IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i17p10761-d900855.html
   My bibliography  Save this article

Estimating Supply and Demand of Organic Seeds in Europe Using Survey Data and MI Techniques

Author

Listed:
  • Francesco Solfanelli

    (Department of Agricultural, Food and Environmental Sciences (D3A), Università Politecnica delle Marche, Via Brecce Bianche, 60131 Ancona, Italy)

  • Emel Ozturk

    (Department of Agricultural, Food and Environmental Sciences (D3A), Università Politecnica delle Marche, Via Brecce Bianche, 60131 Ancona, Italy)

  • Emilia Cubero Dudinskaya

    (Department of Agricultural, Food and Environmental Sciences (D3A), Università Politecnica delle Marche, Via Brecce Bianche, 60131 Ancona, Italy)

  • Serena Mandolesi

    (Department of Agricultural, Food and Environmental Sciences (D3A), Università Politecnica delle Marche, Via Brecce Bianche, 60131 Ancona, Italy)

  • Stefano Orsini

    (Organic Research Centre, Trent Lodge, Stroud Road, Cirencester, Gloucestershire GL7 6JN, UK)

  • Monika Messmer

    (Research Institute of Organic Agriculture (FiBL), Ackerstrasse 113, 5070 Frick, Switzerland)

  • Simona Naspetti

    (Dipartimento di Scienze e Ingegneria della Materia, dell’Ambiente ed Urbanistica (SIMAU), Università Politecnica delle Marche, Via Brecce Bianche, 60131 Ancona, Italy)

  • Freya Schaefer

    (FiBL Deutschland, Kasseler Straße 1a, 60486 Frankfurt am Main, Germany)

  • Eva Winter

    (Research Institute of Organic Agriculture (FiBL), Ackerstrasse 113, 5070 Frick, Switzerland)

  • Raffaele Zanoli

    (Department of Agricultural, Food and Environmental Sciences (D3A), Università Politecnica delle Marche, Via Brecce Bianche, 60131 Ancona, Italy)

Abstract

The lack of sufficient information about organic seed production and use is among the key factors affecting the development of the organic seed market in the EU. Currently, only very basic organic seed market data are being reported at the country level. Those available from each member state are seldom comparable over time between countries and sometimes even within one country. This study provides the first overall statistics on European organic seed supply and demand. Estimates of the organic seed demand and supply of twelve important crops in EU organic agriculture are provided by developing and testing innovative approaches to improve data collection and analysis, such as multiple imputation (MI) techniques to estimate missing values. The estimates are based on data extracted from official EU datasets from 2014 to 2018 and collected by an online survey of 756 farmers, as well as various expert assessments across the EU. The results were provided by four EU geographical regions, with a specific focus on wheat, lucerne, carrot, and apple. Although strong sector and regional differences currently characterise the organic seed market, organic seed demand considerably exceeds supply for most crops. Generally, farms in the central and northern regions revealed a higher organic seed supply than those in the southern and eastern regions, and organic seed supply is higher for wheat than other crops. A significant output of this study is the development of recommendations to improve methodologies to increase the transparency and availability of organic seed market data.

Suggested Citation

  • Francesco Solfanelli & Emel Ozturk & Emilia Cubero Dudinskaya & Serena Mandolesi & Stefano Orsini & Monika Messmer & Simona Naspetti & Freya Schaefer & Eva Winter & Raffaele Zanoli, 2022. "Estimating Supply and Demand of Organic Seeds in Europe Using Survey Data and MI Techniques," Sustainability, MDPI, vol. 14(17), pages 1-23, August.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:17:p:10761-:d:900855
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/17/10761/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/17/10761/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. repec:ipt:iptwpa:jrc80822 is not listed on IDEAS
    2. Edwin Nuijten & Monika M. Messmer & Edith T. Lammerts van Bueren, 2016. "Concepts and Strategies of Organic Plant Breeding in Light of Novel Breeding Techniques," Sustainability, MDPI, vol. 9(1), pages 1-19, December.
    3. Andrew Briggs & Taane Clark & Jane Wolstenholme & Philip Clarke, 2003. "Missing.... presumed at random: cost‐analysis of incomplete data," Health Economics, John Wiley & Sons, Ltd., vol. 12(5), pages 377-392, May.
    4. Susanne Padel & Stefano Orsini & Francesco Solfanelli & Raffaele Zanoli, 2021. "Can the Market Deliver 100% Organic Seed and Varieties in Europe?," Sustainability, MDPI, vol. 13(18), pages 1-14, September.
    5. Wesley Eddings & Yulia Marchenko, 2012. "Diagnostics for multiple imputation in Stata," Stata Journal, StataCorp LP, vol. 12(3), pages 353-367, September.
    6. Kobi Abayomi & Andrew Gelman & Marc Levy, 2008. "Diagnostics for multivariate imputations," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 57(3), pages 273-291, June.
    7. Stefano Orsini & Ambrogio Costanzo & Francesco Solfanelli & Raffaele Zanoli & Susanne Padel & Monika M. Messmer & Eva Winter & Freya Schaefer, 2020. "Factors Affecting the Use of Organic Seed by Organic Farmers in Europe," Sustainability, MDPI, vol. 12(20), pages 1-16, October.
    Full references (including those not matched with items on IDEAS)

