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Poverty, Undernutrition and Vulnerability in Rural India: Public Works versus Food Subsidy

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Author Info
Raghbendra Jha ()
Katsushi S. Imai ()
Raghav Gaiha

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Abstract

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) data, 50th round in 1993-1994 and 61st round in 2004-2005. Treatment-effects model and Propensity Score Matching (PSM) model are used to take account of the sample selection bias in evaluating the effects of RPW or PDS on poverty. We have found significant and negative effects of the household participation in RPW and Food for Work Programmes on poverty, undernutrition (e.g. protein) and vulnerability in 1993 and 2004. On the contrary, poverty and undernutrition are significantly higher for the households with access to PDS than those without, whilst PDS has significant effects on reducing vulnerability of households in 1993 and 2004. We also applied the pseudo panel model which confirms that PDS decreased the vulnerability based on 80% of the poverty threshold. However, state-wise results of treatment effects model show considerable diversity of policy effects among different states.

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Paper provided by Australian National University, Australia South Asia Research Centre in its series ASARC Working Papers with number 2008-08.

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Length: 50
Date of creation: 2008
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Handle: RePEc:pas:asarcc:2008-08

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Related research
Keywords: Poverty; Undernutrition; Vulnerability; Rural Public Works (RPW); Public Distribution System (PDS); Poverty Reduction Policy; Treatment Effects Model; Propensity Score Matching (PSM) Model; India;

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Find related papers by JEL classification:
C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data
C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
I32 - Health, Education, and Welfare - - Welfare and Poverty - - - Measurement and Analysis of Poverty
I38 - Health, Education, and Welfare - - Welfare and Poverty - - - Government Programs; Provision and Effects of Welfare Programs
O15 - Economic Development, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
O22 - Economic Development, Technological Change, and Growth - - Development Planning and Policy - - - Project Analysis

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  1. Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February. [Downloadable!] (restricted)
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  2. Dasgupta, Partha, 1997. "Nutritional status, the capacity for work, and poverty traps," Journal of Econometrics, Elsevier, vol. 77(1), pages 5-37, March. [Downloadable!] (restricted)
  3. Raghav Gaiha & Ganesh Thapa & Katsushi Imai & Vani S. Kulkarni, 2007. "Endowments, discrimination and deprivation among ethnic groups," The School of Economics Discussion Paper Series 0722, Economics, The University of Manchester. [Downloadable!]
  4. Besley, Timothy & Coate, Stephen, 1992. "Workfare versus Welfare Incentive Arguments for Work Requirements in Poverty-Alleviation Programs," American Economic Review, American Economic Association, vol. 82(1), pages 249-61, March. [Downloadable!] (restricted)
  5. Dehejia, Rajeev, 2005. "Practical propensity score matching: a reply to Smith and Todd," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 355-364. [Downloadable!] (restricted)
  6. Shubham Chaudhuri & Jyotsna Jalan & Asep Suryahadi, 2002. "Assessing household vulnerability to poverty from cross-sectional data: A methodology and estimates from Indonesia," Discussion Papers 0102-52, Columbia University, Department of Economics. [Downloadable!]
  7. Verbeek, Marno & Nijman, Theo, 1992. "Can Cohort Data Be Treated as Genuine Panel Data?," Empirical Economics, Springer, vol. 17(1), pages 9-23.
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  8. Raghbendra Jha & Raghav Gaiha, 2003. "Determinants of Undernutrition in Rural India," Departmental Working Papers 2003-06, Australian National University, Economics RSPAS. [Downloadable!]
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  9. Heckman, James J, 1979. "Sample Selection Bias as a Specification Error," Econometrica, Econometric Society, vol. 47(1), pages 153-61, January. [Downloadable!] (restricted)
  10. Todd, Petra E., 2008. "Evaluating Social Programs with Endogenous Program Placement and Selection of the Treated," Handbook of Development Economics, Elsevier. [Downloadable!] (restricted)
  11. Bhalotra, Sonia, 2002. "Welfare Implications of Fiscal Reform: The Case of Food Subsidies in India," Working Papers UNU-WIDER Research Paper , World Institute for Development Economic Research (UNU-WIDER). [Downloadable!]
  12. Foster, Andrew D, 1995. "Nutrition and Health Investment," American Economic Review, American Economic Association, vol. 85(2), pages 148-52, May. [Downloadable!] (restricted)
  13. Sascha O. Becker & Andrea Ichino, 2002. "Estimation of average treatment effects based on propensity scores," Stata Journal, StataCorp LP, vol. 2(4), pages 358-377, November. [Downloadable!]
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