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A Distance Function Model with Good and Bad Outputs

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  • Bokusheva, Raushan
  • Kumbhakar, Subal C.

Abstract

We present an approach that pursues an adequate representation of product transformation possibilities for a technology generating, in addition to marketed (good) products, some environmentally detrimental non-marketed byproducts (bad outputs). As the shadow price of a non-marketed output depends on its marginal transformation rates with marketed outputs, representation of technological relationships between different groups of outputs deserves a particular attention. We model the technology by using two functions: an input distance function describing technically feasible input-output combinations, and a hedonic output function capturing relationships among good and bad outputs. This procedure offers more appropriate consideration and modeling of the interactions between different groups of outputs. An empirical application of the approach to the case of Dutch dairy farms1 demonstrates the complexity of interactions between outputs and the value of more elaborate representations of production possibilities. The analysis indicates that nitrogen surplus abatement costs vary widely among Dutch dairy farms and that these costs have increased substantially over time.

Suggested Citation

  • Bokusheva, Raushan & Kumbhakar, Subal C., 2014. "A Distance Function Model with Good and Bad Outputs," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182765, European Association of Agricultural Economists.
    • Handle: RePEc:ags:eaae14:182765
    DOI: 10.22004/ag.econ.182765
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    2. Silva, Felipe & Fulginiti, Lilyan & Perrin, Richard, 2016. "Trade-off between amazon forest and agriculture in Brazil – shadow price and their substitution estimative for 2006," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235800, Agricultural and Applied Economics Association.
    3. Li, Hong-Zhou & Kopsakangas-Savolainen, Maria & Yan, Ming-Zhe & Wang, Jian-Lin & Xie, Bai-Chen, 2019. "Which provincial administrative regions in China should reduce their coal consumption? An environmental energy input requirement function based analysis," Energy Policy, Elsevier, vol. 127(C), pages 51-63.
    4. Silva, Felipe & Fulginiti, Lilyan E. & Perrin, Richard K., 2016. "Did technical change in agricultural production decrease the emission of pollutants on the Amazon Forest during 1990-2009?," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230092, Southern Agricultural Economics Association.
    5. Quintano, Claudio & Mazzocchi, Paolo & Rocca, Antonella, 2021. "Evaluation of the eco-efficiency of territorial districts with seaport economic activities," Utilities Policy, Elsevier, vol. 71(C).
    6. Bhattacharyya, Aditi & Kutlu, Levent & Sickles, Robin C., 2018. "Pricing Inputs and Outputs: Market prices versus shadow prices, market power, and welfare analysis," Working Papers 18-009, Rice University, Department of Economics.
    7. Tamara Rudinskaya & Zdeňka Náglová, 2021. "Analysis of Consumption of Nitrogen Fertilisers and Environmental Efficiency in Crop Production of EU Countries," Sustainability, MDPI, vol. 13(16), pages 1-13, August.
    8. Dakpo, K Hervé, 2016. "On modeling pollution-generating technologies: a new formulation of the by-production approach," Working Papers 245191, Institut National de la recherche Agronomique (INRA), Departement Sciences Sociales, Agriculture et Alimentation, Espace et Environnement (SAE2).
    9. K Hervé Dakpo, 2016. "On modeling pollution-generating technologies: a new formulation of the by-production approach," Working Papers SMART 16-06, INRAE UMR SMART.
    10. Adewale Henry Adenuga & John Davis & George Hutchinson & Trevor Donnellan & Myles Patton, 2019. "Environmental Efficiency and Pollution Costs of Nitrogen Surplus in Dairy Farms: A Parametric Hyperbolic Technology Distance Function Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(3), pages 1273-1298, November.

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