Several tests of targeting accuracy of the National Rural Employment Guarantee Scheme (NREG) focusing on shares of participants by poverty status, their duration of participation, and earnings from it are used. The analysis is based on primary household data collected from three India states,...

Using pooled household level data for the Indian states of Rajasthan and Andhra Pradesh we find that the size of landholdings is a negative predictor of participation in the National Rural Employment Guarantee Program (NREGP). In state level analysis this pattern survives in Rajasthan but...

This paper focuses on the targeting accuracy of NREG in two Indian states, Madhya Pradesh (MP) and Tamil Nadu (TN), based on household data for 2008–09. In order to overcome the difficulties arising from the use of a headcount index and a specific poverty threshold, stochastic dominance tests...

Using National Sample Survey data for rural India we examine the incidence of capture in two workfare programs in rural India: the Rural Public Works and the Food for Work Programs for 1993-94 and 2004-05 respectively. We discover a high degree of program capture among the general population....

This paper analyses the effects of access to Rural Public Works (RPW) and Public Distribution System (PDS), a public food subsidy programme, on consumption poverty, vulnerability and undernutrition in India drawing upon the large household data sets constructed by National Sample Survey (NSS)...

Using a new data set constructed by converting NSS household consumption figures (rural sector) for the 43rd round (1987-88), 50th round (1993-94) and 55th round (1999- 2000) into their nutritional equivalents, this paper presents new evidence of the extent of undernourishment in terms of...

India’s National Rural Employment Guarantee Scheme (NREGS) has been hailed as one of the country’s most creative social initiatives. Since the program was begun only recently (in 2004-05) there is a need to assess its impact on households not just in one year but over time. To the best of...