IDEAS home Printed from https://ideas.repec.org/a/eee/ecanpo/v80y2023icp1381-1395.html
   My bibliography  Save this article

Compensation schemes for plant quarantine pest costs: A case study for Germany

Author

Listed:
  • Filiptseva, Anna
  • Filler, Günther
  • Odening, Martin

Abstract

Plant quarantine pests worldwide cause considerable economic damage due to direct plant losses, eradication costs, and contamination measures. Although these losses can threaten the survival of a farm, no country to date has a universal compensation solution that encompasses all agricultural sectors. This paper aims to assess various compensation options by, firstly, calculating potential monetary losses caused by selected quarantine pests, which have not been studied in this context before. Secondly, we calculate farmers’ willingness to pay (WTP) for different components of compensation options in plant production using a discrete choice experiment (DCE). We find that monetary losses caused by quarantine pests vary significantly across products and sectors and are highest for intensive vegetable production. The DCE reveals a strong preference for the state compensation and heterogeneity of preferences among farmers depending on their experience with risk management options and perception of pest occurrence. The WTP analysis indicates that requiring preventive plant protection measures as a prerequisite for receiving compensation significantly deters farmers from participating in such a system, as its WTP exhibits the most negative impact compared to all other factors. Due to sectoral differences and path-dependent nature of compensation programs, a universal solution is rather not feasible. Sector-specific solutions must be considered, which does not rule out similar compensation approaches among sectors. Our findings are useful for designing compensation programs for quarantine plant pest cases.

