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# 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
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File URL: http://arxiv.org/pdf/1209.2813

## References listed on IDEAS

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Full references (including those not matched with items on IDEAS)

## Citations

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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.

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