IDEAS home Printed from https://ideas.repec.org/a/ags/gjagec/368989.html
   My bibliography  Save this article

Using Cubic Splines in Crop Insurance Models – A Replication Study

Author

Listed:
  • Schmidt, Lorenz
  • Heydarli, Masud
  • Filler, Günther
  • Odening, Martin

Abstract

This study replicates the work of Bucheli et al. (2022) to evaluate the reliability and generalizability of their findings on the use of cubic spline methods in weather index insurance design in Eastern Germany. The study consists of two parts: a direct replication and an extended replication using different crops and another regional focus of yield data from Saxony, Germany. The direct replication confirms the original findings, while the extended replication reveals limitations in the model's risk reduction capacities. The gain in model fit, compared with daily temperature data, seems to be modest. It is questionable if an index insurance, which is solely based on temperature, will be considered as an attractive risk management tool, given the substantial basis risk that remains with farmers. The study highlights the importance of considering crop-specific risk profiles, regional climate, and agricultural conditions in insurance design. Moreover, our analysis highlights the relevance of FAIR (findable, accessible, interoperable, reusable) data for the performance of replication studies.

Suggested Citation

  • Schmidt, Lorenz & Heydarli, Masud & Filler, Günther & Odening, Martin, . "Using Cubic Splines in Crop Insurance Models – A Replication Study," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 74.
    • Handle: RePEc:ags:gjagec:368989
    DOI: 10.22004/ag.econ.368989
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/368989/files/2635_Schmidt_et_al.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.368989?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
    ---><---

