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A microfoundation for stochastic frontier analysis
Economics Letters, 2016zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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2018
Distance, revenue, cost and profit functions can always be written in the form of regression models with unobserved error terms representing statistical noise and different types of inefficiency. In practice, the noise components are almost always assumed to be random variables (i.e., stochastic).
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Distance, revenue, cost and profit functions can always be written in the form of regression models with unobserved error terms representing statistical noise and different types of inefficiency. In practice, the noise components are almost always assumed to be random variables (i.e., stochastic).
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A Review of: “Stochastic Frontier Analysis”
Econometric Reviews, 2005Stochastic Frontier Analysis by Subal Kumbhakar and C. A. Knox Lovell (Cambridge: Cambridge University Press, 2000).
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2015
The stochastic frontier analysis is an econometric approach to efficiency measurement. The basic idea is the introduction of two error components, a random error term and an inefficiency term. For both terms, a distributional assumption is made, which facilitates maximum likelihood estimation.
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The stochastic frontier analysis is an econometric approach to efficiency measurement. The basic idea is the introduction of two error components, a random error term and an inefficiency term. For both terms, a distributional assumption is made, which facilitates maximum likelihood estimation.
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A stochastic frontier approach to survival analysis
Journal of Applied Statistics, 2013In spite of the best set of covariates and statistical tools for the survival analysis, there are instances when experts do not rule out the existence of many non-observable factors that could influence the survival probability of an individual. The fact that every human body, sick or otherwise, strives to maximize time to death, renders the stochastic
K. Suresh Chandra +2 more
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Stochastic Frontier Analysis and Efficiency Estimation
2008Theoretically, a production function gives the maximum possible output with a given set of inputs. This is different from its common regression counterpart, which specifies the conditional mean of output. The production function defines a boundary or “frontier”, deviations from which can be interpreted as inefficiency.
Christopher Cornwell, Peter Schmidt
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Panel Data Stochastic Frontier Analysis
2015Stochastic frontier analysis based on cross-sectional data is hampered by the fact that only one observation is available for the estimation of two error components. Panel data containing several observations for each firm considerably improve the situation for estimating firm specific efficiency scores if some assumptions on the time path of ...
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Bayesian analysis of stochastic frontier models
2001In this chapter, we described a Bayesian approach to efficiency analysis using stochastic frontier models. With cross-sectional data and a log-linear frontier, a simple Gibbs sampler can be used to carry out Bayesian inference. In the case of a nonlinear frontier, more complicated posterior simulation methods are necessary.
Koop, Gary, Steel, Mark F.J.
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