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Malmquist Productivity Index Decompositions: A Unifying Framework

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  • Zofío, José Luis

    (Departamento de Análisis Económico (Teoría e Historia Económica). Universidad Autónoma de Madrid.)

Abstract

In two widely cited but unpublished working papers, Simar and Wilson (1998) and Zofío and Lovell (1998) proposed an alternative decomposition of the Malmquist Productivity Index, which retained what seemed to be the strongholds of previous proposals with regard to the contribution of technological and efficiency change to productivity change. Namely, a technical change term with regard to the best practice (VRS) technology which is to be found in Ray and Desli (1997) and a scale efficiency change term that illustrates a firm’s situation with regard to optimal scale (benchmark technology), Färe, Grosskopf, Norris and Zhang (1994). Attaining this objective required the introduction of an additional term in the Malmquist Productivity Index decomposition, which would reflect the scale bias of technical change. It is our objective to provide economic rationale for this term within a theory of production context, the existing decompositions and recent articles that further elaborate on this issue. The ideas are illustrated using productivity trends in 17 OECD countries

Suggested Citation

  • Zofío, José Luis, 2006. "Malmquist Productivity Index Decompositions: A Unifying Framework," Working Papers in Economic Theory 2006/12, Universidad Autónoma de Madrid (Spain), Department of Economic Analysis (Economic Theory and Economic History).
    • Handle: RePEc:uam:wpaper:200612
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    References listed on IDEAS

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    1. Simar, L. & Wilson, P.W., 1998. "Productivity Growth in Industrialized Countries," Papers 9810, Catholique de Louvain - Institut de statistique.
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    Cited by:

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    2. George E. Halkos & Nickolaos G. Tzeremes, 2015. "Measuring Seaports' Productivity: A Malmquist Productivity Index Decomposition Approach," Journal of Transport Economics and Policy, University of Bath, vol. 49(2), pages 355-376, April.
    3. Byeong U. Park & Léopold Simar & Valentin Zelenyuk, 2013. "Non-Parametric Approach to Dynamic Time Series Discrete Choice Models," CEPA Working Papers Series WP092013, School of Economics, University of Queensland, Australia.
    4. Andreas Eder & Bernhard Mahlberg & Bernhard Stürmer, 2021. "Measuring and explaining productivity growth of renewable energy producers: An empirical study of Austrian biogas plants," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(1), pages 37-63, February.
    5. Jakub Growiec, 2013. "On the measurement of technological progress across countries," Bank i Kredyt, Narodowy Bank Polski, vol. 44(5), pages 467-504.
    6. Mengchao Yao & Yihua Zhang, 2021. "Evaluation and Optimization of Urban Land-Use Efficiency: A Case Study in Sichuan Province of China," Sustainability, MDPI, vol. 13(4), pages 1-22, February.
    7. Bert Balk, 2003. "The Residual: On Monitoring and Benchmarking Firms, Industries, and Economies with Respect to Productivity," Journal of Productivity Analysis, Springer, vol. 20(1), pages 5-47, July.

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    More about this item

    Keywords

    Productivity Change; Malmquist Indices; Distance Functions;
    All these keywords.

    JEL classification:

    • 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
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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