Statistical Size Distributions in Economics and Actuarial Sciences

Front Cover
Wiley, Aug 11, 2003 - Mathematics - 352 pages
A comprehensive account of economic size distributions around the world and throughout the years

In the course of the past 100 years, economists and applied statisticians have developed a remarkably diverse variety of income distribution models, yet no single resource convincingly accounts for all of these models, analyzing their strengths and weaknesses, similarities and differences. Statistical Size Distributions in Economics and Actuarial Sciences is the first collection to systematically investigate a wide variety of parametric models that deal with income, wealth, and related notions.

Christian Kleiber and Samuel Kotz survey, compliment, compare, and unify all of the disparate models of income distribution, highlighting at times a lack of coordination between them that can result in unnecessary duplication. Considering models from eight languages and all continents, the authors discuss the social and economic implications of each as well as distributions of size of loss in actuarial applications. Specific models covered include:

  • Pareto distributions
  • Lognormal distributions
  • Gamma-type size distributions
  • Beta-type size distributions
  • Miscellaneous size distributions

Three appendices provide brief biographies of some of the leading players along with the basic properties of each of the distributions. Actuaries, economists, market researchers, social scientists, and physicists interested in econophysics will find Statistical Size Distributions in Economics and Actuarial Sciences to be a truly one-of-a-kind addition to the professional literature.

What people are saying - Write a review

We haven't found any reviews in the usual places.

Other editions - View all

About the author (2003)

CHRISTIAN KLEIBER, PhD, is assistant professor in the Department of Statistics at the University of Dortmund in Germany.

SAMUEL KOTZ, PhD, honorary Doctor of Science, is professor and research scholar at the Department of Engineering Management and Systems Engineering at George Washington University in Washington, D.C.

Bibliographic information