Abstract
We outline the principles for constructing a composite QOL index, and evaluate examples of current indices. We first review three of the most successful indices in economics: the Dow-Jones Industrial Average, the Consumer Price Index, and the Consumer Confidence Index, and consider why they are used so widely. We then propose seven principles for constructing a successful QOL index, and examine implications. One relatively new principle that we examine is that an index should maximize agreement with citizens, by requiring that the QOL index should correlate highly with citizens’ actual judgments of QOL when they are given full information. Fourteen existing QOL indices are then reviewed and evaluated on these criteria. We end with common criticisms of indices, and offer recommendations to construct QOL indices that are accepted by citizens and useful to policy makers.
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Notes
- 1.
The geometric mean \( {\tilde{X}}_{n}\) of n positive numbers X 1, X 2, …, X n is the positive nth root of their products, that is, \({\tilde{X}}_{n}=\text{}{\left({{\displaystyle \Pi }}_{i=1}^{n}{X}_{i}\right)}^{\text{\hspace{0.05em}}1/n}\).
- 2.
These principles are consistent with guidelines for constructing composite indicators of all types such as those summarized in Nardo et al. (2005), but are focused on QOL measurement and its unique, substantive features.
- 3.
As research progresses, this model may be modified to include substitutability or complementarity between social indicators that would require modeling interactions among indicators. For example, an individual with higher average income may consider life expectancy more important than an individual with very low income (as life becomes more “worth living,” longer life may be more valuable).
- 4.
The reason for negative correlations is due in part to “restriction of range” problems (e.g., life expectancy varied far less in the USA since 1970 than it does in a cross-sectional sample of nations, where Somalia has a life expectancy of only 40 years). Negative correlations are also due to preferences of individual nations. For example, the USA seems to prefer higher GDP/capita at the expense of some loss in equality, compared to European nations. Such a policy could result in negative correlation between these indicators as inequality is pushed up in order to gain GDP/capita.
- 5.
A uniform distribution of citizen’s importance weights ensures that any proportion between 0 and 1 has equal likelihood of being chosen and assigned to an index component for a simulated individual. In fact, as noted in the text, empirical distributions of importance weights show that some values are more likely to occur than others. Therefore, the assumption of a uniform distribution represents an extreme that is used to ascertain whether or not the resulting index is highly correlated with the QOL index.
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Hagerty, M.R., Land, K.C. (2012). Issues in Composite Index Construction: The Measurement of Overall Quality of Life. In: Land, K., Michalos, A., Sirgy, M. (eds) Handbook of Social Indicators and Quality of Life Research. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-2421-1_9
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