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A conditional full frontier approach for investigating the Averch-Johnson effect

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  • Halkos, George
  • Tzeremes, Nickolaos

Abstract

This paper applies a probabilistic approach in order to develop conditional and unconditional Data Envelopment Analysis (DEA) models for the measurement of sectors’ input oriented technical and scale efficiency levels for a sample of 23 Greek manufacturing sectors. In order to capture the Averch and Johnson effect (A-J effect), we measure sectors’ efficiency levels conditioned on the number of companies competing within the sectors. Particularly, various DEA models have been applied alongside with bootstrap techniques in order to determine the effect of competition conditions on sectors’ inefficiency levels. Additionally, this study illustrates how the recent developments in efficiency analysis and statistical inference can be applied when evaluating the effect of regulations in an industry. The results reveal that sectors with fewer numbers of companies appear to have greater scale and technical inefficiencies due to the existence of the A-J effect.

Suggested Citation

  • Halkos, George & Tzeremes, Nickolaos, 2011. "A conditional full frontier approach for investigating the Averch-Johnson effect," MPRA Paper 35491, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:35491
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    References listed on IDEAS

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    More about this item

    Keywords

    Averch-Johnson effect; Industry regulations; Manufacturing sectors; Nonparametric analysis;
    All these keywords.

    JEL classification:

    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General
    • L59 - Industrial Organization - - Regulation and Industrial Policy - - - Other

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