IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v11y2021i4p323-d531041.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/11/4/323/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/11/4/323/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. 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.
    3. Jussi Lankoski, 2016. "Alternative Payment Approaches for Biodiversity Conservation in Agriculture," OECD Food, Agriculture and Fisheries Papers 93, OECD Publishing.
    4. 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.
    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. "Environmental 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bórawski, Piotr & Bełdycka-Bórawska, Aneta & Jankowski, Krzysztof Jóżef & Dubis, Bogdan & Dunn, James W., 2020. "Development of wind energy market in the European Union," Renewable Energy, Elsevier, vol. 161(C), pages 691-700.
    2. Yao Hu & Tai-Hua Yan & Feng-Wen Chen, 2020. "Energy and Environment Performance of Resource-Based Cities in China: A Non-Parametric Approach for Estimating Hyperbolic Distance Function," IJERPH, MDPI, vol. 17(13), pages 1-23, July.
    3. Qunli Wu & Shuting Gu, 2021. "Exploring the focus of future CO2 emission reduction in China's industrial sectors," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 11(4), pages 682-696, August.
    4. Li, Min & Yang, Yi & He, Zhaoshuang & Guo, Xinbo & Zhang, Ruisheng & Huang, Bingqing, 2023. "A wind speed forecasting model based on multi-objective algorithm and interpretability learning," Energy, Elsevier, vol. 269(C).
    5. Javier Alejo & Antonio Galvao & Gabriel Montes-Rojas & Walter Sosa-Escudero, 2015. "Tests for normality in linear panel-data models," Stata Journal, StataCorp LP, vol. 15(3), pages 822-832, September.
    6. James Mitchell & Richard J. Smith & Martin R. Weale, 2013. "Efficient Aggregation Of Panel Qualitative Survey Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(4), pages 580-603, June.
    7. Rana Muhammad Adnan & Zhongmin Liang & Xiaohui Yuan & Ozgur Kisi & Muhammad Akhlaq & Binquan Li, 2019. "Comparison of LSSVR, M5RT, NF-GP, and NF-SC Models for Predictions of Hourly Wind Speed and Wind Power Based on Cross-Validation," Energies, MDPI, vol. 12(2), pages 1-22, January.
    8. Dobbs, Thomas L., 2006. "Working Lands Agri-environmental Policy Options and Issues for the Next United States Farm Bill," Economics Staff Papers 32013, South Dakota State University, Department of Economics.
    9. Dongxiao Niu & Yi Liang & Wei-Chiang Hong, 2017. "Wind Speed Forecasting Based on EMD and GRNN Optimized by FOA," Energies, MDPI, vol. 10(12), pages 1-18, December.
    10. Zonggui Yao & Chen Wang, 2018. "A Hybrid Model Based on A Modified Optimization Algorithm and An Artificial Intelligence Algorithm for Short-Term Wind Speed Multi-Step Ahead Forecasting," Sustainability, MDPI, vol. 10(5), pages 1-33, May.
    11. Kohlbrecher, Britta & Merkl, Christian, 2022. "Business cycle asymmetries and the labor market," Journal of Macroeconomics, Elsevier, vol. 73(C).
    12. Yiqi Chu & Chengcai Li & Yefang Wang & Jing Li & Jian Li, 2016. "A Long-Term Wind Speed Ensemble Forecasting System with Weather Adapted Correction," Energies, MDPI, vol. 9(11), pages 1-20, October.
    13. Masayuki Hirukawa & Mari Sakudo, 2016. "Testing Symmetry of Unknown Densities via Smoothing with the Generalized Gamma Kernels," Econometrics, MDPI, vol. 4(2), pages 1-27, June.
    14. Koo, Junmo & Han, Gwon Deok & Choi, Hyung Jong & Shim, Joon Hyung, 2015. "Wind-speed prediction and analysis based on geological and distance variables using an artificial neural network: A case study in South Korea," Energy, Elsevier, vol. 93(P2), pages 1296-1302.
    15. Christoph Gortz & John D. Tsoukalas, 2013. "Learning, Capital Embodied Technology and Aggregate Fluctuations," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 16(4), pages 708-723, October.
    16. Liu, Hui & Tian, Hong-qi & Pan, Di-fu & Li, Yan-fei, 2013. "Forecasting models for wind speed using wavelet, wavelet packet, time series and Artificial Neural Networks," Applied Energy, Elsevier, vol. 107(C), pages 191-208.
    17. Wang, Jujie & Li, Yaning, 2018. "Multi-step ahead wind speed prediction based on optimal feature extraction, long short term memory neural network and error correction strategy," Applied Energy, Elsevier, vol. 230(C), pages 429-443.
    18. Turan Bali & Panayiotis Theodossiou, 2007. "A conditional-SGT-VaR approach with alternative GARCH models," Annals of Operations Research, Springer, vol. 151(1), pages 241-267, April.
    19. Jasman Tuyon & Zamri Ahmada, 2016. "Behavioural finance perspectives on Malaysian stock market efficiency," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 16(1), pages 43-61, March.
    20. Angus Moore, 2017. "Measuring Economic Uncertainty and Its Effects," The Economic Record, The Economic Society of Australia, vol. 93(303), pages 550-575, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:11:y:2021:i:4:p:323-:d:531041. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.