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1985
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8 pages
1 file
AI-generated Abstract
The paper presents a comprehensive analysis of various methodologies for measuring production efficiency. It discusses several output and input efficiency measures, including radial and non-radial approaches, as well as the use of linear programming in these contexts. The impact of inefficiencies on production and the conceptual frameworks surrounding production technology are explored, providing insights into optimizing production processes.
In Chap. 1, we introduced efficiency as the use of the fewest inputs (resources) to produce the most outputs (services). This idea is fundamental to much of modern benchmarking literature because it allows us to evaluate performance without clearly defined preferences. That is, we avoid the difficult task of estimating preference functions and deciding on exact priorities. We will expand on this below. Although the notion of efficiency is simple and intuitive at first glance, there are actually many different ways to conceptualize efficiency. We shall discuss some of the most common concepts in this chapter. We will cover classical concepts from production theory, including technical efficiency, allocative efficiency, and scale efficiency , as well as more advanced concepts like dynamic efficiency and structural efficiency. Moreover, several of these concepts can be operationalized in different ways. We can, for example, measure technical efficiency in terms of input space, output space, or both types of spaces. We can also measure it in specific directions, etc. The aim of this chapter is to provide an overview of efficiency-related concepts as well as bits and pieces of the relevant theoretical background.
International Journal of Business and Social Science, 2018
Running the business as efficiently as possible-using human, natural and financial resources-has become the central objective for the development of any society. The efficiency of a firm can really be expressed by comparing the observed values of the input used by the firm and its output values with optimal input and / or output. In the literature, there are two approaches to determine the production boundary (parametric and nonparametric), both using information on the inputs used and the outputs produced by a producer group. This paper presents a non-parametric techniques named Data Envelopment Analysis (DEA) and its applications.
Annals of Public and Cooperative …, 1992
1997
In the literature, technical efficiency is measured as the ratio of observed output to potential output. Although there is no a priori theoretical reasoning, in the stochastic framework of measuring technical efficiency, the potential output is defined as a neutral shift from the observed output. The objective in this paper is to suggest a method to measure technical efficiency without having to consider the potential output as a neutral shift from the observed output.
Journal of Applied Econometrics, 1990
Abstract This paper considers a system consisting of a production frontier and factor share equations to measure firm-specific technical efficiency and input-specific allocative efficiency simulataneously. In estimating the system as a whole, the joint distribution of all errors in ...
Data Envelopment Analysis Journal
Measuring efficiency has been a major item on the health economics agenda over the past quarter century. A thorough review of the literature shows that almost all studies met the basic requirements proposed by Cowing and Stevenson in 1983, as they relied on the solid theoretical foundations of production economics. Many methods were nevertheless developed and used, with some grounded in statistics, others in operations research, or accounting. The objective of this paper is to show how these methods often fail to include all relevant theoretical considerations. For example, authors relying on economic theory have applied empirical methods with stochastic error terms that are sometimes at odds with certain properties of their models. In fact, almost all models can be approached as specific cases of a general model. We will show that each model implies specific assumptions on the nature of the data, and that in some cases, the models are incoherent. framework covered in this methodological synthesis, we will use a simple form of the cost function. i.e., the nonregulated cost function. It is possible to considerably generalize the firm's environment by introducing quasi-fixed or fixed inputs (also called non-discretionary inputs), regulation, technological parameters, etc. The issue of input and output quality will be discussed at a later point. Regardless, knowledge of the cost function is essential and as it is unobserved, it must be inferred from available data. The goal of what follows is therefore precisely to show how one can recover the cost function from available price and quantity data.
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