Impact of Energy Subsidies Elimination on Technology Gap Ratio in Cucumber Production

Esfanjari Kenari, Reza; Karami, Zohre; Ahmadzade, Seyadeh Sedighe

Document Type : Original Article

Authors

¹ Assistant Professor, Agricultural Economics, Faculty of Agricultural Sciences, University of Guilan

² MSc, Agricultural Economics, Shiraz University, Shiraz, Iran

³ Ph.D. Student of Agricultural Economics, Sari Agricultural Sciences and Natural Resources University

Abstract

This paper presents an analysis of technical efficiency and technology gap ratio (TGR) in greenhouse cucumber in Fars Province, Iran. Cucumber production was chosen for this study for the reason that greenhouse productions in this province
mainly have focused on this product. The data used in this study was obtained from a random sample of 127 greenhouses in Fars Province for 2010 to 2011. Metafrontier production function model for firms was used within the parametric framework of stochastic frontier analysis (SFA). The frontier models are applied in the analysis of cross-sectional data by assuming a translog functional form. Results indicate that eliminating energy input subsidies has led to significant decrease in greenhouse cucumber production efficiency so that the mean technical efficiency declined from 98% to 67 % during 2010-2011. Furthermore, subsidies elimination has also led to decrease of the mean technology gap ratio in greenhouses from 0.92 to 0.87, in other words, it has caused more distance from efficient production frontier.

Graphical Abstract

Keywords

Main Subjects

References

Aigner, D. J., Lovell, D., & Schmidt, p. (1977). Formulation and estimation of stochastic frontier production function models. Journal of Econometrics, 6 (1), 21-37.

Battese, G. E., & Coelli, T. (1995). A model for technical inefficiency effects in a stochastic frontier production function for panel data. Empirical Economics, 20 (2), 325-332.

Battese, G. E., & Coelli, T. J. (1992). Frontier production functions, technical efficiency and panel data with application to paddy farmers in India. Journal of Productivity Analysis, 3 (1), 153-169.

Battese, G.E., Rao, D.S.P., & O’Donnell, C. (2004). A metafrontier production function for estimation of technical efficiencies and technology gaps for firms operating under different technologies. Journal of Business Economics, 21 (1), 91-103.

Battese, G. Malik, SJ., & Broca, S. (1993). Production functions for wheat farmers in selected districts of Pakistan: an application of a stochastic frontier production function with time-varying inefficiency effects. Pakistan Development Review, 32 (2), 233-268.

Battese, J., & Rao, D. S. P. (2002). Technology gap, efficiency and stochastic metafrontier function. Journal of Business Economics, 1 (2), 87-93.

Coelli, T.J. (1996). A guide to FRONTIER version 4.1: A computer program for stochastic frontier production and cost function estimation. CEPA Working Papers(No. 7/96), Department of econometrics, University of New England, Armadale.

Kumbhakar, S.C. (2002). Specification and estimation of production risk, risk preferences and technical efficiency. American Journal of Agricultural Economics, 84 (1), 8-22.

Meeusen, W., & Van Den Broak, J. (1977). Efficiency estimation cobb-douglas production function with composed error.Journal of International Economics, 18 (2), 435-444.

Mehrabi Boshrabadi, H., Villano, R., & Fleming, E. (2008). Technical efficiency and environmental-technological gaps in wheat production in Kerman province of Iran: A meta-frontier analysis. Journal of Agricultural Economics, 38 (1), 67-76.

Ministry of Jihad-e-Agriculture (2010). Cultivation and production Database, Agricultural Crops Information. Retrieved from http://www.dbagri.maj.ir/Zrt/year.

Moreira, V. H., & Bravo-Ureta, B. E. (2010). Technical efficiency and metatechnology ratios for dairy farms in three southern cone countries: A stochastic metafronitier model. Journal of Productivity Analysis, 33 (1), 33-45.

Monjezi, N., & M.J. Sheikhdavoodi. (2011).Energy use pattern and optimization of energy consumption for greenhouse cucumber production in Iran using Data Envelopment Analysis (DEA). Modern Applied Science, 5,139-150.

O^,Donnell, C., Battese, G., & Rao, D. S. P. (2005). Metafrontier frameworks for the study of firm-level efficiencies and technology ratios. Unpublished paper, Centre for Efficiency and Productivity Analysis, University of Queensland, Brisbane.

Omid, M., Ghojabeige, F., Delshad, M., & Ahmadi, H. (2010). Energy use pattern and benchmarking of selected greenhouses in Iran using data envelopment analysis. Energy Conversion and Management, 52, 153-162.

Pitt, M., & Lee, L. F. (1981). The Measurement of Sources of Technical Inefficiency in the Indonesian Weavig Industry. Journal of Development Economics, 9 (1), 43-64.

Taki, M., Ajabshirchi, Y., & Mahmoudi, A. (2012). Prediction of output energy for wheat production using artificial neural networks in Esfahan province of Iran. Journal of Agricultural Technology 8(4), 1229-1242.

Villano, R., Mehrabi Boshrabadi, H., & Fleming, E. (2010). When is Metafrontier Analysis Appropriate, An Example of Varietal Differences in Pistachio Production in Iran. Journal of Agricultural Science and Technology, 12,379-389.

International Journal of Agricultural Management and Development

Impact of Energy Subsidies Elimination on Technology Gap Ratio in Cucumber Production

References

References

Battese, G.E., Rao, D.S.P., & O’Donnell, C. (2004). A metafrontier production function for estimation of technical efficiencies and technology gaps for firms operating under different technologies. Journal of Business Economics, 21 (1), 91-103.

Volume 7, Issue 2 - Serial Number 2
June 2017
Pages 237-244

Impact of Energy Subsidies Elimination on Technology Gap Ratio in Cucumber Production

References

References

Battese, G.E., Rao, D.S.P., & O’Donnell, C. (2004). A metafrontier production function for estimation of technical efficiencies and technology gaps for firms operating under different technologies. Journal of Business Economics, 21 (1), 91-103.

Volume 7, Issue 2 - Serial Number 2June 2017Pages 237-244

Volume 7, Issue 2 - Serial Number 2
June 2017
Pages 237-244