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Journal of Productivity Analysis

, Volume 31, Issue 2, pp 113–124 | Cite as

The efficiency of Spanish arable crop organic farms, a local maximum likelihood approach

  • Teresa Serra
  • Barry K. Goodwin
Article

Abstract

The methodologies that have been used in existing research to assess the efficiency with which organic farms are operating are generally based either on the stochastic frontier methodology or on a deterministic non-parametric approach. Recently, Kumbhakar et al. (J Econom 137:1–27, 2007) proposed a new nonparametric, stochastic method based on the local maximum likelihood principle. We use this methodology to compare the efficiency ratings of organic and conventional arable crop farms in the Spanish region of Andalucía. Nonparametrically encompassing the stochastic frontier model is especially useful when comparing the performance of two groups that are likely to be characterized by different production technologies.

Keywords

Organic and conventional farming Technical efficiency Local maximum likelihood approach 

JEL Classification

C14 Q12 D24 

Notes

Acknowledgments

The authors gratefully acknowledge financial support from Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Project RTA2006-00002-00-00. They also thank the Spanish Ministry for Agricultre for permitting access to the FADN dataset.

References

  1. Aigner DJ, Lovell CAK, Schmidt P (1977) Formulation and estimation of stochastic frontier production function models. J Econom 6:21–37. doi: 10.1016/0304-4076(77)90052-5 CrossRefGoogle Scholar
  2. Arrow KJ (1962) The economic implications of learning by doing. Rev Econ Stud 29:155–173. doi: 10.2307/2295952 CrossRefGoogle Scholar
  3. Blobaum R (1983) Barriers to conversion to organic farming practices in the midwestern United States. In: Lockeretz W (ed) Environmentally sound agriculture. Praeger, New York, pp 263–278Google Scholar
  4. Burton M, Rigby D, Young T (2003) Modelling the adoption of organic horticultural technology in the UK using duration analysis. Aust J Agric Resour Econ 47:29–54. doi: 10.1111/1467-8489.00202 CrossRefGoogle Scholar
  5. Cobb D, Feber R, Hopkins A, Stockdate L, O’Riordan T, Clements B, Firbank L, Goulding K, Jarvis S, Macdonald D (1999) Integrating the environmental and economic consequences of converting to organic agriculture: evidence from a case study. Land Use Policy 16:207–221. doi: 10.1016/S0264-8377(99)00023-X CrossRefGoogle Scholar
  6. Dimitri C, Oberholtzer L (2006) EU and U.S. organic markets face strong demand under different policies. Amber Waves 4:12–19Google Scholar
  7. Eurostat. (2007) Database. Available at: http://epp.eurostat.ec.europa.eu. Accessed 19 March 2007
  8. Fairweather JR (1999) Understanding how farmers choose between organic and conventional production: results from New Zealand and policy implications. Agric Hum Values 16:51–63. doi: 10.1023/A:1007522819471 CrossRefGoogle Scholar
  9. Fan J, Gijbels I (1996) Local polynomial modelling and its applications. Chapman & Hall, LondonGoogle Scholar
  10. Fan Y, Li Q, Weersink A (1996) Semiparametric estimation of stochastic production frontier models. J Bus Econ Stat 14:460–468. doi: 10.2307/1392254 CrossRefGoogle Scholar
  11. Farrell MJ (1957) The measurement of productive efficiency. J Roy Stat Soc A 120:253–281. doi: 10.2307/2343100 CrossRefGoogle Scholar
  12. Freyer B, Rantzau R, Vogtmann H (1994) Case studies of farms converting to organic agriculture in Germany. In: Lampkin N, Padel S (eds) The economics of organic farming: an international perspective. CAB International, Oxford, pp 243–263Google Scholar
  13. Isik M, Khanna M (2003) Stochastic technology, risk preferences, and adoption of site-specific technologies. Am J Agric Econ 85:305–317. doi: 10.1111/1467-8276.00121 CrossRefGoogle Scholar
  14. Jondrow J, Lovell CAK, Materov IS, Schmidt P (1982) On the estimation of technical inefficiency in stochastic frontier production models. J Econom 19:233–238. doi: 10.1016/0304-4076(82)90004-5 CrossRefGoogle Scholar
  15. Kumbhakar SC, Tsionas EG (2002) Nonparametric stochastic frontier models. Manuscript presented at the North American Productivity Workshop II, Schenectady, New York, June 19–22Google Scholar
  16. Kumbhakar SC, Tsionas EG (2008) Scale and efficiency measurement using a semiparametric stochastic frontier model: evidence from the US commercial banks. Empir Econ 34:585–602. doi: 10.1007/s00181-007-0137-2 CrossRefGoogle Scholar
  17. Kumbhakar SC, Ghosh S, McGuckin JT (1991) A generalized production frontier approach for estimating determinants of inefficiency in US dairy farms. J Bus Econ Stat 9:279–286. doi: 10.2307/1391292 CrossRefGoogle Scholar
