IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1209.2813.html
   My bibliography  Save this paper

The competitiveness versus the wealth of a country

Author

Listed:
  • Boris Podobnik
  • Davor Horvatic
  • Dror Y. Kenett
  • H. Eugene Stanley

Abstract

Politicians world-wide frequently promise a better life for their citizens. We find that the probability that a country will increase its {\it per capita} GDP ({\it gdp}) rank within a decade follows an exponential distribution with decay constant $\lambda = 0.12$. We use the Corruption Perceptions Index (CPI) and the Global Competitiveness Index (GCI) and find that the distribution of change in CPI (GCI) rank follows exponential functions with approximately the same exponent as $\lambda$, suggesting that the dynamics of {\it gdp}, CPI, and GCI may share the same origin. Using the GCI, we develop a new measure, which we call relative competitiveness, to evaluate an economy's competitiveness relative to its {\it gdp}. For all European and EU countries during the 2008-2011 economic downturn we find that the drop in {\it gdp} in more competitive countries relative to {\it gdp} was substantially smaller than in relatively less competitive countries, which is valuable information for policymakers.

Suggested Citation

  • Boris Podobnik & Davor Horvatic & Dror Y. Kenett & H. Eugene Stanley, 2012. "The competitiveness versus the wealth of a country," Papers 1209.2813, arXiv.org.
  • Handle: RePEc:arx:papers:1209.2813
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1209.2813
    File Function: Latest version
    Download Restriction: no

    Citations

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


    Cited by:

    1. Guan, Wanqiu & Gao, Haoyu & Yang, Mingmin & Li, Yuan & Ma, Haixin & Qian, Weining & Cao, Zhigang & Yang, Xiaoguang, 2014. "Analyzing user behavior of the micro-blogging website Sina Weibo during hot social events," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 340-351.
    2. Chakrabarti, Anindya S., 2016. "Stochastic Lotka–Volterra equations: A model of lagged diffusion of technology in an interconnected world," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 214-223.
    3. Tang, Yong & Luo, Yong & Xiong, Jie & Zhao, Fei & Zhang, Yi-Cheng, 2013. "Impact of monetary policy changes on the Chinese monetary and stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4435-4449.
    4. Schinckus, C., 2013. "Between complexity of modelling and modelling of complexity: An essay on econophysics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3654-3665.
    5. Li, Yuan & Gao, Haoyu & Yang, Mingmin & Guan, Wanqiu & Ma, Haixin & Qian, Weining & Cao, Zhigang & Yang, Xiaoguang, 2015. "What are Chinese talking about in hot weibos?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 546-557.
    6. Paulus, Michal & Kristoufek, Ladislav, 2015. "Worldwide clustering of the corruption perception," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 351-358.
    7. Tang, Pan & Zhang, Ying & Baaquie, Belal E. & Podobnik, Boris, 2016. "Classical convergence versus Zipf rank approach: Evidence from China’s local-level data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 246-253.
    8. Hutzler, S. & Sommer, C. & Richmond, P., 2016. "On the relationship between income, fertility rates and the state of democracy in society," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 9-18.
    9. Kantar, Ersin & Keskin, Mustafa, 2013. "The relationships between electricity consumption and GDP in Asian countries, using hierarchical structure methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(22), pages 5678-5684.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:arx:papers:1209.2813. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (arXiv administrators). General contact details of provider: http://arxiv.org/ .

    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.

    We have no references for this item. You can help adding them by using 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.