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Multidimensional Poverty and Identification of Poor Households: A Case from Kerala, India

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  • Bejoy Thomas
  • Roldan Muradian
  • Gerard De Groot
  • Arie De Ruijter

Abstract

In this paper we compare and contrast the view on poverty of lay people, who are affected by the policies, with that of academics and policy-makers. Drawing from fieldwork in a village in Kerala, India, and applying the 'participatory numbers' approach, we devise a 'local method' to identify poor households, based on the villagers' poverty criteria. The local method is then compared with the official methods used by the national and the state governments. Based on the results, we argue for the need to take into account local dimensions of poverty, in addition to objective/universal dimensions, in the design of poverty reduction programmes. Our findings also suggest that effective risk-mitigation strategies must be devised to help poor households cope with shocks and stresses as well as to prevent the vulnerable non-poor from falling into poverty.

Suggested Citation

  • Bejoy Thomas & Roldan Muradian & Gerard De Groot & Arie De Ruijter, 2009. "Multidimensional Poverty and Identification of Poor Households: A Case from Kerala, India," Journal of Human Development and Capabilities, Taylor & Francis Journals, vol. 10(2), pages 237-257.
    • Handle: RePEc:taf:jhudca:v:10:y:2009:i:2:p:237-257
    DOI: 10.1080/19452820902940968
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    References listed on IDEAS

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    2. McGee, Rosemary, 1999. "'Technical, Objective, Equitable, and Uniform'? A Critique of the Colombian System for the Selection of Beneficiaries of Social Programmes, Sisben," General Discussion Papers 30570, University of Manchester, Institute for Development Policy and Management (IDPM).
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    Cited by:

    1. Shabana Mitra, 2018. "Re-Assessing “trickle-down” Using a Multidimensional Criteria: The Case of India," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(2), pages 497-515, April.
    2. Schleicher, Michael & Souares, Aurélia & Pacere, Athanase Narangoro & Sauerborn, Rainer & Klonner, Stefan, 2016. "Decentralized versus Statistical Targeting of Anti-Poverty Programs: Evidence from Burkina Faso," Working Papers 0623, University of Heidelberg, Department of Economics.
    3. Sabina Alkire & Suman Seth, 2013. "Selecting a Targeting Method to Identify BPL Households in India," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 112(2), pages 417-446, June.
    4. Rishi Kumar, 2018. "Different Approaches to Identify the Poor: Do They converge?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 139(2), pages 589-610, September.
    5. Yanhui Wang & Leyi Qian, 2017. "A PPI-MVM Model for Identifying Poverty-Stricken Villages: A Case Study from Qianjiang District in Chongqing, China," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 130(2), pages 497-522, January.

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