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Measuring and explaining productivity growth of renewable energy producers: An empirical study of Austrian biogas plants

Author

Listed:
  • Andreas Eder

    (Institute for Industrial Research
    University of Natural Resources and Life Sciences)

  • Bernhard Mahlberg

    (Institute for Industrial Research
    Vienna University of Economics and Business)

  • Bernhard Stürmer

    (University College of Agricultural and Environmental Pedagogy
    Austrian Compost and Biogas Association)

Abstract

This study explores productivity growth of 65 Austrian biogas plants from 2006 to 2014 using Data Envelopment Analysis. Productivity growth is measured by calculating the Malmquist productivity index, and the contributions of technical change, efficiency change, and scale change to productivity growth are isolated. The results reveal that the average annual productivity growth between 2006 and 2014 is 1.1%. The decomposition of the Malmquist productivity index shows that the annual scale change, technical change, and efficiency change for the average plant is 0.6%, 0.3%, and 0.3%, respectively. These results indicate that the exploitation of returns to scale is a major driver of productivity growth and technical change is rather low. A second-stage regression analysis reveals that rising feedstock prices incentivized efficiency improvements but initial capital subsidies did not have an impact on technical change and productivity growth.

Suggested Citation

  • 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.
    • Handle: RePEc:kap:empiri:v:48:y:2021:i:1:d:10.1007_s10663-020-09498-y
    DOI: 10.1007/s10663-020-09498-y
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    More about this item

    Keywords

    Data envelopment analysis; Malmquist productivity index; Technical change; Renewable energy sources; Biogas energy;
    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
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

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