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Accounting for Bads in the Measurement of Productivity Growth: A Cost Indirect Malmquist Productivity Measure and it Application to U.S. Agriculture

Author

Listed:
  • Ball, V. Eldon
  • Fare, Rolf
  • Grosskopf, Shawna
  • Zaim, O.
  • Nehring, Richard F.

Abstract

This paper starts with the basic premise that the conventional measures of productivity growth, which ignore joint production of good and bad outputs, are biased. We then construct an alternative productivity growth measure using activity analysis. An application to U.S. agriculture demonstrates its usefulness. More specifically, we show that the Tornqvist index of productivity is biased upward when production of undesirable outputs or "bads" is increasing. Conversely, this same measure of productivity is biased downward when externalities in production are decreasing.

Suggested Citation

  • Ball, V. Eldon & Fare, Rolf & Grosskopf, Shawna & Zaim, O. & Nehring, Richard F., 2001. "Accounting for Bads in the Measurement of Productivity Growth: A Cost Indirect Malmquist Productivity Measure and it Application to U.S. Agriculture," 2001 Annual meeting, August 5-8, Chicago, IL 20442, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    • Handle: RePEc:ags:aaea01:20442
    DOI: 10.22004/ag.econ.20442
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    References listed on IDEAS

    as
    1. Ball, V. Eldon & Butault, Jean-Pierre & Nehring, Richard, 2000. "U. S . Agriculture, 1960-96: A Multilateral Comparison of Total Factor Productivity," Staff Reports 276687, United States Department of Agriculture, Economic Research Service.
    2. V. Eldon Ball & Frank M. Gollop & Alison Kelly-Hawke & Gregory P. Swinand, 1999. "Patterns of State Productivity Growth in the U.S. Farm Sector: Linking State and Aggregate Models," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(1), pages 164-179.
    3. Fare, Rolf, et al, 1989. "Multilateral Productivity Comparisons When Some Outputs Are Undesirable: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 90-98, February.
    4. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    5. Fare, R. & Grosskopf, S. & Pasurka, C., 1986. "Effects on relative efficiency in electric power generation due to environmental controls," Resources and Energy, Elsevier, vol. 8(2), pages 167-184, June.
    6. Daniel Tyteca, 1997. "Linear Programming Models for the Measurement of Environmental Performance of Firms—Concepts and Empirical Results," Journal of Productivity Analysis, Springer, vol. 8(2), pages 183-197, May.
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    Cited by:

    1. Genzhong Li & Decai Tang & Valentina Boamah & Zhiwei Pan, 2021. "Evaluation and Influencing Factors of Agricultural Green Efficiency in Jianghuai Ecological Economic Zone," Sustainability, MDPI, vol. 14(1), pages 1-15, December.
    2. 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.

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