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Evaluation of world's largest social welfare scheme: An assessment using non-parametric approach

机译:评估世界上最大的社会福利计划:使用非参数方法的评估

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Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) is the world's largest social welfare scheme in India for the poverty alleviation through rural employment generation. This paper aims to evaluate and rank the performance of the states in India under MGNREGA scheme. A non parametric approach, Data Envelopment Analysis (DEA) is used to calculate the overall technical, pure technical, and scale efficiencies of states in India. The sample data is drawn from the annual official reports published by the Ministry of Rural Development, Government of India. Based on three selected input parameters (expenditure indicators) and five output parameters (employment generation indicators), I apply both input and output oriented DEA models to estimate how well the states utilize their resources and generate outputs during the financial year 2013-14. The relative performance evaluation has been made under the assumption of constant returns and also under variable returns to scale to assess the impact of scale on performance. The results indicate that the main source of inefficiency is both technical and managerial practices adopted. 11 states are overall technically efficient and operate at the optimum scale whereas 18 states are pure technical or managerially efficient. It has been found that for some states it necessary to alter scheme size to perform at par with the best performing states. For inefficient states optimal input and output targets along with the resource savings and output gains are calculated. Analysis shows that if all inefficient states operate at optimal input and output levels, on an average 17.89% of total expenditure and a total amount of $780million could have been saved in a single year. Most of the inefficient states perform poorly when it comes to the participation of women and disadvantaged sections (SC&ST) in the scheme. In order to catch up with the performance of best performing states, inefficient states on an average need to enhance women participation by 133%. In addition, the states are also ranked using the cross efficiency approach and results are analyzed. State of Tamil Nadu occupies the top position followed by Puducherry, Punjab, and Rajasthan in the ranking list. To the best of my knowledge, this is the first pan-India level study to evaluate and rank the performance of MGNREGA scheme quantitatively and so comprehensively. (C) 2016 Elsevier Ltd. All rights reserved.
机译:圣雄甘地国家农村就业保障法案(MGNREGA)是印度最大的社会福利计划,旨在通过创造农村就业机会来减轻贫困。本文旨在评估和评估MGNREGA计划下印度各邦的表现。数据包络分析(DEA)是一种非参数方法,用于计算印度各州的总体技术效率,纯技术效率和规模效率。样本数据取自印度政府农村发展部发布的年度官方报告。基于三个选定的输入参数(支出指标)和五个输出参数(就业产生指标),我同时应用了面向输入和输出的DEA模型,以估算各州在2013-14财政年度内如何利用其资源并产生输出。相对绩效评估是在恒定回报和可变规模报酬的假设下进行的,以评估规模对绩效的影响。结果表明,效率低下的主要根源是采用的技术和管理实践。 11个州总体上在技术上是有效的,并且以最佳规模运行,而18个州在技术上或管理上是纯效率的。已经发现,对于某些状态,有必要改变方案的大小以使其与最佳性能的状态相称。对于低效状态,将计算最佳的输入和输出目标以及资源节省和输出增益。分析表明,如果所有效率低下的州都以最佳的投入和产出水平运行,则平均每年可以节省总支出的17.89%,总共可以节省7.8亿美元。当涉及妇女和弱势群体(SC&ST)参与该计划时,大多数效率低下的州表现不佳。为了赶上表现最好的州的表现,效率低下的州平均需要将妇女参与率提高133%。此外,还使用交叉效率方法对状态进行排名并分析结果。泰米尔纳德邦排名第一,其次是Puducherry,Punjab和Rajasthan。据我所知,这是第一个对MGNREGA计划的性能进行定量评估和综合排名的泛印度水平研究。 (C)2016 Elsevier Ltd.保留所有权利。

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