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Optimal disability assistance when fraud and stigma matter

  • Laurence, JACQUET

    (UNIVERSITE CATHOLIQUE DE LOUVAIN, Institut de Recherches Economiques et Sociales (IRES))

I study the optimal redistributive structure when individuals with distinct productivities also differ in disutility of work due to either disability or distase for work. Taxpayers have resentment against inactive benefit recipients because some of them are not actually disabled but lazy. Therefore, disabled people who take up transfers are stigmatized. Their stigma disutility increases with the number of non-disabled recipients. Tagging transfers according to disability characteristics decreases stigme. However, tagging is costly and imperfect. In this context, I show how the level of the per capital cost of monitoring relative to labor earnings of low-wage workers determines the optimality of tagging. Under mild conditions, despite their stigma disutility, inactive and disabled people get a strictly lower consumption than low-wage workers. The results are valid under a utilitarian criterion and a criterion which does not compensage for distate for work.

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Paper provided by Université catholique de Louvain, Département des Sciences Economiques in its series Discussion Papers (ECON - Département des Sciences Economiques) with number 2006052.

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Length: 32
Date of creation: 01 Nov 2006
Date of revision:
Handle: RePEc:ctl:louvec:2006052
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  11. Laurence, JACQUET & Bruno, VAN DER LINDEN, 2003. "The Normative Analysis of ‘Tagging’ Revisited : Dealing with Stigmatization," Discussion Papers (IRES - Institut de Recherches Economiques et Sociales) 2003030, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
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  17. Salanie, Bernard, 2002. "Optimal demogrants with imperfect tagging," Economics Letters, Elsevier, vol. 75(3), pages 319-324, May.
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  23. Jon Harkness, 1993. "Labour Force Participation by Disabled Males in Canada," Canadian Journal of Economics, Canadian Economics Association, vol. 26(4), pages 878-89, November.
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