Stochastic Frontier Firm Efficiency Analysis
Stochastic frontier analysis (SFA) estimates how far a firm falls short of the best attainable output for its inputs while explicitly separating that shortfall from random noise. Aigner, Lovell and Schmidt's 1977 model introduced the defining idea: a production frontier whose error term is the sum of a symmetric, two-sided noise component and a one-sided, nonnegative inefficiency component. Because deviations below the frontier can come either from bad luck and measurement error or from genuine underperformance, SFA models both and recovers a firm-specific technical-efficiency estimate. Battese and Coelli's 1995 panel-data extension let the mean of the inefficiency term depend on firm characteristics, so analysts can simultaneously estimate the frontier and explain why some firms are more inefficient than others.
Allikakirje
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- 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
- Battese, G. E., & Coelli, T. J. (1995). A model for technical inefficiency effects in a stochastic frontier production function for panel data. Empirical Economics, 20(2), 325-332. · DOI 10.1007/BF01205442
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