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Sustainability of Farms in EU Countries in the Context of Income Indicators: Regression Analysis Based on a New Classification

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  • Alena Andrejovská

    (Faculty of Economics, Department of Finance, Technical University of Košice, 04200 Kosice, Slovakia)

  • Jozef Glova

    (Faculty of Economics, Department of Banking and Investment, Technical University of Košice, 04200 Kosice, Slovakia)

Abstract

The sustainability of agriculture in the common market of the European Union is mainly influenced by the income of agricultural enterprises, which reflects the development potential of the entire sector. The present contribution deals with the importance of income indicators for the long-term sustainability of agricultural enterprises. We aimed to identify and quantify statistically significant determinants of the main income indicators of agricultural enterprises in individual countries of the European Union—namely, the net added value of the farm expressed per unit of agricultural work, the family farm income per family work unit, and the net farm income. We performed a linear regression analysis, in which the statistical significance of independent variables was gradually tested, including economic and environmental indicators, the economic size of the enterprise, total subsidies per hectare, depreciation, taxes, and wages. The established goal was complemented by a correlation analysis tracking the dependence between the economic size of enterprises—which is presented in the literature as a decisive indicator—and the tax burden in EU countries. We used the Farm Accountancy Data Network’s harmonised database for 2009–2018. The regression analysis results confirmed the environmental indicators’ statistical significance. Furthermore, the results of the correlation analysis confirmed the proposed hypothesis that the size of the company is a strong indicator and affects the tax burden of agricultural enterprises.

Suggested Citation

  • Alena Andrejovská & Jozef Glova, 2022. "Sustainability of Farms in EU Countries in the Context of Income Indicators: Regression Analysis Based on a New Classification," Agriculture, MDPI, vol. 12(11), pages 1-14, November.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:11:p:1884-:d:967762
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