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.
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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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