Food Stamps and Food Insecurity: What Can Be Learned in the Presence of Nonclassical Measurement Error?

Policymakers have been puzzled to observe that food stamp households appear more likely to be food insecure than observationally similar eligible nonparticipating households. We reexamine this issue allowing for nonclassical reporting errors in food stamp participation and food insecurity. Extending...

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Publicado en:Journal of Human Resources Vol. 43; no. 2; pp. 352 - 383
Autores principales: Gundersen, Craig, Kreider, Brent
Formato: Artículo
Publicado: University of Wisconsin Press Spring2008
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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          Gundersen, Craig
          Kreider, Brent
      su:
        Food stamps
        Food consumption
        Mathematical models
        Child nutrition
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        subj:
          Food stamps
          Food consumption
          Mathematical models
          Child nutrition
      keyword: Food supply -- United States -- Mathematical models
      ab: Policymakers have been puzzled to observe that food stamp households appear more likely to be food insecure than observationally similar eligible nonparticipating households. We reexamine this issue allowing for nonclassical reporting errors in food stamp participation and food insecurity. Extending the literature on partially identified parameters, we introduce a nonparametric framework that makes transparent what can be known about conditional probabilities when a binary outcome and conditioning variable are both subject to nonclassical measurement error. We find that the food insecurity paradox hinges on assumptions about the data that are not supported by the previous food stamp participation literature. Reprinted by permission of the publisher.
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    language: English
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