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Crop Insurance and pesticide use in French agriculture: an empirical analysis

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  • Chakir, Raja
  • Hardelin, Julien

Abstract

This paper investigates the factors affecting the demand for crop–hail insurance and explores the potential relation with pesticide use for a sample of French farmers on the period 1993-2004, for the Meuse department. An econometric model involving two simultaneous equations with mixed censored/continuous dependent variables is estimated. Estimation results show that, in the case of rapeseed, insurance demand is significantly and positively related to pesticide use, but that the magnitude of this interaction is quite small. Insurance demand is positively influenced by the coefficient of variation of yield and the loss ratio, and is negatively influenced by Common Agricultural Policy subsidies and diversification of activity at farm level. These results shed light on the determinants of French farmers’ decisions related to risk management.

Suggested Citation

  • Chakir, Raja & Hardelin, Julien, 2014. "Crop Insurance and pesticide use in French agriculture: an empirical analysis," Review of Agricultural and Environmental Studies - Revue d'Etudes en Agriculture et Environnement (RAEStud), Institut National de la Recherche Agronomique (INRA), vol. 95(1).
    • Handle: RePEc:ags:frraes:208763
    DOI: 10.22004/ag.econ.208763
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    Cited by:

    1. Geoffroy Enjolras & Magali Aubert, 2020. "How does crop insurance influence pesticide use? Evidence from French farms," Review of Agricultural, Food and Environmental Studies, INRA Department of Economics, vol. 101(4), pages 461-485.
    2. Aubert, Magali & Enjolras, Geoffroy, 2014. "Between the approved and the actual dose. A diagnosis of pesticide overdosing in French vineyards," Review of Agricultural and Environmental Studies - Revue d'Etudes en Agriculture et Environnement (RAEStud), Institut National de la Recherche Agronomique (INRA), vol. 95(3).
    3. Agnieszka Kurdyś-Kujawska & Agnieszka Sompolska-Rzechuła & Joanna Pawłowska-Tyszko & Michał Soliwoda, 2021. "Crop Insurance, Land Productivity and the Environment: A Way forward to a Better Understanding," Agriculture, MDPI, vol. 11(11), pages 1-17, November.
    4. Geoffroy Enjolras & Magali Aubert, 2018. "Does crop insurance lead to better environmental practices? Evidence from French farms," Post-Print hal-02048349, HAL.
    5. Mauro Vigani & Jonas Kathage, 2019. "To Risk or Not to Risk? Risk Management and Farm Productivity," American Journal of Agricultural Economics, John Wiley & Sons, vol. 101(5), pages 1432-1454, October.
    6. Möhring, Niklas & Dalhaus, Tobias & Enjolras, Geoffroy & Finger, Robert, 2020. "Crop insurance and pesticide use in European agriculture," Agricultural Systems, Elsevier, vol. 184(C).
    7. Zheng, Yanan & Goodhue, Rachael E., 2022. "Intensive or Extensive Margin Effects? Growers’ Responses to the Restriction of High-Volatile Organic Compound (VOC) Pesticide Products in the San Joaquin Valley, California," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322085, Agricultural and Applied Economics Association.
    8. Magali Aubert & Geoffroy Enjolras, 2012. "Quand le surdosage devient la norme : un diagnostic des exploitations viticoles françaises," Post-Print hal-02749128, HAL.

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    More about this item

    Keywords

    Crop Production/Industries; Environmental Economics and Policy; Risk and Uncertainty;
    All these keywords.

    JEL classification:

    • Q15 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Land Ownership and Tenure; Land Reform; Land Use; Irrigation; Agriculture and Environment
    • Q24 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Land
    • Q22 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Fishery
    • Q33 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Resource Booms (Dutch Disease)
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models

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