The Relationship Between Education and Adult Mortality in the United States

Prior research has uncovered a large and positive correlation between education and health. This paper examines whether education has a causal impact on health. I follow synthetic cohorts using successive U.S. censuses to estimate the impact of educational attainment on mortality rates. I use compulsory education laws from 1915 to 1939 as instruments for education. The results suggest that education has a causal impact on mortality, and that this effect is perhaps larger than has been previously estimated in the literature.

Commentary on "Immigration, health, and New York City: early results based on the U.S. new immigrant cohort of 2003"

This article is commentary on a paper presented at a conference organized by the Federal Reserve Bank of New York in April 2005, "Urban Dynamics in New York City." The goal of the conference was threefold: to examine the historical transformations of the engine-of-growth industries in New York and distill the main determinants of the city's historical dominance as well as the challenges to its continued success; to study the nature and evolution of immigration flows into New York; and to analyze recent trends in a range of socioeconomic outcomes, both for the general population and recent immigrants more specifically.Immigrants - New York (N.Y.) ; Medical care - New York (N.Y.) ; Economic conditions - New York (N.Y.) ; Federal Reserve District, 2nd

Were Compulsory Attendance and Child Labor Laws Effective? An Analysis from 1915 to 1939

Secondary schooling experienced incredible growth in the first 40 years of the 20th Century. Was legislation on compulsory attendance and child labor responsible for this growth? Using individual data from the 1960 census, I estimate the effect of several laws on educational attainment for individuals who were 14 years old between 1915 and 1939. The results show that legally requiring a child to attend school for one more year, either by increasing the age required to obtain a work permit or by lowering the entrance age, increased educational attainment by about 5%. The effect was similar for white males and females, but there was no effect for blacks. Continuation school laws, which required working children to attend school on a part time basis, were effective for white males only. These laws increased the education only of those in the lower percentiles of the distribution of education. By increasing the education of the lower tail, the laws contributed to the decrease in educational inequality, perhaps by as much as 15%. States with more wealth and a higher percentage of immigrants were more likely to pass more stringent laws, and states with higher percentage of blacks were less likely to do so. Importantly, the results suggest that the laws were not endogenous during this period.

Health Inequality, Education and Medical Innovation

Recent studies suggest that health inequalities across socio-economic groups in the US are large and have been growing. We hypothesize that, as in other, non-health contexts, this pattern occurs because more educated people are better able than to take advantage of technological advances in medicine than are the less educated. We test this hypothesis by relating education gradients in mortality with measures medical innovation. We focus on overall mortality and cancer mortality, examining both the incidence of cancer and survival conditional on disease incidence. We find evidence supporting the hypothesis that education gradients are steeper for diseases with more innovation.

Education and Health: Evaluating Theories and Evidence

There is a large and persistent association between education and health. In this paper, we review what is known about this link. We first document the facts about the relationship between education and health. The education %u2018gradient%u2019 is found for both health behaviors and health status, though the former does not fully explain the latter. The effect of education increases with increasing years of education, with no evidence of a sheepskin effect. Nor are there differences between blacks and whites, or men and women. Gradients in behavior are biggest at young ages, and decline after age 50 or 60. We then consider differing reasons why education might be related to health. The obvious economic explanations %u2013 education is related to income or occupational choice %u2013 explain only a part of the education effect. We suggest that increasing levels of education lead to different thinking and decision-making patterns. The monetary value of the return to education in terms of health is perhaps half of the return to education on earnings, so policies that impact educational attainment could have a large effect on population health.

Bounds in Competing Risks Models and the War on Cancer

In 1971 President Nixon declared war on cancer and increased the federal funds allocated to cancer research dramatically. Thirty years later, many have declared this war a failure. Overall cancer statistics confirm this view: age-adjusted mortality in 2000 was essentially unchanged from the early 1970s. At the same time, age-adjusted mortality rates from cardiovascular disease have fallen quite dramatically. Since the causes underlying cancer and cardiovascular disease are likely to be correlated, the decline in mortality rates from cardiovascular disease may be somewhat responsible for the rise in cancer mortality. It is natural to model mortality with more than one cause of death as a competing risks model. Such models are fundamentally unidentified, and it is therefore difficult to get a clear picture of the progress in cancer. This paper derives bounds for aspects of the underlying distributions under a number of different assumptions. Most importantly, we do not assume that the underlying risks are independent, and impose weak parametric assumptions in order to obtain identification. The theoretical contribution of the paper is to provide a framework to estimate competing risk models with interval data and discrete explanatory variables, both of which are common in empirical applications. We use our method to estimate changes in cancer and cardiovascular mortality since 1970. The estimated bounds for the effect of time on the duration until death for either cause are fairly tight and we find that trends in cancer show much larger improvements than previously estimated. For example, we find that time until death from cancer increased by about 10% for white males and 20% for white women.

The Effect of Education on Medical Technology Adoption: Are the More Educated More Likely to Use New Drugs

There is a large body of work that documents a strong, positive correlation between education and measures of health, but little is known about the mechanisms by which education might affect health. One possibility is that more educated individuals are more likely to adopt new medical technologies. We investigate this theory by asking whether more educated people are more likely to use newer drugs, while controlling for other individual characteristics, such as income and insurance status. Using the 1997 MEPS, we find that more highly educated people are more likely to use drugs more recently approved by the FDA. We find that education only matters for individuals who repeatedly purchase drugs for a given condition, suggesting that the more educated are better able to learn from experience.

Bounds in Competing Risks Models and the War on Cancer

Competing risks models are fundamentally unidentified. This paper derives bounds for aspects of the underlying distributions under a number of different assumptions. These bounds are then applied to mortality data from the US. We find that trends in cancer show much larger improvements than was previously estimated.Bounds; Competing Risks; Cancer

Education and Health: Insights from International Comparisons

In this review we synthesize what is known about the relationship between education and health. A large number of studies from both rich and poor countries show that education is associated with better health. While previous work has thought of the effect of education separately for rich and poor countries, we argue that there are insights to be gained by integrating the two. For example, education is associated with lower malnutrition in most countries, but in richer countries the educated have lower BMIs whereas in poor countries the educated have higher BMIs. This suggests that the behaviors associated with better health differ depending on the level of development. We illustrate this approach by comparing the effects of education on various health and health behaviors around the world, to generate hypotheses about why education is so often (but not always) predictive of health. Finally, we review the empirical evidence on the relationship between education and health, paying particular attention to causal evidence and evidence on mechanisms linking education to better health.