Inexact discretionary inputs in data envelopment analysis

In this chapter, the relationship between fuzzy concepts and the efficiency score in Data envelopment analysis (DEA) is dealt with.A new DEA model for handling crisp data using fuzzy concept is proposed.In addition, the relationship between possibility sets and the efficiency score in the traditional crisp CCR model is presented.The relationship provides an alternative perspective of viewing efficiency.With the usage of the appropriate fuzzy and possibility sets to represent certain characteristics of the input data, many DEA models involving input data with various characteristics could be studied.Furthermore, based upon the proposed models, two nondiscretionary models are introduced in which some inputs or outputs, in a fuzzy sense, are inexact discretionary variables.For this purpose, a two-stage algorithm will be presented to treat the DEA model in the presence of an inexact discretionary variable.With this relationship, a new perspective of viewing and exploring other DEA models is now made possible

A reasonable benchmarking frontier using DEA : an incentive scheme to improve efficiency in public hospitals

There exists research relating management concepts with productivity measurement methods that offers useful solutions for improving management control in the public sector. Within this sphere, we connect agency theory with efficiency analysis and describe how to define an incentives scheme that can be applied in the public sector to monitor the efficiency and productivity of managers. To fulfill the main objective of this research, we propose an iterative process for determining what we define as a ‘reasonable frontier’, a concept that provides the foundation required to establish the incentive scheme for the managers. Our ‘reasonable frontier’ has the following properties: i) it detects the presence of outliers, ii) it proposes a procedure to establish the influence introduced by extreme observations, and iii) it sorts out the problem of data masking. The proposed method is applied to a sample of hospitals taken from the public network of the Spanish health service. The results obtained confirm the applicability of the proposal made. Summing up, we define and apply a useful method, combining aspects of agency theory and efficiency analysis, which is of interest to those public authorities trying to design effective incentive schemes which influence the decision making of the public managers

Azorean agriculture efficiency by PAR

The producers always aspire at increasing the efficiency of their production process. However, they do not always succeed in optimizing their production. In the last years, the interest on Data Envelopment Analysis (DEA) as a powerful tool for measuring efficiency has increased. This is due to the large amount of data sets collected to better understand the phenomena under study, and, at the same time, to the need of timely and inexpensive information. The “Productivity Analysis with R” (PAR) framework establishes a user-friendly data envelopment analysis environment with special emphasis on variable selection and aggregation, and summarization and interpretation of the results. The starting point is the following R packages: DEA (Diaz-Martinez and Fernandez-Menendez, 2008) and FEAR (Wilson, 2007). The DEA package performs some models of Data Envelopment Analysis presented in (Cooper et al., 2007). FEAR is a software package for computing nonparametric efficiency estimates and testing hypotheses in frontier models. FEAR implements the bootstrap methods described in (Simar and Wilson, 2000). PAR is a software framework using a portfolio of models for efficiency estimation and providing also results explanation functionality. PAR framework has been developed to distinguish between efficient and inefficient observations and to explicitly advise the producers about possibilities for production optimization. PER framework offers several R functions for a reasonable interpretation of the data analysis results and text presentation of the obtained information. The output of an efficiency study with PAR software is self- explanatory. We are applying PAR framework to estimate the efficiency of the agricultural system in Azores (Mendes et al., 2009). All Azorean farms will be clustered into homogeneous groups according to their efficiency measurements to define clusters of “good” practices and cluster of “less good” practices. This makes PAR appropriate to support public policies in agriculture sector in Azores.N/

Measuring Technical Efficiency of Dairy Farms with Imprecise Data: A Fuzzy Data Envelopment Analysis Approach

This article integrates fuzzy set theory in Data Envelopment Analysis (DEA) framework to compute technical efficiency scores when input and output data are imprecise. The underlying assumption in convectional DEA is that inputs and outputs data are measured with precision. However, production agriculture takes place in an uncertain environment and, in some situations, input and output data may be imprecise. We present an approach of measuring efficiency when data is known to lie within specified intervals and empirically illustrate this approach using a group of 34 dairy producers in Pennsylvania. Compared to the convectional DEA scores that are point estimates, the computed fuzzy efficiency scores allow the decision maker to trace the performance of a decision-making unit at different possibility levels.fuzzy set theory, Data Envelopment Analysis, membership function, α-cut level, technical efficiency, Farm Management, Production Economics, Productivity Analysis, Research Methods/ Statistical Methods, Risk and Uncertainty, D24, Q12, C02, C44, C61,

