Technical efficiency of Greek olive growing farms: a robust approach with panel data

  • S. Kourtesi Dept. Economics, Aristotle University. Thessaloniki
  • P. Fousekis Dept. Economics, Aristotle University. Thessaloniki
  • A. Polymeros Dept. Statistics, Athens University of Economics and Business; Farm Accountancy Data Network, Ministry of Rural Development and Food. Athens
Keywords: nonparametric estimation, conditional efficiency, environmental variables, agriculture

Abstract

The assessment of technical efficiency in the agricultural sector and the influence of exogenous (environmental) variables on the production process has been a major topic of economic research especially for managers and policy makers. The methological innovation of the present study involves the impact of environmental variables on efficiency and the utilization of panel data for the empirical analysis. This has been pursued using full nonparametric robust frontier techniques (the alpha-quantile estimator) and a panel data set of olive growing farms in Greece from the Farm Accountancy Data Network of the EU. According to the empirical results, the ratio of owned to total land, the ratio of family to total labor, the degree of specialization, and a farm’s location have a statistically significant impact on performance, which is not constant but varies over the 2006 to 2009 period considered.

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References

Aitchison J, Aitken CBB, 1976. Multivariate binary discrimination by kernel method. Biom 63: 413-420.

Aragon Y, Daouia A, Thomas-Agnan C, 2005. Nonparametric frontier estimation: a conditional quantile-based approach. Econom Theory 21: 358-389. http://dx.doi.org/10.1017/S0266466605050206

Banker R, Chang H, Natarajian R, 2007. Estimating DEA technical and allocative inefficiency using aggregate cost or revenue data. J Prod Anal 27: 115-121. http://dx.doi.org/10.1007/s11123-006-0027-1

Battese GE, Coelli TJ, 1988. Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data. J Econom 3: 387-399. http://dx.doi.org/10.1016/0304-4076(88)90053-X

Cazals C, Florens JP, Simar L, 2002. Nonparametric frontier estimation: a robust approach. J Econom 1: 1-25. http://dx.doi.org/10.1016/S0304-4076(01)00080-X

Charnes A, Cooper WW, Rhodes E, 1978. Measuring the efficiency of decision making units. Eur J Oper Res 2: 429-444. http://dx.doi.org/10.1016/0377-2217(78)90138-8

Daouia D, Simar L, 2007. Nonparametric efficiency analysis: a multivariate conditional quantile approach. J Econom 140: 375-400. http://dx.doi.org/10.1016/j.jeconom.2006.07.002

Daraio C, Simar L, 2005. Introducing environmental variables in nonparametric frontier models: a probabilistic approach. J Product Anal 24(1): 93-121. http://dx.doi.org/10.1007/s11123-005-3042-8

Daraio C, Simar L, 2006. A robust nonparametric approach to evaluate and explain the performance of mutual funds. Eur J Oper Res 175: 516-542. http://dx.doi.org/10.1016/j.ejor.2005.06.010

Daraio C, Simar L, 2007. Advanced robust and nonparametric methods in efficiency analysis, Methodology and applications, Series: Studies in Productivity and Efficiency. Springer.

De Witte K, Kortelainen M, 2013. What explains performance of students in a heterogeneous environment? Conditional efficiency estimation with continuous and discrete environmental variables. Appl Econ 45(17): 2401-2412. http://dx.doi.org/10.1080/00036846.2012.665602

Deprins D, Simar L, Tulkens H, 1984. Measuring labor efficiency in post offices. In: The performance of public enterprises: concepts and measurements (Marchand M, Pestieau P, Tulkens H, eds.). North-Holland, pp: 243-267.

EC, 2012. Member states factsheets- Greece. European Commission, Agricultural Policy Perspectives, May 2012.

Gavian S, Ehui S, 1999. Measuring the production efficiency of alternative land tenure contracts in a mixed crop-livestock system in Ethiopia. Agric Econ 20: 37-49. http://dx.doi.org/10.1016/S0169-5150(98)00067-X

Giannakas K, Tran KC, Tzouvelekas V, 2000. Efficiency, technological change and output growth in Greek olive growing farms: a box-cox approach. Appl Econ 32: 909-916. http://dx.doi.org/10.1080/000368400322246

Hall P, Racine JS, Li Q, 2004. Cross-validation and the estimation of conditional probability densities. J Am Stat Assoc 99(486): 1015-1026. http://dx.doi.org/10.1198/016214504000000548

Hayfield T, Racine JS, 2008. Nonparametric econometrics: the np package. J Stat Soft 27(5): 1-32.

