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| DEA× | Stochastic Frontier Analysis× | |
|---|---|---|
| Field≠ | Decision-making | Econometrics |
| Family≠ | MCDM | Regression model |
| Year of origin≠ | 1978 | 1977 |
| Originator≠ | Charnes, A., Cooper, W. W., Rhodes, E. | Aigner, Lovell & Schmidt (1977); Battese & Coelli (1995) for panels |
| Type≠ | Non-parametric efficiency frontier (CCR model) | Frontier regression model |
| Seminal source≠ | Charnes, A., Cooper, W. W., Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research DOI ↗ | 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 ↗ |
| Aliases≠ | — | SFA, stochastic frontier model, stochastic production frontier, Stokastik Sınır Analizi (SFA) |
| Related≠ | 0 | 3 |
| Summary≠ | DEA (Data Envelopment Analysis (CCR model) for efficiency-based ranking) is a dea multi-criteria decision-making (MCDM) method introduced by Charnes, A., Cooper, W. W., Rhodes, E. in 1978. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. | Stochastic Frontier Analysis is a frontier regression model, introduced by Aigner, Lovell and Schmidt in 1977, that estimates a production, cost, or profit function while separating each unit's technical inefficiency from ordinary statistical noise. It splits the error term into a symmetric random component and a one-sided inefficiency component, producing firm- or country-level efficiency scores. |
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