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Technical Efficiency Under Producer’S Individual Technology: A Metafrontier Analysis

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  • Wang, Xiaobing
  • Hockmann, Heinrich

Abstract

Differences in resource endowment between regions influence the technologies applied in agriculture and cause location-specific effects on production and technical change. Access to technologies may also differ within regions because producers may apply different technologies in production due to different characteristics. Within this setting, we extend the existing literature by considering that producers face region- and farm-specific production frontiers. The treatment of essentially heterogeneous technical efficiency (TE) is performed following a two-step procedure. First, a random coefficient specification of the production technology is used to measure the interactions of technology adoption with time, input factors and output. Second, linear programming techniques are employed to envelop the optimal level of technology. This procedure is applied to household-level data from eastern, central and western provinces in China. Our results provide evidence that technical efficiency is significantly affected by farm heterogeneity. This factor influences TE directly as a producer-specific input, and indirectly through interaction with observable inputs such as land, labor, capital and intermediate inputs. Our results also prove the assumption that farming technology exhibits region-specific characteristics. Furthermore, there is a disparity of TE across provinces that narrows over the study period and is driven by the shifts of production to the metafrontier.

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  • Wang, Xiaobing & Hockmann, Heinrich, 2012. "Technical Efficiency Under Producer’S Individual Technology: A Metafrontier Analysis," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126755, International Association of Agricultural Economists.
    • Handle: RePEc:ags:iaae12:126755
    DOI: 10.22004/ag.econ.126755
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    1. Yanjie Zhang & Xiaobing Wang & Thomas Glauben & Bernhard Brümmer, 2011. "The impact of land reallocation on technical efficiency: evidence from China," Agricultural Economics, International Association of Agricultural Economists, vol. 42(4), pages 495-507, July.
    2. Yiping Huang & K.P. Kalirajan, 1997. "Potential of China's grain production: evidence from the household data," Agricultural Economics, International Association of Agricultural Economists, vol. 17(2-3), pages 191-199, December.
    3. Liu, Zinan & Zhuang, Juzhong, 2000. "Determinants of Technical Efficiency in Post-Collective Chinese Agriculture: Evidence from Farm-Level Data," Journal of Comparative Economics, Elsevier, vol. 28(3), pages 545-564, September.
    4. Pender, John L. & Place, Frank & Ehui, Simeon K., 1999. "Strategies for sustainable agricultural development in the East African highlands:," EPTD discussion papers 41, International Food Policy Research Institute (IFPRI).
    5. Bryce Stewart & Terrence Veeman & James Unterschultz, 2009. "Crops and Livestock Productivity Growth in the Prairies: The Impacts of Technical Change and Scale," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 57(3), pages 379-394, September.
    6. Yujiro Hayami, 1969. "Sources of Agricultural Productivity Gap Among Selected Countries," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 51(3), pages 564-575.
    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. Bernhard Brümmer & Thomas Glauben & Geert Thijssen, 2002. "Decomposition of Productivity Growth Using Distance Functions: The Case of Dairy Farms in Three European Countries," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(3), pages 628-644.
    9. Huang, Jikun & Wang, Xiaobing & Zhi, Huayong & Huang, Zhurong & Rozelle, Scott, 2011. "Subsidies and distortions in China’s agriculture: evidence from producer-level data," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 55(1), pages 1-19.
    10. Bill Greene with Antonio Alvarez (Univ. of Oviedo) & Carlos Arias (Univ. of Leon), 2004. "Accounting For Unobservables In Production Models: Management And Inefficiency," Econometric Society 2004 Australasian Meetings 341, Econometric Society.
    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. 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.
    13. HU, Ruifa & YANG, Zhijian & KELLY, Peter & HUANG, Jikun, 2009. "Agricultural extension system reform and agent time allocation in China," China Economic Review, Elsevier, vol. 20(2), pages 303-315, June.
    14. Mao, Weining & Koo, Won W., 1997. "Productivity growth, technological progress, and efficiency change in chinese agriculture after rural economic reforms: A DEA approach," China Economic Review, Elsevier, vol. 8(2), pages 157-174.
    15. Jirong Wang & Eric J. Wailes & Gail L. Cramer, 1996. "A Shadow-Price Frontier Measurement of Profit Efficiency in Chinese Agriculture," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(1), pages 146-156.
    16. Shenggen Fan, 1991. "Effects of Technological Change and Institutional Reform on Production Growth in Chinese Agriculture," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 73(2), pages 266-275.
    17. 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.
    18. Boris Bravo-Ureta & Daniel Solís & Víctor Moreira López & José Maripani & Abdourahmane Thiam & Teodoro Rivas, 2007. "Technical efficiency in farming: a meta-regression analysis," Journal of Productivity Analysis, Springer, vol. 27(1), pages 57-72, February.
    19. Hayami, Yujiro & Ruttan, Vernon W, 1970. "Agricultural Productivity Differences Among Countries," American Economic Review, American Economic Association, vol. 60(5), pages 895-911, December.
    20. Chen, Zhuo & Song, Shunfeng, 2008. "Efficiency and technology gap in China's agriculture: A regional meta-frontier analysis," China Economic Review, Elsevier, vol. 19(2), pages 287-296, June.
    21. Kung, James Kai-sing, 2002. "Off-Farm Labor Markets and the Emergence of Land Rental Markets in Rural China," Journal of Comparative Economics, Elsevier, vol. 30(2), pages 395-414, June.
    22. K.P. Kalirajan & M.B. Obwona & S. Zhao, 1996. "A Decomposition of Total Factor Productivity Growth: The Case of Chinese Agricultural Growth before and after Reforms," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(2), pages 331-338.
    23. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    24. W, Y, 1995. "Productivity Growth, Technological Progress, and Technical Efficiency Change in China: A Three-Sector Analysis1," Journal of Comparative Economics, Elsevier, vol. 21(2), pages 207-229, October.
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