A Multilevel Heckman Model to Investigate Financial Assets Among Older People in Europe
Abstract
This paper applies a multilevel Heckman model to investigate the household behaviour (in an ageing population) on portfolio choices across Europe. Exploiting the richness of the data collected by the Survey of Health, Ageing and Retirement in Europe, both the ownership pattern and the amount invested in short-term and long-term assets are analysed. This statistical solution is suitable to take into account both the hierarchical nature of the data and the features of the variables of interest. Model estimates support the choice of a multilevel framework. The sample selection approach allows to highlight different results when analysing the ownership of a financial product rather than the amount invested in it.
Keywords
Ageing Financial assets Multilevel modelling Sample selectionNotes
Acknowledgements
The SHARE data collection has been primarily funded by the European Commission through FP5 (QLK6-CT-2001-00360), FP6 (SHARE-I3: RII-CT-2006-062193, COMPARE: CIT5-CT-2005-028857, SHARELIFE: CIT4-CT-2006-028812) and FP7 (SHARE-PREP: N.211909, SHARE-LEAP: N.227822, SHARE M4: N.261982). Additional funding from the German Ministry of Education and Research, the U.S. National Institute on Aging (U01_AG09740-13S2, P01_AG005842, P01_AG08291, P30_AG12815, R21_AG025169, Y1-AG-4553-01, IAG_BSR06-11, OGHA_04-064) and from various national funding sources is gratefully acknowledged (see www.share-project.org).
References
- 1.Börsch-Supan, A.: Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 4. Release version: 5.0.0. SHARE-ERIC. Data set. (2016). https://doi.org/10.6103/SHARE.w4.500
- 2.Börsch-Supan, A., Brandt, M., Hunkler, C., Kneip, T., Korbmacher, J., Malter, F., Schaan, B., Stuck, S., Zuber, S.: Data resource profile: the survey of health, ageing and retirement in Europe (SHARE). Int. J. Epidemiol. 42, 992–1001 (2013)CrossRefGoogle Scholar
- 3.Börsch-Supan, A., Brandt, M., Litwin, H., Weber, G. (eds.): Active Ageing and Solidarity Between Generations in Europe: First Results from SHARE After the Economic Crisis. De Gruyter, Berlin (2013)Google Scholar
- 4.Christelis, D., Jappelli, T., Padula, M.: Wealth and portfolio composition. In: Börsch-Supan, A., Brugiavini, A., Jürges, H., Mackenbach, J., Siegrist, J., Weber, G. (eds.) Health, Ageing and Retirement in Europe. First Results from the Survey on Health, Ageing and Retirement in Europe, pp. 310–317. MEA, Mannheim (2005)Google Scholar
- 5.Christelis, D., Jappelli, T., Paccagnella, O., Weber, G.: Income, wealth and financial fragility in Europe. J. Eur. Soc. Policy 19, 359–376 (2009)CrossRefGoogle Scholar
- 6.Fitzgerald, J., Gottschalk, P., Moffitt, R.: An analysis of sample attrition in panel data: the Michigan panel study of income dynamics. J. Hum. Resour. 33, 251–299 (1998)CrossRefGoogle Scholar
- 7.Grilli, L., Rampichini, C.: Selection bias in linear mixed models. Metron 68, 309–329 (2010)MathSciNetCrossRefMATHGoogle Scholar
- 8.Guiso, L., Jappelli, T., Terlizzese, D.: Income risk, borrowing constraints, and portfolio choice. Am. Econ. Rev. 86, 158–172 (1996)Google Scholar
- 9.Guiso, L., Haliassos, M., Jappelli, T. (eds.): Household Portfolios. MIT Press, Cambridge, MA (2002)Google Scholar
- 10.Heckman, J.: Sample selection bias as a specification error. Econometrica 47, 153–162 (1979)MathSciNetCrossRefMATHGoogle Scholar
- 11.Hurd, M., Shoven, J.B.: The economic status of the elderly. In: Bodie, Z., Shoven, J.B. (eds.) Financial Aspects of the United States Pension System, pp. 359–398. University of Chicago Press, USA (1983)Google Scholar
- 12.Malter, F., Börsch-Supan, A. (eds.): SHARE Wave 4: Innovations & Methodology. MEA, Max Planck Institute for Social Law and Social Policy, Munich (2013)Google Scholar
- 13.McCarthy, D.: Household portfolio allocation: a review of the literature. Prepared for presentation at the Tokyo, Japan, February 2004 International Forum organized by the ESRI (2004)Google Scholar
- 14.Rabe-Hesketh, S., Skrondal, A., Pickles, A.: Multilevel Selection Models using gllamm. Stata User Group Meeting in Maastricht. http://fmwww.bc.edu/RePEc/dsug2002/select.pdf (2002)
- 15.Rabe-Hesketh, S., Skrondal, A., Pickles, A.: GLLAMM manual. U.C. Berkeley Division of Biostatistics Working Paper Series, Working Paper 160. www.biostat.jhsph.edu/~fdominic/teaching/bio656/software/gllamm.manual.pdf (2004)