Gini’s nuclear family

The purpose of this paper is to justify the use of the Gini coefficient and two close relatives for summarizing the basic information of inequality in distributions of income. To this end we employ a specific transformation of the Lorenz curve, the scaled conditional mean curve, rather than the Lorenz curve as the basic formal representation of inequality in distributions of income. The scaled conditional mean curve is shown to possess several attractive properties as an alternative interpretation of the information content of the Lorenz curve and furthermore proves to yield essential information on polarization in the population. The paper also provides asymptotic distribution results for the empirical scaled conditional mean curve and the related family of empirical measures of inequality.      

Approximate Bayesianity of Frequentist Confidence Intervals for a Binomial Proportion

The well-known Wilson and Agresti–Coull confidence intervals for a binomial proportion p are centered around a Bayesian estimator. Using this as a starting point, similarities between frequentist confidence intervals for proportions and Bayesian credible intervals based on low-informative priors are studied using asymptotic expansions. A Bayesian motivation for a large class of frequentist confidence intervals is provided. It is shown that the likelihood ratio interval for p approximates a Bayesian credible interval based on Kerman’s neutral noninformative conjugate prior up to O(n^{? 1}) in the confidence bounds. For the significance level α ? 0.317, the Bayesian interval based on the Jeffreys’ prior is then shown to be a compromise between the likelihood ratio and Wilson intervals. Supplementary materials for this article are available online.     

From classes to copulas: wages,capital, and top incomes

Public debates about the rise in top income shares often focus on the growing dispersion in earnings, and the soaring pay for top executives and financial-sector employees. But can the change in the marginal distribution of earnings on its own explain the rise in top income shares? Are top executives replacing capital owners in the group of top-income earners, or are we rather witnessing a fusion of top capital and top earnings? This paper proposes an extension of the copula framework and uses it for exploring the changing composition of top incomes. It illustrates that changes in top income shares can easily be decomposed into respective changes in the marginal distributions of labour and capital income and the changing association between the two types of income. An application using tax record data from Norway shows that the association between top labour and capital incomes grew stronger between 1995 and 2005 in the top half of the wage and capital income distribution, though it declined for the top 1% of capital income receivers. A gender decomposition demonstrates that the association of wage and capital incomes at the top is particularly striking for men, whilst women are largely under-represented in the top halves of the two marginal distributions.     

The significance of meaning. Why IPBES needs the social sciences and humanities

The term “biodiversity” is often used to describe phenomena of nature, which can be studied without a reference to the socially constructed, evaluative, or indeed normative contexts. In our paper, we challenge this conception by focusing particularly on methodological aspects of biodiversity research. We thereby engage with the idea of interdisciplinary biodiversity research as a scientific approach directed at the recognition and management of contemporary society in its ecological embedding. By doing this, we explore how research on and assessments of biodiversity can be enhanced if meaning, aspiration, desires, and related aspects of agency are methodically taken into account. In six sections, we substantiate our claim that the discourse on biodiversity (including the IPBES (Intergovernmental science-policy Platform on Biodiversity and Ecosystem Services) debate) is incomplete without contributions from the social sciences and humanities. In the introduction, a brief overview of biodiversity’s conceptual history is provided showing that “biodiversity” is a lexical invention intended to create a strong political momentum. However, that does not impede its usability as a research concept. Section 2 examines the origins of the Convention on Biological Diversity (CBD) by way of sociological discourse analysis. Subsequently, it proposes a matrix as a means to structure the ambiguities and tensions inherent in the CBD. The matrix reemphasizes our main thesis regarding the need to bring social and ethical expertise to the biodiversity discourse. In Section 3, we offer a brief sketch of the different methods of the natural and social sciences as well as ethics. This lays the groundwork for our Section 4, which explains and illustrates what social sciences and ethics can contribute to biodiversity research. Section 5 turns from research to politics and argues that biodiversity governance necessitates deliberative discourses in which participation of lay people plays an important role. Section 6 provides our conclusions.     

Accounting for family background when designing optimal income taxes: a microeconometric simulation analysis

We develop an extended version of Roemer’s Equality of Opportunity (EOp) criterion that accounts for income differentials between as well as within types, where types are defined by circumstances that are beyond people’s control (parental education, in this study). A microeconometric model of labour supply in Italy is employed to identify income tax-transfer rules that are optimal according to the extended EOp criterion. Overall, the results do not conform to the perhaps common expectation that the more conventional Equality of Outcome criterion is more supportive of “interventionist” (redistributive) policies than the EOp approach.     

Recursive location and scale estimators

It is shown that a recursive estimator with the same asymptotic properties as the median has convergence properties in finite samples which depend heavily on the scale of the data. A simple modification which adjusts for the scale is suggested and its application illustrated on simulated data. The modified estimator has much improved properties which are similar to those of the sample (non-recursive) median.