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Are distance measures effective at measuring efficiency? DEA meets the vintage model

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  • Constantin Belu

Abstract

In this paper I develop a model of capacity expansion that accounts for differences in the productivity of the installed capital due to technical progress exhibited by the ex ante production function. A putty-clay set-up is assumed, meaning flexible input coefficients and substitution possibilities ex ante, but fixed input coefficients ex post. Based on the model, I generate a capacity distribution of DMUs (vintages) describing an industry with a homogeneous output and perform an efficiency analysis employing data envelopment analysis, a popular non-parametric method for estimating efficiency. The results show that in some circumstances older vintages might appear on the efficiency frontier, unlike some newer vintages that are found to be inefficient, despite benefiting from the advancement of the technology. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Constantin Belu, 2015. "Are distance measures effective at measuring efficiency? DEA meets the vintage model," Journal of Productivity Analysis, Springer, vol. 43(3), pages 237-248, June.
    • Handle: RePEc:kap:jproda:v:43:y:2015:i:3:p:237-248
    DOI: 10.1007/s11123-015-0438-y
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    References listed on IDEAS

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    3. Abel, Andrew B. & Eberly, Janice C., 1999. "The effects of irreversibility and uncertainty on capital accumulation," Journal of Monetary Economics, Elsevier, vol. 44(3), pages 339-377, December.
    4. Kumbhakar, Subal C. & Heshmati, Almas & Hjalmarsson, Lennart, 1997. "Temporal patterns of technical efficiency: Results from competing models," International Journal of Industrial Organization, Elsevier, vol. 15(5), pages 597-616, August.
    5. Caballero, Ricardo J & Pindyck, Robert S, 1996. "Uncertainty, Investment, and Industry Evolution," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 37(3), pages 641-662, August.
    6. Jeffrey Campbell, 1998. "Entry, Exit, Embodied Technology, and Business Cycles," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 1(2), pages 371-408, April.
    7. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    8. Mark Doms & Eric J. Bartelsman, 2000. "Understanding Productivity: Lessons from Longitudinal Microdata," Journal of Economic Literature, American Economic Association, vol. 38(3), pages 569-594, September.
    9. repec:bla:scandj:v:85:y:1983:i:3:p:393-402 is not listed on IDEAS
    10. 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.
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    12. Førsund, Finn R., 2010. "Dynamic Efficiency Measurement," Indian Economic Review, Department of Economics, Delhi School of Economics, vol. 45(2), pages 125-159.
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    Cited by:

    1. Hampf, Benjamin, 2017. "Rational inefficiency, adjustment costs and sequential technologies," European Journal of Operational Research, Elsevier, vol. 263(3), pages 1095-1108.
    2. Kristiaan Kerstens & Jafar Sadeghi & Ignace Woestyne & John Walden, 2024. "Short-run Johansen frontier-based industry models: methodological refinements and empirical illustration on fisheries," Journal of Productivity Analysis, Springer, vol. 61(1), pages 47-62, February.
    3. Hampf, Benjamin, 2016. "Rational Inefficiency, Adjustment Costs and Sequential Technologies," VfS Annual Conference 2016 (Augsburg): Demographic Change 145796, Verein für Socialpolitik / German Economic Association.
    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. Førsund, Finn. R., 2015. "Productivity Interpretations of the Farrell Efficiency Measures and the Malmquist Index and its Decomposition," Memorandum 14/2015, Oslo University, Department of Economics.

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    More about this item

    Keywords

    Technical efficiency; Vintage; Putty-clay; Best-practice; Data envelopment analysis; DEA; C61; D24;
    All these keywords.

    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

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