MODELS OF DISTRIBUTION OF GDP AT THE GLOBAL LEVEL
Abstract
Problem of distribution gathers the attention of researchers for years. In their research they analyze the uniformity of distribution using Pareto model of distribution, the Lorenz curve and the Gini coefficient. Also some authors are testing the applicability of models from statistical physics to the problem of distribution to better describe it. In addition to the analysis of distribution at the level of states and certain groups such as the Forbes list, the problem is spreading to the global level, where we analyze the distribution of GDP as a measure of the wealth of individual countries.
In this paper we analyzed the distribution of GDP of countries applying the Pareto model, Lorenz curve, Gini coefficient and Boltzmann Gibbs distribution from statistical physics. The analysis was done for 2015, while the Gini coefficient analysis was done during the period from 1990 to 2015.
Keywords
Full Text:
PDFReferences
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 Distribution (pp.3-14). New York: Springer.
Chakrabarti, B. & Chatterjee, A. (2003). Ideal Gas-Like Distributions in Economics: Effects of Saving Propensity. In: Takayasu H. (eds) The Application of Econophysics (pp.280-285). Tokyo: Springer.
Cvetanović, S. (2005). Teorija privrednog razvoja [Theory of economic development]. Niš: Ekonomski fakultet u Nišu.
Dragulescu, A. & Yakovenko, V. (2001). Exponential and power-law probability distributions of wealth and income in the United Kingdom and the United States. Physica A, 299 (1-2), 213-221.
Dragulescu, A. (2002). Applications of physics to economics and finance: Money, income, wealth, and the stock market, Dissertation Abstracts International, Volume: 64-01, Section: B, page: 0245.; 94 p (https://arxiv.org/pdf/cond-mat/0307341v2.pdf)
Dunford, R., Su Q., Tamang E. & Wintour A. (2014). The Pareto Principle. The Plymouth Student Scientist, 7 (1), 140-148.
Kitanović, D. & Golubović, N. (2006). Osnovi ekonomije [Basic Ecomomics]. Niš: Ekonomski fakultet u Nišu.
Klass, O., Biham, O., Levy, M., Malcai, O. & Solomon, S. (2006). The Forbes 400 and the Pareto wealth distribution. Economics Letters 90, 290 – 295.
Levy, M. & Solomon, S. (1997). New evidence for the power-law distribution of wealth. Physica A, 242 (1-2), 90-94.
Oltean, E. & Kusmartsev, F. (2014). An Econophysical Approach of Polynomial Distribution Applied to Income and Expenditure. American Journal of Modern Physics, 3 (2), 88-92.
Sinha, S. (2006). Evidence for Power-law tail of the wealth distribution in India. Physica A, 359 (1), 555-562.
Skipper, R. (2011). Zipf ’s Law and Its Correlation to the GDP of Nations. The University of Maryland McNair Scholars Undergraduate Research Journal, 3, 2011, 217-226.
Yakovenko, V. (2008). Econophysics, Statistical Mechanics Approach to, In: Encyclopedia of Complexity and System Science (pp.2800-2826). New York: Springer.
Yakovenko, V. (2010), Statistical Mechanics of Money, Debt and Energy Consumtion. Science and Culture, 76 (9-10), 430-436.
Statistical base of UN, http://unstats.un.org/unsd/snaama/dnltransfer.asp?fID=2, accessed 31.08.2017.
DOI: https://doi.org/10.22190/FUEO1802177T
Refbacks
- There are currently no refbacks.
© University of Niš, Serbia
Creative Commons License CC BY-NC-ND
ISSN 0354-4699 (Print)
ISSN 2406-050X (Online)