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The role of pest pressure in technical and environmental inefficiency analysis of Dutch arable farms: an event-specific data envelopment approach

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  • Theodoros Skevas

    (University of Missouri)

  • Teresa Serra

    (University of Illinois)

Abstract

This article provides estimates of farm technical and environmental inefficiency that recognize the effect of pest pressure on farmers’ production environment. This effect is modeled through the use of an event-specific production technology, which is empirically implemented using Data Envelopment Analysis (DEA). A regional biodiversity variable and two variables reflecting impacts of pesticides on farmland biodiversity are used to partition the data into high and low pest infestation events. The DEA representation is applied to data from Dutch arable farms. Results show that the degree of inefficiency overstatement from a model that ignores the event-specific nature of the production technology increases with pest infestation. Mean environmental inefficiency of the sample farms is low, implying that these farms are, on average, minimizing their impacts on farmland biodiversity. Environmental inefficiency provides an indicator of farm-level environmental sustainability that could help towards a more effective distribution of farm-support payments and make agriculture more environmentally sound.

Suggested Citation

  • Theodoros Skevas & Teresa Serra, 2016. "The role of pest pressure in technical and environmental inefficiency analysis of Dutch arable farms: an event-specific data envelopment approach," Journal of Productivity Analysis, Springer, vol. 46(2), pages 139-153, December.
    • Handle: RePEc:kap:jproda:v:46:y:2016:i:2:d:10.1007_s11123-016-0476-0
    DOI: 10.1007/s11123-016-0476-0
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    2. Tang, L. & Zhou, J. & Liu, Q., 2018. "Beyond quantity: the crowding-in effects of perception of climate risk on chemical use by Chinese rice farmers," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277220, International Association of Agricultural Economists.
    3. Amer Ait Sidhoum, 2023. "Measuring farm productivity under production uncertainty," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 67(4), pages 672-687, October.
    4. Heidari, Mohammad Davoud & Turner, Ian & Ardestani-Jaafari, Amir & Pelletier, Nathan, 2021. "Operations research for environmental assessment of crop-livestock production systems," Agricultural Systems, Elsevier, vol. 193(C).
    5. Theodoros Skevas & Teresa Serra, 2017. "Derivation of netput shadow prices under different levels of pest pressure," Journal of Productivity Analysis, Springer, vol. 48(1), pages 25-34, August.
    6. Leonidas Sotirios Kyrgiakos & Georgios Kleftodimos & George Vlontzos & Panos M. Pardalos, 2023. "A systematic literature review of data envelopment analysis implementation in agriculture under the prism of sustainability," Operational Research, Springer, vol. 23(1), pages 1-38, March.
    7. Jakub Staniszewski & Anika Muder, 2023. "Structural and weather-related factors of the sustainable intensification process in agriculture of the European Union regions," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 69(10), pages 385-393.
    8. Tang, Liqun & Zhou, Jiehong & Bobojonov, Ihtiyor & Zhang, Yanjie & Glauben, Thomas, 2018. "Induce or reduce? The crowding-in effects of farmers’ perceptions of climate risk on chemical use in China," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 20, pages 27-37.
    9. Tao Du, 2017. "Performance Measurement of Healthcare Service and Association Discussion between Quality and Efficiency: Evidence from 31 Provinces of Mainland China," Sustainability, MDPI, vol. 10(1), pages 1-19, December.
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    More about this item

    Keywords

    Data envelopment analysis; Event-specific model; Efficiency; Production uncertainty; Pest pressure;
    All these keywords.

    JEL classification:

    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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