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Technical efficiency and environmental‐technological gaps in wheat production in Kerman province of Iran

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  • Hossein Mehrabi Boshrabadi
  • Renato Villano
  • Euan Fleming

Abstract

This article reports on an analysis of technical efficiency and environment‐technology gaps in wheat farming in Iran. A random sample of 676 farmers was selected from the province of Kerman in 2004. In this study, Kerman is divided into five regions based on climatic and geographical conditions. The province is situated in the south‐eastern part of Iran and contains substantial variations in climate. The technical efficiency indices are computed using three approaches. First, a standard stochastic production frontier was employed using pooled cross‐sectional data. Secondly, regional stochastic frontier production functions were estimated. Lastly, the metafrontier approach was used because production environments and technologies are expected to differ between the five regions. Use of this method enabled technical efficiency scores to be corrected by the coefficient of the environment‐technology gap ratio (ETGR). Estimates of the frontier were obtained assuming a translog functional form. Results indicate that farms differ in technical efficiencies, ETGRs and the use they make of inputs. Mean ETGRs vary substantially between farms and across regions whereas mean technical efficiencies are reasonably similar across regions but differ in the extent of variation among farms within each region. A low ETGR for the north‐western region is attributable to a lack of water resources, restricting the ability of farmers to benefit from improved varieties, and small‐sized farms, which militate against mechanization embodying labor‐saving technologies. The results do not lead to definitive policy prescriptions. But they do provide indicators of where farm‐level research is likely to be most effective in closing the environment‐technology gap, for example by enabling farmers to take greater advantage of the productivity‐enhancing effects of improved technologies embodied in cropping machinery and irrigation facilities. The ability of farmers to alleviate the environmental constraints on wheat production is likely to vary across regions, and will depend on the nature of these constraints and the ability of researchers to design technologies suited to each region that will overcome them.

Suggested Citation

  • Hossein Mehrabi Boshrabadi & Renato Villano & Euan Fleming, 2008. "Technical efficiency and environmental‐technological gaps in wheat production in Kerman province of Iran," Agricultural Economics, International Association of Agricultural Economists, vol. 38(1), pages 67-76, January.
  • Handle: RePEc:bla:agecon:v:38:y:2008:i:1:p:67-76
    DOI: 10.1111/j.1574-0862.2007.00282.x
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    1. Subal C. Kumbhakar, 2002. "Specification and Estimation of Production Risk, Risk Preferences and Technical Efficiency," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(1), pages 8-22.
    2. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    3. 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.
    4. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    5. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
    6. Bakhshoodeh, Mohammad & Thomson, Kenneth J., 2001. "Input and output technical efficiencies of wheat production in Kerman, Iran," Agricultural Economics, Blackwell, vol. 24(3), pages 307-313, March.
    7. 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.
    8. George E. Battese & D. S. Prasada Rao, 2002. "Technology Gap, Efficiency, and a Stochastic Metafrontier Function," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 1(2), pages 87-93, August.
    9. 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.
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    Cited by:

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    3. Asante, Bright O. & Temoso, Omphile & Addai, Kwabena N. & Villano, Renato A., 2019. "Evaluating productivity gaps in maize production across different agroecological zones in Ghana," Agricultural Systems, Elsevier, vol. 176(C).
    4. Otieno, David Jakinda & Hubbard, Lionel J. & Ruto, Eric, 2011. "Technical efficiency and technology gaps in beef cattle production systems in Kenya: A stochastic metafrontier analysis," 85th Annual Conference, April 18-20, 2011, Warwick University, Coventry, UK 108947, Agricultural Economics Society.
    5. Yung-Hsiang LU & Ku-Hsieh CHEN & Chun-Cheng WU, 2015. "Cross-country analysis of efficiency and productivity in the biotech industry: an application of the generalized metafrontier Malmquist productivity index," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 61(3), pages 116-134.
    6. Otieno, David Jakinda & Hubbard, Lionel J. & Ruto, Eric, 2012. "Determinants of technical efficiency in beef cattle production in Kenya," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 125853, International Association of Agricultural Economists.
    7. Jacob Asravor & Alexander N. Wiredu & Khalid Siddig & Edward E. Onumah, 2019. "Evaluating the Environmental-Technology Gaps of Rice Farms in Distinct Agro-Ecological Zones of Ghana," Sustainability, MDPI, vol. 11(7), pages 1-16, April.
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    10. Lachaud, Michee & Bravo-Ureta, Boris & Ludena, Carlos, 2015. "Agricultural Productivity Growth in Latin America and the Caribbean (LAC): An analysis of Climatic Effects, Convergence, and Catch-up," 2015 Conference, August 9-14, 2015, Milan, Italy 211721, International Association of Agricultural Economists.
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    12. Cardwell, Ryan & Ghazalian, Pascal L., 2022. "State-trading enterprises and productivity: Farm-level evidence from Canadian agriculture," 96th Annual Conference, April 4-6, 2022, K U Leuven, Belgium 321159, Agricultural Economics Society - AES.
    13. Xiangfei Xin & Yi Zhang & Jimin Wang & John Alexander Nuetah, 2016. "Effects of Farm Size on Technical Efficiency in China's Broiler Sector: A Stochastic Meta-Frontier Approach," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 64(3), pages 493-516, September.
    14. Agnes Gold & Stefan Gold, 2019. "Drivers of Farm Efficiency and Their Potential for Development in a Changing Agricultural Setting in Kerala, India," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 31(4), pages 855-880, September.
    15. Saeid Hajihassaniasl & Recep Kök, 2016. "Scale effect in Turkish manufacturing industry: stochastic metafrontier analysis," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 5(1), pages 1-17, December.
    16. Nwigwe, Cecilia & Okoruwa, Victor & Obi-Egbedi, Oghenerueme, 2015. "Efficiency differentials and technological gaps in beef cattle production systems in Nigeria," 2015 Conference, August 9-14, 2015, Milan, Italy 229377, International Association of Agricultural Economists.
    17. Lachaud, Michee Arnold & Bravo-Ureta, Boris E. & Ludena, Carlos E., 2015. "Agricultural productivity growth in Latin America and the Caribbean and other world regions: An analysis of climatic effects, convergence and catch-up," Working Papers 40, University of Connecticut, Department of Agricultural and Resource Economics, Charles J. Zwick Center for Food and Resource Policy.
    18. Villano, Renato & Asante, Bright Owusu & Bravo-Ureta, Boris, 2019. "Farming systems and productivity gaps: Opportunities for improving smallholder performance in the Forest-Savannah transition zone of Ghana," Land Use Policy, Elsevier, vol. 82(C), pages 220-227.
    19. Ahmad, Shabbir & Shankar, Sriram & Steen, John & Verreynne, Martie-Louise & Burki, Abid Aman, 2021. "Using measures of efficiency for regionally-targeted smallholder policy intervention: The case of Pakistan’s horticulture sector," Land Use Policy, Elsevier, vol. 101(C).

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