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The Spanish Horticulture Sector: A dynamic efficiency analysis of Outdoor and Greenhouse farms

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  • Lambarraa, Fatima

Abstract

The horticulture sector plays a relevant role in Spanish agriculture and economy. Their participation in the final agricultural production reached 37% and it represents an important source of employment generating the half of the job in the entire Spanish agricultural sector (MARM, 2010). The purpose of this paper is the evaluation of dynamic technical efficiency for both outdoor and greenhouse Spanish farms specialized in horticulture production. A dynamic stochastic frontier model is developed to estimate the long run technical efficiency and it persistence for both samples. This analysis has been applied to 126 and 90 Spanish greenhouses and outdoor horticulture farms respectively using Farm Accounting Data Network. Those farms were observed during 6 years from 1999 to 2004. The static efficiency level of greenhouse farms is higher than outdoor farms by approximately 12%. The evolution of the static efficiency level during the studied period shows an increase by 15% in the greenhouse farms comparing to a decrease by 11% for outdoor horticulture farms. This difference can be explained by a best control of the use of different inputs in the case of greenhouse horticulture as well as the implantation of high technology that improves efficiency level over years. The empirical results also show a big difference of level between static and dynamic technical efficiency for both samples. These results are consistent with the high value of the technical inefficiency persistence parameter for both cases which suggests that the technical inefficiency is highly persistent and shows a strong competition in this sector.

Suggested Citation

  • Lambarraa, Fatima, 2012. "The Spanish Horticulture Sector: A dynamic efficiency analysis of Outdoor and Greenhouse farms," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126797, International Association of Agricultural Economists.
    • Handle: RePEc:ags:iaae12:126797
    DOI: 10.22004/ag.econ.126797
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    1. van den Broeck, Julien & Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1994. "Stochastic frontier models : A Bayesian perspective," Journal of Econometrics, Elsevier, vol. 61(2), pages 273-303, April.
    2. William Greene, 2003. "Simulated Likelihood Estimation of the Normal-Gamma Stochastic Frontier Function," Journal of Productivity Analysis, Springer, vol. 19(2), pages 179-190, April.
    3. 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.
    4. Coelli, T. J., 1992. "A computer program for frontier production function estimation : Frontier version 2.0," Economics Letters, Elsevier, vol. 39(1), pages 29-32, May.
    5. Koop, Gary & Osiewalski, Jacek & Steel, Mark F J, 1994. "Bayesian Efficiency Analysis with a Flexible Form: The AIM Cost Function," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 339-346, July.
    6. Jacek Osiewalski & Mark Steel, 1998. "Numerical Tools for the Bayesian Analysis of Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 10(1), pages 103-117, July.
    7. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
    8. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    9. Kumbhakar, Subal C., 1987. "The specification of technical and allocative inefficiency in stochastic production and profit frontiers," Journal of Econometrics, Elsevier, vol. 34(3), pages 335-348, March.
    10. Yangseon Kim & Peter Schmidt, 2000. "A Review and Empirical Comparison of Bayesian and Classical Approaches to Inference on Efficiency Levels in Stochastic Frontier Models with Panel Data," Journal of Productivity Analysis, Springer, vol. 14(2), pages 91-118, September.
    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. 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.
    13. Efthymios Tsionas, 2000. "Full Likelihood Inference in Normal-Gamma Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 13(3), pages 183-205, May.
    14. Alvarez, Antonio & Arias, Carlos, 2004. "Technical efficiency and farm size: a conditional analysis," Agricultural Economics, Blackwell, vol. 30(3), pages 241-250, May.
    15. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
    16. Konstantinos Giannakas & Kien C. Tran & Vangelis Tzouvelekas, 2003. "On the choice of functional form in stochastic frontier modeling," Empirical Economics, Springer, vol. 28(1), pages 75-100, January.
    17. Ho-chuan Huang, 2004. "Estimation of Technical Inefficiencies with Heterogeneous Technologies," Journal of Productivity Analysis, Springer, vol. 21(3), pages 277-296, May.
    18. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200.
    19. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    20. Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 5-27, July.
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    Agricultural Finance; Research Methods/ Statistical Methods;

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