Suggested Citation

  • Filiptseva, Anna & Filler, Günther & Odening, Martin, 2023. "Compensation schemes for plant quarantine pest costs: A case study for Germany," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 1381-1395.
  • Handle: RePEc:eee:ecanpo:v:80:y:2023:i:c:p:1381-1395
    DOI: 10.1016/j.eap.2023.10.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0313592623002527
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eap.2023.10.005?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jaakko Heikkilä & Jarkko K. Niemi & Katriina Heinola & Eero Liski & Sami Myyrä, 2016. "Anything left for animal disease insurance? A choiceexperiment approach," Review of Agricultural, Food and Environmental Studies, INRA Department of Economics, vol. 97(4), pages 237-249.
    2. Jürgen Meyerhoff & Ulf Liebe, 2009. "Status Quo Effect in Choice Experiments: Empirical Evidence on Attitudes and Choice Task Complexity," Land Economics, University of Wisconsin Press, vol. 85(3), pages 515-528.
    3. Thomas Dohmen & Armin Falk & David Huffman & Uwe Sunde & Jürgen Schupp & Gert G. Wagner, 2011. "Individual Risk Attitudes: Measurement, Determinants, And Behavioral Consequences," Journal of the European Economic Association, European Economic Association, vol. 9(3), pages 522-550, June.
    4. Douadia Bougherara & Xavier Gassmann & Laurent Piet & Arnaud Reynaud, 2017. "Structural estimation of farmers’ risk and ambiguity preferences: a field experiment," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 44(5), pages 782-808.
    5. Daniel Hellerstein & Nathaniel Higgins & John Horowitz, 2013. "The predictive power of risk preference measures for farming decisions -super-†," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 40(5), pages 807-833, December.
    6. Greene, William H. & Hensher, David A., 2003. "A latent class model for discrete choice analysis: contrasts with mixed logit," Transportation Research Part B: Methodological, Elsevier, vol. 37(8), pages 681-698, September.
    7. Arne Hole & Julie Kolstad, 2012. "Mixed logit estimation of willingness to pay distributions: a comparison of models in preference and WTP space using data from a health-related choice experiment," Empirical Economics, Springer, vol. 42(2), pages 445-469, April.
    8. Brian Wansink, 2003. "Farmers' Preferences for Crop Insurance Attributes," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 25(2), pages 415-429.
    9. Johannes Möllmann & Marius Michels & Oliver Musshoff, 2019. "German farmers’ acceptance of subsidized insurance associated with reduced direct payments," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 79(3), pages 408-424, May.
    10. Luisa Menapace & Gregory Colson & Roberta Raffaelli, 2016. "A comparison of hypothetical risk attitude elicitation instruments for explaining farmer crop insurance purchases," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 43(1), pages 113-135.
    11. Heinola, Katriina, 2016. "Anything left for animal disease insurance? A choice experiment approach," 156th Seminar, October 4, 2016, Wageningen, The Netherlands 249985, European Association of Agricultural Economists.
    12. Douadia Bougherara & Xavier Gassmann & Laurent Piet & Arnaud Reynaud, 2017. "Corrigendum: Structural estimation of farmers’ risk and ambiguity preferences: a field experiment," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 44(5), pages 809-809.
    13. Bate, Andrew M. & Jones, Glyn & Kleczkowski, Adam & Touza, Julia, 2021. "Modelling the effectiveness of collaborative schemes for disease and pest outbreak prevention," Ecological Modelling, Elsevier, vol. 442(C).
    14. Ranjan Kumar Ghosh & Shweta Gupta & Vartika Singh & Patrick S. Ward, 2021. "Demand for Crop Insurance in Developing Countries: New Evidence from India," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(1), pages 293-320, February.
    15. Kevin Schneider & Wopke van der Werf & Martina Cendoya & Monique Mourits & Juan A. Navas-Cortés & Antonio Vicent & Alfons Oude Lansink, 2020. "Impact of Xylella fastidiosa subspecies pauca in European olives," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(17), pages 9250-9259, April.
    16. Hirschauer, Norbert & Grüner, Sven & Mußhoff, Oliver & Becker, Claudia & Jantsch, Antje, 2020. "Can p-values be meaningfully interpreted without random sampling?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 14, pages 71-91.
    17. Marcel F. Jonker & Bas Donkers & Esther de Bekker‐Grob & Elly A. Stolk, 2019. "Attribute level overlap (and color coding) can reduce task complexity, improve choice consistency, and decrease the dropout rate in discrete choice experiments," Health Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 350-363, March.
    18. Filiptseva, Anna & Filler, Günther & Odening, Martin, 2022. "Compensation Options for Quarantine Costs in Plant Production," 62nd Annual Conference, Stuttgart, Germany, September 7-9, 2022 329595, German Association of Agricultural Economists (GEWISOLA).
    19. Emily Lancsar & Denzil G. Fiebig & Arne Risa Hole, 2017. "Discrete Choice Experiments: A Guide to Model Specification, Estimation and Software," PharmacoEconomics, Springer, vol. 35(7), pages 697-716, July.
    20. Junyi Shen, 2009. "Latent class model or mixed logit model? A comparison by transport mode choice data," Applied Economics, Taylor & Francis Journals, vol. 41(22), pages 2915-2924.
