Results 271 to 280 of about 84,600 (310)

Stochastic Frontier Analysis

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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STOCHASTIC FRONTIER ANALYSIS OF SINGAPORE MANUFACTURING INDUSTRIES

The Singapore Economic Review, 2004
Previous papers on Singapore manufacturing productivity have focused almost exclusively on total factor productivity (TFP) growth rates and ignored the problem of measuring the extent of learning-by-doing. In this paper, we examine an alternative measure: the rate of technical efficiency change. Using data from 1974–1998, a translog production frontier
SOO-WEI KOH, SHAHIDUR RAHMAN, G. K. RANDOLPH TAN   +2 more
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Panel Data Stochastic Frontier Analysis

2015
Stochastic 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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A Review of: “Stochastic Frontier Analysis”

Econometric Reviews, 2005
Stochastic Frontier Analysis by Subal Kumbhakar and C. A. Knox Lovell (Cambridge: Cambridge University Press, 2000).
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Stochastic Frontier Analysis and Efficiency Estimation

2008
Theoretically, 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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A microfoundation for stochastic frontier analysis

Economics Letters, 2016
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Stochastic Frontier Analysis

2022
Sokvibol Kea, Saleh Shahriar
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Integrated spatial dependence into Stochastic Frontier Analysis

2012
An approach to incorporate spatial dependence into stochastic frontier analysis is developed and applied to a sample of 215 dairy farms in England and Wales. A number of alternative specifications for the spatial weight matrix are used to analyse the effect of these on the estimation of spatial dependence.
Areal, Francisco Jose, Balcombe, Kelvin, Tiffin, Richard, Areal, Francisco Jose, Balcombe, Kelvin, Tiffin, Richard   +5 more
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Stochastic frontier analysis

2020
Scotti, Davide, Volta, Nicola
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Stochastic frontier analysis with fat-tailed error models

2010
Summary: The stochastic frontier analysis [\textit{D. Aigner} et al., J. Econom. 6, No.~1, 21--37 (1977; Zbl 0366.90026); \textit{W. Meeusen} and \textit{J. van den Broeck}, Int. Econ. Rev. 18, 435--444, corrigendum 790 (1977; Zbl 0366.90025)] has been widely used to estimate the technical efficiency of firms. The basic idea lies in the introduction of
Gupta, Arjun K., Nguyen, Ngoc
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