The growth of novel flexible work formats raises a number of questions about their effects upon health and the potential required changes in public policy. However, answering these questions is hampered by lack of suitable data. This is the first paper that draws on comprehensive longitudinal administrative data to examine the impact of self-employment in terms of health. It also considers an objective measure of health – hospital admissions – that is not subject to recall or other biases that may affect previous studies. Our findings, based on a representative sample of over 100,000 individuals followed monthly from 2005 to 2011 in Portugal, indicate that the likelihood of hospital admission of self-employed individuals is about half that of wage workers. This finding holds even when accounting for a potential self-selection of the healthy into self-employment. Similar results are found for mortality rates.
Studies of intergenerational mobility have largely ignored health despite the central importance of health to welfare. We present the first estimates of intergenerational health mobility in the US by using repeated measures of self-reported health status (SRH) during adulthood from the PSID. Our main finding is that there is substantially greater health mobility than income mobility in the US. A possible explanation is that social institutions and policies are more effective at disrupting intergenerational health transmission than income transmission. We further show that health and income each capture a distinct dimension of social mobility. We also characterize heterogeneity in health mobility by child gender, parent gender, race, education, geography and health insurance coverage in childhood. We find some important differences in the patterns of health mobility compared with income mobility and also find some evidence that there has been a notable decline in health mobility for more recent cohorts. We use a rich set of background characteristics to highlight potential mechanisms leading to intergenerational health persistence.
The hypothesis that active community involvement is beneficial for health finds strong support in the medical literature and in most policy guidelines for active ageing in OECD countries. We test it empirically and find that voluntary work has a significant impact on several measures of mental wellbeing. When accounting for fixed effects, panel attrition, endogeneity, and reverse causality, the positive effect of voluntary work remains robust. For the first time in the literature, we calculate the monetary equivalent of mental wellbeing benefits of voluntary work with the compensating variation approach, and estimate them up to a maximum of around 9,500 euros per indicator. Our results imply that policies fostering voluntary work of the elderly would contribute to active ageing and the wellbeing of the elderly and reduce welfare costs for society.
The objective of this research is to measure and compare the importance of the contribution of inequality of opportunity in child health inequality. The latter is decomposed into within opportunity inequality and the between opportunity inequality using a non-parametric approach after building groups with deducted circumstance variables.
The results showed that the total health inequality experienced a decrease between 1998 and 2013 from 0.65 to 0.26 in 15 years unlike the inequality of opportunities which has increased. It goes from 0.14 to 0.18 respectively in 1998 and 2013. The relatively low levels of inequality of opportunity are interpreted as an estimate of the lower bound of the set of variables of circumstances that can influence child health. Considering the results, the increase in the level of inequality of health opportunity would come more from the increase of the “unfavorable opportunity” group’s contribution.
Using longitudinal data from the Panel Study of Income Dynamics for 1997-2013 and difference-in-differences (DD) and difference-in-difference-in-differences (DDD) techniques, we estimate the effects of minimum wages on absence from work due to own and others’ (such as children’s) illnesses. We use person fixed effects within both linear and two-part models, the latter to explore changes at extensive and intensive margins. A lower educated group (likely affected by minimum wages) is compared with higher educated groups (likely unaffected). Within the lower educated group, we find higher minimum wages are associated with lower rates of absence due to own and others’ illness combined and due to own illness alone, but not associated with absence due to others’ illness. A $1 increase in the real minimum wage results in 19% (in DD model) and 32% (DDD) decreases in the absence rate due to own illness evaluated at the mean. These findings are strongest for persons who are not employed year-round and among the lowest wage earners. In additional analysis, we show that these effects are likely not due to changes in labor supply or job-related attributes. Instead, we find a possible mechanism: higher minimum wages improve self-reported health for lower educated workers.
We study the causes of “nutritional inequality”: why the wealthy tend to eat more healthfully than the poor in the U.S. Using two event study designs exploiting entry of new supermarkets and households’ moves to healthier neighborhoods, we reject that neighborhood environments have economically meaningful effects on healthy eating. Using a structural demand model, we find that exposing low-income households to the same food availability and prices experienced by high-income households would reduce nutritional inequality by only 9%, while the remaining 91% is driven by differences in demand. In turn, these income-related demand differences are partially explained by education, nutrition knowledge, and regional preferences. These findings contrast with discussions of nutritional inequality that emphasize supply-side issues such as food deserts.
Recent headlines frequently refer to rising inequality and its implication on economic growth and social welfare. Addressing the latter is difficult and requires more than simply looking at GDP, as Kuznets long ago pointed out. In this paper we focus on the importance of the income measure underlying the inequality measure when examining the relationship between GDP growth and inequality. We create a mapping using Census Bureau household survey data and Bureau of Labor Statistics (BLS) consumer expenditure data to create distributional measures of the Bureau of Economic Analysis (BEA) personal income. We show that for the period 2000‐2012, inequality using personal income is substantively lower than inequality measured using Census Bureau money income, and the trends in both inequality and median income are different. This demonstrates the importance of using a measure a national accounts based measure of income when examining the relationships between inequality and growth.