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Inference in the spatial autoregressive efficiency model with an application to Dutch dairy farms

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  • Skevas, Ioannis

Abstract

This article extends the conventional spatial autoregressive efficiency model by including firm characteristics that may impact efficiency. This extension allows performing the typical inference in spatial autoregressive models that involves the derivation of direct and indirect marginal effects, with the latter revealing the nature and magnitude of spatial spillovers. Furthermore, this study accounts for the endogeneity of the spatial autoregressive efficiency model using a lag spatial lag efficiency component, which makes inference to be performed in a long-run framework. The case study concerns specialized Dutch dairy farms observed over the period 2009–2016 and for which exact geographical coordinates of latitude and longitude are available. The results reveal that the efficiency scores are spatially dependent. The derived marginal effects further suggest that farmers’ long-run efficiency is driven by changes in both their own and their neighbors’ characteristics, highlighting the existence of motivation and learning domino effects between neighboring producers.

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  • Skevas, Ioannis, 2020. "Inference in the spatial autoregressive efficiency model with an application to Dutch dairy farms," European Journal of Operational Research, Elsevier, vol. 283(1), pages 356-364.
    • Handle: RePEc:eee:ejores:v:283:y:2020:i:1:p:356-364
    DOI: 10.1016/j.ejor.2019.10.033
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    2. Iordanis Parikoglou & Grigorios Emvalomatis & Fiona Thorne, 2022. "Precision livestock agriculture and productive efficiency: The case of milk recording in Ireland," Agricultural Economics, International Association of Agricultural Economists, vol. 53(S1), pages 109-120, November.
    3. Skevas, Ioannis & Skevas, Theodoros, 2021. "A generalized true random-effects model with spatially autocorrelated persistent and transient inefficiency," European Journal of Operational Research, Elsevier, vol. 293(3), pages 1131-1142.
    4. He Jiang, 2023. "Robust forecasting in spatial autoregressive model with total variation regularization," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 195-211, March.
    5. Pablo Argüelles & Luis Orea, 2021. "Managing power supply interruptions: a bottom-up spatial (frontier) model with an application to a Spanish electricity network," Empirical Economics, Springer, vol. 60(6), pages 2867-2896, June.
    6. Ioannis Skevas & Alfons Oude Lansink, 2020. "Dynamic Inefficiency and Spatial Spillovers in Dutch Dairy Farming," Journal of Agricultural Economics, Wiley Blackwell, vol. 71(3), pages 742-759, September.
    7. Ioannis Skevas, 2023. "A novel modeling framework for quantifying spatial spillovers on total factor productivity growth and its components," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(4), pages 1221-1247, August.
    8. Musau, Andrew & Kumbhakar, Subal C. & Mydland, Ørjan & Lien, Gudbrand, 2021. "Determinants of allocative and technical inefficiency in stochastic frontier models: An analysis of Norwegian electricity distribution firms," European Journal of Operational Research, Elsevier, vol. 288(3), pages 983-991.
    9. Kassoum Ayouba, 2023. "Spatial dependence in production frontier models," Journal of Productivity Analysis, Springer, vol. 60(1), pages 21-36, August.
    10. Bergantino, Angela Stefania & Intini, Mario & Volta, Nicola, 2020. "Spatial competition and efficiency: an investigation in the airport sector," The Warwick Economics Research Paper Series (TWERPS) 1287, University of Warwick, Department of Economics.
    11. Ioannis Skevas & Alfons Oude Lansink & Theodoros Skevas, 2023. "Analysing inefficiency in a non‐parametric spatial‐dynamic by‐production framework: A k‐nearest neighbour proposal," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(2), pages 591-607, June.
    12. Adjin, K. Christophe & Henning, Christian H. C. A., 2020. "Climate variability and farm inefficiency: A spatial stochastic frontier analysis of Senegalese agriculture," Working Papers of Agricultural Policy WP2020-09, University of Kiel, Department of Agricultural Economics, Chair of Agricultural Policy.
    13. Kevin Schneider & Ioannis Skevas & Alfons Oude Lansink, 2021. "Spatial Spillovers on Input‐specific Inefficiency of Dutch Arable Farms," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(1), pages 224-243, February.

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    More about this item

    Keywords

    OR in agriculture; Efficiency; Spatial autoregressive model; Marginal effects; Dairy farms;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets

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