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Development of Organic Milk Production in Poland on the Background of the EU

Author

Listed:
  • Piotr Bórawski

    (Department of Agrotechnology and Agribusiness, Faculty of Agriculture and Forestry, University of Warmia and Mazury in Olsztyn, 10-719 Olsztyn, Poland)

  • Marek Bartłomiej Bórawski

    (Faculty of Law and Administration, University of Warmia and Mazury in Olsztyn, 10-725 Olsztyn, Poland)

  • Andrzej Parzonko

    (Department of Economics and Organization of Enterprises, Institute of Economics and Finance, Warsaw University of Life Science—SGGW-Warsaw, 02-787 Warszawa, Poland)

  • Ludwik Wicki

    (Department of Economics and Organization of Enterprises, Institute of Economics and Finance, Warsaw University of Life Science—SGGW-Warsaw, 02-787 Warszawa, Poland)

  • Tomasz Rokicki

    (Department of Logistics, Institute of Economics and Finance, Warsaw University of Life Science—SGGW-Warsaw, 02-787 Warszawa, Poland)

  • Aleksandra Perkowska

    (Department of Logistics, Institute of Economics and Finance, Warsaw University of Life Science—SGGW-Warsaw, 02-787 Warszawa, Poland)

  • James William Dunn

    (Department of Agricultural Economics, Sociology, and Education, Faculty of Agricultural Sciences, Pennsylvania State University, University Park, PA 16802, USA)

Abstract

Organic milk production is an environmentally friendly production system based on local forage and a ban on using chemical fertilizers and certain other rules. Organic milk is considered to be healthier and is gaining attention worldwide. The market for organic products is increasing. The aim of the paper was to analyze changes in the development of organic dairy production in Poland in the context of the EU. We analyzed the changes on the European Union (EU) level and the Poland level. To analyze the changes in organic milk production on European Union level, we used the autoregressive integrated moving average model (ARIMA). Our results show that both organic milk production and the farm area used for organic production will increase. Moreover, we analyzed the organic dairy farms running rural accountancy within the Farm Accountancy Data Network (FADN) in Poland in the years 2007–2018. We used tabular and graphic methods to present the data. In the analysis the methods of correlation and regression were used. Germany, France, Austria, and Great Britain are the countries with the largest numbers of organic dairy cows. Our prognosis examined the development of organic milk production in the European Union (EU). The number of cows on dairy organic farms will increase in most countries in the EU. Then, we analyzed the impact of the chosen factors on three dependent variables: organic milk production, total production of organic dairy farms, and income from family farms. The most important independent variables were cow numbers, the value of fixed assets, the value of current assets, long-term debt, and short-term debt.

Suggested Citation

  • Piotr Bórawski & Marek Bartłomiej Bórawski & Andrzej Parzonko & Ludwik Wicki & Tomasz Rokicki & Aleksandra Perkowska & James William Dunn, 2021. "Development of Organic Milk Production in Poland on the Background of the EU," Agriculture, MDPI, vol. 11(4), pages 1-25, April.
    • Handle: RePEc:gam:jagris:v:11:y:2021:i:4:p:323-:d:531041
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    References listed on IDEAS

