Abstract
We analyze three sets of income data: the US Panel Study of Income Dynamics (PSID), the British Household Panel Survey (BHPS), and the German Socio-Economic Panel (GSOEP). It is shown that the empirical income distribution is consistent with a two-parameter lognormal function for the low-middle income group (97%–99% of the population), and with a Pareto or power law function for the high income group (1%–3% of the population). This mixture of two qualitatively different analytical distributions seems stable over the years covered by our data sets, although their parameters significantly change in time. It is also found that the probability density of income growth rates almost has the form of an exponential function.
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References
Nirei M, Souma W (2004) Two Factors Model of Income Distribution Dynamics. SFI Working Paper: http://www.santafe.edu/research/publications/workingpapers/04-10-029.pdf
Drăgulescu AA, Yakovenko VM (2001) Evidence for the Exponential Distribution of Income in the USA. The European Physical Journal B 20:585–589
Drăgulescu AA, Yakovenko VM (2001) Exponential and Power-Law Probability Distributions of Wealth and Income in the United Kingdom and the United States. Physica A 299:213–221
Drăgulescu AA (2003) Applications of Physics to Economics and Finance: Money, Income, Wealth, and the Stock Market. E-print: http://arXiv.org/cond-mat/0307341
Silva AC, Yakovenko VM (2005) Temporal Evolution of the “Thermal” and “Superthermal” Income Classes in the USA During 1983–2001. Europhysics Letters 69:304–310
Willis G, Mimkes J (2004), Evidence for the Independence of Waged and Unwaged Income, Evidence for Boltzmann Distributions in Waged Income, and the Outlines of a Coherent Theory of Income Distribution. E-print: http://arXiv.org/cond-mat/0406694
Chatterjee A, Chakrabarti BK, Manna SS (2003) Money in Gas-Like Markets: Gibbs and Pareto Laws. E-print: http://arXiv.org/cond-mat/0311227
Sinha S (2005) Evidence for Power-law Tail of the Wealth Distribution in India. E-print: http://arXiv.org/cond-mat/0502166
Montroll EW, Shlesinger MF (1982) Maximum Entropy Formalism, Fractals, Scaling Phenomena, and 1/f Noise: A Tale of Tails. Journal of Statistical Physics 32:209–230
Souma W (2001) Universal Structure of the Personal Income Distribution. Fractals 9:463–470
Souma W (2002), Physics of Personal Income. E-print: http://arXiv.org/cond-mat/0202388
Di Matteo T, Aste T, Hyde ST (2003) Exchanges in Complex Networks: Income and Wealth Distributions. E-print: http://arXiv.org/cond-mat/0310544
Clementi F, Gallegati M (2005) Power Law Tails in the Italian Personal Income Distribution. Physica A 350:427–438
Kaniadakis G (2001) Non-linear Kinetics Underlying Generalized Statistics. Physica A 296:405–425
Kaniadakis G (2002) Statistical Mechanics in the Context of Special Relativity. E-print: http://arXiv.org/cond-mat/0210467
Burkhauser RV, Butrica BA, Daly MC, Lillard DR (2001) The Cross-National Equivalent File: A Product of Cross-national Research. In: Becker I, Ott N, Rolf G (eds) Soziale Sicherung in einer dynamischen Gesellschaft. Festschrift für Richard Hauser zum 65. Geburtstag. Campus, Frankfurt/New York
OECD Statistical Compendium 2003#2
Kim K, Yoon SM (2004) Power Law Distributions in Korean Household Incomes. E-print: http://arXiv.org/cond-mat/0403161
Sutton J (2001) The Variance of Firm Growth Rates: The Scaling Puzzle. STICERD — Economics of Industry Papers 27, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE
Stanley MHR, Amaral LAN, Buldyrev SV, Havlin S, Leschhorn H, Maass P, Salinger MA, Stanley HE (1996) Scaling Behavior in the Growth of Companies. Nature 379:804–806
Amaral LAN, Buldyrev SV, Havlin S, Leschhorn H, Maass P, Salinger MA, Stanley HE, Stanley MHR (1997) Scaling Behavior in Economics: I. Empirical Results for Company Growth. J. Phys. I France 7:621–633
Amaral LAN, Buldyrev SV, Havlin S, Leschhorn H, Maass P, Salinger MA, Stanley HE, Stanley MHR (1997) Scaling Behavior in Economics: The Problem of Quantifying Company Growth. Physica A 244:1–24
Lee Y, Amaral LAN, Canning D, Meyer M, Stanley HE (1998) Universal Fea tures in the Growth Dynamics of Complex Organizations. Physical Review Letters 81:3275–3278
Bottazzi G, Secchi A (2002) On The Laplace Distribution of Firms Growth Rates. LEM Working Paper no. 2002-20
Bottazzi G, Secchi A (2003) A Stochastic Model of Firm Growth. Physica A 324:213–219
Bottazzi G, Secchi A (2003) Why Are Distributions of Firm Growth Rates Tent-shaped? Economic Letters 80:415–420
Levy M (2003) Are Rich People Smarter? Journal of Economic Theory 110:42–64
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Clementi, F., Gallegati, M. (2005). Pareto’s Law of Income Distribution: Evidence for Germany, the United Kingdom, and the United States. In: Chatterjee, A., Yarlagadda, S., Chakrabarti, B.K. (eds) Econophysics of Wealth Distributions. New Economic Windows. Springer, Milano. https://doi.org/10.1007/88-470-0389-X_1
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DOI: https://doi.org/10.1007/88-470-0389-X_1
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