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On endogenizing direction vectors in parametric directional distance function-based models

Author

Listed:
  • Rolf Färe
  • Carl Pasurka
  • Michael Vardanyan

    (LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique)

Abstract

Empirical studies of production technologies using directional distance functions have traditionally resorted to ad hoc ways of choosing direction vectors for these functions. Yet it is well known that the assumptions placed on the direction vector can have a non-negligible impact on the estimation results. Several recent studies have attempted to address this issue using econometric estimation and Data Envelopment Analysis. We demonstrate the use of parametric nonlinear programming to select the direction vector optimally. Data on the US electric power plants from early 2000s are used to show the difference between results obtained with endogenously determined direction vectors and ad hoc vectors.
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Suggested Citation

  • Rolf Färe & Carl Pasurka & Michael Vardanyan, 2017. "On endogenizing direction vectors in parametric directional distance function-based models," Post-Print hal-01744614, HAL.
  • Handle: RePEc:hal:journl:hal-01744614
    DOI: 10.1016/j.ejor.2017.03.040
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    1. Krüger, Jens & Hampf, Benjamin, 2015. "Optimal Directions for Directional Distance Functions: An Exploration of Potential Reductions of Greenhouse Gases," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 77007, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    2. Chambers, Robert & Färe, Rolf & Grosskopf, Shawna & Vardanyan, Michael, 2013. "Generalized quadratic revenue functions," Journal of Econometrics, Elsevier, vol. 173(1), pages 11-21.
    3. Atkinson, Scott E. & Tsionas, Mike G., 2016. "Directional distance functions: Optimal endogenous directions," Journal of Econometrics, Elsevier, vol. 190(2), pages 301-314.
    4. Bruno, Clementina & Manello, Alessandro, 2015. "Benchmarking and effects of reforms in the fixed telecommunications industry: A DDF approach," Telecommunications Policy, Elsevier, vol. 39(2), pages 127-139.
    5. John Swinton, 2004. "Phase I Completed: An Empirical Assessment of the 1990 CAAA," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 27(3), pages 227-246, March.
    6. Coggins, Jay S. & Swinton, John R., 1996. "The Price of Pollution: A Dual Approach to Valuing SO2Allowances," Journal of Environmental Economics and Management, Elsevier, vol. 30(1), pages 58-72, January.
    7. Rolf Färe & Carlos Martins-Filho & Michael Vardanyan, 2010. "On functional form representation of multi-output production technologies," Journal of Productivity Analysis, Springer, vol. 33(2), pages 81-96, April.
    8. R. Färe & S. Grosskopf & G. Whittaker, 2013. "Directional output distance functions: endogenous directions based on exogenous normalization constraints," Journal of Productivity Analysis, Springer, vol. 40(3), pages 267-269, December.
    9. Falavigna, Greta & Ippoliti, Roberto & Manello, Alessandro & Ramello, Giovanni B., 2015. "Judicial productivity, delay and efficiency: A Directional Distance Function (DDF) approach," European Journal of Operational Research, Elsevier, vol. 240(2), pages 592-601.
    10. Cinzia Daraio & Léopold Simar, 2016. "Efficiency and benchmarking with directional distances: a data-driven approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(7), pages 928-944, July.
    11. Luenberger, David G., 1992. "Benefit functions and duality," Journal of Mathematical Economics, Elsevier, vol. 21(5), pages 461-481.
    12. Curtis Carlson & Dallas Burtraw & Maureen Cropper & Karen L. Palmer, 2000. "Sulfur Dioxide Control by Electric Utilities: What Are the Gains from Trade?," Journal of Political Economy, University of Chicago Press, vol. 108(6), pages 1292-1326, December.
    13. Yaisawarng, Suthathip & Klein, J Douglass, 1994. "The Effects of Sulfur Dioxide Controls on Productivity Change in the U.S. Electric Power Industry," The Review of Economics and Statistics, MIT Press, vol. 76(3), pages 447-460, August.
    14. John R. Swinton, 1998. "At What Cost do We Reduce Pollution? Shadow Prices of SO2 Emissions," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 63-83.
    15. Martini, Gianmaria & Manello, Alessandro & Scotti, Davide, 2013. "The influence of fleet mix, ownership and LCCs on airports’ technical/environmental efficiency," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 50(C), pages 37-52.
    16. Benjamin Hampf & Jens J. Krüger, 2015. "Optimal Directions for Directional Distance Functions: An Exploration of Potential Reductions of Greenhouse Gases," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(3), pages 920-938.
    17. Jose Zofio & Jesus Pastor & Juan Aparicio, 2013. "The directional profit efficiency measure: on why profit inefficiency is either technical or allocative," Journal of Productivity Analysis, Springer, vol. 40(3), pages 257-266, December.
    18. Antonio Peyrache & Cinzia Daraio, 2012. "Empirical tools to assess the sensitivity of directional distance functions to direction selection," Applied Economics, Taylor & Francis Journals, vol. 44(8), pages 933-943, March.
    19. Coelli, Tim & Perelman, Sergio, 1999. "A comparison of parametric and non-parametric distance functions: With application to European railways," European Journal of Operational Research, Elsevier, vol. 117(2), pages 326-339, September.
    20. Robert G. Chambers, 2002. "Exact nonradial input, output, and productivity measurement," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 20(4), pages 751-765.
    21. Chambers, Robert G. & Fare, Rolf & Grosskopf, Shawna, 1996. "Productivity Growth in APEC Countries," Working Papers 197843, University of Maryland, Department of Agricultural and Resource Economics.
    22. Benoit Dervaux & Gary Ferrier & Herve Leleu & Vivian Valdmanis, 2004. "Comparing French and US hospital technologies: a directional input distance function approach," Applied Economics, Taylor & Francis Journals, vol. 36(10), pages 1065-1081.
    23. Fare, Rolf & Grosskopf, Shawna & Noh, Dong-Woon & Weber, William, 2005. "Characteristics of a polluting technology: theory and practice," Journal of Econometrics, Elsevier, vol. 126(2), pages 469-492, June.
    24. Rolf Färe & Shawna Grosskopf & William L. Weber, 2001. "Shadow Prices of Missouri Public Conservation Land," Public Finance Review, , vol. 29(6), pages 444-460, November.
    25. Chambers, Robert G. & Chung, Yangho & Fare, Rolf, 1996. "Benefit and Distance Functions," Journal of Economic Theory, Elsevier, vol. 70(2), pages 407-419, August.
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    8. Layer, Kevin & Johnson, Andrew L. & Sickles, Robin C. & Ferrier, Gary D., 2020. "Direction selection in stochastic directional distance functions," European Journal of Operational Research, Elsevier, vol. 280(1), pages 351-364.
    9. Ma, Chunbo & Hailu, Atakelty & You, Chaoying, 2019. "A critical review of distance function based economic research on China’s marginal abatement cost of carbon dioxide emissions," Energy Economics, Elsevier, vol. 84(C).
    10. Tsionas, Mike G., 2020. "Directional technology distance functions through duality," Economics Letters, Elsevier, vol. 190(C).
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    16. Wu, F. & Wang, S.Y. & Zhou, P., 2023. "Marginal abatement cost of carbon dioxide emissions: The role of abatement options," European Journal of Operational Research, Elsevier, vol. 310(2), pages 891-901.
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