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    1. Agnieszka Kurdyś-Kujawska & Agnieszka Strzelecka & Danuta Zawadzka, 2021. "The Impact of Crop Diversification on the Economic Efficiency of Small Farms in Poland," Agriculture, MDPI, vol. 11(3), pages 1-21, March.
    2. Jussi Lankoski, 2016. "Alternative Payment Approaches for Biodiversity Conservation in Agriculture," OECD Food, Agriculture and Fisheries Papers 93, OECD Publishing.
    3. Adenuga, Adewale Henry & Davis, John & Hutchinson, George & Patton, Myles & Donnellan, Trevor, 2019. "Environmental technical efficiency and phosphorus pollution abatement cost in dairy farms : A parametric hyperbolic distance function approach," 93rd Annual Conference, April 15-17, 2019, Warwick University, Coventry, UK 289576, Agricultural Economics Society - AES.
    4. Jushan Bai & Serena Ng, 2005. "Tests for Skewness, Kurtosis, and Normality for Time Series Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 49-60, January.
    5. Rotz, C. Alan & Holly, Michael & de Long, Aaron & Egan, Franklin & Kleinman, Peter J.A., 2020. "An environmental assessment of grass-based dairy production in the northeastern United States," Agricultural Systems, Elsevier, vol. 184(C).
    6. Dimitri, Carolyn & Oberholtzer, Lydia, 2006. "EU and U.S. Organic Markets Face Strong Demand Under Different Policies," Amber Waves:The Economics of Food, Farming, Natural Resources, and Rural America, United States Department of Agriculture, Economic Research Service, pages 1-8, February.
    7. Erdem, Ergin & Shi, Jing, 2011. "ARMA based approaches for forecasting the tuple of wind speed and direction," Applied Energy, Elsevier, vol. 88(4), pages 1405-1414, April.
    8. Czyżewski, Bazyli & Matuszczak, Anna & Grzelak, Aleksander & Guth, Marta & Majchrzak, Adam, 2019. "Environmentally Sustainable Value in Agriculture Revisited: How Investment Subsidies Foster Eco-Efficiency," Roczniki (Annals), Polish Association of Agricultural Economists and Agribusiness - Stowarzyszenie Ekonomistow Rolnictwa e Agrobiznesu (SERiA), vol. 2019(4).
    9. Adewale Henry Adenuga & John Davis & George Hutchinson & Trevor Donnellan & Myles Patton, 2019. "Environmental Efficiency and Pollution Costs of Nitrogen Surplus in Dairy Farms: A Parametric Hyperbolic Technology Distance Function Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(3), pages 1273-1298, November.
    10. de Jong, Piet & Penzer, Jeremy, 2004. "The ARMA model in state space form," Statistics & Probability Letters, Elsevier, vol. 70(1), pages 119-125, October.
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    Cited by:

    1. Beata Kalinowska & Piotr Bórawski & Aneta Bełdycka-Bórawska & Bogdan Klepacki & Aleksandra Perkowska & Tomasz Rokicki, 2022. "Sustainable Development of Agriculture in Member States of the European Union," Sustainability, MDPI, vol. 14(7), pages 1-21, March.
    2. Adam Pawlewicz & Wojciech Gotkiewicz & Katarzyna Brodzińska & Katarzyna Pawlewicz & Bartosz Mickiewicz & Paweł Kluczek, 2022. "Organic Farming as an Alternative Maintenance Strategy in the Opinion of Farmers from Natura 2000 Areas," IJERPH, MDPI, vol. 19(7), pages 1-22, March.
    3. Maria Zuba-Ciszewska & Aleksandra Kowalska & Aneta Brodziak & Louise Manning, 2023. "Organic Milk Production Sector in Poland: Driving the Potential to Meet Future Market, Societal and Environmental Challenges," Sustainability, MDPI, vol. 15(13), pages 1-21, June.
    4. Paweł Solarczyk & Tomasz Sakowski & Marcin Gołębiewski & Jan Slósarz & Grzegorz Grodkowski & Kinga Grodkowska & Luisa Biondi & Massimiliano Lanza & Antonio Natalello & Kamila Puppel, 2023. "The Impact of Calf Rearing with Foster Cows on Calf Health, Welfare, and Veal Quality in Dairy Farms," Agriculture, MDPI, vol. 13(9), pages 1-23, September.
    5. Juan D. Borrero & Jesus Mariscal, 2022. "Predicting Time SeriesUsing an Automatic New Algorithm of the Kalman Filter," Mathematics, MDPI, vol. 10(16), pages 1-13, August.
    6. Bogdan Klepacki & Barbara Kusto & Piotr Bórawski & Aneta Bełdycka-Bórawska & Konrad Michalski & Aleksandra Perkowska & Tomasz Rokicki, 2021. "Investments in Renewable Energy Sources in Basic Units of Local Government in Rural Areas," Energies, MDPI, vol. 14(11), pages 1-17, May.
    7. Aneta Bełdycka-Bórawska & Piotr Bórawski & Lisa Holden & Tomasz Rokicki & Bogdan Klepacki, 2022. "Factors Shaping Performance of Polish Biodiesel Producers Participating in the Farm Accountancy Data Network in the Context of the Common Agricultural Policy of the European Union," Energies, MDPI, vol. 15(19), pages 1-25, October.
    8. Piotr Bórawski & Aneta Bełdycka-Bórawska & Lisa Holden & Tomasz Rokicki, 2022. "The Role of Renewable Energy Sources in Electricity Production in Poland and the Background of Energy Policy of the European Union at the Beginning of the COVID-19 Crisis," Energies, MDPI, vol. 15(22), pages 1-17, November.

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