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Energy Efficiency and Mitigation of Greenhouse Gas Emissions in Mexico's Manufacturing Sector

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  • Anna D. Mata
  • Héctor M. Núñez

Abstract

This study examines the energy efficiency and environmental performance of Mexico's manufacturing sector across regions. We employ a Data Envelopment Analysis model that optimizes the weighted output-input ratio for each decision-making unit. Specifically, a non-radial directional distance function model is used to account for both desirable outputs and undesirable outputs, represented by greenhouse gas emissions. The findings show that including undesirable outputs reduces the estimated economic efficiency. Over the analysis period, the production frontier shifted only modestly. Regionally, northern states perform best, while southern states lag behind, revealing considerable potential for national energy and emission savings.

Suggested Citation

  • Anna D. Mata & Héctor M. Núñez, 2025. "Energy Efficiency and Mitigation of Greenhouse Gas Emissions in Mexico's Manufacturing Sector," Working Papers 2025-10, Banco de México.
    • Handle: RePEc:bdm:wpaper:2025-10
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    File URL: https://www.banxico.org.mx/publications-and-press/banco-de-mexico-working-papers/%7BF465355C-5D73-9479-AAA2-9E30BC6BDA9E%7D.pdf
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    References listed on IDEAS

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    1. Leopold Simar & Paul Wilson, 2000. "A general methodology for bootstrapping in non-parametric frontier models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(6), pages 779-802.
    2. Esmeralda Ramalho & Joaquim Ramalho & Pedro Henriques, 2010. "Fractional regression models for second stage DEA efficiency analyses," Journal of Productivity Analysis, Springer, vol. 34(3), pages 239-255, December.
    3. Zaim, Osman, 2004. "Measuring environmental performance of state manufacturing through changes in pollution intensities: a DEA framework," Ecological Economics, Elsevier, vol. 48(1), pages 37-47, January.
    4. Böhmelt, Tobias & Vaziri, Farzad & Ward, Hugh, 2018. "Does green taxation drive countries towards the carbon efficiency frontier?," Journal of Public Policy, Cambridge University Press, vol. 38(4), pages 481-509, December.
    5. Wu, F. & Fan, L.W. & Zhou, P. & Zhou, D.Q., 2012. "Industrial energy efficiency with CO2 emissions in China: A nonparametric analysis," Energy Policy, Elsevier, vol. 49(C), pages 164-172.
    6. A. Charnes & W. W. Cooper & E. Rhodes, 1981. "Evaluating Program and Managerial Efficiency: An Application of Data Envelopment Analysis to Program Follow Through," Management Science, INFORMS, vol. 27(6), pages 668-697, June.
    7. Bannister, Geoffrey J. & Stolp, Chandler, 1995. "Regional concentration and efficiency in Mexican manufacturing," European Journal of Operational Research, Elsevier, vol. 80(3), pages 672-690, February.
    8. Wang, H. & Zhou, P. & Zhou, D.Q., 2013. "Scenario-based energy efficiency and productivity in China: A non-radial directional distance function analysis," Energy Economics, Elsevier, vol. 40(C), pages 795-803.
    9. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    10. Zhongsheng Hua & Yiwen Bian, 2007. "DEA with Undesirable Factors," Springer Books, in: Joe Zhu & Wade D. Cook (ed.), Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis, chapter 0, pages 103-121, Springer.
    11. Daoping Wang & Kerui Du & Ning Zhang, 2022. "Measuring technical efficiency and total factor productivity change with undesirable outputs in Stata," Stata Journal, StataCorp LLC, vol. 22(1), pages 103-124, March.
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    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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