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Technical Efficiency and Allocative Efficiency of Beef Cattle Fattening in the Content of Digital Economy: An Empirical Study Based on Survey in China

Author

Listed:
  • Yongjie Xue

    (School of Economics, Shandong Women’s University, Ji’nan 250300, China)

  • Zhenhua Qi

    (School of Economics, Shandong Women’s University, Ji’nan 250300, China)

  • Jinling Yan

    (College of Economics and Management, Hebei Agricultural University, Baoding 071000, China)

  • Dahai Li

    (Marine Development Studies Institute, Ocean University of China, Qingdao 266100, China)

  • Huifeng Zhao

    (College of Economics and Management, Hebei Agricultural University, Baoding 071000, China)

  • Haijing Zheng

    (School of Humanities and Law, Zhejiang A&F University, Hangzhou 311300, China)

Abstract

This study applies data envelopment analysis (DEA) to gauge technical efficiency and allocative efficiency in China’s beef cattle-fattening industry using survey data. The Tobit model considers the salient determinants that drive these efficiencies. The results indicate that (1) large-scale farms exhibit robust TE and pure technical efficiencies (PTE), whereas scale efficiencies (SE) diverge significantly between large and medium-sized operations. The cost efficiency (CE) of smaller farms lags behind their larger counterparts, with the latter displaying greater revenue efficiencies (RE) and profit efficiency (PE). (2) The influence of identical factors on the efficiency of beef cattle fattening production can vary, sometimes antithetically, across different scales. Local policy interventions must be differentiated according to farm type and size. (3) The unique context of China’s national conditions and the status quo of livestock farming render the dual implementation of environmental regulations and technological subsidies less viable for Chinese beef cattle farms. These entities should prioritize production over technological innovation and advancement. Policymakers should adopt strategies such as targeted skill/technological training for farm managers at particular scales of operation. This could represent a critical trajectory to augment the efficiency of beef cattle production and increase beef yield in China.

Suggested Citation

  • Yongjie Xue & Zhenhua Qi & Jinling Yan & Dahai Li & Huifeng Zhao & Haijing Zheng, 2024. "Technical Efficiency and Allocative Efficiency of Beef Cattle Fattening in the Content of Digital Economy: An Empirical Study Based on Survey in China," Agriculture, MDPI, vol. 14(7), pages 1-24, June.
    • Handle: RePEc:gam:jagris:v:14:y:2024:i:7:p:1007-:d:1422785
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    References listed on IDEAS

    as
    1. Maristela M. Martins & Humberto F. S. Spolador & Eric Njuki, 2022. "Production environment and managerial techniques in explaining productivity growth in Brazilian beef cattle production," Agribusiness, John Wiley & Sons, Ltd., vol. 38(2), pages 371-385, April.
    2. Oleg Badunenko & Harald Tauchmann, 2019. "Simar and Wilson two-stage efficiency analysis for Stata," Stata Journal, StataCorp LP, vol. 19(4), pages 950-988, December.
    3. Timothy J. Coelli & D.S. Prasada Rao & Christopher J. O’Donnell & George E. Battese, 2005. "An Introduction to Efficiency and Productivity Analysis," Springer Books, Springer, edition 0, number 978-0-387-25895-9, March.
    4. Fare, Rolf & Shawna Grosskopf & Mary Norris & Zhongyang Zhang, 1994. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries," American Economic Review, American Economic Association, vol. 84(1), pages 66-83, March.
    5. Yongjie Xue & Jinling Yan & Yongfu Cui & Huifeng Zhao & Ya’nan Zhang & Changhai Ma & Haijing Zheng, 2022. "The Technical Efficiency of Beef Calf Production Systems: Evidence from a Survey in Hebei, China," Agriculture, MDPI, vol. 12(10), pages 1-22, October.
    6. Johnson, Andrew L. & Kuosmanen, Timo, 2012. "One-stage and two-stage DEA estimation of the effects of contextual variables," European Journal of Operational Research, Elsevier, vol. 220(2), pages 559-570.
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