  18. Kumbhakar SC, Park BU, Simar L, Tsionas EG (2007) Nonparametric stochastic frontiers: a local maximum likelihood approach. J Econom 137:1–27. doi: 10.1016/j.jeconom.2006.03.006 CrossRefGoogle Scholar
  19. Lampkin N (1994) Changes in physical and financial performance during conversion to organic farming: case studies of two English dairy farms. In: Lampkin N, Padel S (eds) The economics of organic farming: an international perspective. CAB International, Oxford, pp 223–241Google Scholar
  20. Lampkin N, Padel S (1994) Organic farming and agricultural policy in Western Europe: an overview. In: Lampkin N, Padel S (eds) The economics of organic farming: an international perspective. CAB International, Oxford, pp 437–456Google Scholar
  21. Llorens L, Rohner-Thielen E (2007) Different organic farming patterns within the EU-25. Statistics in focus. Agriculture and fisheries 69/2007. European Communities, BrusselsGoogle Scholar
  22. Lohr L, Park TA (2006) Technical efficiency of US organic farmers: the complementary roles of soil management techniques and farm experience. Agric Resour Econ Rev 35:327–338Google Scholar
  23. Lohr L, Salomonsson L (2000) Conversion subsidies for organic production: results from Sweden and lessons for the United States. Agric Econ 22:133–146. doi: 10.1111/j.1574-0862.2000.tb00013.x CrossRefGoogle Scholar
  24. Martins-Filho C, Yao F (2007) Nonparametric frontier estimation via local linear regression. J Econom 141:283–319. doi: 10.1016/j.jeconom.2007.01.005 CrossRefGoogle Scholar
  25. Offermann F, Nieberg H (2000) Economic performance of organic farms in Europe. Org Farming Eur: Econ Policy 5:1–198Google Scholar
  26. Oude Lansink A, Jensma K (2003) Analysing profits and economic behaviour of organic and conventional Dutch arable farms. Agric Econ Rev 4:19–31Google Scholar
  27. Oude Lansink A, Pietola K, Bäckman S (2002) Efficiency and productivity of conventional and organic farms in Finland 1994–1997. Eur Rev Agric Econ 29:51–65. doi: 10.1093/erae/29.1.51 CrossRefGoogle Scholar
  28. Padel S (2001) Conversion to organic farming: a typical example of the diffusion of an innovation? Sociol Ruralis 41:40–61. doi: 10.1111/1467-9523.00169 CrossRefGoogle Scholar
  29. Padel S, Lampkin NH (1994) Conversion to organic farming: an overview. In: Lampkin NH, Padel S (eds) The economics of organic farming: and international perspective. CAB International, Wallingford, pp 295–313Google Scholar
  30. Pietola K, Oude Lansink A (2001) Farmer response to policies promoting organic farming technologies in Finland. Eur Rev Agric Econ 28:1–15. doi: 10.1093/erae/28.1.1 CrossRefGoogle Scholar
  31. Rougoor CW, Trip G, Huirne RBM, Renkema JA (1998) How to define and study farmers’ management capacity: theory and use in agricultural economics. Agric Econ 18:261–272. doi: 10.1016/S0169-5150(98)00021-8 CrossRefGoogle Scholar
  32. Serra T, Zilberman D, Gil JM (2008a) Differential uncertainties and risk attitudes between conventional and organic producers: the case of Spanish arable crop farmers. Agric Econ 39:219–229Google Scholar
  33. Serra T, Zilberman D, Gil JM (2008b) Farm’s technical inefficiencies in the presence of government programs. Austr J Agric Econ 52:57–76. doi: 10.1111/j.1467-8489.2008.00412.x CrossRefGoogle Scholar
  34. Sipiläinen T, Oude Lansink A (2005) Learning in organic farming-an application on Finnish dairy farms. Manuscript presented at the XIth Congress of the EAAE, Copenhagen, Denmark, August 24–17Google Scholar
  35. Simar L, Wilson PW (2000) Statistical inference in nonparametric frontier models: the state of the art. J Productiv Anal 13:49–78. doi: 10.1023/A:1007864806704 CrossRefGoogle Scholar
  36. Spanish Ministry for Agriculture (2005) Estadísticas 2005. Agricultura ecológica España. Available at http://www.mapa.es/alimentacion/pags/ecologica/pdf/2005.pdf. Accessed 19 March 2007
  37. Stevens-Garmon J, Huang CL, Lin BH (2007) Organic demand: a profile of consumers in the fresh produce market. Choices (New York, NY) 22:109–115Google Scholar
  38. Thompson G (1998) Consumer demand for organic foods: what we know and what we need to know. Am J Agric Econ 80:1113–1118. doi: 10.2307/1244214 CrossRefGoogle Scholar
  39. Tzouvelekas V, Pantzios CJ, Fotopoulos C (2001) Technical efficiency of alternative farming systems: the case of Greek organic and conventional olive-growing farms. Food Policy 26:549–569. doi: 10.1016/S0306-9192(01)00007-0 CrossRefGoogle Scholar
  40. Tzouvelekas V, Pantzios CJ, Fotopoulos C (2002) Empirical evidence of technical efficiency levels in Greek organic and conventional farms. Agric Econ Rev 3:49–60Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  1. 1.CREDA-UPC-IRTA, Parc Mediterrani de la Tecnologia, Edifici ESABCastelldefelsSpain
  2. 2.Agricultural and Resource Economics DepartmentNorth Carolina State UniversityRaleighUSA

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