Center on the Economics and Demography of Aging

The Hispanic Health Paradox is that despite their disadvantaged socioeconomic status, Hispanics in the U.S. experience mortality outcomes that are similar to those of non-Hispanic whites. Why being Hispanic is protective remains an active subject of research. In this paper, we explore how a novel, continuous metric of Hispanic identity based on an individual’s first name helps us better understand health among Hispanics in the U.S. Health and Retirement Study (HRS), a rich dataset of Americans aged 50 and older. We document and characterize the Hispanic Health Paradox in mortality and health status in the HRS, and we examine the information contained within first names. We uncover a striking asymmetry in how the Hispanicity of the first name is associated with health outcomes and to a lesser extent with health inputs. For foreign-born Hispanics, a more Hispanic first name often signals healthier outcomes; but for native-born Hispanics, the reverse is true. The evidence is consistent with a story of an immigrant health advantage and differential assimilation among the second and later generations in which the more assimilated, with less distinctively Hispanic names, are healthier. But disadvantages among native Hispanics with more Hispanic names do not appear to be attributable to drinking,smoking, or exercise.

The foreign-born share of the U.S. population has been gradually rising in recent decades and is approaching its historic maximum. Areas that have not traditionally received immigrants have experienced greater increases in the foreign-born share than have other areas with persistently high levels of immigration. This raises clear questions about the macroeconomic impacts of immigration on native workers. Economic theory suggests that immigration shifts out labor supply, reducing wages for natives in the short run because labor demand is downward sloping, and raising unemployment among natives if wages do not fall. Although theoretically sound and widely cited in the U.S. immigration debate, this static view has received mixed support in the scientific literature. Researchers continue to debate whether influxes of immigrants like the Mariel Boatlift of 1980 reduced wages or employment among native workers in Miami, with a body of empirical evidence that often appears ambiguous.

We contribute to this debate by comparing recent trends in the employment rates of native workers in immigrant-receiving geographical areas to recent trends in other areas. We utilize the rich geographic resolution offered by the annual U.S. American Community Survey, which samples roughly 1 percent of the entire U.S. population and allows us to examine trends in public data within areas as small as 80,000 residents. The time period covered by the ACS, 2005-2016, provides us a unique look at employment outcomes during a period of much economic turbulence and differential immigration patterns across states and regions.

In contrast to the implication of the static model, we find that rising foreign-born shares of thelocal labor force are robustly associated with increases in native employment rates over 2005-2016. Our model predicts each percentage-point increase in the foreign-born share isassociated with an increase in the native employment rate of 0.075 percentage point. Because the variation in the foreign-born share is large (SD = 0.15) relative to the variation in the native employment rate (SD = 0.04), our model implies that up to one quarter of the cross-sectional variation in native employment could be accounted for by variation in the foreign-born share ofthe labor force. By contrast, average annual changes in native employment and the foreign-born share are both about 0.1 percent, implying that a much smaller share of the typical annual change in native employment, only about 5 to 7 percent, might be attributable to changes inthe foreign-born share of the labor force.

These results suggest that during the first two decades of the 21st century, the presence of foreign-born workers was not detrimental to the employment prospects of native workers and may have been a net benefit. Whether immigrant labor actually raises the employment of natives on its own or is a marker of third factors that are causal is less clear and remains the subject of future investigations.

The longterm historical decline in infant mortality has been accompanied by increasing concentration of infant deaths at the earliest stages of infancy. The influence of prenatal and neonatal conditions has become increasingly dominant relative to postnatal conditions as external causes of death such as infectious disease have been diminished. In the mid-1960s Coale and Demeny developed formulas describing the dependency of the average age of death in infancy on the level of infant mortality from data obtained up to that time.

Almost at the same time as Coale and Demeny’s analysis, as shown in this paper, in the more developed countries a steady rise in average age of infant death began. This paper demonstrates this phenomenon with several different data sources, including the linked individual birth and infant death datasets available from the US National Center for Health Statistics and the Human Mortality Database. A possible explanation for the increase in average age of death in infancy is proposed, and modifications of the Coale-Demeny formulas for practical application to contemporary low levels of mortality are offered.

Estimates based on official vital statistics underestimate mortality for Italy during the World Wars. This paper uses a modeling strategy to estimate mortality for Italy based on data from both civilian and military authorities. The model uses the same principles as the one used to reconstruct war losses for England/Wales (Jdanov et al. 2005) and can be adapted to other countries even when we lack detailed knowledge of historical events during wartime. The results produce much lower estimates of life expectancy at birth for males during wartime than the previously published estimates that exclude military deaths. For example, in 1917, the former was nearly 15 years lower than the latter (31.0 versus 45.8 years).

Aggregate health expenditures as a share of GDP have risen in the United States from about 5 percent in 1960 to nearly 14 percent in recent years. Why? This paper explores a simple explanation based on technological progress. Technological advances allow diseases to be cured today, at a cost, that could not be cured at any price in the past. When this technological progress is combined with a Medicare-like transfer program to pay the health expenses of the elderly, the model is able to reproduce the basic facts of recent U.S. experience, including the large increase in the health expenditure share, a rise in life expectancy, and an increase in the size of health-related transfer payments as a share of GDP.