Input, Output and Graph Technical Efficiency Measures on Non-Convex FDH Models with Various Scaling Laws: An Integrated Approach Based upon Implicit Enumeration Algorithms

In a recent article, Briec, Kerstens and Vanden Eeckaut (2004) develop a series of nonparametric, deterministic non-convex technologies integrating traditional returns to scale assumptions into the non-convex FDH model. They show, among other things, how the traditional technical input efficiency measure can be analytically derived for these technology specifications. In this paper, we develop a similar approach to calculate output and graph measures of technical efficiency and indicate the general advantage of such solution strategy via enumeration. Furthermore, several analytical formulas are established and some algorithms are proposed relating the three measurement orientations to one another.Data Envelopment Analysis, Free Disposal Hull, technical efficiency

A reasonable benchmarking frontier using DEA : an incentive scheme to improve efficiency in public hospitals

There exists research relating management concepts with productivity measurement methods that offers useful solutions for improving management control in the public sector. Within this sphere, we connect agency theory with efficiency analysis and describe how to define an incentives scheme that can be applied in the public sector to monitor the efficiency and productivity of managers. To fulfill the main objective of this research, we propose an iterative process for determining what we define as a ‘reasonable frontier’, a concept that provides the foundation required to establish the incentive scheme for the managers. Our ‘reasonable frontier’ has the following properties: i) it detects the presence of outliers, ii) it proposes a procedure to establish the influence introduced by extreme observations, and iii) it sorts out the problem of data masking. The proposed method is applied to a sample of hospitals taken from the public network of the Spanish health service. The results obtained confirm the applicability of the proposal made. Summing up, we define and apply a useful method, combining aspects of agency theory and efficiency analysis, which is of interest to those public authorities trying to design effective incentive schemes which influence the decision making of the public managers.

Agricultural Economics Education in Ukrainian Agricultural Universities: An Efficiency Analysis Using Data Envelopment Analysis

Ukraine's transition from a centrally-planned to a market economy has had a profound effect upon its agricultural sector and agricultural universities. A substantial reduction in state financing has forced universities to adopt a range of survival strategies, with varying degrees of success. In this paper we use data envelopment analysis to examine the technical efficiency of 44 agricultural economics programs from 19 Ukrainian universities during the 2002/03 academic year. Our empirical results indicate wide disparities in performance, ranging from 36% to 100% technical efficiency. A second-stage analysis suggests that factors such as student demand, commercial activities and staff quality help explain a portion of this variation.higher education, Ukraine, efficiency, data envelopment analysis, Teaching/Communication/Extension/Profession, I21, C14, Q16,

EXOGENOUS PRODUCTION SHOCKS AND TECHNICAL EFFICIENCY AMONG TRADITIONAL IVORIEN RICE FARMERS

This paper uses a unique panel data set and data envelopment analysis (DEA) to obtain estimates of technical efficiency for 492 traditional rice plots in Côte d'Ivoire. The objective of this paper is to explore the importance of explicitly controlling for exogenous shocks to production in technical efficiency estimation. We show how omission of such variables in highly stochastic production environments can lead to serious inferential errors, with potentially significant policy implications. Conventional DEA estimation of a production frontier, followed by second-stage Tobit estimation of the correlates of plot- level technical efficiency, suggest widespread and substantial inefficiency related to crop fragmentation and seed varieties. However, when one controls for unobserved groupwise cross-sectional and intertemporal heterogeneity and introduces measurable exogenous shocks into the second-stage estimation, managerial characteristics become jointly insignificant and state-conditional technical efficiency becomes nearly universal. The implication is that conventional technical efficiency estimates that refute the classic Schultzian "poor but efficient" hypothesis may be incorrect because they ignore farmers' vulnerability to adverse states of nature against which they cannot insure.Africa (Sub-Saharan), Ivory Coast, production frontiers, agricultural productivity, rice., Crop Production/Industries, Productivity Analysis, O12, Q12, D2,