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Statistical Size Distributions in Economics and Actuarial Sciences
Abstract
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.
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Cites
An introduction to probability theory and its applications
(1958) · Journal of the Franklin Institute · doi:10.1016/0016-0032(58)90688-4 · Cited by 29,269
The Statistical Analysis of Failure Time Data.
Aitkin, M., Kalbfleisch, J. D., & Prentice, R. L. (1981) · Biometrics · doi:10.2307/2530581 · Cited by 9,877
Continuous Univariate Distributions.
Omori, Y., Johnson, N. L., Kotz, S., & Balakrishnan, N. (1995) · Journal of the American Statistical Association · doi:10.2307/2291547 · Cited by 9,084
Self-citationInvestment in Human Capital: A Theoretical Analysis
Becker, G. S. (1962) · Journal of Political Economy · doi:10.1086/258724 · Cited by 8,063
Nelsen, R. B. (1999) · Lecture Notes in Statistics · doi:10.1007/978-1-4757-3076-0 · Cited by 7,744
Becker, G. S. (1983) · Cited by 6,708
Embrechts, P., Klüppelberg, C., & Mikosch, T. (1997) · doi:10.1007/978-3-642-33483-2 · Cited by 4,402
Non-Uniform Random Variate Generation
Devroye, L. (1986) · Springer eBooks · doi:10.1007/978-1-4613-8643-8 · Cited by 4,041
On the measurement of inequality
Atkinson, A. B. (1970) · Journal of Economic Theory · doi:10.1016/0022-0531(70)90039-6 · Cited by 3,945
Robust Statistics: The Approach Based on Influence Functions
Ruppert, D. (1987) · Technometrics · doi:10.2307/1269782 · Cited by 3,880
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The Economics of Climate Change
Stern, N. (2010) · Climate Ethics · doi:10.1093/oso/9780195399622.003.0010 · Cited by 2,702
Power Laws in Economics and Finance
Gabaix, X. (2009) · Annual Review of Economics · doi:10.1146/annurev.economics.050708.142940 · Cited by 907
Summarizing Insurance Scores Using a Gini Index
Frees, E. W., Meyers, G., & Cummings, A. D. (2011) · Journal of the American Statistical Association · doi:10.1198/jasa.2011.tm10506 · Cited by 96
Metadata
- Authors
- Kleiber, C., & Kotz, S.
- Venue
- Wiley Series in Probability and Statistics
- Publisher
- Wiley
- Published
- 2003-08-08
- ISSN
- 1940-6347 (ISSN-L)
- OpenAlex
- W1498017815
- Cited by
- 1,117
- References
- 144
- FWCI
- 18.10
- Type
- book
- Language
- en
- Open access
- closed
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