IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v389y2010i16p3023-3038.html
   My bibliography  Save this article

Maximization of statistical heterogeneity: From Shannon’s entropy to Gini’s index

Author

Listed:
  • Eliazar, Iddo
  • Sokolov, Igor M.

Abstract

Different fields of Science apply different quantitative gauges to measure statistical heterogeneity. Statistical Physics and Information Theory commonly use Shannon’s entropy which measures the randomness of probability laws, whereas Economics and the Social Sciences commonly use Gini’s index which measures the evenness of probability laws. Motivated by the principle of maximal entropy, we explore the maximization of statistical heterogeneity–for probability laws with a given mean–in the four following scenarios: (i) Shannon entropy maximization subject to a given dispersion level; (ii) Gini index maximization subject to a given dispersion level; (iii) Shannon entropy maximization subject to a given Gini index; (iv) Gini index maximization subject to a given Shannon entropy. Analysis of these four scenarios results in four different classes of heterogeneity-maximizing probability laws–yielding an in-depth description of both the marked differences and the interplay between the Physical “randomness-based” and the Economic “evenness-based” approaches to the maximization of statistical heterogeneity.

Suggested Citation

  • Eliazar, Iddo & Sokolov, Igor M., 2010. "Maximization of statistical heterogeneity: From Shannon’s entropy to Gini’s index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3023-3038.
    • Handle: RePEc:eee:phsmap:v:389:y:2010:i:16:p:3023-3038
    DOI: 10.1016/j.physa.2010.03.045
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437110002906
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2010.03.045?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Alfarano, Simone & Milakovic, Mishael, 2008. "Does classical competition explain the statistical features of firm growth?," Economics Letters, Elsevier, vol. 101(3), pages 272-274, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Khosravi Tanak, A. & Mohtashami Borzadaran, G.R. & Ahmadi, J., 2017. "Maximum Tsallis entropy with generalized Gini and Gini mean difference indices constraints," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 554-560.
    2. Khosravi Tanak, A. & Mohtashami Borzadaran, G.R. & Ahmadi, Jafar, 2018. "New functional forms of Lorenz curves by maximizing Tsallis entropy of income share function under the constraint on generalized Gini index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 511(C), pages 280-288.
    3. Viktor Stojkoski & Petar Jolakoski & Arnab Pal & Trifce Sandev & Ljupco Kocarev & Ralf Metzler, 2021. "Income inequality and mobility in geometric Brownian motion with stochastic resetting: theoretical results and empirical evidence of non-ergodicity," Papers 2109.01822, arXiv.org.
    4. Fontanari, Andrea & Taleb, Nassim Nicholas & Cirillo, Pasquale, 2018. "Gini estimation under infinite variance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 256-269.
    5. Khosravi Tanak, A. & Mohtashami Borzadaran, G.R. & Ahmadi, J., 2015. "Entropy maximization under the constraints on the generalized Gini index and its application in modeling income distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 657-666.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Scharfenaker, Ellis, 2020. "Implications of quantal response statistical equilibrium," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    2. Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2020. "Exploiting ergodicity in forecasts of corporate profitability," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    3. Eliazar, Iddo, 2017. "Inequality spectra," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 824-847.
    4. Einar Erlingsson & Simone Alfarano & Marco Raberto & Hlynur Stefánsson, 2013. "On the distributional properties of size, profit and growth of Icelandic firms," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 57-74, April.
    5. Giulio Bottazzi & Angelo Secchi, 2011. "A new class of asymmetric exponential power densities with applications to economics and finance," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 20(4), pages 991-1030, August.
    6. Paulo L. dos Santos, 2017. "The Principle of Social Scaling," Complexity, Hindawi, vol. 2017, pages 1-9, December.
    7. Sylvain Barde, 2015. "Back to the Future: Economic Self-Organisation and Maximum Entropy Prediction," Computational Economics, Springer;Society for Computational Economics, vol. 45(2), pages 337-358, February.
    8. Mundt, Philipp & Förster, Niels & Alfarano, Simone & Milaković, Mishael, 2014. "The real versus the financial economy: A global tale of stability versus volatility," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 8, pages 1-26.
    9. Alfarano, Simone & Milaković, Mishael & Irle, Albrecht & Kauschke, Jonas, 2012. "A statistical equilibrium model of competitive firms," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 136-149.
    10. Williams, Michael A. & Pinto, Brijesh P. & Park, David, 2015. "Global evidence on the distribution of firm growth rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 102-107.
    11. Scharfenaker, Ellis & dos Santos, Paulo L., 2015. "The distribution and regulation of Tobin’s q," Economics Letters, Elsevier, vol. 137(C), pages 191-194.
    12. Halvarsson, Daniel, 2013. "Identifying High-Growth Firms," Ratio Working Papers 215, The Ratio Institute.
    13. David Vidal-Tomás & Alba Ruiz-Buforn & Omar Blanco-Arroyo & Simone Alfarano, 2022. "A Cross-Sectional Analysis of Growth and Profit Rate Distribution: The Spanish Case," Mathematics, MDPI, vol. 10(6), pages 1-20, March.
    14. Cohen, Morrel H. & Eliazar, Iddo I., 2013. "Econophysical visualization of Adam Smith’s invisible hand," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 813-823.
    15. Jangho Yang, 2018. "Information Theoretic Approaches In Economics," Journal of Economic Surveys, Wiley Blackwell, vol. 32(3), pages 940-960, July.
    16. Matthias Duschl & Thomas Brenner, 2013. "Characteristics of regional industry-specific employment growth rates' distributions," Papers in Regional Science, Wiley Blackwell, vol. 92(2), pages 249-270, June.
    17. Mundt, Philipp & Oh, Ilfan, 2019. "Asymmetric competition, risk, and return distribution," Economics Letters, Elsevier, vol. 179(C), pages 29-32.
    18. Oh, Ilfan, 2019. "Autonomy of profit rate distribution and its dynamics from firm size measures: A statistical equilibrium approach," BERG Working Paper Series 146, Bamberg University, Bamberg Economic Research Group.
    19. Eliazar, Iddo I. & Cohen, Morrel H., 2013. "On the physical interpretation of statistical data from black-box systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(13), pages 2924-2939.
    20. Mundt, Philipp & Oh, Ilfan, 2019. "Asymmetric competition, risk, and return distribution," BERG Working Paper Series 145, Bamberg University, Bamberg Economic Research Group.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:389:y:2010:i:16:p:3023-3038. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.