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Bayesian Approach to Disentangling Technical and Environmental Productivity

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  • Malikov, Emir
  • Kumbhakar, Subal C.
  • Tsionas, Efthymios G.

Abstract

This paper models the firm's production process as a system of simultaneous technologies for desirable and undesirable outputs. Desirable outputs are produced by transforming inputs via the conventional transformation function, whereas (consistent with the material balance condition) undesirable outputs are by-produced via the so-called "residual generation technology". By separating the production of undesirable outputs from that of desirable outputs, not only do we ensure that undesirable outputs are not modeled as inputs and thus satisfy costly disposability, but we are also able to differentiate between the traditional (desirable-output-oriented) technical productivity and the undesirable-output-oriented environmental, or so-called "green", productivity. To measure the latter, we derive a Solow-type Divisia environmental productivity index which, unlike conventional productivity indices, allows crediting the ceteris paribus reduction in undesirable outputs. Our index also provides a meaningful way to decompose environmental productivity into environmental technological and efficiency changes.

Suggested Citation

  • Malikov, Emir & Kumbhakar, Subal C. & Tsionas, Efthymios G., 2015. "Bayesian Approach to Disentangling Technical and Environmental Productivity," MPRA Paper 64877, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:64877
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    References listed on IDEAS

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    Cited by:

    1. Emir Malikov & Subal C. Kumbhakar & Mike G. Tsionas, 2016. "A Cost System Approach to the Stochastic Directional Technology Distance Function with Undesirable Outputs: The Case of us Banks in 2001–2010," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1407-1429, November.
    2. Sushama Murty & R. Robert Russell, "undated". "Bad Outputs," Centre for International Trade and Development, Jawaharlal Nehru University, New Delhi Discussion Papers 17-06, Centre for International Trade and Development, Jawaharlal Nehru University, New Delhi, India.
    3. Iordanis Parikoglou & Grigorios Emvalomatis & Doris Läpple & Fiona Thorne & Michael Wallace, 2024. "The contribution of innovation to farm-level productivity," Journal of Productivity Analysis, Springer, vol. 62(2), pages 239-255, October.
    4. Finn R. Førsund, 2018. "Multi-equation modelling of desirable and undesirable outputs satisfying the materials balance," Empirical Economics, Springer, vol. 54(1), pages 67-99, February.
    5. Emir Malikov & Raushan Bokusheva & Subal C. Kumbhakar, 2018. "A hedonic-output-index-based approach to modeling polluting technologies," Empirical Economics, Springer, vol. 54(1), pages 287-308, February.
    6. Sushama Murty & Resham Nagpal, "undated". "Weighted index of graph efficiency improvements for a by-production technology and its application to Indian coal-based thermal power sector," Centre for International Trade and Development, Jawaharlal Nehru University, New Delhi Discussion Papers 18-08, Centre for International Trade and Development, Jawaharlal Nehru University, New Delhi, India.

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    More about this item

    Keywords

    bad output; by-production; efficiency; MCMC; productivity;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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