Measuring Quality of Life: Issues and Options

1. Measuring Quality of Life:Issues and Options Munir A. Sheikh Chief Statistician of Canada July 2009

2. Context • Improvements in the quality of life (QoL) are clearly the main objective citizens and policy makers strive for. • National Statistical Offices (NSOs) do not generally put out QoL information for methodological reasons. • Progress in developing information to support regular publication of QoL indicators is desirable but the challenge remains immense. Statistics Canada • Statistique Canada

3. Principal Challenge / Objective • It is my view that the principal challenge in this area is: • For QoL information to be popular, it needs to be simple; preferably a single indicator. • However, such a simple construct(s) does not seem to be either statistically feasible or methodologically defensible. • A case in point is the attractiveness of the GDP numbers: • Even though no one producing this information claims it to be representative of QoL, it does inappropriately get used in that context; • Some have been trying, inappropriately, to expand GDP measurement to become a QoL measure; • Others seem to have fun criticizing GDP as a bad measure of QoL (not realizing it was never intended for that purpose). • Discussions of future directions of QoL measurement should: • Worry about statistical / methodological issues; and, • Focus on simplicity. • Which, of course, means: it won’t be easy. Statistics Canada • Statistique Canada

4. Possible Approaches • There are four possible approaches to measuring QoL, with their own pros and cons. • The four approaches are: • A composite index of well-being • A “dashboard” of headline indicators • Indicators of subjective well-being • A “commensurable domains” approach • These are discussed next. Statistics Canada • Statistique Canada

5. Composite Index of Well-Being • Aggregation over critical domains to produce one index. Pros • A simple / single indicator, superficially easy to follow and compare over time. Cons • What domains to include? • How to aggregate within each domain? • How to aggregate across domains? • Is the aggregation linear or non-linear? Assessment • Not easy for anyone to answer these questions. • Questions beyond the scope of an NSO. • One option is to undertake specialized surveys for some of the answers. This has its own challenges. Statistics Canada • Statistique Canada

6. Dashboard of Headline Indicators • Publish a small number of headline indicators and let citizens / governments form their own overall judgments. Pros • More methodologically defensible, though challenges remain. • NSOs can play a large role in putting out dashboard information. Cons • “What domains to include” issue still remains. • “How to aggregate within each domain” issue still remains. • “Is the aggregation linear or non-linear” issue still remains. • The larger the number of headline indicators, the less useful / popular the approach. Assessment • This seems like the middle-of-the-road approach, with some progress made, but enough challenges remaining, with the approach never catching on to serve the same kind of role as economic statistics. Statistics Canada • Statistique Canada

7. Indicators of Subjective Well-Being • Based on sample survey question(s) asking citizens how they feel re QoL. Pros • Simple / single indicator. • Avoids issue of what determines QoL (can be infinite number of variables). • Can provide both time-series and cross-sectional data. • May allow analysis of factors influencing outcomes (and weights) using econometric analysis. Cons • Robustness and validity of question(s) being asked. • Cultural differences influencing answers to questions. • Averages may mask huge differences across populations. • Context of surveys in which questions asked may influence responses. Assessment • Useful tool if done properly. But not enough as stand alone. • Since outcomes influenced by an infinite number of national and personal factors, determining what the information is telling may be a challenge. Statistics Canada • Statistique Canada

8. Statistics Canada Measurement of Subjective Well-Being (I) • Statistics Canada has surveyed subjective well-being going back almost 20 years, at the request of clients. • Subjective well-being questions have been included in many surveys: • General Social Survey (GSS); • Canadian Community Health Survey (CCHS); • Healthy Aging Survey (HAS); • Canadian Survey of Giving, Volunteering and Participating (CSGVP); • Aboriginal Children Survey (ACS); • Aboriginal Peoples Survey (APS); • National Longitudinal Survey of Children and Youth (NLSCY); • Participation and Activity Limitations Survey (PALS); • Longitudinal Survey of Immigrants to Canada (LSIC); • Survey of Labour Income and Dynamics (SLID); • Census. • The sample size in some cases can be quite large (e.g. CCHS surveys 65,000 respondents annually) Statistics Canada • Statistique Canada

9. Statistics Canada Measurement of Subjective Well-Being (II) • These surveys have covered a wide range of topics, including: • Subjective levels of satisfaction with life, employment, housing, income, education, community, neighbourhood, social capital, health status, health care services • Time use budgets and patterns • Activity limitation factors, both physical and mental • Level of happiness • Pain factors • Stress levels • Discrimination • Trust in institutions and types of individuals Statistics Canada • Statistique Canada

10. Statistics Canada Measurement of Subjective Well-Being (III) • Some facts: • Questions within each survey are coordinated. Across surveys they have not been; • Questions on subjective well-being appear at regular intervals in some surveys (e.g. CCHS) while they are more ad hoc in others (e.g. GSS); • The measurement scales are quite different across surveys and questions (from a four point to an eleven point scale); • There has not been a coordinated focus on asking consistent questions across surveys to draw an overall picture of subjective well-being; • There has not been much analysis of what this information may be telling us either within Statistics Canada or outside, until recently; • There has not been much communication from Statistics Canada on subjective well-being either in its Daily releases or analytical publications. • This is all explained by the fact that SWB has not been a major priority of users. Statistics Canada • Statistique Canada

11. Cumulative percentages on life satisfaction questions Canada circa 2008 Canada circa 2003 Cumulative % Cumulative % Statistics Canada • Statistique Canada

12. Commensurable Domains Approach (I) • Aggregate, in a manner somewhat analogous to GDP, but with time rather than dollars as the numeraire, selected major domains of well-being • Essentially combine time use survey questionnaires with life table methods, to measure the amount of time spent over the life course in valued activities, e.g. • the average number of years citizens enjoy adequate leisure time and money and health; • or alternatively life expectancy weighted by the satisfaction derived from the time spent in various activities such as time with family, paid work, and entertainment; • so we might observe, say, that while life expectancy overall has risen from 78 to 81 years over the past 20 years, “satisfaction weighted” life expectancy actually fell from 69 to 67 years (n.b. hypothetical) • With this kind of (partial) summary index, we can compare one major set of dimensions of QoL over time. And given the cross-section data underlying this class of indices, comparisons across population sub-groups are also feasible. Statistics Canada • Statistique Canada

13. Commensurable Domains Approach (II) Pros • Has the potential to be a simple, single indicator, just like the GDP (with considerable complexity hidden underneath). • Survey-based, so it reflects the way citizens feel. Cons • Problem of “what domains to include” remains. • Problem of adding / averaging individual utility levels. Assessment • The approach requires considerable new work, but could be promising. Statistics Canada • Statistique Canada

14. Concluding Observations from an NSO • NSOs cannot be in the business of taking on tasks that belong to others. • e.g. selecting weights needed to construct aggregated indicators unless “principled weights” already exist (e.g. spending patterns for CPI). • However, it is an NSO’s responsibility to provide any input data that may be needed by policy makers in constructing QoL indicators. • NSOs have to follow methodological rigour in whatever tasks they consider appropriate for their mandate. • The importance citizens place on QoL indicators, and their nature, can have huge implications on resource allocation within NSOs and the priorities attached to various types of data. Statistics Canada • Statistique Canada