Estimating output-specific efficiencies /
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| Author / Creator: | Gstach, Dieter. |
|---|---|
| Imprint: | Dordrecht : Boston : Kluwer Academic, c2002. |
| Description: | xiii, 204 p. : ill. ; 25 cm. |
| Language: | English |
| Series: | Applied optimization ; v. 61 |
| Subject: | |
| Format: | Print Book |
| URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/4704068 |
Table of Contents:
- Preface
- Acknowledgments
- Part I. Motivating the concept
- 1.. Introduction
- 1. Outline of the book
- 2. Related literature
- 3. Motivation
- 4. Geometrical illustration
- 5. Interpreting the difference
- Part II. Operationalizing the concept
- 2.. Technology Estimation
- 1. Statistical structures underlying DEA
- 2. Output-ratios to characterize technology
- 3. DEA bias correction
- 4. Estimator consistency
- 3.. Relation to Radial Measures
- 1. Ouput-specific vs. radial efficiencies
- 2. An example that works
- 3. So why not use simple regression analysis?
- 4. A counterexample
- 4.. Markov Chain Monte Carlo Analysis
- 1. The Metropolis-Hastings algorithm
- 2. Single-component updates
- 3. Sampling from conjugate distributions
- 5.. Data Generating Process
- 1. Target output ratios
- 2. Output specific efficiencies
- 3. Distribution of output vectors
- 6.. Identification
- 1. The basic tradeoff in an expectational perspective
- 2. The role of domain observations
- 3. Likelihood surface
- 7.. Posterior Distributions
- 1. The prior assumptions
- 2. Sampling
- 3. Scale Invariance
- Part III. Evaluating the concept
- 8.. Estimator Performance
- 1. Sample generation
- 2. Case of DEA-estimated frontier
- 3. Case of known frontier
- Part IV. Putting the concept to work
- 9.. An Application
- 1. A brief review of related literature
- 2. Estimating technology
- 3. The statistical model
- 4. Constructing the Markov chains
- 5. Data
- 6. Results
- 7. Conclusions from the application
- 10.. Concluding Remarks
- 1. Summary
- 2. Routes for future research
- References
