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Comparative Multidimensional Analysis of the Current State of European Economies Based on the Complex of Macroeconomic Indicators

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  • Sergei Aliukov

    (Department of Digital Economics and Information Technologies, South Ural State University, 76 Lenin Prospekt, 454080 Chelyabinsk, Russia)

  • Jan Buleca

    (Faculty of Economics, Technical University of Kosice, Nemcovej 32, 04001 Kosice, Slovak Republic)

Abstract

The stability of the economy of any country is primarily determined by the totality of macroeconomic indicators that describe the current economic state. This article provides a multi-dimensional analysis of the macroeconomic situation in Europe according to the data of 2020. The purpose of the article is to give a clear idea of the relative position of the economies of European countries, their proximity or the significance of their differences to determine each country’s place in the overall European economic system. Research objectives: (1) to identify the necessary macroeconomic indicators for the research; (2) to determine the direction of the impact of these indicators on the economic situation of European countries; (3) to carry out a cluster division of the studied countries with the identification of the main characteristics of each cluster; (4) to identify the main macroeconomic indicators that determine the level of welfare of European countries, (5) to reduce the dimension of the multi-dimensional economic space using integrated latent factors, (6) to build a fuzzy mathematical model to predict the level of welfare of the country when the specified values of latent factors are achieved. The methodological basis of the analysis is the methods of processing multi-dimensional information, such as multi-dimensional scaling, cluster analysis, factor analysis, multivariate regression analysis, analysis of variance, discriminant analysis, and fuzzy modelling methods. The multivariate data processing was performed using the SPSS and FuzzyTech computer programs. The results obtained in the article can be useful in carrying out macroeconomic reforms to improve the economic condition of the countries.

Suggested Citation

  • Sergei Aliukov & Jan Buleca, 2022. "Comparative Multidimensional Analysis of the Current State of European Economies Based on the Complex of Macroeconomic Indicators," Mathematics, MDPI, vol. 10(5), pages 1-29, March.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:5:p:847-:d:765948
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    as
    1. James H. Stock, 2019. "The business cycle is alive and well," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 54(1), pages 79-84, January.
    2. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
    3. Marcellino, Massimiliano & Musso, Alberto, 2011. "The reliability of real-time estimates of the euro area output gap," Economic Modelling, Elsevier, vol. 28(4), pages 1842-1856, July.
    4. Francesca Parente, 2019. "A Multidimensional Analysis of the EU Regional Inequalities," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(3), pages 1017-1044, June.
    5. Quah, Danny, 1997. "Empirics for growth and distribution," LSE Research Online Documents on Economics 2138, London School of Economics and Political Science, LSE Library.
    6. Costanzo Ranci & Jason Beckfield & Laura Bernardi & Andrea Parma, 2021. "New Measures of Economic Insecurity Reveal its Expansion Into EU Middle Classes and Welfare States," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 158(2), pages 539-562, December.
    7. Domenico Giannone & Lucrezia Reichlin, 2005. "Trends and cycles in the Euro Area: how much heterogeneity and should we worry about it?," Macroeconomics 0511016, University Library of Munich, Germany.
    8. Fisher, Jonathan D. & Johnson, David S. & Smeeding, Timothy M. & Thompson, Jeffrey P., 2020. "Estimating the marginal propensity to consume using the distributions of income, consumption, and wealth," Journal of Macroeconomics, Elsevier, vol. 65(C).
    9. Marcellino, Massimiliano & Musso, Alberto, 2010. "Real time estimates of the euro area output gap: reliability and forecasting performance," Working Paper Series 1157, European Central Bank.
    10. Quah, Danny, 1997. "Empirics for Growth and Distribution: Stratification, Polarization, and Convergence Clubs," CEPR Discussion Papers 1586, C.E.P.R. Discussion Papers.
    11. Angelini, Elena & Marcellino, Massimiliano, 2011. "Econometric analyses with backdated data: Unified Germany and the euro area," Economic Modelling, Elsevier, vol. 28(3), pages 1405-1414, May.
    12. Reichlin, Lucrezia & Giannone, Domenico & Small, David, 2005. "Nowcasting GDP and Inflation: The Real Time Informational Content of Macroeconomic Data Releases," CEPR Discussion Papers 5178, C.E.P.R. Discussion Papers.
    13. Vladimir Zhuravlyov & Tatyana Khudyakova & Natalia Varkova & Sergei Aliukov & Svetlana Shmidt, 2019. "Improving the Strategic Management of Investment Activities of Industrial Enterprises as a Factor for Sustainable Development in a Crisis," Sustainability, MDPI, vol. 11(23), pages 1-20, November.
    14. James H. Stock & Mark W. Watson, 2012. "Generalized Shrinkage Methods for Forecasting Using Many Predictors," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(4), pages 481-493, June.
    15. Marek Walesiak & Grażyna Dehnel & Marek Obrębalski, 2021. "Assessment of the Europe 2020 Strategy: A Multidimensional Indicator Analysis via Dynamic Relative Taxonomy," Energies, MDPI, vol. 14(16), pages 1-20, August.
    16. Marcellino, Massimiliano & Musso, Alberto, 2010. "The Forecasting Performance of Real Time Estimates of the Euro Area Output Gap," CEPR Discussion Papers 7763, C.E.P.R. Discussion Papers.
    17. Barro, Robert J, 2000. "Inequality and Growth in a Panel of Countries," Journal of Economic Growth, Springer, vol. 5(1), pages 5-32, March.
    18. Danny Quah, 1997. "Empirics for Growth and Distribution," CEP Discussion Papers dp0324, Centre for Economic Performance, LSE.
    19. Vladimir Zhuravlyov & Natalia Varkova & Sergei Aliukov & Tatyana Khudyakova, 2018. "Strategic Aspects of Ensuring Sustainable Development of Gold Enterprises of the Russian Federation," Sustainability, MDPI, vol. 10(12), pages 1-18, November.
    20. Cristina Raluca Gh. Popescu & Gheorghe N. Popescu, 2019. "An Exploratory Study Based on a Questionnaire Concerning Green and Sustainable Finance, Corporate Social Responsibility, and Performance: Evidence from the Romanian Business Environment," JRFM, MDPI, vol. 12(4), pages 1-79, October.
    21. repec:ucp:bkecon:9780226316529 is not listed on IDEAS
    22. Quah, Danny T, 1997. "Empirics for Growth and Distribution: Stratification, Polarization, and Convergence Clubs," Journal of Economic Growth, Springer, vol. 2(1), pages 27-59, March.
    23. Sommers, Paul M & Suits, Daniel B, 1971. "A Cross-Section Model of Economic Growth," The Review of Economics and Statistics, MIT Press, vol. 53(2), pages 121-128, May.
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    1. Larissa M. Batrancea & Mehmet Ali Balcı & Ömer Akgüller & Lucian Gaban, 2022. "What Drives Economic Growth across European Countries? A Multimodal Approach," Mathematics, MDPI, vol. 10(19), pages 1-20, October.

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