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Measuring technical efficiency of Spanish pig farming: Quantile stochastic frontier approach

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  • Juan Cabas Monje
  • Bouali Guesmi
  • Amer Ait Sidhoum
  • José María Gil

Abstract

The pig meat production plays a significant role in the Spanish agrofood system. The assessment of the efficiency performance with which farmers are operating is necessary to define adequate policy and management strategies. In this context, this study aimed to determine the technical efficiency (TE) performance of pig farms and to examine the key factors that may affect the production system in Spain. To do so, the analysis relies on the quantile stochastic frontier model using a sample of Spanish pig farms. Results show a significant difference between production frontier parameters across the selected quantiles, which support the relevance of using the quantile regression approach. The optimal quantile for the stochastic frontier indicates an average TE level of 75%. In addition, empirical findings suggest that pig farmers in Spain give more importance to the adoption of high technology to improve their economic and technical performance as well as their competitiveness at the European pig market.

Suggested Citation

  • Juan Cabas Monje & Bouali Guesmi & Amer Ait Sidhoum & José María Gil, 2023. "Measuring technical efficiency of Spanish pig farming: Quantile stochastic frontier approach," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 67(4), pages 688-703, October.
    • Handle: RePEc:bla:ajarec:v:67:y:2023:i:4:p:688-703
    DOI: 10.1111/1467-8489.12518
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    as
    1. Lansink, Alfons Oude & Reinhard, Stijn, 2004. "Investigating technical efficiency and potential technological change in Dutch pig farming," Agricultural Systems, Elsevier, vol. 79(3), pages 353-367, March.
    2. Behr, Andreas, 2010. "Quantile regression for robust bank efficiency score estimation," European Journal of Operational Research, Elsevier, vol. 200(2), pages 568-581, January.
    3. Kelvin Balcombe & Iain Fraser & Jae Kim, 2006. "Estimating technical efficiency of Australian dairy farms using alternative frontier methodologies," Applied Economics, Taylor & Francis Journals, vol. 38(19), pages 2221-2236.
    4. Tsionas, Mike G. & Assaf, A. George & Andrikopoulos, Athanasios, 2020. "Quantile stochastic frontier models with endogeneity," Economics Letters, Elsevier, vol. 188(C).
    5. Alvarez, Antonio & del Corral, Julio & Tauer, Loren W., 2012. "Modeling Unobserved Heterogeneity in New York Dairy Farms: One-Stage versus Two-Stage Models," Agricultural and Resource Economics Review, Cambridge University Press, vol. 41(3), pages 275-285, December.
    6. Weill, Laurent, 2013. "Bank competition in the EU: How has it evolved?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 100-112.
    7. Kounetas, Konstantinos, 2015. "Heterogeneous technologies, strategic groups and environmental efficiency technology gaps for European countries," Energy Policy, Elsevier, vol. 83(C), pages 277-287.
    8. Chunping Liu & Audrey Laporte & Brian S. Ferguson, 2008. "The quantile regression approach to efficiency measurement: insights from Monte Carlo simulations," Health Economics, John Wiley & Sons, Ltd., vol. 17(9), pages 1073-1087, September.
    9. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    10. Seunghwa Rho & Peter Schmidt, 2015. "Are all firms inefficient?," Journal of Productivity Analysis, Springer, vol. 43(3), pages 327-349, June.
    11. Efthymios G. Tsionas, 2002. "Stochastic frontier models with random coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(2), pages 127-147.
    12. Audrey Laporte & Adrian Rohit Dass, 2016. "The Use of Panel Quantile Regression for Efficiency Measurement: Insights from Monte Carlo Simulations," Working Papers 160005, Canadian Centre for Health Economics.
    13. Arne Henningsen & Tomasz Gerard Czekaj & Björn Forkman & Mogens Lund & Aske Schou Nielsen, 2018. "The Relationship between Animal Welfare and Economic Performance at Farm Level: A Quantitative Study of Danish Pig Producers," Journal of Agricultural Economics, Wiley Blackwell, vol. 69(1), pages 142-162, February.
    14. Tian, Xu & Sun, Feifei & Zhou, Yingheng, 2015. "Technical Efficiency and Its Determinants in China's Hog Production," 2015 Conference, August 9-14, 2015, Milan, Italy 212718, International Association of Agricultural Economists.
    15. Jradi, Samah & Parmeter, Christopher F. & Ruggiero, John, 2019. "Quantile estimation of the stochastic frontier model," Economics Letters, Elsevier, vol. 182(C), pages 15-18.
    16. Arne Henningsen & Christian Henning, 2009. "Imposing regional monotonicity on translog stochastic production frontiers with a simple three-step procedure," Journal of Productivity Analysis, Springer, vol. 32(3), pages 217-229, December.
