C. A. Knox Lovell

Formulation and estimation of stochastic frontier production function models

Previous studies of the so-called frontier production function have not utilized an adequate characterization of the disturbance term for such a model. In this paper we provide an appropriate specification, by defining the disturbance term as the sum of symmetric normal and (negative) half-normal random variables. Various aspects of maximum-likelihood estimation for the coefficients of a production function with an additive disturbance term of this sort are then considered.

ON THE ESTIMATION OF TECHNICAL INEFFICIENCY IN THE STOCHASTIC FRONTIER PRODUCTION FUNCTION MODEL

Abstract The error term in the stochastic frontier model is of the form ( v – u ), where v is a normal error term representing pure randomness, and u is a non-negative error term representing technical inefficiency. The entire ( v – u ) is easily estimated for each observation, but a previously unsolved problem is how to separate it into its two components, v and u . This paper suggests a solution to this problem, by considering the expected value of u , conditional on ( v – u ). An explicit formula is given for the half-normal and exponential cases.

Measuring cost efficiency in banking: Econometric and linear programming evidence

Abstract This paper compares two techniques for estimating production economies and efficiencies. One approach involves the econometric estimation of a cost frontier; the second is a series of linear programs which calculate a production frontier. The two techniques are very different in principle, both possesing certain advantages and disadvantages. Our emperical implementation of these techniques shows that they yield very similar results regarding cost economies, and dissimilar results regarding cost efficiencies. These are important findings to the extent that policy decisions and evaluation often rely on only one of the two types of approaches available.

Measuring the technical efficiency of production

Production technology is commonly modelled by means of a production function, which in the scalar output case specifies the maximum output obtainable from an input vector. The degree to which the actual output of a production unit approaches its maximum is called the technical efficiency of production. A technically efficient unit must operate on its production function, although this condition is not sufficient; a technically inefficient unit may operate beneath its production function, although this condition is not necessary. If the notion of technical efficiency is to have empirical content, it must be based on a proper measure, or index, of the technical efficiency of a production unit. It is the purpose of this paper to specify a set of properties such an efficiency measure should satisfy, to show that the widely used measure proposed by Farrell [4] does not satisfy these properties, and to introduce a new measure that does satisfy these properties. The pioneering work on technical efficiency is that of Farrell. Inspired by the work of Debreu [2] and Koopmans [7], Farrell suggested a measure of technical efficiency that can be interpreted, somewhat loosely for the moment, in either of two ways: as the ratio of technically minimal to actual inputs, given output and the input mix, or as the ratio of actual to technically

Stochastic Frontier Analysis: Author Index

published by the press syndicate of the university of cambridge A catalog record for this book is available from the British Library.

Stochastic Frontier Analysis: Frontmatter

published by the press syndicate of the university of cambridge A catalog record for this book is available from the British Library.

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

Abstract Earlier papers by Aiger, Lovell and Schmidt and by Meeusen and van den Broeck have considered stochastic frontier production functions. this paper extends that work by considering the duality between stochastic frontier production and cost funstions, under the assumtions of exact cost minimization (tecchnical inefficiency only) and of inexact cost minimization (technical and allocative inefficiency). We show how to measure both types of inefficiency, and the associated cost of inefficiency. The techniques are illustrated using data on steam-electric generating plants.

Econometric Estimation of Technical and Environmental Efficiency: An Application to Dutch Dairy Farms

In this article we estimate the technical and environmental efficiency of a panel of Dutch dairy farms. Nitrogen surplus, arising from the application of excessive amounts of manure and chemical fertilizer, is treated as an environmentally detrimental input. A stochastic translog production frontier is specified to estimate the output-oriented technical efficiency. Environmental efficiency is estimated as the input-oriented technical efficiency of a single input, the nitrogen surplus of each farm. The mean output-oriented technical efficiency is rather high, 0.894, but the mean input-oriented environmental efficiency is only 0.441. Intensive dairy farms are both technically and environmentally more efficient than extensive farms. Copyright 1999, Oxford University Press.

Environmental efficiency with multiple environmentally detrimental variables; estimated with SFA and DEA

Abstract The objective of this paper is to estimate comprehensive environmental efficiency measures for Dutch dairy farms. The environmental efficiency scores are based on the nitrogen surplus, phosphate surplus and the total (direct and indirect) energy use of an unbalanced panel of dairy farms. We define environmental efficiency as the ratio of minimum feasible to observed use of multiple environmentally detrimental inputs, conditional on observed levels of output and the conventional inputs. We compare two methods for the calculation of efficiency; namely Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA). This paper reveals the strengths and weaknesses for estimating environmental efficiency of the methods applied. Both SFA and DEA can estimate environmental efficiency scores. The mean technical efficiency scores (output-oriented, SFA 89%, DEA 78%) and the mean comprehensive environmental efficiency scores (SFA 80%, DEA 52%) differ between the two methods. SFA allows hypothesis testing, and the monotonicity hypothesis is rejected for the specification including phosphate surplus. DEA can calculate environmental efficiency scores for all specifications, because regularity is imposed in this method.

Resources and Functions: A New View of Inequality in Australia

The degree of inequality in the levels of well-being of its citizens tells us a great deal about a society. It enables us to judge its social and economic system, to identify those citizens with a claim on community compassion, to identify the sources of hardship, and to devise strategies for reducing levels of hardship. The value of such information is undoubted. But we confront a severe practical problem in first defining, and then measuring, what we mean by well-being. It is surely multi-dimensional, and difficult to reduce to a scalar-valued index.