Development of a Multidimensional Living Conditions Index (LCI)
- 475 Downloads
The scope of this study ranges from the identification of key drivers of living conditions from a wide spectrum of context-based indicators to the development of a concrete composite measure of living conditions within the framework of a multivariate analysis. The Living Conditions Index (LCI) is a standardized aggregate score that summarizes five components and 18 indicators in a single number. Three different approaches, principal component analysis (PCA), range equalization (RE), and division by mean (DM) are used to assess the impact of different methods of weighting and standardization procedures on the composite. Between the RE and DM methods, the RE method is preferred because it accounts for wider variations and strong correlations to the PCA composite. In general, the PCA method appears promising, particularly for cross-community comparisons as it is based on a weighting scheme. Extreme variability between quintiles that comprise the LCI indicates that the score represents a summary of economic, housing, and cultural diversities. The paper advocates for a future plan of research in the light of identified gaps in data, and more emphasis on disparities in economic conditions. A major implication of the study is that the composite provides a new tool in child development research for characterizing community-based living conditions and detecting disparities in the distribution of child developmental outcomes.
KeywordsLiving Conditions Index Macro-analysis Principal components analysis Range equalization Division by mean Canada
The author thanks the Faculty of Extension, University of Alberta, Edmonton, for funding this project. The contents, however, are solely the responsibility of the author and do not represent the official views of the funding agency. The author would like to thank Dr. Susan Lynch, Director, Early Child Development Mapping Project (ECMap) Alberta and the ECMap team for their support in carrying out this project. Special thanks are also due to Shea Betts and Xian Wang for their help in extracting the Census data in the very initial stage of the project and Mr. Darcy Reynard for supplying the GIS data on the density variables.
- Anand, S., & Sen, A. (1997). Concepts of human development and poverty: A multidimensional perspective, Human Development Papers 1997, UNDP.Google Scholar
- Beckerman, W. (1978). Measure of leisure, equality, and welfare. Paris: OECD.Google Scholar
- Bronfenbrenner, U., & Morris, P. (1998). The ecology of developmental processes. In W. Damon & R. M. Lerner (Eds.), Handbook of child psychology: Theoretical models of human development (5th ed., Vol. 1, pp. 993–1028). New York: Wiley.Google Scholar
- Center for Communication and Civic Engagement. (2007). Measuring social and economic development: A look at the Human Development Index (HDI) [PowerPoint slides]. Seattle: Center for Communication and Civic Engagement, University of Washington.Google Scholar
- Ceriani, L., & Gigliarano, C. (2013). Sujective and objective well-being: A Bayesian networks approach. Retrieved from www.ecineq.org/ecineq_bari13/FILESxBari13/CR2/p261.pdf.
- Chavis, D. M., Lee, K. S., & Acosta, J. D. (2008). The sense of community (SCI) revised: The reliability of the SCI-2. Paper presented at the 2nd International Community Psychology Conference, Lisboa, Portugal.Google Scholar
- Cohen, A. (2009). The multidimensional poverty assessment tool: Design development and application of a new framework for measuring rural poverty. Rome: International Fund for Agricultural Development.Google Scholar
- Cvrlje, D., & Ćorić, T. (2010). Macro & micro aspects of standard of living and quality of life in a small transition economy: The case of Croatia. EFZG Working Paper Series, 1002.Google Scholar
- De Neve, J.-E., Diener, E., Tay, L., & Xuereb, C. (2013). The objective benefits of subjective well-being. In J. Helliwell, R. Layard, & J. Sachs (Eds.), World happiness report 2013. New York: UN Sustainable Development Network.Google Scholar
- Dickes, P., Valentova, M., & Borsenberger, M. (2009). Social cohesion: Measurement based on the data from European Value Study. Paper presented at the NTTS (New Techniques and Technologies for Statistics) conference, Eurostat, Brussels.Google Scholar
- Ebert, U., & Welsch, H. (2007). The social evaluation of income distribution: An assessment based on happiness surveys. New York: Maxwell School of Citizenship and Public Affairs. Retrieved from http://worlddatabaseofhappiness.eur.nl//hap_bib/freetexts/ebert_u_2004.pdf.
- European Union. (2013). Smarter, greener, more inclusive? Indicators to support the Europe 2020 strategy. Luxembourg: Publication Office of the European Union.Google Scholar
- Fallowfield, L. (2009). What is quality of life?. London: Hayward Medical Communications.Google Scholar
- Fernald, L. C. H., Kariger, P., Engle, P., & Raikes, A. (2009). Examining early child development in low-income countries: A toolkit for the assessment of children in the first five years of life. Washington, DC: The World Bank.Google Scholar
- Frey, B. S., & Stutzer, A. (2002). Happiness and economics. Princeton: Princeton University Press.Google Scholar
- Garelli, S. (2011). Competitiveness 20 years later. In The IMD world competitiveness yearbook (pp. 29–34). Lausanne: IMD World Competitiveness Center.Google Scholar
- Giovannini, E., & Hall, J. (2007). Measuring well-being and societal progress. Retrieved from http://www.beyond-gdp.eu/download/oecd_measuring-progress.pdf.
