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Corporate efficiency in the UK: a stochastic frontier analysis


  • Syed Manzur Quader
  • Michael Dietrich


Purpose - – Using a panel of 1,122 UK firms listed on the London Stock Exchange over the period of 1981-2009, corporate efficiencies are predicted in this paper as inverse proxies of agency cost and the agency cost hypotheses are tested. The paper aims to discuss this issue. Design/methodology/approach - – Stochastic frontier analysis is used to estimate corporate efficiency of firms, but from two different perspectives. The long-run and short-run corporate efficiencies are predicted focussing on modern approach of value maximization and traditional approach of profit maximization, respectively. Findings - – The estimation results reveal that, an average firm in the sample achieves 74.5 percent of its best performing peer's market value and 86.6 percent of its best performing peer's profit and both of them are highly significant in the analysis. The long-run market value efficiency supports the agency cost of outside equity and the short-run profit efficiency supports the agency cost of outside debt hypothesis. Also there is a positive rank correlation between these two efficiencies which confirms that an average firm in the UK suffers from inefficiency or agency conflicts to a certain extent, no matter whether the firm is driven by short-run or long-run growth perspectives. Research limitations/implications - – The predicted broad measures of agency costs in the paper have wider implications in enhancing the understanding of the UK firms’ corporate performance especially when they operate under a relatively free and market based governance and financial system. Originality/value - – The work is distinguished by the large panel of UK firms and a long period of time that is considered. Emphasizing on the empirical implications of the distinctions between short-run and long-run efficiency is also novel.

Suggested Citation

  • Syed Manzur Quader & Michael Dietrich, 2014. "Corporate efficiency in the UK: a stochastic frontier analysis," International Journal of Productivity and Performance Management, Emerald Group Publishing, vol. 63(8), pages 991-1011, November.
  • Handle: RePEc:eme:ijppmp:v:63:y:2014:i:8:p:991-1011

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