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Bayesian Performance Evaluation

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Abstract

The distinguishing feature of the Bayesian approach in performance evaluation is that parameter uncertainty of the various models is formally taken into account along with model uncertainty as well. The usual sampling-theory approach proceeds conditionally on the parameter estimates that have been obtained. Of course, the bootstrap can be used but the justification of the bootstrap itself is only asymptotic. We do not intend here to compare and contrast, in detail, the Bayesian versus the sampling-theory approach. We should mention, however, that the Bayesian approach is equipped with numerical techniques that can handle complicated models of performance, where the sampling-theory approach is quite difficult to implement.

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Notes

  1. 1.

    See Geweke (1999). For details in stochastic frontiers, see Assaf et al. (2017).

  2. 2.

    All random effects are mutually independent and independent of the regressors for all DMUs and at all time periods.

  3. 3.

    We assume for simplicity that we have only one output and that technical inefficiency and allocative distortion parameters \(\xi\) are time-invariant.

  4. 4.

    These can be identified even if there are firm and time effects in the production function.

  5. 5.

    See Table F4.4 in http://pages.stern.nyu.edu/~wgreene/Text/Edition7/tablelist8new.htm which contains data sets for W. Greene, Econometric Analysis, 8th edition, Pearson, 2018.

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Acknowledgements

The author is indebted to an anonymous reviewer for comments on an earlier version of this chapter. Dedicated to John Geweke, Bill Greene, and Subal Kumbhakar for all that they taught me throughout the years.

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Authors and Affiliations

  1. Lancaster University Management School, Lancaster, UK

    Mike G. Tsionas

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  1. Mike G. Tsionas
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Correspondence to Mike G. Tsionas .

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Editors and Affiliations

  1. Utrecht School of Economics, Utrecht University, Utrecht, The Netherlands

    Thijs ten Raa

  2. Stern School of Business, New York University, New York, NY, USA

    William H. Greene

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Tsionas, M.G. (2019). Bayesian Performance Evaluation. In: ten Raa, T., Greene, W. (eds) The Palgrave Handbook of Economic Performance Analysis. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-23727-1_11

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