    References listed on IDEAS

    as
    1. Marijn Velde & Francesco Tubiello & Anton Vrieling & Fayçal Bouraoui, 2012. "Impacts of extreme weather on wheat and maize in France: evaluating regional crop simulations against observed data," Climatic Change, Springer, vol. 113(3), pages 751-765, August.
    2. Joshua D. Woodard & Bruce J. Sherrick, 2011. "Estimation of Mixture Models using Cross-Validation Optimization: Implications for Crop Yield Distribution Modeling," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(4), pages 968-982.
    3. Schmidt, Lorenz & Odening, Martin & Schlanstein, Johann & Ritter, Matthias, 2022. "Exploring the weather-yield nexus with artificial neural networks," Agricultural Systems, Elsevier, vol. 196(C).
    4. Alan P Ker & Tor N Tolhurst, 2019. "On the Treatment of Heteroscedasticity in Crop Yield Data," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 101(4), pages 1247-1261.
    5. Richard E. Just & Quinn Weninger, 1999. "Are Crop Yields Normally Distributed?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(2), pages 287-304.
    6. Willemijn Vroege & Robert Finger, 2020. "Insuring Weather Risks in European Agriculture," EuroChoices, The Agricultural Economics Society, vol. 19(2), pages 54-62, August.
    7. Anthony Louis D'Agostino & Wolfram Schlenker, 2016. "Recent weather fluctuations and agricultural yields: implications for climate change," Agricultural Economics, International Association of Agricultural Economists, vol. 47(S1), pages 159-171, November.
    8. Anastassiadis Friederike & Feil Jan-Henning & Musshoff Oliver & Schilling Philipp, 2014. "Analysing Farmers’ Use of Price Hedging Instruments: An Experimental Approach," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 12(1), pages 181-192, January.
    9. Joshua D. Woodard & Philip Garcia, 2008. "Basis risk and weather hedging effectiveness," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 68(1), pages 99-117, May.
    10. Vedenov, Dmitry V. & Barnett, Barry J., 2004. "Efficiency of Weather Derivatives as Primary Crop Insurance Instruments," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 29(3), pages 1-17, December.
    11. Zhiwei Shen & Martin Odening & Ostap Okhrin, 2018. "Adaptive local parametric estimation of crop yields: implications for crop insurance rate making," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 45(2), pages 173-203.
    12. Calum G. Turvey, 2001. "Weather Derivatives for Specific Event Risks in Agriculture," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 23(2), pages 333-351.
    13. Martin Odening & Zhiwei Shen, 2014. "Challenges of insuring weather risk in agriculture," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 74(2), pages 188-199, July.
    14. Miroslav Trnka & Reimund P. Rötter & Margarita Ruiz-Ramos & Kurt Christian Kersebaum & Jørgen E. Olesen & Zdeněk Žalud & Mikhail A. Semenov, 2014. "Adverse weather conditions for European wheat production will become more frequent with climate change," Nature Climate Change, Nature, vol. 4(7), pages 637-643, July.
    15. M. Ritter & O. Mußhoff & M. Odening, 2014. "Minimizing Geographical Basis Risk of Weather Derivatives Using A Multi-Site Rainfall Model," Computational Economics, Springer;Society for Computational Economics, vol. 44(1), pages 67-86, June.
    16. Elodie Blanc & Wolfram Schlenker, 2017. "The Use of Panel Models in Assessments of Climate Impacts on Agriculture," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 11(2), pages 258-279.
    17. A. J. Challinor & J. Watson & D. B. Lobell & S. M. Howden & D. R. Smith & N. Chhetri, 2014. "A meta-analysis of crop yield under climate change and adaptation," Nature Climate Change, Nature, vol. 4(4), pages 287-291, April.
    18. Martin Odening & Zhiwei Shen, 2014. "Challenges of insuring weather risk in agriculture," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 74(2), pages 188-199, July.
    19. Bucheli, Janic & Dalhaus, Tobias & Finger, Robert, 2022. "Temperature effects on crop yields in heat index insurance," Food Policy, Elsevier, vol. 107(C).
    20. Ardian Harri & Keith H. Coble & Alan P. Ker & Barry J. Goodwin, 2011. "Relaxing Heteroscedasticity Assumptions in Area-Yield Crop Insurance Rating," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(3), pages 703-713.
    21. Zhanhui Chen & Yang Lu & Jinggong Zhang & Wenjun Zhu, 2024. "Managing Weather Risk with a Neural Network-Based Index Insurance," Management Science, INFORMS, vol. 70(7), pages 4306-4327, July.
    22. Albers, Hakon & Gornott, Christoph & Hüttel, Silke, 2017. "How do inputs and weather drive wheat yield volatility? The example of Germany," Food Policy, Elsevier, vol. 70(C), pages 50-61.
    23. Jing Zou & Martin Odening & Ostap Okhrin, 2024. "Data-driven determination of plant growth stages for improved weather index insurance design," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 84(4/5), pages 297-319, August.
    24. Jesse Tack & Keith Coble & Barry Barnett, 2018. "Warming temperatures will likely induce higher premium rates and government outlays for the U.S. crop insurance program," Agricultural Economics, International Association of Agricultural Economists, vol. 49(5), pages 635-647, September.
