Identifying causal paths between health and socio-economic status: Evidence from European older workforce surveys
Abstractrelationship. In addition, such a relationship takes place early in life and keeps on evolving over time so that both one’s health and SES at a given point in time result from the cumulative effects of this spiral. Thus, only by simultaneously accounting for both pathways as well as for their dynamics would one be able to provide a clear picture of both the process of health accumulation and the dynamics of SES formation. We estimate a structural model where a variety of causal paths between different health dimensions and SES measures as well as their dynamics are simultaneously accounted for. This allows distinction between significant causal paths and insignificant ones, while accounting for endogeneity as well as for cofounders. We use the SOCIOLD survey where the targeted population is that of the older workforce (50 and older) from six EU countries (Denmark, Finland, France, Greece, the Netherlands and the UK). Our results show that (i) reverse causality is indeed a crucial issue: one’s previous socio-economic status influences current health and previous health influences current socioeconomic status, (ii) there are cumulative effects in the sense that both health and socio-economic statuses depend on their past values and (iii) the results are sensitive to whether simultaneity is explicitly accounted for or not.
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Bibliographic InfoPaper provided by University of Aarhus, Aarhus School of Business, Department of Economics in its series Working Papers with number 07-8.
Length: 54 pages
Date of creation: 01 Jan 2007
Date of revision:
Contact details of provider:
Postal: The Aarhus School of Business, Prismet, Silkeborgvej 2, DK 8000 Aarhus C, Denmark
Phone: +45 89 486396
Fax: +45 8615 5175
Web page: http://www.asb.dk/departments/nat.aspx
More information through EDIRC
Health status; Socio-economic status; Causal paths; Asymptotic least squares;
Find related papers by JEL classification:
- C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
- I10 - Health, Education, and Welfare - - Health - - - General
- J14 - Labor and Demographic Economics - - Demographic Economics - - - Economics of the Elderly; Economics of the Handicapped; Non-Labor Market Discrimination
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