Application of a Systems Approach to Studying Global Socio-Economic Inequality

Czesław Mesjasz, Lidia Mesjasz

Abstract


Ideas drawn from broadly-defined systems thinking, including complex systems studies, have already been used to describe and explain social and economic inequality at various levels of the societal hierarchy, beginning with individuals and ending on the global scale. Bearing in mind the studies on economic and social inequality, the following research question can be asked: What are the universal, systemic characteristics of socio-economic inequality on the global scale? How could a systems approach, including complex systems studies, be helpful in studying socio-economic inequality on the global scale? As a point of departure in the literature survey, two conjectures are formulated and discussed. First, socio-economic inequality constitutes an inherent part of developed societies on the global scale and affects regions, countries, social groups, and individuals. Second, a systems approach, and complex systems studies in particular, can be helpful in analyses of socio-economic inequality by helping to identify causal relations. This concerns, in particular, the theory of hierarchical systems and the Power Law.


Keywords


complex systems, inequality, systems approach, Power Law, scale-free networks

Full Text:

PDF

References


Alvaredo, F., Chancel, L., Piketty, T., Saez, E. and Zucman, G. (2017) “The Elephant Curve of Global Inequality and Growth”. WID.world Working Paper 20, https://wid.world/document/elephant-curve-global-inequality-growth-wid-world-working-paper-2017-20 (accessed: 23 May 2018).

Andriani, P. and McKelvey, B. (2009) “Perspective – From Gaussian to Paretian Thinking: Causes and Implications of Power Laws in Organizations”. Organization Science 20(6), https://doi.org/10.1287/orsc.1090.0481.

Ashby, W. R. (1963) An Introduction to Cybernetics. New York: Wiley.

Barabási, A.-L. (2003) Linked. How Everything is Connected to Everything Else and What It Means for Business, Science, and Everyday Life. New York: Penguin.

Barabási, A.-L. and Albert, R. (1999) “Emergence of Scaling in Random Networks”. Science 286(5439).

Barkin, S. J. (2003) Social Construction and the Logic of Money: Financial Predominance and International Economic Leadership. Albany, NY: State University of New York Press.

Bar-Yam, Y. (1997) Dynamics of Complex Systems. Reading, MA: Addison-Wesley.

Bertalanffy, L. von (1968) General Systems Theory. New York: Braziller.

Biggiero, L. (2001) “Sources of Complexity in Human Systems”. Nonlinear Dynamics, Psychology and Life Sciences 5(1).

Bosch, H. van der (2017) “Own Country Second, World First! Redeeming The Losers Of Globalization”. Science for Society, April 15th, https://hermanvandenbosch.com/2017/04/15/own-country-second-world-first (accessed: 17 April 2018).

Broido, A. D. and Clauset, A. (2018) Scale-free Networks Are Rare, https://arxiv.org/abs/1801.03400 (accessed: 16 April 2018).

Brzeziński, M. (2013) Do Wealth Distributions Follow Power Laws? Evidence From “Rich Lists”, https://arxiv.org/pdf/1304.0212.pdf (accessed: 14 January 2017).

Buchanan, M. (2002) Nexus: Small Worlds and the Groundbreaking Science of Networks. New York: W. W. Norton & Company.

Carter, P. L. and Reardon, S. F. (2014) “Inequality Matters”. A William T. Grant Foundation Inequality Paper, September, Stanford University, https://ed.stanford.edu/sites/default/files/inequalitymatters.pdf (accessed: 21 January 2017).

Castellani, B. (2018) Brian Castellani on the Complexity Sciences, http://theory-culturesociety.org/brian-castellani-on-the-complexity-sciences (accessed: 20 February 2018).

Chatterjee, A., Ghosh, A., Inoue, J.-C. and Chakrabarti, B. K. (2015) “Social Inequality: From Data to Statistical Physics Modeling”. Journal of Physics. Conference Series 638.

Cilliers, P. (1998) Complexity and Postmodernism. London: Routledge.

Concepts of Inequality (2015) “United Nations Development Strategy and Policy Analysis Unit“. Development Issues 1, October 21st, http://www.un.org/en/development/desa/policy/wess/wess_dev_issues/dsp_policy_01.pdf (accessed: 7 January 2017).

Dijk, J. A. G. M. van (2005) The Deepening Divide. Inequality in Information Society, Thousand Oaks: Sage Publications.

Freund, C. (2016 ) Deconstructing Branko Milanovic’s “Elephant Chart”: Does It Show What Everyone Thinks?, Peterson Institute for International Economics (PIIE) November 30th, https://piie.com/blogs/realtime-economic-issues-watch/deconstructing-branko-milanovics-elephant-chart-does-it-show (accessed: 22 April 2018).

Gleick, J. (1987) Chaos: The Making of a New Science. New York: Viking Press.

Holland, J. D. (1995) Hidden Order. How Adaptation Builds Complexity. New York: Basic Books.

Kauffman, S. A. (1995) At Home in the Universe. The Search for Laws of Self-organization and Complexity. New York/Oxford: Oxford University Press.

