Data Envelopment Analysis - Wang Zhichao
- From Foundations to Modern Advancements
Efficiency analysis methods are widely developed and applied in numerous fields, including agriculture, banking, energy, and healthcare, among others. The two mainstream approaches to efficiency analysis include data envelopment analysis (DEA) and stochastic frontier analysis (SFA). Data Envelopment Analysis: From Foundations to Modern Advancements provides a complete overview of DEA and its major variations from a practical perspective.
The authors introduce the canonical envelopment-type estimators in the production function in Section 2, their advancements in Section 3, and the estimation of cost, revenue, and profit efficiency in Section 4. The reader is then introduced to several more advanced streams of DEA literature: the productivity indexes with DEA (Section 5), the statistical properties (Section 6), including the recent development in aggregation, bias-correction, explanation of efficiency, and the "two-stage DEA" for explaining the inefficiency (Section 7). Finally, the authors provide demonstrations of some prevalent DEA estimators in R and other software using hospital data.
EAN: 9781638284468
Efficiency analysis methods are widely developed and applied in numerous fields, including agriculture, banking, energy, and healthcare, among others. The two mainstream approaches to efficiency analysis include data envelopment analysis (DEA) and stochastic frontier analysis (SFA). Data Envelopment Analysis: From Foundations to Modern Advancements provides a complete overview of DEA and its major variations from a practical perspective.
The authors introduce the canonical envelopment-type estimators in the production function in Section 2, their advancements in Section 3, and the estimation of cost, revenue, and profit efficiency in Section 4. The reader is then introduced to several more advanced streams of DEA literature: the productivity indexes with DEA (Section 5), the statistical properties (Section 6), including the recent development in aggregation, bias-correction, explanation of efficiency, and the "two-stage DEA" for explaining the inefficiency (Section 7). Finally, the authors provide demonstrations of some prevalent DEA estimators in R and other software using hospital data.
EAN: 9781638284468