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The Role of Technical Efficiency Achieving Sustainable Development: A Dynamic Analysis of Norwegian Dairy Farms

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  • Habtamu Alem

    (Department of Economics and Society, Norwegian Institute of Bioeconomy Research (NIBIO), Raveien 9, 1430 ÅS, Norway)

Abstract

Growing environmental concerns have prompted governments to make sustainable choices in agricultural resource use. Evaluating the sustainability of agricultural systems is a key issue for the implementation of policies and practices aimed at revealing sustainability. This study aimed to evaluate the performance of Norwegian dairy farms, accounting for marginal effects of environmental (exogenous) variables. We adopted the dynamic parametric approach within the input distance function framework to estimate the performance of Norwegian dairy farms, focusing on the technical efficiency and determinates. For comparison, we also estimated the static parametric model, which was used by previous studies. We used unbalanced farm-level panel data for the period 2000–2018. The result shows a mean technical efficiency score of 0.92 for the dynamic model and 0.87 for the static models. The empirical result shows that the previous studies that focused on the static model reported a biased result on the performance of dairy farms. The dynamic efficiency score suggests that Norwegian dairy farms can reduce the input requirement of producing the average output by 8% if the operation becomes technically efficient. The environmental variables have a different effect on the performance of the farmers; thus, policymakers need to place special focus on these variables for the sustainable development of the dairy sector.

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  • Habtamu Alem, 2021. "The Role of Technical Efficiency Achieving Sustainable Development: A Dynamic Analysis of Norwegian Dairy Farms," Sustainability, MDPI, vol. 13(4), pages 1-11, February.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:4:p:1841-:d:495671
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    1. Efthymios G. Tsionas, 2006. "Inference in dynamic stochastic frontier models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 669-676, July.
    2. Zhimin Huang & Susan Li, 2001. "Stochastic DEA Models With Different Types of Input-Output Disturbances," Journal of Productivity Analysis, Springer, vol. 15(2), pages 95-113, March.
    3. Laure Latruffe & Boris E. Bravo-Ureta & Alain Carpentier & Yann Desjeux & Víctor H. Moreira, 2017. "Subsidies and Technical Efficiency in Agriculture: Evidence from European Dairy Farms," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(3), pages 783-799.
    4. Christopher O’Donnell & D. Rao & George Battese, 2008. "Metafrontier frameworks for the study of firm-level efficiencies and technology ratios," Empirical Economics, Springer, vol. 34(2), pages 231-255, March.
    5. Subhash C. Ray, 1982. "A Translog Cost Function Analysis of U.S. Agriculture, 1939–77," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 64(3), pages 490-498.
    6. Habtamu Alem & Gudbrand Lien & J. Brian Hardaker & Atle Guttormsen, 2019. "Regional differences in technical efficiency and technological gap of Norwegian dairy farms: a stochastic meta-frontier model," Applied Economics, Taylor & Francis Journals, vol. 51(4), pages 409-421, January.
    7. Subal Kumbhakar & Gudbrand Lien & J. Hardaker, 2014. "Technical efficiency in competing panel data models: a study of Norwegian grain farming," Journal of Productivity Analysis, Springer, vol. 41(2), pages 321-337, April.
    8. Diewert, W E, 1974. "Functional Forms for Revenue and Factor Requirements Functions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 15(1), pages 119-130, February.
    9. Kumbhakar,Subal C. & Wang,Hung-Jen & Horncastle,Alan P., 2015. "A Practitioner's Guide to Stochastic Frontier Analysis Using Stata," Cambridge Books, Cambridge University Press, number 9781107609464.
    10. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    11. Hung-Jen Wang, 2002. "Heteroscedasticity and Non-Monotonic Efficiency Effects of a Stochastic Frontier Model," Journal of Productivity Analysis, Springer, vol. 18(3), pages 241-253, November.
    12. Zhu, Xueqin & Milán Demeter, Róbert, 2012. "Technical efficiency and productivity differentials of dairy farms in three EU countries: the role of CAP subsidies," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 13(1), pages 1-27.
    13. Ductor, Lorenzo & Grechyna, Daryna, 2015. "Financial development, real sector, and economic growth," International Review of Economics & Finance, Elsevier, vol. 37(C), pages 393-405.
    14. Lien, Gudbrand & Kumbhakar, Subal C. & Alem, Habtamu, 2018. "Endogeneity, heterogeneity, and determinants of inefficiency in Norwegian crop-producing farms," International Journal of Production Economics, Elsevier, vol. 201(C), pages 53-61.
    15. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    16. Alem, Habtamu, 2020. "Performance of the Norwegian dairy farms: A dynamic stochastic approach," Research in Economics, Elsevier, vol. 74(3), pages 263-271.
    17. Daniel Atsbeha & Dadi Kristofersson & Kyrre Rickertsen, 2015. "Broad breeding goals and production costs in dairy farming," Journal of Productivity Analysis, Springer, vol. 43(3), pages 403-415, June.
    18. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    19. David Hadley, 2006. "Patterns in Technical Efficiency and Technical Change at the Farm‐level in England and Wales, 1982–2002," Journal of Agricultural Economics, Wiley Blackwell, vol. 57(1), pages 81-100, March.
    20. Jean Joseph Minviel & Timo Sipiläinen, 2018. "Dynamic stochastic analysis of the farm subsidy-efficiency link: evidence from France," Journal of Productivity Analysis, Springer, vol. 50(1), pages 41-54, October.
    21. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    22. Alem, Habtamu & Lien, Gudbrand & Kumbhakar, Subal C. & Hardaker, J. Brian, 2019. "Are Diversification And Structural Change Good Policy? An Empirical Analysis Of Norwegian Agriculture," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 51(1), pages 1-26, February.
    23. Timothy J. Coelli & D.S. Prasada Rao & Christopher J. O’Donnell & George E. Battese, 2005. "An Introduction to Efficiency and Productivity Analysis," Springer Books, Springer, edition 0, number 978-0-387-25895-9, December.
    24. Seung Ahn & Robin Sickles, 2000. "Estimation of long-run inefficiency levels: a dynamic frontier approach," Econometric Reviews, Taylor & Francis Journals, vol. 19(4), pages 461-492.
    25. Luis Orea & Subal C. Kumbhakar, 2004. "Efficiency measurement using a latent class stochastic frontier model," Empirical Economics, Springer, vol. 29(1), pages 169-183, January.
    26. Habtamu Alem, 2021. "A Metafrontier Analysis on the Performance of Grain-Producing Regions in Norway," Economies, MDPI, vol. 9(1), pages 1-10, February.
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