Jeong S, Park B, Simar L, 2010. Nonparametric conditional efficiency measures: asymptotic properties. Ann Oper Res 173: 105-122. http://dx.doi.org/10.1007/s10479-008-0359-5

Karagiannis G, Tzouvelekas V, 2009. Measuring technical efficiency in the stochastic varying coefficient frontier model. Agric Econ 40: 389-396. http://dx.doi.org/10.1111/j.1574-0862.2009.00386.x

Kourtesi S, Fousekis P, Polymeros A, 2012. Conditional efficiency estimation with environmental variables: evidence from Greek cereal farms. Sci Bull-Econ Sci 11: 43-52.

Larsen K, 2010. Effects of machinery-sharing arrangements on farm efficiency: evidence from Sweden. Agric Econ 41: 497-506. http://dx.doi.org/10.1111/j.1574-0862.2010.00461.x

Latruffe L, Davidova S, Balcombe K, 2008. Application of a double bootstrap to investigation of determinants of technical efficiency of farms in Central Europe. J Product Anal 29: 183-191. http://dx.doi.org/10.1007/s11123-007-0074-2

Li Q, Racine JS, 2007. Nonparametric econometrics: theory and practice. Princeton Univ. Press. Princeton, NJ, USA.

Odeck J, 2007. Measuring technical efficiency and productivity growth: a comparison of SFA and DEA on Norwegian grain production data. Appl Econ 39: 2617-2630. http://dx.doi.org/10.1080/00036840600722224

Papageorgiou LC, 1987. The role of the olive tree in Greece. Olivae 19: 7-11.

Pastor J, Ruiz J, Sirvent I, 1999. A statistical test for detecting influential observations in DEA. Eur J Oper Res 115: 542-554. http://dx.doi.org/10.1016/S0377-2217(98)00153-2

Racine JS, Hart J, Li Q, 2006. Testing the significance of categorical predictor variables in nonparametric regression models. Econom Rev 25(4): 523-544. http://dx.doi.org/10.1080/07474930600972590

Sckokai P, Moro D, 2006. Modelling the reforms of the common agricultural policy for arable crops under uncertainty. Am J Agric Econ 88: 43-56. http://dx.doi.org/10.1111/j.1467-8276.2006.00857.x

Simar L, Wilson P, 2007. Estimation and inference in two-stage, semi-parametric models of production processes. J Econom 136(1): 31-64. http://dx.doi.org/10.1016/j.jeconom.2005.07.009

Stevenson RE, 1980. Likelihood functions for generalized stochastic frontier estimation. J Econom 13(1): 57-66. http://dx.doi.org/10.1016/0304-4076(80)90042-1

Tzouvelekas V, Giannakas K, Midmore P, Mattas K, 1997. Technical efficiency measures for olive-growing farms in Crete, Greece. Int Adv Econ Res 3(2): 154-170. http://dx.doi.org/10.1007/BF02294936

Tzouvelekas V, Pantzios CJ, Fotopoulos C, 2001. Technical efficiency of alternative farming systems: the case Greek organic and conventional olive-growing farms. Food Policy 29: 546-569.

Tzouvelekas V, Pantzios CJ, Fotopoulos C 2002a. Empirical evidence of technical efficiency levels in Greek organic and conventional farms. Agric Econ Rev 3: 49-60.

Tzouvelekas V, Pantzios CJ, Fotopoulos C, 2002b. Measuring multiple and single factor technical efficiency in organic farming. The case of Greek wheat farms. Br Food J 104(8): 591-609. http://dx.doi.org/10.1108/00070700210425967

Zhu X, Karagiannis G, Lansink AO, 2008. Analysing the impact of direct subsidies on the performance of the Greek olive farms with a non-monotonic efficiency effects model. Proc 12th Cong Eur Assoc Agric Econ, EAAE, Ghent, Belgium, Aug 26-29, Paper No 43612.

Published
2013-11-14
How to Cite
Kourtesi, S., Fousekis, P., & Polymeros, A. (2013). Technical efficiency of Greek olive growing farms: a robust approach with panel data. Spanish Journal of Agricultural Research, 11(4), 908-918. https://doi.org/10.5424/sjar/2013114-4423
Section
Agricultural economics