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Modeling economic system using fuzzy cognitive maps

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Abstract

Macro-economic planning and policy decisions on various economic parameters do drive national economic activities leading to economic and social growth. These undergo dynamic changes on account of their mutual inter-relations and interactions and also due to factors internal and external to the economy. The objective of this work is to attempt and model major chosen economic variables using fuzzy cognitive map to decipher the development paradigm of the national economic system with respect to their mutual influences. Using the data of the Indian state, the study concluded that policy makers in developing nations must take steps to increase government spending, strengthen the local currency, reduce liabilities, increase fiscal deficit (within acceptable limits) and boost tax revenue in decreasing order of priority for early achievement of the desired objectives of higher GDP growth rate and social development. Moreover, the developed model inferred the possibility of GDP growth rate being influenced by under-reporting of services output in earlier years as compared to the later part of the study period. The methodology suggested and the results of the work do add to knowledge facilitating its use by policy makers and economic planners.

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Reference

  • Abid M, Mraihi R (2014) Disaggregate energy consumption versus economic growth in Tunisia: cointegration and structural break analysis. J Knowl Econ. doi:10.1007/s13132-014-0184-9

    Google Scholar 

  • Adam A, Moutos T (2014) Do capital importing countries pay higher prices for their import of goods? J Int Money Finance 40:95–108

    Article  Google Scholar 

  • Ajukumar VN, Gandhi MS, Gandhi OP (2012) Assessment of human reliability factors in maintenance using fuzzy cognitive map approach. Qual Reliab Eng Int. doi:10.1002/qre.1569

    Google Scholar 

  • Amisano G, Fagan G (2013) Money growth and inflation: a regime switching approach. J Int Money Finance 33:118–145

    Article  Google Scholar 

  • Axelrod R (1976) Structure of decision: the cognitive maps of political elites. Princeton University Press, New Jersey

    Google Scholar 

  • Baum A, Checherita-Westphal C, Rother P (2013) Debt and growth: new evidence for the euro area. J Int Money Finance 32:809–821

    Article  Google Scholar 

  • Beine M, Docquier F, Rapoport H (2001) Brain drain and economic growth: theory and evidence. J Dev Econ 64(1):275–289

    Article  Google Scholar 

  • Betz F (2013) Modeling a layered financial structure in a knowledge economy. J Knowl Econ. doi:10.1007/s13132-013-0167-2

    Google Scholar 

  • Bird RM, Zolt EM (2003) Introduction to tax policy design and development. Course on practical issues of tax policy in developing countries, World Bank, April 28–May 1 2003

  • Carrère C, De Melo J (2012) Fiscal spending and economic growth: some stylized facts. World Dev 40(9):1750–1761

    Article  Google Scholar 

  • Carvalho JP, Tomé JA (2004) Qualitative modeling of an economic system using rule-based fuzzy cognitive maps. In: FUZZ-IEEE, pp 659–664

  • Caselli F, Esquivel G, Lefort F (1996) Reopening the convergence debate: a new look at cross-country growth empirics. J Econ Growth 1(3):363–389

    Article  MATH  Google Scholar 

  • Dollar D, Kleineberg T, Kraay A (2013) Growth is still good for the poor. LIS Working paper series no. 596. Luxembourg Income Study, Cross-National Data Center, Luxembourg

  • Edison HJ, Levine R, Ricci L, Sløk T (2002) International financial integration and economic growth. J Int Money Finance 21(6):749–776

    Article  Google Scholar 

  • Esfahani HS, Ramírez MT (2003) Institutions, infrastructure, and economic growth. J Dev Econ 70(2):443–477

    Article  Google Scholar 

  • Feldkircher M (2014) The determinants of vulnerability to the global financial crisis 2008 to 2009: credit growth and other sources of risk. J Int Money Finance 43:19–49

    Article  Google Scholar 

  • Flora P, Agrawal G (2013) A co-integration and causality analysis of highest FDI recipient in Asian economies. J Knowl Econ. doi:10.1007/s13132-013-0177-0

    Google Scholar 

  • Gupta P, Gandhi OP (2014) Equipment redesign feasibility through maintenance-work-order records using fuzzy cognitive maps. Int J Syst Assur Eng Manag 5(1):21–31

    Article  Google Scholar 

  • Haq M (1995) Reflections of human development. Oxford University Press, New York

    Google Scholar 

  • Harvey CR (1989) Forecasts of economic growth from the bond and stock markets. Financ Anal J 45(5):38–45

    Article  Google Scholar 

  • Hazewinkel M (ed) (2001) Hyperbolic functions, encyclopedia of mathematics. Springer, Berlin. ISBN 978-1-55608-010-4

    Google Scholar 

  • Human Development Report (2013) http://www.undp.org/content/undp/en/home/librarypage/hdr/human-development-report-2013/ Accessed 25 July 2014

  • Iyer S, Kitson M, Toh B (2005) Social capital, economic growth and regional development. Reg Stud 39(8):1015–1040

    Article  Google Scholar 

  • Johnson S, Ostry J, Subramanian A (2007) The prospects for sustained growth in Africa: benchmarking the constraints. IMF Working paper no. WP/07

  • Johnson S, Larson W, Papageorgiou C, Subramanian A (2013) Is newer better? Penn world table revisions and their impact on growth estimates. J Monet Econ 60(2):255–274

    Article  Google Scholar 

  • Jones CI (2002) Sources of US economic growth in a world of ideas. Am Econ Rev 92(1):220–239

    Article  Google Scholar 

  • Kaplan M, Ozturk I, Kalyoncu H (2011) Energy consumption and economic growth in turkey: cointegration and causality analysis. Rom J Econ Forecast 2:31–41

