Inequalities in subjective well-being among the 50+ in the United States and Europe: is it money or health?
Tuesday, June 24, 2014: 9:10 AM
Waite Phillips 207 (Waite Phillips Hall)
The goal of this study is to determine how the distributions of subjective well-being (SWB) among the 50+ relate to the distributions of income and health in the United States and Europe. Most of the policy and scientific attention on disparities has focused either on income or health per se, or on the socioeconomic inequalities in health. So far, little attention has been paid to the distribution of well-being. In this study, we estimate the income- and health-related inequalities in SWB, document their contributing factors, and compare them across the US and Europe. We measure the cognitive dimension of SWB, using life satisfaction scales. We first linearize and rescale these ordinal variables by using ordered probit models. Then, we estimate Gini (G) and concentration indices (C) by taking into account the bounded nature of the SWB measures, using Erreygers’ methodology. Finally, a decomposition method reveals which factors contribute the most to the income- and health-related inequalities in SWB, and whether their contribution is through (i) their own correlation with SWB and/or (ii) their variation across the income or health distributions. Sensitivity analyses are conducted to explore the risk of ‘scale of reference bias’, i.e. some individuals may report different levels of SWB despite having the same latent or ‘true’ SWB. The analyses are conducted on the 2010 wave of the ‘Health and Retirement Study’ (HRS) and the 2011 wave of the ‘Survey of Health, Ageing and Retirement in Europe’ (SHARE). The latter survey has been developed based on the former. The samples include about 20,000 and 37,000 observations respectively. Preliminary results reveal that, as expected, SWB is disproportionately concentrated among healthier individuals: in Europe, Chealth=0.1850 (se=0.0024). It is also more favorably distributed among persons with highest income, but to a lesser extent: Cincome=0.0926 (se=0.0033). Self-assessed health and mental health are the two largest contributors of both the income- and health-related inequalities in SWB. Income does not explain the health-related inequalities, when relative income ¾i.e. the person’s income compared to the one of her reference group¾ plays a significant role in the income-related inequalities. The comparison of the contributing factors in the US and Europe will inform on the key factors and groups of persons that policy needs to target when attempting to reduce inequalities.