Koestler, A. (1967) The Ghost in the Machine. London: Penguin Group.

Krauss, A. (2015) “The Scientific Limits of Understanding the (Potential) Relationship between Complex Social Phenomena: The Case of Democracy and Inequality”. Journal of Economic Methodology 23(1), https://doi.org/10.1080/1350178x.2015.1069372.

Lakner, C. and Milanovic, B. (2013) “Global Income Distribution: From the Fall of the Berlin Wall to the Great Recession”. World Bank Policy Research Working Paper 6719.

Lakner, C. and Milanovic, B. (2015) “Global Income Distribution: From the Fall of the Berlin Wall to the Great Recession”. The World Bank Economic Review 30(2), https://doi.org/10.1093/wber/lhv039.

Lakoff, G. and Johnson, M. (1995) Metaphors We Live by. Chicago: University of Chicago Press.

Lloyd, S. (2001) “Measures of Complexity: A Nonexhaustive List”. IEEE Control Systems Magazine 21(4), https://doi.org/10.1109/MCS.2001.939938.

Luhmann, N. (1995) Social Systems. Palo Alto, CA: Stanford University Press.

Luhman, N. (1997) Die Gesellschaft der Gesellschaft. Frankfurt am Main: Suhrkamp.

Mesjasz, C. (2010) “Complexity of Social Systems”. Acta Physica Polonica A 117(4), http://przyrbwn.icm.edu.pl/APP/PDF/117/a117z468.pdf (accessed: 14 June 2018).

Milanovic, B. (2005) Worlds Apart: Measuring International and Global Inequality. Princeton, NJ: Princeton University Press.

Milanovic, B. (2016) Global Inequality. A New Approach for the Age of Globalization. Cambridge, MA: The Belknap Press of Harvard University Press.

Newman, M. E. J. (2006) Power Laws, Pareto Distributions and Zipf’s law, https://arxiv.org/pdf/cond-mat/0412004.pdf (accessed: 14 March 2015).

Piketty, T. (2014) Capital in the Twenty-first Century. Cambridge, MA: Harvard University Press.

Piketty, T. and Saez, E. (2014) “Inequality in the Long Run”. Science 344(6186), https://doi.org/10.1126/science.1251936.

Prigogine, I. and Stengers, I. (1984) Order Out of Chaos. New York: Bantam.

Sandefur, J. (2018) Chart of the Week #1: Is the Elephant Graph Flattening Out?, Center for Global Development, January 4th, https://www.cgdev.org/blog/chart-week-1-elephant-graph-flattening-out (accessed: 22 October 2018).

Sen, A. K. (1995) Inequality Re-examined. Oxford: Oxford University Press.

Sen, A. K. (1999) Development as Freedom. New York: Oxford University Press.

Shan, Y. and Yang, A. (2008) Applications of Complex Adaptive Systems. New York: IGI Publishing.

Simon, H. A. (1962) “The Architecture of Complexity”. Proceedings of the American Philosophical Society 106(6).

Simon, H. A. (1995) Near Decomponsability and Complexity: How a Mind Resides in a Brain in J. H. Morowitz, J. L. Singer (eds) The Mind, The Brain And Complex Adaptive Systems [Santa Fe Institute Series]. Reading, MA: Addison-Wesley.

Stanford Encyclopedia of Philosophy, http://plato.stanford.edu/contents.html (accessed: 7 January 2016).

Stiglitz, J. (2012) The Price of Inequality. How Today’s Divided Society Endangers Our Future. New York: W. W. Norton & Company.

Stiglitz, J. (2015) The Great Divide. Unequal Societies and What We Can Do About Them. New York: W. W. Norton & Company.

“A Three-headed Hydra” (2014) Economist, July 16th, http://www.economist.com/blogs/freeexchange/2014/07/measuring-inequality (accessed: 11 February 2017).

Turchin, P. and Gavrilets, S. (2009) “Evolution of Complex Hierarchical Societies”. Social Evolution & History 8(2), http://www.socionauki.ru/journal/articles/129288/ (accessed: 26 January 2017).

Waldrop, M. M. (1992) Complexity: The Emerging Science at the Edge of Order and Chaos. New York: Simon & Schuster.

Warnecke, H. J. (1993) The Fractal Company. A Revolution in Corporate Culture. Berlin–Heidelberg: Springer Verlag.

Weaver, W. (1948) “Science and Complexity”. American Scientist 36(4).

Wiener, N. (1961) Cybernetics: Or Control and Communication in the Animal and the Machine. Paris–Cambridge, MA: Hermann & CIE–MIT Press.

World Inequality Report 2018 (2018) World Inequality Lab, https://wir2018.wid.world/ (accessed: 23 May 2018).

Yakovenko, V. M. and Rosser, J. B. (2009) “Colloquium: Statistical Mechanics of Money, Wealth, and Income”. Reviews of Modern Physics 81(1703), https://doi.org/10.1103/RevModPhys.81.1703.




DOI: https://doi.org/10.15678/AOC.2019.2102