Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-26T05:13:17.390Z Has data issue: false hasContentIssue false
  • English
  • Français

Using Microsimulation to Reassess Aging Trends in Canada

Published online by Cambridge University Press:  12 May 2014

Jacques Légaré ,
Yann Décarie  and
Alain Bélanger
Jacques Légaré*
Affiliation:
Département de démographie, Université de Montréal
Yann Décarie
Affiliation:
Centre Urbanisation Culture Société Institut national de la recherche scientifique, Montréal
Alain Bélanger
Affiliation:
Centre Urbanisation Culture Société Institut national de la recherche scientifique, Montréal
*
†La correspondance et les demandes de tirés-à-part doivent être adressées à: / Correspondence and requests for offprints should be sent to: Jacques Légaré, Université de Montréal – Démographie, C.P. 6128, Succursale “Centre Ville”, Montréal, QC H3C 3J7 ([email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

Population aging is the population issue of the XXI century and many indices are used to measure its level and pace. In Science (2010), Sanderson and Scherbov suggested improvements to the measure of elderly dependency ratio. They identified several limitations to the use of chronological age as the main variable and proposed a new index, the Adult Disability Dependency Ratio, defined as the number of adults at least 20 years old with disabilities divided by the number of similarly aged adults without disabilities. They used the Sullivan prevalence-based method by multiplying derived disability rates to macro population projections. They showed results for several ECE and OECD countries; results for Canada (see online annex, available at https://www.sciencemag.org/content/329/5997/1287/suppl/DC1) were derived using coefficients of Italy. However, disability is a complex multidimensional process (see Carrière, Keefe, Légaré, Lin, & Rowe, 2007; Légaré and Décarie, 2011), and microsimulation can take into account its implied complexity. Our results for Canada, presented here, exceed those in Science to show how more-sophisticated projections of disabled older adults can improve the analysis. We used LifePaths, a Statistics Canada’s microsimulation model, to provide a perspective of the phenomena unobtainable with prevalence-based methods.

Résumé

Le vieillissement de la population est l’enjeux démographique du XXI ième siècle et plusieurs indicateurs sont utilisés pour en mesurer le niveau et les tendances. Dans Science (2010), Sanderson et Scherbov ont suggéré des améliorations à la mesure du rapport de dépendance des personnes âgées. Ils ont identifié plusieurs limites à l’utilisation de l’âge chronologique comme la principale variable et ont proposé un nouvel indice, le rapport de dépendance des adultes avec incapacités, défini comme le nombre d’adultes ayant une incapacité qui ont au moins 20 ans, divisé par le nombre d’adultes du même âge sans incapacité. Ils ont utilisé la méthode de Sullivan, basée sur la prévalence, en multipliant des taux d’incapacité dérivés à des projections démographiques de niveau macro. Ils ont montré leurs résultats pour plusieurs pays de la CEE et de l’OCDE. Les résultats pour le Canada (voir l’annexe en ligne) ont été calculés en utilisant les coefficients de l’Italie. Cependant, l’incapacité est un processus complexe et multidimensionnel (voir Carrière et al, 2007; Légaré et Décarie, 2011), et la microsimulation peut tenir compte de cette complexité implicite. Nos résultats pour le Canada, présentés ici, sont supérieurs à ceux de Science, et indique comment des projections plus élaborées des personnes âgées avec incapacités peuvent améliorer l’analyse. Nous avons utilisé LifePaths, un modèle de microsimulation de Statistique Canada, pour fournir une perspective du phénomène du vieillissement impossible à obtenir en utilisant des méthodes basées sur la prévalence.

