Subjective Health Status of the Older Population: Is It Related to Country-Specific Economic Development Measures?

It is now common to use the individual's self-assessed-health-status (SAHS), which expresses her/his holistic 'internal' view, as a measure of health. The use of SAHS is supported by numerous studies that show that SAHS is a better predictor of mortality and morbidity than medical records. The 2011 wave of the rich Survey of Health Aging and Retirement Europe (SHARE) is used for the exploration of the full spectrum of factors behind the health-status in 16 European countries, using about 33 thousand observations. Special emphasis is given to the examination of development country measures and their correlation with aggregate country-levels of subjective-health. The empirical analysis includes 2 layers: (i) estimation of SAHS equations, using a large set of personal socio-economic characteristics as explanatory variables (controlling for country fixed-effects); and (ii) study of the correlations between average country SAHSs – controlled for differences in populations’ socio-economic characteristics – and objective country-specific aggregate macroeconomic development variables (logarithm of per-capita GDP; the Human Development Index; life expectancy at birth; per-capita expenditures on health; percentage of GDP spent on education; income inequality). The second part of the empirical examination (that borrows the technique used by Oswald and Wu, 2010) is novel and will lead to an answer to our core question: Is subjective-health affected by the country's economic development level?

The main findings are: (i) the estimation of self-assessed-health-status regressions provides clear evidence of the effects of a large set of socio-economic variables on the individual’s subjective rating of her/his health status, beyond and above the obvious effects of health conditions; (ii) the second, more innovative, finding is related to the effects of country-specific economic development variables on the subjective-health of the residents, beyond and above those of the personal characteristics. Country dummy variables are added to the SAHS regression, to derive the country-specific aggregate SAHSs. These country dummies are then examined for correlations with a set of objective country economic development measures. It appears that the first five development measures (logarithm of per-capita GDP; the Human Development Index; life expectancy at birth; per-capita expenditures on health; percentage of GDP spent on education) are positively and significantly correlates with aggregate SAHSs, while Income Inequality does not correlate significantly with SAHS.

It is therefore not only ‘who you are’ that affects the subjective rating of health, but also ‘in which country you live’. Those who live in more developed countries report higher levels of subjective-health (everything else being equal). Overall, our findings indicate that what is true for the individual is also true for the country as a whole: both individual and country-level development factors affect subjective-health and the two levels accumulate and reinforce the subjective-health assessment. This seems to be at odds with the ‘Easterlin Paradox’ that emphasizes within country individual effects and denies cross-country effects.