- Groh, A. P., & Wich, M. (2009). A composite measure to determine a host country’s attractiveness for foreign direct investment. IESE Business School, University of Navarra, Working Paper WP-833.Google Scholar
- Hale, T. (2004). An extended example using Theil’s T Statistic: U.S. income inequality by county. Retrieved from utip.gov.utexas.edu/tutorials/extended_example.doc.Google Scholar
- Haughey, D. (2010). Pareto analysis step by step. London: Project Smart.Google Scholar
- IMD World Competitiveness Center. (2010). Customized products. Lausanne: IMD World Competitiveness Center.Google Scholar
- Jordan, P. W. (2010). The good society framework—Understanding quality of life. Retrieved from http://www.orcacomputer.com/isqols/content/NEWS/GoodSocietyFrameworkGeneralEdit.pdf.
- Kaiser, H. F., & Rice, J. (1974). Little jiffy, mark IV. Educational and Psychological Measurement, 39, 711–714.Google Scholar
- Kolenikov, S. (1998). The methods of the quality of life assessment (Master’s thesis). Moscow: New Economic School.Google Scholar
- Krishnan, V. (2010). Constructing an area-based socioeconomic index: A principal components analysis approach. Edmonton: University of Alberta, Faculty of Extension.Google Scholar
- Leschke, J., Watt, A., & Finn, M. (2008). Putting a number of job quality? Constructing a European job quality index. WP ETUI-REHS, 2008, 03.Google Scholar
- Lutero, G. (2010). The aggregation problem in its hystorical perspective: A summary overview. Retrieved from www.fao.org//rural/wye_city_group/2010/May/WYE_2010.4.1_Lutero.pdf.
- Major Cities Unit. (2010). State of Australian cities 2010. Canberra: Major Cities Unit.Google Scholar
- Michalos, A. C. (2011). Quality of life assessment is too important to be left to economists. Canadian Centre for Policy Alternatives Review. Retrieved from http://www.policyalternatives.ca/publications/reports/quality-life-assessment-too-important-be-left-economists.
- Nardo, M., & Saisana, M. (2005). Handbook on constructing composite indicators: Putting theory into practice. OECD/JRC, Institute for the Protection and Security of the Citizen Unit of Econometrics and Applied Statistics. Retrieved from http://epp.eurostat.ec.europa.eu/portal/page/portal/research_methodology/documents/S11P3_OECD_EC_HANDBOOK_NARDO_SAISANA.pdf.
- Nardo, M., Saisana, M., Saltelli, A., & Tarantola, S. (2005b). Tools for composite indicators building. European Commission, Joint Research Centre Working Paper EUR 21682 EN.Google Scholar
- Nardo, M., Saisana, M., Saltelli, A., Tarantola, S., Hoffman, A., & Giovannini, E. (2005a). Handbook on constructing composite indicators: Methodology and user guide. OECD, Statistics Working Paper STD/DOC (2005)3.Google Scholar
- Nunnally, J. (1978). Psychometric theory. New York: McGraw-Hill.Google Scholar
- Philips Center for Health and Well-being. (2010a). Philips index for health and well-being: A global perspective. Amsterdam: Philips Center for Health and Well-being.Google Scholar
- Philips Center for Health and Well-being. (2010b). Outcome of the 1st think tank meeting on livable cities. Amsterdam: Philips Center for Health and Well-being.Google Scholar
- Reinstadler, A., & Ray, J. (2010). Macro determinants of individual income poverty in 93 regions of Europe. Luxembourg: Eurostat.Google Scholar
- Ross, D. P., & Roberts, P. (2013). Income and child well-being: A new perspective on the poverty debate. Ottawa: Canadian Council on Social Development. Retrieved from www.ccsd.ca/pubs/inckids/1.htm.
- Rosselet-McCauley, S. (2011). Appendix I: Methodology and principles of analysis. In The IMD world competitiveness yearbook. Lausanne: IMD World Competitiveness Center.Google Scholar
- Saltelli, A., Nardo, M., Saisana, M., & Tarantola, S. (2004). Composite indicators—The controversy and the way forward, OECD World Forum on Key Indicators, Palermo, 10-13 November.Google Scholar
- Salzman, J. (2003). Methodological choices encountered in the construction of composite indices of economic and social wellbeing. Ottawa: Center for the Study of Living Standards. Retrieved from www.csls.ca/events/cea2003/salzman-typol-cea2003.pdf.
- Schlossberg, M. (2002). Visualizing accessibility with GIS. Solstice: An Electronic Journal of Geography and Mathematics, XIII (2). Retrieved from http://hdl.handle.net/2027.42/60283.
- Sharpe, A. (2004). Literature review of frameworks for macro-indicators. Ottawa: Centre for the Study of Living Standards.Google Scholar
- The Economist (2011). Inequality: Unbottled Gini.Google Scholar
- Trocmé, N., MacLaurin, B., Fallon, B., Shlonsky, A., Mulcahy, M., & Esposito, T. (2009). National child welfare outcomes indicator matrix (NOM). Montreal: Centre for Research on Children and Families, McGill University.Google Scholar
- UNDP. (2004). ICT and human development: Towards building a composite index for Asia, realizing the Millennium Development Goals, Technical Paper. UNDP: Elsevier.Google Scholar
- UNICEF. (2007). Child poverty in perspective: An overview of child well-being in rich countries, Innocenti Report Card 7. Florence: UNICEF Innocenti Research Centre.Google Scholar
- Vyas, S., & Kumaranayake, L. (2006). Constructing socioeconomic status indices: How to use principal components analysi? Advance Access Publication, 9, 459–468.Google Scholar
- Wilkinson, R., & Pickett, K. (2009). The Spirit Level: Why more equal societies almost always do better. London: Allen Lane.Google Scholar
- World Health Organization. (2004). WHO quality of life-BREF. Geneva: World Health Organization.Google Scholar