IDEAS home Printed from https://ideas.repec.org/a/spr/qualqt/v49y2015i1p39-50.html
   My bibliography  Save this article

Modelling social inequalities in health in contemporary Switzerland

Author

Listed:
  • Della Sara
  • Lucchini Mario

Abstract

The relationship between income and health has been widely established. However, there are some issues which need to be addressed in order to study accurately the socio-economic gradient in health. Firstly, there is a specific issue linked to the dynamic nature of health. The current health status is closely linked to past health circumstances and is a good predictor of future health status. Hence we should implement models which are able to take into account the dynamic nature of health. Secondly, the study of health can be affected by a more general problem that often plagues sociological models aimed at estimating causal effects, that of non-observed heterogeneity leading to endogeneity. Both genetic factors and psychological predispositions that are important predictors of health may easily be correlated with one’s socio-economic status, thus creating endogeneity. If analyzed with the appropriate methods, panel data help us tackle these issues. In this work we study the effect of income on self-assessed health in Switzerland using 13 waves (from 1999 to 2012) of the Swiss Household Panel. We apply a fixed effects model, a random effect model and a dynamic panel model (more precisely, the Mundlak–Chamberlain model). Whereas in both the fixed and the random effects models income appears to be significantly related to health, in the Mundlak–Chamberlain model this effect disappears. Results show that models based on different assumptions and including a different set of controls give quite different results. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Della Sara & Lucchini Mario, 2015. "Modelling social inequalities in health in contemporary Switzerland," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(1), pages 39-50, January.
    • Handle: RePEc:spr:qualqt:v:49:y:2015:i:1:p:39-50
    DOI: 10.1007/s11135-013-9972-8
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11135-013-9972-8
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11135-013-9972-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jylhä, Marja, 2009. "What is self-rated health and why does it predict mortality? Towards a unified conceptual model," Social Science & Medicine, Elsevier, vol. 69(3), pages 307-316, August.
    2. Timothy J. Halliday, 2008. "Heterogeneity, state dependence and health," Econometrics Journal, Royal Economic Society, vol. 11(3), pages 499-516, November.
    3. Rosen, Sherwin, 2007. "Studies in Labor Markets," National Bureau of Economic Research Books, University of Chicago Press, number 9780226726304, April.
    4. repec:ucp:bknber:9780226726281 is not listed on IDEAS
    5. Lorenzo Cappellari & Stephen P. Jenkins, 2004. "Modelling low income transitions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(5), pages 593-610.
    6. repec:dau:papers:123456789/10510 is not listed on IDEAS
    7. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    8. James J. Heckman, 1981. "Heterogeneity and State Dependence," NBER Chapters, in: Studies in Labor Markets, pages 91-140, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Francesco Bartolucci & Claudia Pigini, 2017. "Granger causality in dynamic binary short panel data models," Working Papers 421, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    2. Francesco Bartolucci & Valentina Nigro & Claudia Pigini, 2018. "Testing for state dependence in binary panel data with individual covariates by a modified quadratic exponential model," Econometric Reviews, Taylor & Francis Journals, vol. 37(1), pages 61-88, January.
    3. Mario Lucchini & Christine Butti & Sara Della Bella & Angela Lisi, 2018. "The application of a topological clustering technique to capture forms and dynamics of deprivation in contemporary Switzerland," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(1), pages 227-248, January.
    4. Giarda, Elena, 2013. "Persistency of financial distress amongst Italian households: Evidence from dynamic models for binary panel data," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3425-3434.
    5. Trinh, Long Q., 2016. "Dynamics of Innovation and Internationalization among Small and Medium-Sized Enterprises in Viet Nam," ADBI Working Papers 580, Asian Development Bank Institute.
    6. Dang, Rey & Houanti, L'Hocine & Sahut, Jean-Michel & Simioni, Michel, 2021. "Do women on corporate boards influence corporate social performance? A control function approach," Finance Research Letters, Elsevier, vol. 39(C).
    7. Demoussis, Michael & Giannakopoulos, Nicholas, 2006. "The dynamics of home computer ownership in Greece," Information Economics and Policy, Elsevier, vol. 18(1), pages 73-86, March.
    8. Juan M. Villa & Miguel Niño-Zarazúa, 2019. "Poverty dynamics and graduation from conditional cash transfers: a transition model for Mexico’s Progresa-Oportunidades-Prospera program," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 17(2), pages 219-251, June.
    9. Sara Ayllón Gatnau, 2009. "Modelling state dependence and feedback effects between poverty, employment and parental home emancipation among European youth," Economics Working Papers 1180, Department of Economics and Business, Universitat Pompeu Fabra.
    10. Manudeep Bhuller & Christian N. Brinch & Sebastian Königs, 2017. "Time Aggregation and State Dependence in Welfare Receipt," Economic Journal, Royal Economic Society, vol. 127(604), pages 1833-1873, September.
    11. Mavromaras, Kostas & McGuinness, Seamus, 2012. "Overskilling dynamics and education pathways," Economics of Education Review, Elsevier, vol. 31(5), pages 619-628.
    12. Cuesta, Maite Blázquez & Budría, Santiago, 2017. "Unemployment persistence: How important are non-cognitive skills?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 69(C), pages 29-37.
    13. Lucchetti, Riccardo & Pigini, Claudia, 2017. "DPB: Dynamic Panel Binary Data Models in gretl," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i08).
    14. Mavromaras, Kostas & Polidano, Cain, 2011. "NILS Working paper no 165. Improving the employment rates of people with disabilities through vocational education," NILS Working Papers 26068, National Institute of Labour Studies.
    15. Regina T. Riphahn & Christoph Wunder, 2016. "State dependence in welfare receipt: transitions before and after a reform," Empirical Economics, Springer, vol. 50(4), pages 1303-1329, June.
    16. Li Donni, Paolo, 2019. "The unobserved pattern of material hardship and health among older Americans," Journal of Health Economics, Elsevier, vol. 65(C), pages 31-42.
    17. Mavromaras, Kostas & Polidano, Cain, 2011. "Improving the Employment Rates of People with Disabilities through Vocational Education," IZA Discussion Papers 5548, Institute of Labor Economics (IZA).
    18. Andriopoulou, Eirini & Tsakloglou, Panos, 2011. "The Determinants of Poverty Transitions in Europe and the Role of Duration Dependence," IZA Discussion Papers 5692, Institute of Labor Economics (IZA).
    19. Deza, Monica, 2015. "Is there a stepping stone effect in drug use? Separating state dependence from unobserved heterogeneity within and between illicit drugs," Journal of Econometrics, Elsevier, vol. 184(1), pages 193-207.
    20. Schnitzlein, Daniel D. & Stephani, Jens, 2016. "Locus of Control and low-wage mobility," Journal of Economic Psychology, Elsevier, vol. 53(C), pages 164-177.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:qualqt:v:49:y:2015:i:1:p:39-50. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.