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Estimating technical and allocative inefficiency relative to stochastic production and cost frontiers

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TLDR
In this paper, the duality between stochastic frontier production and cost funstions, under the assumtions of exact cost minimization (tecchnical inefficiency only) and of inexact cost minimisation (technical and allocative inefficiency).
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This article is published in Journal of Econometrics.The article was published on 1979-02-01. It has received 552 citations till now. The article focuses on the topics: Inefficiency & Allocative efficiency.

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Citations
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On the estimation of technical inefficiency in the stochastic frontier production function model

TL;DR: In this paper, the expected value of u, conditional on (v − u ) is considered, where v is a normal error term representing pure randomness, and u is a non-negative error term describing technical inefficiency.
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Frontier production functions, technical efficiency and panel data: With application to paddy farmers in India

TL;DR: In this article, a stochastic frontier production function model for panel data is presented, for which the firm effects are an exponential function of time, and the best predictor for the technical efficiency of an individual firm at a particular time period is presented for this timevarying model.
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A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms

TL;DR: In this paper, the authors investigated farm-level efficiency of U.S. dairy farmers by estimating their technical and allocative efficiency, and found that levels of education of the farmer are important factors determining technical inefficiency and large farms are more efficient than small and medium-sized farms.
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Measuring the technical efficiency of production

TL;DR: The purpose of this paper is to specify a set of properties such an efficiency measure should satisfy, to show that the widely used measure proposed by Farrell does not satisfy them, and to introduce a new measure that does satisfy these properties.
References
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Journal ArticleDOI

Formulation and estimation of stochastic frontier production function models

TL;DR: In this paper, the authors define the disturbance term as the sum of symmetric normal and (negative) half-normal random variables, and consider various aspects of maximum-likelihood estimation for the coefficients of a production function with an additive disturbance term of this sort.
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Specification and estimation of Cobb-Douglas production function models

TL;DR: In this article, a sampling theory and Bayesian estimation technique for the Cobb-Douglas production function model is presented, where profits are stochastic and maximization of the mathematical expectation of profits is posited.
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Using a Probabilistic Frontier Production Function to Measure Technical Efficiency

TL;DR: In this article, the authors used linear programming techniques to estimate a frontier Cobb-Douglas production function for U.S. agriculture from 1960 to 1967, using the "average farm" in each state in each year as an observation.
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