Disability and Low Income Persistence in Italian Households
AbstractWe apply dynamic probit models allowing for unobserved heterogeneity and endogenous initial conditions to IT-SILC data to investigate the low income persistence of households with disabled members. We find that their probability of being in a low income state is higher when compared with households without disabled members. In both cases household head’s characteristics, as employment status and education, contribute to determine low income positions. Our results also support the hypothesis of endogenous initial conditions. Both unobserved heterogeneity and state dependence are important to determine low income positions. Our findings suggest that a structural intervention geared at lifting households out of low income in future requires to get them out of low income at present. Moreover, preventing rather than rescuing actions are preferable.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 28303.
Date of creation: Sep 2010
Date of revision:
Income persistence; disability; dynamic probit model; initial conditions.;
Other versions of this item:
- Giuliana Parodi & Dario Sciulli, 2012. "Disability and low income persistence in Italian households," International Journal of Manpower, Emerald Group Publishing, vol. 33(1), pages 9-26, June.
- J14 - Labor and Demographic Economics - - Demographic Economics - - - Economics of the Elderly; Economics of the Handicapped; Non-Labor Market Discrimination
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Longitudinal Data; Spatial Time Series
- I32 - Health, Education, and Welfare - - Welfare and Poverty - - - Measurement and Analysis of Poverty
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-01-30 (All new papers)
- NEP-HEA-2011-01-30 (Health Economics)
- NEP-LAB-2011-01-30 (Labour Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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