    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. Bucheli, Janic & Dalhaus, Tobias & Finger, Robert, 2022. "Temperature effects on crop yields in heat index insurance," Food Policy, Elsevier, vol. 107(C).
    2. Schmidt, Lorenz & Odening, Martin & Schlanstein, Johann & Ritter, Matthias, 2022. "Exploring the weather-yield nexus with artificial neural networks," Agricultural Systems, Elsevier, vol. 196(C).
    3. Schmitt, Jonas & Offermann, Frank & Söder, Mareike & Frühauf, Cathleen & Finger, Robert, 2022. "Extreme weather events cause significant crop yield losses at the farm level in German agriculture," Food Policy, Elsevier, vol. 112(C).
    4. Buchholz, Matthias & Musshoff, Oliver, 2014. "The role of weather derivatives and portfolio effects in agricultural water management," Agricultural Water Management, Elsevier, vol. 146(C), pages 34-44.
    5. Yan Sun, 2025. "Evaluating the Effectiveness of Weather Index Insurance: Empirical Assessment Framework and Policy Recommendations for Fair Premium Subsidies," Empirical Economics, Springer, vol. 69(1), pages 263-298, July.
    6. Doms, Juliane, "undated". "Put, call or strangle? About the challenges in designing weather index insurances to hedge performance risk in agriculture," 57th Annual Conference, Weihenstephan, Germany, September 13-15, 2017 261990, German Association of Agricultural Economists (GEWISOLA).
    7. Tappi, Marco & Carucci, Federica & Gatta, Giuseppe & Giuliani, Marcella Michela & Lamonaca, Emilia & Santeramo, Fabio Gaetano, 2023. "Temporal and design approaches and yield-weather relationships," MPRA Paper 117488, University Library of Munich, Germany.
    8. Shenan Wu & Barry K. Goodwin & Keith Coble, 2020. "Moral hazard and subsidized crop insurance," Agricultural Economics, International Association of Agricultural Economists, vol. 51(1), pages 131-142, January.
    9. Arora, Gaurav & Agarwal, Sandip K., 2020. "Agricultural input use and index insurance adoption: Concept and evidence," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304508, Agricultural and Applied Economics Association.
    10. Kleiman, Rachel M. & Characklis, Gregory W. & Kern, Jordan D., 2022. "Managing weather- and market price-related financial risks in algal biofuel production," Renewable Energy, Elsevier, vol. 200(C), pages 111-124.
    11. repec:ags:aaea22:335759 is not listed on IDEAS
    12. Yong Liu & Alan P. Ker, 2021. "Simultaneous borrowing of information across space and time for pricing insurance contracts: An application to rating crop insurance policies," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(1), pages 231-257, March.
    13. Barratt, Jonathan & Kath, Jarrod & Mushtaq, Shahbaz & Collins, Brian & Chenu, Karine & Christopher, Jack & An-Vo, Duc-Anh, 2025. "Strategic use of index-based frost insurance to reduce financial risk and improve income stability for wheat producers in Australia," Agricultural Systems, Elsevier, vol. 226(C).
    14. Arata, Linda & Fabrizi, Enrico & Sckokai, Paolo, 2020. "A worldwide analysis of trend in crop yields and yield variability: Evidence from FAO data," Economic Modelling, Elsevier, vol. 90(C), pages 190-208.
    15. Raucci, Gian Lucca & Silveira, Rodrigo Lanna F. & Capitani, Daniel H D, "undated". "Development Of Weather Derivatives: Evidence From Brazilian Soybean Market," 2018 Annual Meeting, August 5-7, Washington, D.C. 274105, Agricultural and Applied Economics Association.
    16. Christopher N. Boyer & B. Wade Brorsen & Emmanuel Tumusiime, 2015. "Modeling skewness with the linear stochastic plateau model to determine optimal nitrogen rates," Agricultural Economics, International Association of Agricultural Economists, vol. 46(1), pages 1-10, January.
    17. Schmidt, Lorenz & Odening, Martin & Schlanstein, Johann & Ritter, Matthias, "undated". "Estimation of the Farm-Level Yield-Weather-Relation Using Machine Learning," 61st Annual Conference, Berlin, Germany, September 22-24, 2021 317075, German Association of Agricultural Economists (GEWISOLA).
    18. Andrea Martínez Salgueiro & Maria-Antonia Tarrazon-Rodon, 2021. "Weather derivatives to mitigate meteorological risks in tourism management: An empirical application to celebrations of Comunidad Valenciana (Spain)," Tourism Economics, , vol. 27(4), pages 591-613, June.
    19. Chemeris, Anna & Liu, Yong & Ker, Alan P., 2022. "Insurance subsidies, climate change, and innovation: Implications for crop yield resiliency," Food Policy, Elsevier, vol. 108(C).
    20. A. Ford Ramsey & Yong Liu, 2023. "Linear pooling of potentially related density forecasts in crop insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 90(3), pages 769-788, September.
    21. Jensen, Nathaniel D. & Barrett, Christopher B. & Mude, Andrew G., 2014. "Basis Risk and the Welfare Gains from Index Insurance: Evidence from Northern Kenya," MPRA Paper 59153, University Library of Munich, Germany.

    More about this item

    Keywords

    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:ags:gjagec:368989. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/iahubde.html .

    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.