    21. Moshe Ben-Akiva & Joffre Swait, 1986. "The Akaike Likelihood Ratio Index," Transportation Science, INFORMS, vol. 20(2), pages 133-136, May.
    22. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    23. Bruce J. Sherrick & Gary D. Schnitkey & Paul N. Ellinger & Peter J. Barry & Brian Wansink, 2003. "Farmers' Preferences for Crop Insurance Attributes," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 25(2), pages 415-429.
    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. Filiptseva, Anna & Filler, Günther & Odening, Martin, 2022. "Compensation Options for Quarantine Costs in Plant Production," 62nd Annual Conference, Stuttgart, Germany, September 7-9, 2022 329595, German Association of Agricultural Economists (GEWISOLA).
    2. Nordmeyer, Eike Florenz & Danne, Michael & Musshoff, Oliver, 2023. "Can satellite-retrieved data increase farmers' willingness to insure against drought? – Insights from Germany," Agricultural Systems, Elsevier, vol. 211(C).
    3. Fabio G., Santeramo & Ilaria, Russo & Emilia, Lamonaca, 2022. "Italian subsidised crop insurance: what the role of policy changes," MPRA Paper 115299, University Library of Munich, Germany.
    4. Chen, Gang & Ratcliffe, Julie & Milte, Rachel & Khadka, Jyoti & Kaambwa, Billingsley, 2021. "Quality of care experience in aged care: An Australia-Wide discrete choice experiment to elicit preference weights," Social Science & Medicine, Elsevier, vol. 289(C).
    5. Bougherara, Douadia & Lapierre, Margaux & Préget, Raphaële & Sauquet, Alexandre, 2021. "Do farmers prefer increasing, decreasing, or stable payments in Agri-environmental schemes?," Ecological Economics, Elsevier, vol. 183(C).
    6. Jørgensen, Sisse Liv & Termansen, Mette & Pascual, Unai, 2020. "Natural insurance as condition for market insurance: Climate change adaptation in agriculture," Ecological Economics, Elsevier, vol. 169(C).
    7. Kotu, Bekele Hundie & Oyinbo, Oyakhilomen & Hoeschle-Zeledon, Irmgard & Nurudeen, Abdul Rahman & Kizito, Fred & Boyubie, Benedict, 2022. "Smallholder farmers’ preferences for sustainable intensification attributes in maize production: Evidence from Ghana," World Development, Elsevier, vol. 152(C).
    8. Nordmeyer, Eike Florenz, 2023. "German farmers' perceived usefulness of satellite-based index insurance - Insights from a transtheoretical model," 97th Annual Conference, March 27-29, 2023, Warwick University, Coventry, UK 334557, Agricultural Economics Society - AES.
    9. Camille Tevenart & Marielle Brunette, 2021. "Role of Farmers’ Risk and Ambiguity Preferences on Fertilization Decisions: An Experiment," Sustainability, MDPI, vol. 13(17), pages 1-27, August.
    10. Bougherara, Douadia & Lapierre, Margaux & Préget, Raphaële & Sauquet, Alexandre, 2021. "Do farmers prefer increasing, decreasing, or stable payments in Agri-environmental schemes?," Ecological Economics, Elsevier, vol. 183(C).
    11. Seong Ok Lyu, 2021. "Applying discrete choice models to understand sport tourists’ heterogeneous preferences for Winter Olympic travel products," Tourism Economics, , vol. 27(3), pages 482-499, May.
    12. Yoo, James & Ready, Richard C., 2014. "Preference heterogeneity for renewable energy technology," Energy Economics, Elsevier, vol. 42(C), pages 101-114.
    13. Espino, Raquel & Román, Concepción, 2020. "Valuation of transfer for bus users: The case of Gran Canaria," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 131-144.
    14. Daniele Pacifico, 2013. "On the role of unobserved preference heterogeneity in discrete choice models of labour supply," Empirical Economics, Springer, vol. 45(2), pages 929-963, October.
    15. Kanberger, Elke D. & Ziegler, Andreas, 2023. "On the preferences for an environmentally friendly and fair energy transition: A stated choice experiment for Germany," Energy Policy, Elsevier, vol. 182(C).
    16. Richartz, P. Christoph & Abdulai, Awudu & Kornher, Lukas, 2020. "Attribute Non Attendance and Consumer Preferences for Online Food Products in Germany," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 69(1), March.
    17. Xiong, Yingge & Tobias, Justin L. & Mannering, Fred L., 2014. "The analysis of vehicle crash injury-severity data: A Markov switching approach with road-segment heterogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 109-128.
    18. Vásquez Lavin, Felipe & Barrientos, Manuel & Castillo, Álvaro & Herrera, Iván & Ponce Oliva, Roberto D., 2020. "Firewood certification programs: Key attributes and policy implications," Energy Policy, Elsevier, vol. 137(C).
    19. Hurtubia, Ricardo & Nguyen, My Hang & Glerum, Aurélie & Bierlaire, Michel, 2014. "Integrating psychometric indicators in latent class choice models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 64(C), pages 135-146.
    20. Robert Huber & Hang Xiong & Kevin Keller & Robert Finger, 2022. "Bridging behavioural factors and standard bio‐economic modelling in an agent‐based modelling framework," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(1), pages 35-63, February.

    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:eee:ecanpo:v:80:y:2023:i:c:p:1381-1395. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/economic-analysis-and-policy .

    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.