Data Envelopment Analysis

Huguenin, Jean‐Marc

doi:10.1002/9781118644898.ch10

Cited by 27 publications

(37 citation statements)

References 59 publications

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“…Under various assumptions regarding the nature of returns to scale, a decomposition of (in)efficiency can be made to reveal its various sources (Huguenin, ). Under the constant returns to scale assumption, the generated scores provide a measure of “total” efficiency.…”

Section: Methodsmentioning

confidence: 99%

Fertiliser subsidy and agricultural productivity in Senegal

Seck

2017

World Economy

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This paper tackles one of the most complex and multifaceted agricultural policy decisions faced by African governments; that is, whether it makes sense to subsidise fertilisers. It combines a data envelopment analysis to compute efficiency scores and regression analyses that deal with self‐selectivity and endogeneity issues to examine the productive efficiency of farmers who benefited from the subsidy programme in the very atypical irrigated system of the Senegal River Valley. The results based on farm‐level data indicate that the subsidy programme seems to be working, as it appears to be associated with increased efficiency; hence, providing empirical support to the political will to revamp subsidy programmes. The results also suggest various ways to improve the effectiveness of the subsidy programme in conjunction with additional policy options to further unlock the agricultural potentials of the region.

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Section: Methodsmentioning

confidence: 99%

Fertiliser subsidy and agricultural productivity in Senegal

Seck

2017

World Economy

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“…For example, in the distance expression in Table 1, dD is the distance between points d and D. Table 1 shows the types of efficiencies represented by distance expressions (Figure 1). However, technical efficiency does not reveal the cause of the inefficiency [36]. Causes of inefficiencies may be management problems or scale problems [36].…”

Section: Methodsmentioning

confidence: 99%

“…However, technical efficiency does not reveal the cause of the inefficiency [36]. Causes of inefficiencies may be management problems or scale problems [36]. The DEA method decomposes technical efficiency into pure technical efficiency and scale efficiency in an attempt to resolve inefficiency issues.…”

Section: Methodsmentioning

confidence: 99%

“…However, DEA researchers argue that inefficiency cannot attain a value of absolute '0'. There are cases where it is necessary to assume some inefficiency, considering the characteristics of the analysis unit [36]. Biobank and cohort technologies are all cases of large-scale national projects in that they collect and utilize human resources.…”

Section: Efficiency Measurement Of Candidate Technology Sectorsmentioning

confidence: 99%

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The Efficiency Analysis of National R&D Planning for the Field of Precision Medicine in Korea

Lee

Sohn

Won

et al. 2018

Journal of Open Innovation: Technology, Market, and Complexity

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Precision medicine has received a lot of attention in recent years and we have not yet found any research cases that apply Data Envelopment Analysis (DEA) to investment decision making in this area. The purpose of this study is to analyze the relative efficiency of candidate technology sectors in order to determine priorities for government investment in precision medicine. The results of the efficiency analysis can be used as an important reference for government policy makers to determine the amount of government investment in the next year for each candidate technology sector. The candidate technology for government investment in precision medicine was decided for 23 sectors based on the data analysis and the opinions of expert committees. This study applies the input-oriented DEA in regard to 23 technology sectors, which is widely used to analyze relative efficiency in terms of inputs versus outputs and to enhance efficiency through the propositional reduction of inputs. The input variables include the government’s research and development (R&D) investment and forward and backward industry linkage effects. The output variables are the employment creation effect, value-added effect, number of Korean patents, and number of Korean papers. Our analysis results show that the 23 technology sectors in precision medicine overall have a high efficiency, with the exception of the biobank technology sector. Therefore, since the Biobank technology sector has strong infrastructure characteristics, it seems to require continuous investment. The efficiency of DEA is high in most precision medicine sectors; therefore, overall, investing in these technologies is expected to yield good benefits.

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“…By studying the distance relationship of the DMUs under the frontier with that of the efficient peer DMU, located on the frontier, one can quickly analyze the scope to enhance the output or limiting the inputs. In recent years, this method has gained the attention of many researchers and academicians, and thus there has been plenty of studies on the theoretical as well as practical applications of DEA (Bapat, 2012;Huguenin, 2013;Klimberg & Ratick, 2008;Silva et al, 2018;Yeh, 1996). Further (Sufian, 2007) stated that one of the major rewards of using the DEA technique for measuring efficiency differentials is that the technique is independent of the sample sizes and can be equally utilitarian for research, which comprises of less data for analysis.…”

Section: Data Envelopment Analysismentioning

confidence: 99%

Trends in Indian Private Sector Bank Efficiency: Non-Stochastic Frontier DEA Window Analysis Approach

Kumar¹,

Anand²,

Batra³

2020

JAFEB

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The study examines the efficiency of private sector banks in India with the help of Window DEA (Data Envelopment Analysis) for a period from 2005 to 2017. With a window of three years, the period was divided into 11 windows. The study outcomes show that 59.9% of all private sector banks in India operate at more than 0.9 level of efficiency, and there are only three occasions when banks were operating at the efficiency value between 0.6 to 0.7. Further, the consistency in the efficiency scores of the banks has also been analyzed using an efficiency mapping matrix, and the mean efficiency score of the bank in each window is studied. The score of standard deviation was interpreted accordingly for these banks. Banks that are showing the highest efficiency scores also have a higher variance of efficiency scores. There was no bank identified in the matrix that promises high-efficiency ratings with low variability. The study concludes that the analysis of the efficiency mapping matrix indicates that, as a DMU escalates in the efficiency scores, the standard deviation reflecting the risk in overall efficiency scores also tends to rise. The findings complement the concept of higher risk to higher return or greater efficiency.

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Data Envelopment Analysis

Cited by 27 publications

References 59 publications

Fertiliser subsidy and agricultural productivity in Senegal

Fertiliser subsidy and agricultural productivity in Senegal

The Efficiency Analysis of National R&D Planning for the Field of Precision Medicine in Korea

Trends in Indian Private Sector Bank Efficiency: Non-Stochastic Frontier DEA Window Analysis Approach

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