Suchergebnisse

In income modelling studies, such well-known distributions as the Dagum, the lognormal or the Zenga distributions are often used as approximations of the observed distributions. The objective of the research described in the article is to verify the possibility of using other type of distributions, i.e. asymmetric distributions derived from normal distribution (ND) in the context of income modelling. Data from the 2011 EU-SILC survey on the monthly gross income per capita in Poland were used to assess the most important characteristics of the discussed distributions. The probability distributions were divided into two groups: I – distributions commonly used for income modelling (e.g. the Dagum distribution) and II – distributions derived from ND (e.g. the SU Johnson distribution). In addition to the visual evaluation of the usefulness of the analysed probability distributions, various numerical criteria were applied: information criteria for econometric models (such as the Akaike Information Criterion, Schwarz's Bayesian Information Criterion and the Hannan-Quinn Information Criterion), measures of agreement, as well as empirical and theoretical characteristics, including a measure based on quantiles, specifically defined by the authors for the purposes of this article. The research found that the SU Johnson distribution (Group II), similarly to the Dagum distribution (Group I), can be successfully used for income modelling.

Income Distribution was written primarily as a textbook intended for undergraduate economics majors. The material, however, is treated with sufficient rigor to meet the needs of first year graduate students also. The book may also serve the needs of sociologists and political scientists whoare primarily interested in the related social justice topics of income inequality and poverty. Each chapter is logically connected with the preceding chapters, providing a general overview of income distribution and its applications.

Canonical theories of political economy struggle to explain patterns of distribution in authoritarian regimes. In this Element, Albertus, Fenner, and Slater challenge existing models and introduce an alternative, supply-side, and state-centered theory of 'coercive distribution'. Authoritarian regimes proactively deploy distributive policies as advantageous strategies to consolidate their monopoly on power. These policies contribute to authoritarian durability by undercutting rival elites and enmeshing the masses in lasting relations of coercive dependence. The authors illustrate the patterns, timing, and breadth of coercive distribution with global and Latin American quantitative evidence and with a series of historical case studies from regimes in Latin America, Asia, and the Middle East. By recognizing distribution's coercive dimensions, they account for empirical patterns of distribution that do not fit with quasi-democratic understandings of distribution as quid pro quo exchange. Under authoritarian conditions, distribution is less an alternative to coercion than one of its most effective expressions

This article theorizes camp as an aesthetic category that references the divided parts of global society, or the moment of political economy called distribution. By completing Sianne Ngai's unfinished taxonomy of aesthetic categories, I simultaneously collect a promiscuous archive of contemporary cultural materials (classics like the movies of John Waters and the early performances of Bette Midler, as well as such recent works as Zadie Smith's novel White Teeth, the television show Tim and Eric Awesome Show, Great Job!, and music videos by Fergie, Nicki Minaj, and Psy) and show how this archive provides lessons on the distribution of wealth, precarity, and belonging in our world.

Devoted to the problem of fitting parametric probability distributions to data, this treatment uniquely unifies loss modeling in one book. Data sets used are related to the insurance industry, but can be applied to other distributions. Emphasis is on the distribution of single losses related to claims made against various types of insurance policies. Includes five sets of insurance data as examples.

The known sampling distributions and simulation methods associated with multivariate t distributions are reviewed. We believe that this review will serve as an important reference and encourage further research activities in the area.