling choices are illustrated with findings from the empirical literature on income inequality of opportunity.     

ON BOOTSTRAPPING A CLASS OF DIFFERENTIABLE STATISTICAL FUNCNONALS WITH APPLICATIONS TO L– AND M– ESTIMATES

EFRON'S (1979) "bootstrap" method is justified for a class of differentiable statistical functionals which includes many L – and M –statistics. For illustration, a Monte Carlo study for the trimmed means is also included.     

NUMERICAL METHODS FOR ESTIMATION AND INFERENCE IN BAYESIAN VAR-MODELS

In Bayesian analysis of vector autoregressive models, and especially in forecasting applications, the Minnesota prior of Litterman is frequently used. In many cases other prior distributions provide better forecasts and are preferable from a theoretical standpoint. Several of these priors require numerical methods in order to evaluate the posterior distribution. Different ways of implementing Monte Carlo integration are considered. It is found that Gibbs sampling performs as well as, or better, then importance sampling and that the Gibbs sampling algorithms are less adversely affected by model size. We also report on the forecasting performance of the different prior distributions. © 1997 by John Wiley & Sons, Ltd.     

WAGE INEQUALITY IN TURKEY: DECOMPOSITION BY STATISTICAL REGIONS, 1980–2001

This paper analyzes wage inequality in the Turkish manufacturing sector annually from 1980 to 2001, and also provides some evidence for inequality in the post‐2001 period. Using the between‐groups component of Theil's T statistic, the paper provides more information on wage inequality. It decomposes the evolution of inequality by statistical regions – The Nomenclature of Territorial Units for Statistics – (i.e. NUTS‐1 and NUTS‐2). The decompositions show that inequality has increased since the late 1980s in the private sector both between regions of NUTS‐1 and NUTS‐2.     

BAYESIAN INFERENCE METHODS FOR UNIVARIATE AND MULTIVARIATE GARCH MODELS: A SURVEY

This survey reviews the existing literature on the most relevant Bayesian inference methods for univariate and multivariate GARCH models. The advantages and drawbacks of each procedure are outlined as well as the advantages of the Bayesian approach versus classical procedures. The paper makes emphasis on recent Bayesian non‐parametric approaches for GARCH models that avoid imposing arbitrary parametric distributional assumptions. These novel approaches implicitly assume infinite mixture of Gaussian distributions on the standardized returns which have been shown to be more flexible and describe better the uncertainty about future volatilities. Finally, the survey presents an illustration using real data to show the flexibility and usefulness of the non‐parametric approach.     

THE DRIVERS OF INCOME INEQUALITY IN RICH COUNTRIES

Rising income inequality has recently come centre‐stage as a core societal concern for rich countries. The diagnosis of the forces driving inequality upwards and their relative importance remain hotly contested, notably with respect to the roles of globalization versus technology and of market forces versus institutions and policy choices. This survey provides a critical review and synthesis of recent research. The focus is on income inequality across the entire distribution, rather than only on what has been happening at the very top. We pay particular attention to include what has been learned from the analysis of micro‐data, to ensure that the coverage is not unduly US‐centric and to analyses of the interrelations between the different drivers of inequality. The marked differences in inequality trends across countries and time periods reflect how global economic forces such as globalization and technological change have interacted with differing national contexts and institutions. Major analytical challenges stand in the way of a consensus emerging on the relative importance of different drivers in how income inequality has evolved in recent decades.     

THE EFFECT OF KNOWLEDGE ACCESSIBILITY ON INTERNATIONAL INCOME INEQUALITY

Using a structural model of new economic geography, we estimate the effect of accessibility to foreign knowledge on international income distribution. Whereas previous literature has mainly focused on the importance of geographical accessibility to foreign markets, this paper emphasizes the role of accessibility to foreign knowledge in determining international income inequality. Using cross-country data of income per worker, bilateral trade flows, and number of flight passengers, we find evidence that the accessibility to foreign knowledge raises per capita income significantly.     

给防患于未然者记头功

他们因能干而下岗了 一次与几位企业界搞管理的朋友吃饭,席间一位姓张的朋友向一位企业界的朋友姚总推荐人才。姓张的朋友说他认识很久的一位朋友前几天被企业辞退了,看能否在姚总手下谋个差事,并极力推荐这位朋友如何如何能干,绝对是一把好手,他十分了解,敢以自己的人格担保。于是有人问:“能干的人为何下岗了?”姓张的朋友说:“说起来大家都不信,我的这位朋     

THE GINI CONCENTRATION INDEX: A REVIEW OF THE INFERENCE LITERATURE

More than a century ago, Corrado Gini proposed his well-known concentration index for measuring the degree of inequality in the distribution of income and wealth. His index is still extremely relevant and widely used in several fields of research and application. In this paper, we focus on the inferential properties of the Gini index, and discuss the main directions of analysis proposed in the literature. The aim of the paper is to provide a comprehensive review of the main developments on the inferential aspects of the Gini concentration ratio. We feel that this work can provide a valuable contribution to those scholars who are approaching the large amount of literature on the inferential properties of the Gini index.     

SOURCES OF REGIONAL INCOME INEQUALITY: AN EXAMINATION OF SMALL REGIONS IN QUEENSLAND

In this study, data for the 125 Local Government Areas of Queensland are used to explain the cross-sectional variation in the Gini coefficient of income inequality. This study updates earlier work for Australian regions that has used the 1981, 1986 and 1991 census data sets and incorporates a wider range of variables, allowing the testing of several competing hypotheses. The study commences with an analysis of the spatial pattern of income inequality in Queensland. Previous work in this area has not considered problems such as spatial autocorrelation, and although no evidence of this is found, the testing uncovers heteroscedasticity with the estimation techniques used in the final version of the model accounting for this problem.