Bayesian Efficiency Analysis With a Flexible Form
The AIM Cost Function
Bibliographic Data
| ID | 19418665 |
|---|---|
| Authors | Gary Koop (0000-0002-6091-378X, University of Toronto), Jacek Osiewalski (0000-0002-6710-6825, Krakow University of Economics), Mark F J Steel (0000-0001-9858-9279, Tilburg University) |
| Year | 1994 |
| Volume | 12 |
| Issue | 3 |
| Pages | 339-346 |
| Publication date | 1994-07-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Business and Economic Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0735-0015 • E-ISSN: 1537-2707 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/07350015.1994.10524549 |
| OpenAlex | W1963604941 |
| Language | EN |
| Citations received | 7 |
| References cited | 18 |
In this article we describe the use of Gibbs sampling methods for drawing posterior inferences in a cost frontier model with an asymptotically ideal price aggregator, nonconstant returns to scale, and composed error. An empirical example illustrates the sensitivity of efficiency measures to assumptions made about the functional form of the frontier. We also examine the consequences of imposing regularity through parametric restrictions alone
Bayesian probability · Econometrics · Economics · Frontier · Gibbs sampling · Mathematical economics · Monotonic function · News aggregator · Parametric statistics · Statistics · Computer Science · Economic and Environmental Valuation · Efficiency Analysis Using DEA · Mathematics · Monetary Policy and Economic Impact
On the Choice of Functional Forms
A Simple Method for Imposing Local Curvature in Some Flexible Consumer-Demand Systems
On the Estimation of Demand Systems Through Consumption Efficiency
Reconsidering heterogeneity in panel data estimators of the stochastic frontier model
Addressing endogeneity when estimating stochastic ray production frontiers
Dynamic Asymptotically Ideal Models and Finite Approximation
Measuring Potential Efficiency Gains from Deregulation of Electricity Generation
Monte Carlo sampling methods using Markov chains and their applications
Sampling-Based Approaches to Calculating Marginal Densities
On the bias in flexible functional forms and an essentially unbiased form
Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error
Equation of State Calculations by Fast Computing Machines
Formulation and estimation of stochastic frontier production function models
| Citations per year | 0.23 |
|---|---|
| Citation span | 1996 - 2022 (27) |
| Highly cited | No |