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Farmers’ responses to the changes in Hungarian agricultural insurance system

Author

Listed:
  • Anna Zubor-Nemes
  • József Fogarasi
  • András Molnár
  • Gábor Kemény

Abstract

Purpose - The purpose of this paper is to investigate the role of crop insurance among Hungarian crop farmers and the responses to the introduction of the two-scheme risk management system. Specifically, first, it examines the economic and environmental factors affecting the willingness of farmers to contract crop insurance. Second, it reveals the relationship between having crop insurance and technical efficiency of crop producing farms. Design/methodology/approach - Probit models of panel data are applied to explore the factors of insurance decisions. The relationship between efficiency and insurance is investigated with two-stage data envelopment analysis (DEA) model with double bootstrap using panel data for the 2001 to 2014 period. Findings - The results of Probit model estimations show that the education, the size, the indebtedness of crop producing farms and the new two-scheme risk management system are in positive correlation, while the concentration of farming activity are in negative correlation with the crop insurance contracting. The estimations of two-stage DEA model reveal that crop producing farms with an agricultural insurance contract are more efficient than the farmers without using this risk management tool. Originality/value - Empirical investigation of the influencing factors of agricultural insurance demand in Hungary and the examination of the relationship between insurance and technical efficiency may contribute to the development of Hungarian risk management system.

Suggested Citation

  • Anna Zubor-Nemes & József Fogarasi & András Molnár & Gábor Kemény, 2018. "Farmers’ responses to the changes in Hungarian agricultural insurance system," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 78(2), pages 275-288, March.
    • Handle: RePEc:eme:afrpps:afr-06-2017-0048
    DOI: 10.1108/AFR-06-2017-0048
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    Citations

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    Cited by:

    1. Shaolong Zeng & Bingying Qi & Minglin Wang, 2022. "Agricultural Insurance and Agricultural Economic Growth: The Case of Zhejiang Province in China," IJERPH, MDPI, vol. 19(20), pages 1-21, October.
    2. Sofia Kislingerová & Jindřich Špička, 2022. "Factors Influencing the Take-Up of Agricultural Insurance and the Entry into the Mutual Fund: A Case Study of the Czech Republic," JRFM, MDPI, vol. 15(8), pages 1-17, August.
    3. Luigi Biagini & Simone Severini, 2022. "Can Machine Learning discover the determining factors in participation in insurance schemes? A comparative analysis," Papers 2212.03092, arXiv.org, revised Dec 2022.
    4. 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.
    5. Donatella Porrini & Giulio Fusco & Pier Paolo Miglietta, 2019. "Post-Adversities Recovery and Profitability: The Case of Italian Farmers," IJERPH, MDPI, vol. 16(17), pages 1-12, September.
    6. Codruţa Mare & Daniela Manaţe & Gabriela-Mihaela Mureşan & Simona Laura Dragoş & Cristian Mihai Dragoş & Alexandra-Anca Purcel, 2022. "Machine Learning Models for Predicting Romanian Farmers’ Purchase of Crop Insurance," Mathematics, MDPI, vol. 10(19), pages 1-13, October.
    7. Shirinyan Lada & Arych Mykhailo & Rohanova Hanna, 2021. "Influence of Insurance on Competitiveness of Food Enterprises in Ukraine," Management Theory and Studies for Rural Business and Infrastructure Development, Sciendo, vol. 43(1), pages 5-12, March.

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