    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. Freya Schäfer & Kaja Gutzen & Maaike Raaijmakers & Katharina Meyer & Xenia Gatzert & Martin Sommer & Ágnes Bruszik & Monika M. Messmer, 2022. "Securing Commitments from Stakeholders in 10 EU Member States—The Organic Seed Declaration to Foster Stakeholder Involvement," Sustainability, MDPI, vol. 14(15), pages 1-13, July.
    2. M. Carreras & M. García-Goñi & P. Ibern & J. Coderch & L. Vall-Llosera & J. Inoriza, 2011. "Estimates of patient costs related with population morbidity: can indirect costs affect the results?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 12(4), pages 289-295, August.
    3. Gerko Vink & Laurence E. Frank & Jeroen Pannekoek & Stef Buuren, 2014. "Predictive mean matching imputation of semicontinuous variables," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(1), pages 61-90, February.
    4. Martin, Eisele & Zhu, Junyi, 2013. "Multiple imputation in a complex household survey - the German Panel on Household Finances (PHF): challenges and solutions," MPRA Paper 57666, University Library of Munich, Germany.
    5. Masa, Rainier & Khan, Zoheb & Chowa, Gina, 2020. "Youth food insecurity in Ghana and South Africa: Prevalence, socioeconomic correlates, and moderation effect of gender," Children and Youth Services Review, Elsevier, vol. 116(C).
    6. Samuel C. M. Faulconer & M. Rachél Hveem & Mikaela J. Dufur, 2022. "Gendered Associations between Single Parenthood and Child Behavior Problems in the United Kingdom," IJERPH, MDPI, vol. 19(24), pages 1-16, December.
    7. Rohe, Sebastian & Oltmer, Marie & Wolter, Hendrik & Gmeiner, Nina & Tschersich , Julia, 2022. "Forever Niche: Why do organic vegetable varieties not diffuse?," Papers in Innovation Studies 2022/8, Lund University, CIRCLE - Centre for Innovation Research.
    8. Kobi Abayomi & Gonzalo Pizarro, 2013. "Monitoring Human Development Goals: A Straightforward (Bayesian) Methodology for Cross-National Indices," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 110(2), pages 489-515, January.
    9. Kilic, Talip & Zezza, Alberto & Carletto, Calogero & Savastano, Sara, 2017. "Missing(ness) in Action: Selectivity Bias in GPS-Based Land Area Measurements," World Development, Elsevier, vol. 92(C), pages 143-157.
    10. Jörg Drechsler, 2011. "Multiple imputation in practice—a case study using a complex German establishment survey," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(1), pages 1-26, March.
    11. Breitwieser, Anja & Wick, Katharina, 2016. "What We Miss By Missing Data: Aid Effectiveness Revisited," World Development, Elsevier, vol. 78(C), pages 554-571.
    12. Janet MacNeil Vroomen & Iris Eekhout & Marcel G. Dijkgraaf & Hein van Hout & Sophia E. de Rooij & Martijn W. Heymans & Judith E. Bosmans, 2016. "Multiple imputation strategies for zero-inflated cost data in economic evaluations: which method works best?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 17(8), pages 939-950, November.
    13. repec:jss:jstsof:29:i09 is not listed on IDEAS
    14. Siddique, Juned & Harel, Ofer, 2009. "MIDAS: A SAS Macro for Multiple Imputation Using Distance-Aided Selection of Donors," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 29(i09).
    15. Burns, Christopher & Prager, Daniel & Ghosh, Sujit & Goodwin, Barry, 2015. "Imputing for Missing Data in the ARMS Household Section: A Multivariate Imputation Approach," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205291, Agricultural and Applied Economics Association.
    16. Roman Matkovskyy, 2016. "A comparison of pre- and post-crisis efficiency of OECD countries: evidence from a model with temporal heterogeneity in time and unobservable individual effect," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 13(2), pages 135-167, December.
    17. Agnieszka Szparaga & Maciej Kuboń & Sławomir Kocira & Ewa Czerwińska & Anna Pawłowska & Patryk Hara & Zbigniew Kobus & Dariusz Kwaśniewski, 2019. "Towards Sustainable Agriculture—Agronomic and Economic Effects of Biostimulant Use in Common Bean Cultivation," Sustainability, MDPI, vol. 11(17), pages 1-21, August.
    18. Richard Grieve & John Cairns & Simon G. Thompson, 2010. "Improving costing methods in multicentre economic evaluation: the use of multiple imputation for unit costs," Health Economics, John Wiley & Sons, Ltd., vol. 19(8), pages 939-954, August.
    19. Kilic,Talip & Yacoubou Djima,Ismael & Carletto,Calogero & Kilic,Talip & Yacoubou Djima,Ismael & Carletto,Calogero, 2017. "Mission impossible? exploring the promise of multiple imputation for predicting missing GPS-based land area measures in household surveys," Policy Research Working Paper Series 8138, The World Bank.
    20. Gilles Grolleau & Alain Marciano & Naoufel Mzoughi, 2021. "Scandals : a ‘reset button’ to drive change?," Post-Print hal-02921614, HAL.
    21. Bernadette Li & John Cairns & James Fotheringham & Rommel Ravanan, 2016. "Predicting hospital costs for patients receiving renal replacement therapy to inform an economic evaluation," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 17(6), pages 659-668, July.

    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:jsusta:v:14:y:2022:i:17:p:10761-:d:900855. 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.