Keywords

vieillissmentCanadatendances futuresLifePathsmicrosimulationpolitique de populationagingCanadafuture trendsLifePathsmicrosimulationpopulation policies
Type
Research Notes / Notes de recherche
Information
Canadian Journal on Aging / La Revue canadienne du vieillissement , Volume 33 , Issue 2 , June 2014 , pp. 208 - 219
Copyright
Copyright © Canadian Association on Gerontology 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bourbeau, R. (2002). L’effet de la “sélection d’immigrants en bonne santé” sur la mortalité canadienne aux grands âges. Cahiers québécois de démographie, 31(2), 249–274.Google Scholar
Carrière, Y., Keefe, J., Légaré, J., Lin, X., & Rowe, G. (2007). Population aging and immediate family composition: Implications for future home care services, Genus, 63(1–2), 11–31.Google Scholar
Chen, J., Ng, E., & Wilkins, R. (1996). The health of Canada's immigrants in 1994–95. Health Reports, 7(4), 33–45.Google Scholar
European Health Expectancy Monitoring Unit. (2009). Data on activity limitations from statistics on income and living conditions (SILC) survey. Retrieved 11, May, 2011 fromhttp://www.ehemu.eu/.Google Scholar
Gilbert, N., & Troitzsch, K. G. (2005). Simulation for the social scientist. Maidenhead Berkshire McGraw-Hill International.Google Scholar
Hummer, R. A., & Hernandez, E. M. (2013). The effect of educational attainment on adult mortality in the United States. Population Reference Bureau, 68(1), 1–20.Google ScholarPubMed
Le Bourdais, C., & Lapierre-Adamcyk, E. (2004). Changes in conjugal life in Canada: Is cohabitation progressively replacing marriage? Journal of Marriage and Family, 66(4), 929–942.Google Scholar
Légaré, J., & Décarie, Y. (2011). Using Statistics Canada LifePaths MicrosimulationModel to project the health status of Canadian elderly. International Journal of Microsimulation, 4(3), 48–56.CrossRefGoogle Scholar
Légaré, J., Décarie, Y. and Bélanger, A. (2011).  ”Using micosimulation to reassess aging trends in Canada.” 3rd General Conference of the International Microsimulation Association, Stockholm, Sweden, June 2011Google Scholar
Légaré, J., Keefe, J., Vézina, S., & Décarie, Y. (2012). Future care needs of older Canadians needing assistance: Who will do how much and for whom? Final Report: Project 2. Prepared for Human Resources and Skills Development Canada, contract no. 9755-09-0017/02.Google Scholar
MacDonald, B-J., & Moore, K. (2011). Moving beyond the limitations of traditional replacement rates, Society of Actuaries, http://www.soa.org/research/research-projects/pension/default.aspx.Google Scholar
MacDonald, B-J., Keefe, J., Spin, P., Vézina, S., & Décarie, Y. (2012). Assessing gaps in receipt of needed support: Who will go without? Final Report: Project 3. Prepared for Human Resources and Skills Development Canada, contract no. 9755-09-0017/02.Google Scholar
Moore, K., Robson, W., & Laurin, A. (2010). Canada’s looming retirement challenge: Will future retirees be able to maintain their living standards upon retirement? C.D. Howe Institute Commentary, No. 317.Google Scholar
Orcutt, G. (1957). A new type of socio-economic system. Review of Economics and Statistics, 39(2), 116–123.CrossRefGoogle Scholar
Organisation for Economic Co-operation and Development (OECD). (2011). Society at a Glance 2011, OECD Social Indicators. Retrieved from www.oecd.org/els/social/indicators/SAG.Google Scholar
Robine, J-M. (2005). Are we living longer and in better health? Paper presented at the conference AGIR: Aging, health and retirement in Europe, Brussels, March 10.Google Scholar
Robine, J-M., & Cambois, E. (2013). Les espérances de vie en bonne santé des européens. Population et Sociétés, 499, 1–4.CrossRefGoogle Scholar
Rowe, G. (2005). Analysing health status transitions using NPHS longitudinal data. Ottawa, SEAMD, Statistics Canada.Google Scholar
Sanderson, W. C., & Scherbov, S. (2010). Re-measuring aging. Science, 329(597), 1287–1288.Google Scholar
Spielauer, M. (2007). Dynamic microsimulation of health care demand, health care finance and the economic impact of health behaviours: Survey and review. International Journal of Microsimulation, 1(1) 35–53.CrossRefGoogle Scholar
Spielauer, M. (2009). What is dynamic social science microsimulation? Retrieved 1, March, 2011http://www.statcan.gc.ca/microsimulation/pdf/chap1-eng.pdf.Google Scholar
Statistics Canada. (2011). The LifePaths Microsimulation Model: An Overview. Retrieved 15 September 2011 fromhttp://www.statcan.gc.ca/microsimulation/pdf/lifepaths-overview-vuedensemble-eng.pdf.Google Scholar
Statistics Canada. (2010). Population projections for Canada, Provinces and Territories: 2009–2036, (Catalogue No. 91-520-X). Retrieved 18 February 2011 fromhttp://www.statcan.gc.ca/pub/91-520-x/91-520-x2010001-eng.pdf.Google Scholar
Sullivan, D. F. (1971). A single index of mortality and morbidity. HSMHA Health Report, 86, 347–354.CrossRefGoogle ScholarPubMed
Torrance, G. W., Feeny, D. H., Furlong, W. J., Barr, R. D., Zhang, Y., & Wang, Q. (1996). Multiattributable utility function for a comprehensive health status classification system. Medical Care, 34, 702–722.Google Scholar
Troitzsch, K. G., Mueller, U., Gilbert, N. G., & Doran, J. E. (1996). Social science microsimulation. Berlin: Springer-Verlag.Google Scholar
Wolfson, M. (2011). Projecting the adequacy of Canadians’ retirement incomes: Current prospects and possible reform options. IRPP Study 17. Montreal: Institute for Research on Public Policy.Google Scholar
Wolfson, M., & Rowe, G. (2004). Disability and informal support: Prospects for Canada. In Cohen, S. B., & Lepkowski, J. M. (Eds.), Eighth Conference on Health Survey Research Methods (pp. 15–22). Hyattsville, MD: National Center for Health Statistics.Google Scholar
Wolfson, M., & Rowe, G. (2007). Aging and inter-generational fairness: A Canadian analysis. In Lambert, Peter J. (Ed.) Equity Research on Economic Inequality, Volume 15 (pp. 197–231), Bingley Emerald Group Publishing Limited.Google Scholar
Zaidi, A, Harding, A., & Williamson, P. (2009). New frontiers in microsimulation modelling, International Microsimulation Association. Inaugural meeting, 2007 Vienna, Austria, Farnham: Ashgate.Google Scholar