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Macroeconomic Factors of Economic Growth in the European Union in 2000-2016: A Multidimensional Analysis

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  • Batóg Jacek

    (University of Szczecin, Szczecin, Poland)

  • Batóg Barbara

    (University of Szczecin, Szczecin, Poland)

Abstract

The creation of an effective growth policy requires the identification of its key determinants. The study used one of the methods of multidimensional analysis – discriminant analysis. It is widely used on a microeconomic scale, especially in the area of forecasting bankruptcy of enterprises, but in the area of economic growth, it has not been used in practice so far. In addition to the main objective of identifying the most important economic growth factors of the European Union countries in 2000-2016, the impact of the crisis and accession to the EU was examined. The statistical data sources were the databases of Eurostat and the Conference Board (Total Economy Database). The results obtained allowed us to conclude that the rate of Gross Domestic Product growth in the EU countries was determined by consumption, investment, export and labour productivity, and in periods of economic slowdown also public debt. The enlargement of the EU resulted in an increase in the importance of export.

Suggested Citation

  • Batóg Jacek & Batóg Barbara, 2019. "Macroeconomic Factors of Economic Growth in the European Union in 2000-2016: A Multidimensional Analysis," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 23(3), pages 1-14, September.
    • Handle: RePEc:vrs:eaiada:v:23:y:2019:i:3:p:1-14:n:1
    DOI: 10.15611/eada.2019.3.01
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    References listed on IDEAS

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    Keywords

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    JEL classification:

    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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