    17. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    18. Lajos Baráth & Imre Fertő & Jakub Staniszewski, 2021. "Technological Heterogeneity in Pig Farming: A Metafrontier Approach—Perspectives from Hungary and Poland," Agriculture, MDPI, vol. 11(10), pages 1-13, October.
    19. Amy Hsu & Adrian Rohit Dass & Whitney Berta & Peter Coyte & Audrey Laporte, 2017. "Efficiency estimation with panel quantile regression: An application using longitudinal data from nursing homes in Ontario, Canada," Working Papers 170003, Canadian Centre for Health Economics.
    20. Jradi, Samah & Parmeter, Christopher F. & Ruggiero, John, 2021. "Quantile estimation of stochastic frontiers with the normal-exponential specification," European Journal of Operational Research, Elsevier, vol. 295(2), pages 475-483.
    21. Svend Rasmussen, 2010. "Scale efficiency in Danish agriculture: an input distance--function approach," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 37(3), pages 335-367, September.
    22. Bouali Guesmi & Teresa Serra & Allen Featherstone, 2015. "Technical efficiency of Kansas arable crop farms: a local maximum likelihood approach," Agricultural Economics, International Association of Agricultural Economists, vol. 46(6), pages 703-713, November.
    23. 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.
    24. Loren W. Tauer, 2016. "Production Response in the Interior of the Production Set," Springer Proceedings in Business and Economics, in: William H. Greene & Lynda Khalaf & Robin Sickles & Michael Veall & Marcel-Cristian Voia (ed.), Productivity and Efficiency Analysis, edition 1, chapter 0, pages 71-82, Springer.
    25. Lin, Boqiang & Du, Kerui, 2014. "Measuring energy efficiency under heterogeneous technologies using a latent class stochastic frontier approach: An application to Chinese energy economy," Energy, Elsevier, vol. 76(C), pages 884-890.
    26. 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.
    27. Tsekouras, Kostas & Chatzistamoulou, Nikos & Kounetas, Kostas & Broadstock, David C., 2016. "Spillovers, path dependence and the productive performance of European transportation sectors in the presence of technology heterogeneity," Technological Forecasting and Social Change, Elsevier, vol. 102(C), pages 261-274.
    28. George Battese & D. Rao & Christopher O'Donnell, 2004. "A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies," Journal of Productivity Analysis, Springer, vol. 21(1), pages 91-103, January.
    29. Gordana Manevska‐Tasevska & Helena Hansson & Katarina Labajova, 2017. "Impact of Management Practices on Persistent and Residual Technical Efficiency – a Study of Swedish pig Farming," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 38(6), pages 890-905, September.
    30. Larue, Solène & Latruffe, Laure, 2009. "Agglomeration externalities and technical efficiency in French pig production," Working Papers 210403, Institut National de la recherche Agronomique (INRA), Departement Sciences Sociales, Agriculture et Alimentation, Espace et Environnement (SAE2).
    31. 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, June.
    32. 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 9781107029514.
    33. William C. Horrace & Christopher F. Parmeter, 2018. "A Laplace stochastic frontier model," Econometric Reviews, Taylor & Francis Journals, vol. 37(3), pages 260-280, March.
    34. 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.
    35. Sauer, Johannes & Hockmann, Heinrich, 2005. "The Need for Theoretically Consistent Efficiency Frontiers," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24497, European Association of Agricultural Economists.
    36. Tracy Bradfield & Robert Butler & Emma Dillon & Thia Hennessy & Paul Kilgarriff, 2021. "The Effect of Land Fragmentation on the Technical Inefficiency of Dairy Farms," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(2), pages 486-499, June.
    37. Diego Matricano, 2022. "Economic and social development generated by innovative startups: does heterogeneity persist across Italian macro-regions?," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 31(6), pages 467-484, August.
    38. Antonio Alvarez & Julio del Corral, 2010. "Identifying different technologies using a latent class model: extensive versus intensive dairy farms," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 37(2), pages 231-250, June.
    39. Llorca, Manuel & Orea, Luis & Pollitt, Michael G., 2014. "Using the latent class approach to cluster firms in benchmarking: An application to the US electricity transmission industry," Operations Research Perspectives, Elsevier, vol. 1(1), pages 6-17.
    40. Ho-chuan Huang, 2004. "Estimation of Technical Inefficiencies with Heterogeneous Technologies," Journal of Productivity Analysis, Springer, vol. 21(3), pages 277-296, May.
    41. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    42. Johannes Sauer & Catherine J. Morrison Paul, 2013. "The empirical identification of heterogeneous technologies and technical change," Applied Economics, Taylor & Francis Journals, vol. 45(11), pages 1461-1479, April.
    43. 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.
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