Abstract
The stochastic frontier analysis is an econometric approach to efficiency measurement. The basic idea is the introduction of two error components, a random error term and an inefficiency term. For both terms, a distributional assumption is made, which facilitates maximum likelihood estimation.
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Notes
- 1.
For example a winemaker cutting his grapevines too rigorously and thereby lowering his harvest.
- 2.
For example, the weather conditions could be either advantageous or disadvantageous for the winemaker.
References
Aigner D, Lovell CK, Schmidt P (1977) Formulation and estimation of stochastic frontier production function models. J Econometrics 6:21–37
Greene WH (2008) The econometric approach to efficiency analysis. In: Fried HO, Lovell CAK, Schmidt SS (eds) The measurement of productive efficiency and productivity growth, chap 2. Oxford University Press, New York, pp 92–250
Kumbhakar SC, Lovell CK (2000) Stochastic frontier analysis. Cambridge University Press, Cambridge
Meeusen W, van de Broeck J (1977) Efficiency estimation from Cobb–Douglas production functions with composed errors. Int Econ Rev 18:435–444
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Behr, A. (2015). Stochastic Frontier Analysis. In: Production and Efficiency Analysis with R. Springer, Cham. https://doi.org/10.1007/978-3-319-20502-1_8
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DOI: https://doi.org/10.1007/978-3-319-20502-1_8
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