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| 초효율 자료포락분석× | 부트스트랩 DEA: 효율성 점수에 대한 편향 보정 및 신뢰 구간× | |
|---|---|---|
| 분야 | 효율성 분석 | 효율성 분석 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1993 | 1998 |
| 창시자≠ | Andersen & Petersen | Simar & Wilson |
| 유형≠ | Nonparametric linear programming model | Nonparametric efficiency estimation with bootstrap inference |
| 원전≠ | Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis. Management Science, 39(10), 1261–1264. DOI ↗ | Simar, L., & Wilson, P. W. (1998). Sensitivity analysis of efficiency scores: How to bootstrap in nonparametric frontier models. Management Science, 44(1), 49–61. DOI ↗ |
| 별칭 | Andersen-Petersen Model, Super-Radial DEA, Ranking DEA, Süper Etkinlik VZA | Bootstrapped DEA, DEA Bootstrap Inference, Simar-Wilson Bootstrap, Bootstrap Sınır Analizi |
| 관련 | 2 | 2 |
| 요약≠ | Super-Efficiency DEA is a nonparametric linear programming extension of classical Data Envelopment Analysis (DEA) introduced by Andersen and Petersen (1993). While standard DEA assigns a maximum efficiency score of 1.0 to all units on the efficient frontier, Super-Efficiency DEA allows efficient units to receive scores greater than 1.0 by temporarily removing the evaluated unit from the reference set. This modification enables full ranking of all decision-making units (DMUs), including those previously indistinguishable at the frontier. | Bootstrap Data Envelopment Analysis (Bootstrap DEA) is a resampling-based extension of standard DEA that provides statistically valid inference for efficiency scores. Introduced by Simar and Wilson in 1998, it addresses the core weakness of classical DEA — its inability to quantify uncertainty in estimated scores — by constructing bootstrap confidence intervals and bias-corrected efficiency estimates from repeatedly resampled pseudo-frontiers. |
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