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 Modeling Structural Changes in the Livestock Market in the European Union Piskunova O. V., Savina S. S., Kravchenko V. L., Dronchak O. V., Matsyshena S. M.
Piskunova, Olena V. et al. (2025) “Modeling Structural Changes in the Livestock Market in the European Union.” Business Inform 2:732–732. https://doi.org/10.32983/2222-4459-2025-2-732-732
Section: Economic and Mathematical Modeling
Article is written in UkrainianDownloads/views: 0 | |
UDC 519.866
Abstract: The aim of this study is to analyze structural changes in the livestock product market in the European Union countries from 2000 to 2022, identifying trends and features of the development of the livestock industry in the context of implementing a comprehensive strategy for the restructuring of agriculture within the framework of the Green Deal. The initial dataset of statistical information contained an excessively extensive list of various types of livestock products; therefore, the research primarily focused on those produced in the largest volumes. By 2022, the largest volumes in meat production were attributed to pork, poultry, and cattle. To analyze the production of the main types of livestock products during 2000–2022 and to allow for the calculation of forecasts for future periods, a trend construction approach was applied for time series. The application of linear trend analysis was considered for the data of each of the three time series. The analysis of the results for each of the models allows us to draw the following conclusions: there is a constant increase in pork production. The production of poultry meat is also growing, and this growth is more rapid than that of pork production, while cattle meat production exhibits the opposite trend and is continually decreasing. Since the obtained trends have opposite directions, the next step involved examining a time series that describes the total production of livestock products, allowing for an accurate representation of the overall production picture. Linear and nonlinear trends were constructed for the time series that describes total production. A logistic curve was used as the nonlinear trend. The fact that the behavior of the time series data is best described by the logistic curve indicates that in the dynamics of the livestock market’s development, a transition to a new level is occurring. The analysis of the obtained trend indicates that during the period from 2000 to 2022, livestock product manufacturers in the European Union continued to increase production volumes. However, due to the adoption of the Green Deal strategy and the intensive campaign in the media against meat consumption, recent growth has halted, and some stabilization is observed. There are also certain changes in the structure of the livestock market. As a forecast for the future period, a further decline in the production of cattle can be indicated; in spite of this, due to the increase in the production of other types of livestock, there is stabilization of the overall production near the current level, approximately 144 kg per year per person. The conducted analysis of livestock production data in the EU countries forms the basis for further research that should continue in the direction of seeking development prospects for the domestic livestock industry in the context of integration into the European economic space.
Keywords: livestock market, time series, linear trend, logistics curve.
Fig.: 5. Tabl.: 5. Formulae: 4. Bibl.: 11.
Piskunova Olena V. – Doctor of Sciences (Economics), Professor, Professor, Department of Mathematical Modeling and Statistics, Kyiv National Economic University named after Vadym Hetman (54/1 Beresteiskyi Ave., Kyiv, 03057, Ukraine) Email: [email protected] Savina Svitlana S. – Candidate of Sciences (Economics), Associate Professor, Associate Professor, Department of Mathematical Modeling and Statistics, Kyiv National Economic University named after Vadym Hetman (54/1 Beresteiskyi Ave., Kyiv, 03057, Ukraine) Email: [email protected] Kravchenko Viktoriia L. – Senior Lecturer, Department of Mathematical Modeling and Statistics, Kyiv National Economic University named after Vadym Hetman (54/1 Beresteiskyi Ave., Kyiv, 03057, Ukraine) Email: [email protected] Dronchak Oleksandr V. – Postgraduate Student, Department of Mathematical Modeling and Statistics, Kyiv National Economic University named after Vadym Hetman (54/1 Beresteiskyi Ave., Kyiv, 03057, Ukraine) Email: [email protected] Matsyshena Sofiia M. – Masters Student, Kyiv National Economic University named after Vadym Hetman (54/1 Beresteiskyi Ave., Kyiv, 03057, Ukraine) Email: [email protected]
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