Showing papers on "Data envelopment analysis published in 1978"
TL;DR: A nonlinear (nonconvex) programming model provides a new definition of efficiency for use in evaluating activities of not-for-profit entities participating in public programs and methods for objectively determining weights by reference to the observational data for the multiple outputs and multiple inputs that characterize such programs.
25,433 citations
TL;DR: In this paper, an empirical estimation of a stochastic frontier Cobb-Douglas production function using micro data from a cross-section of Brazilian manufacturing firms is provided, and a measure of mean technical efficiency is also developed and employed with the Brazilian data.
119 citations
TL;DR: In this paper, the authors show how to find the efficient frontier for two cases: the single index model and a model assuming the correlation coefficient between all stocks is identical, and examine both the case of short selling is allowed and the case where it is disallowed.
Abstract: In each of these papers, we assumed the existence of a risk free asset and hence a unique optimum portfolio. This was not necessary. The purpose of this paper is to show how this assumption can be relaxed and our simple technique used to generate the full efficient frontier. In particular, we will show how the simple techniques described in the above papers can be used to find all corner portfolios. Since portfolios intermediate to corner portfolios are linear combinations of corner portfolios, this technique allows the construction of the full efficient frontier. In this paper, we will demonstrate how to find the efficient frontier for two cases: the single index model and a model assuming the correlation coefficient between all stocks is identical. We will examine both the case where short selling is allowed and the case where it is disallowed. The extension of the procedure described here to all
73 citations
01 Nov 1978
TL;DR: Data Envelopment Analysis (DEA) as mentioned in this paper is used to decompose the efficiency of decision making units (DMU's) into two parts: (1) a component resulting from managerial decisions and (2) a part resulting from constraints (called programs) under which management operates.
Abstract: : A method called Data Envelopment Analysis (DEA) is used to decompose the efficiency of Decision Making Units (DMU's) into two parts: (1) a component resulting from managerial decisions and (2) a component resulting from constraints (called programs) under which management operates. The DEA approach accomplishes this by enveloping the input-output observations with extremal relations developed in terms of a specified nonlinear programming model (and/or its linear programming equivalent). Differences between the observations and the progam specific envelopes -- called alpha-envelopes--are imputed to managerial inefficiencies. An inter-program envelope is then constructed from 2 or more such alpha-envelopes and used to identify 'program' inefficiencies, which are the inefficiencies that remain after the previously determined managerial inefficiencies have been eliminated. Numerical illustrations accompanied by suggested tests of a probabilistic/information theoretic character are provided by means of recenty released data from 'Program Follow Through.' Designed as a study of possible ways of reenforcing or extending Program Head Start - an ongoing pre-school program for disadvantaged children -- the Program Follow Through experiment provides data on agreed upon inputs and outputs for both PFT (Program Follow Through) and matched NFT (Not Follow Through) participants in various parts of the U.S.
24 citations