    Google Scholar 

  • Knack S, Keefer P (1995) Institutions and economic performance: cross-country tests using alternative institutional measures. Econ Polit 7(3):207–227

    Article  Google Scholar 

  • Kosko B (1986) Fuzzy cognitive maps. Int J Man Mach Stud 24(1):65–75

    Article  MATH  Google Scholar 

  • Kosko B (1992) Neural networks and fuzzy systems. Prentice-Hall, Upper Saddle River

    MATH  Google Scholar 

  • Koulouriotis DE, Diakoulakis IE, Emiris DM (2001) A fuzzy cognitive map-based stock market model: synthesis, analysis and experimental results. In: The 10th IEEE international conference on fuzzy systems, vol 1, pp 465–468)

  • Levine R (1997) Financial development and economic growth: views and agenda. J Econ Lit 35(2):688–726

    Google Scholar 

  • Levine R (2003) More on finance and growth: more finance, more growth? Fed Reserve Bank of St Louis Rev 85(July/August 2003):31–46

    Google Scholar 

  • Levine R, Zervos S (1996) Stock market development and long-run growth. World Bank Econ Rev 10(2):323–339

    Article  Google Scholar 

  • Lotz JR, Morss ER (1967) Measuring “tax effort” in developing countries (Evaluation de l’effort fiscal dans les pays en voie de développement) (Medición del” esfuerzo tributario” de los países en desarrollo). Staff Papers-International Monetary Fund, pp 478–499

  • Lucas A (1983) Public policy diffusion research: integrating analytic paradigms. Knowledge 4(3):379–408

    Article  Google Scholar 

  • Mawson P (2002) Measuring economic growth in New Zealand. Working paper 02/14, New Zealand Treasury, Wellington 6008, New Zealand

  • Mishra S, Salk H, Nathan K (2013) Measuring human development index: the old, the new and the elegant. http://www.igidr.ac.in/pdf/publication/WP-2013-020.pdf Accessed on 1 Sept 2014

  • Östermark R (1996) A fuzzy control model (FCM) for dynamic portfolio management. Fuzzy Sets Syst 78(3):243–254

    Article  MATH  MathSciNet  Google Scholar 

  • Pagano P, Schivardi F (2003) Firm size distribution and growth. Scand J Econ 105(2):255–274

    Article  Google Scholar 

  • Papageorgiou EI (2011, June) Review study on fuzzy cognitive maps and their applications during the last decade. In: 2011 IEEE international conference on fuzzy systems (FUZZ), pp 828–835

  • Papava V (2000) State, public sector and theoretical prerequisites to a model of an “economy without taxes”. Int J Soc Econ 27(1):45–61

    Article  Google Scholar 

  • Qureshi MA (2009) Human development, public expenditure and economic growth: a system dynamics approach. Int J Soc Econ 36(1/2):93–104

    Article  Google Scholar 

  • Rao RV (2008) Evaluation of environmentally conscious manufacturing programs using multiple attribute decision making methods. Proc Inst Mech Eng B J Eng Manuf 222(3):441–451

    Article  Google Scholar 

  • Reserve Bank of India (2013) Handbook of statistics on the Indian Economy—2012–2013. Pub: Director, Data Management and Dissemination Division, Department of Statistics and Information Management, Reserve Bank of India, Bandra (E), Mumbai, India. http://dbie.rbi.org.in. Accessed on 30 July 2014

  • Rodriguez F, Rodrik D (2001) Trade policy and economic growth: a skeptic’s guide to the cross-national evidence. In: Bernanke B, Rogoff KS (eds) NBER Macroeconomics Annual 2000, vol 15, The MIT Press. Cambridge, pp 261–338

    Google Scholar 

  • Saidi K, Hassen LB, Hammami MS (2014) Econometric analysis of the relationship between ICT and economic growth in Tunisia. J Knowl Econ. doi:10.1007/s13132-014-0204-9

    Google Scholar 

  • Sharma R, Chitkara S (2006) Informal Sector in the Indian System of National Accounts. Expert Group on Informal Sector Statistics (Delhi Group), Central Statistical Organization, Paper No. 6

  • Stylios CD, Groumpos PP (1998) The challenge of modeling supervisory systems using fuzzy cognitive maps. J Intell Manuf 9(4):339–345

    Article  Google Scholar 

  • Stylios CD, Groumpos PP (1999) Mathematical formulation of fuzzy cognitive maps. In: Proceedings of the 7th mediterranean conference on control and automation (MED99), Haifa, Israel, 2251–2261, 28–30 June

  • Taber R (1991) Knowledge processing with fuzzy cognitive maps. Expert Syst Appl 2(1):83–87

    Article  Google Scholar 

  • Taber R, Siegel M (1987) Estimation of expert credibility weights using fuzzy cognitive maps. In: Proceedings of the IEEE first international conference on neural networks, San Diego, CA, USA, 319–325

  • Wolf A (2002) Does education matter? Myths about education and economic growth. Perspectives 6(4):115–118

    Google Scholar 

  • Yin W, Li J (2014) Macroeconomic fundamentals and the exchange rate dynamics: a no-arbitrage macro-finance approach. J Int Money Finance 41:46–64

    Article  Google Scholar 

  • Zhou S, Liu Z-Q, Zhang JY (2006) Fuzzy causal networks: general model, inference and convergence. IEEE Trans Fuzzy Syst 14(3):412–420

    Article  Google Scholar 

Download references

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Correspondence to Shalini Gupta.

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Gupta, S., Gupta, S. Modeling economic system using fuzzy cognitive maps. Int J Syst Assur Eng Manag 8 (Suppl 2), 1472–1486 (2017). https://doi.org/10.1007/s13198-017-0616-6

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  • DOI: https://doi.org/10.1007/s13198-017-0616-6

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