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Measuring the biases in self-reported disability status: evidence from aggregate data

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  • Naoko Akashi-Ronquest
  • Paul Carrillo
  • Bruce Dembling
  • Steven Stern

Abstract

Self-reported health status measures are generally used to analyse Social Security Disability Insurance's (SSDI) application and award decisions as well as the relationship between its generosity and labour force participation. Due to endogeneity and measurement error, the use of self-reported health and disability indicators as explanatory variables in economic models is problematic. We employ county-level aggregate data, instrumental variables and spatial econometric techniques to analyse the determinants of variation in SSDI rates and explicitly account for the endogeneity and measurement error of the self-reported disability measure. Two surprising results are found. First, it is shown that measurement error is the dominating source of the bias and that the main source of measurement error is sampling error. Second, results suggest that there may be synergies for applying for SSDI when the disabled population is larger.

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  • Naoko Akashi-Ronquest & Paul Carrillo & Bruce Dembling & Steven Stern, 2011. "Measuring the biases in self-reported disability status: evidence from aggregate data," Applied Economics Letters, Taylor & Francis Journals, vol. 18(11), pages 1053-1060.
    • Handle: RePEc:taf:apeclt:v:18:y:2011:i:11:p:1053-1060
    DOI: 10.1080/13504851.2010.524603
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    2. Thomas Barnay, 2016. "Health, work and working conditions: a review of the European economic literature," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 17(6), pages 693-709, July.
    3. Thomas Barnay & Éric Defebvre, 2019. "Gender Differences in the Influence of Mental Health on Job Retention," LABOUR, CEIS, vol. 33(4), pages 507-532, December.
    4. Adriana Barone & Cristian Barra, 2020. "The Relationship between Employment and Mental Health Problems in Italy: Evidence from EHIS2 Microdata," Working Papers 3_240, Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno, revised Jul 2020.
    5. Thomas Barnay & Eric Defebvre, 2016. "The influence of mental health on job retention," TEPP Working Paper 2016-06, TEPP.
    6. Thomas Barnay & Éric Defebvre, 2018. "L'influence des conditions de travail passées sur la santé et la consommation de médicaments auto-déclarées des retraités," Post-Print hal-02070314, HAL.

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