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Regression modelProductive efficiency estimation

Stochastic Frontier Model

The stochastic frontier model is a parametric method for estimating productive efficiency that separates a producer's shortfall from best practice into two parts: genuine inefficiency and random noise. Introduced independently in 1977 by Aigner, Lovell, and Schmidt and by Meeusen and van den Broeck, it specifies a production (or cost) function with a composed error term — a symmetric disturbance for luck and measurement error plus a one-sided, non-negative term for inefficiency — and estimates it by maximum likelihood, yielding firm-specific efficiency scores that, unlike deterministic methods, are robust to statistical noise.

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Vyanzo

  1. Aigner, D., Lovell, C. A. K., & Schmidt, P. (1977). Formulation and estimation of stochastic frontier production function models. Journal of Econometrics, 6(1), 21–37. DOI: 10.1016/0304-4076(77)90052-5
  2. Meeusen, W., & van den Broeck, J. (1977). Efficiency estimation from Cobb-Douglas production functions with composed error. International Economic Review, 18(2), 435–444. DOI: 10.2307/2525757

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 22). Stochastic Frontier Production Function Model. ScholarGate. https://scholargate.app/sw/economics/stochastic-frontier-analysis

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ScholarGateStochastic Frontier Model (Stochastic Frontier Production Function Model). Imepatikana 2026-06-24 kutoka https://scholargate.app/sw/economics/stochastic-frontier-analysis · Seti ya data: https://doi.org/10.5281/zenodo.20539026