The Dynamics of Residential Sorting and Health: Implications of Climate Change in the U.S. (2019, JMP)
Abstract. This study combines the seminal ideas of Tiebout (1956) and Grossman (1972) to develop a new empirical framework for evaluating treatments that have spatially differentiated effects on health and environmental quality. Individuals are modeled as choosing a residential location based on their heterogeneous preferences for local public goods and their beliefs about how their location choices will affect the future evolution of their health. Thus, the choice of residential location constitutes a health investment, in addition to providing current and future consumption values of local public goods. To estimate the dynamic model of location choice, I employ a sample of 5.5 million seniors from 2001-2013. Seniors’ preferences for public goods, private goods, and their rates of intertemporal substitution between health and consumption are allowed to vary flexibly with age and health. Results suggest that seniors’ willingness-to-pay (WTP) for warmer winters is uniformly positive, while WTP to avoid warmer summers varies with age and health. Their average annual WTP to avoid future climate change in the U.S. predicted under a “business as usual” scenario for global carbon emissions ranges from $962 for older, sicker groups who are more vulnerable to climate change’s negative effects on health to -$1,894 for younger, healthier groups, who value warmer winters and are relatively resilient and mobile.
The Illness-Poverty-Amenity Trap (2019)
Joint work with Nicolai Kuminoff and Jonathan Ketcham
Abstract. This study investigates the interaction between residential sorting and health among senior citizens in the United States. We extend Tiebout’s (1956) sorting model to recognize that health may affect the rate at which retirees are willing to trade public and private goods. Local public goods such as air pollution and climate may also affect the rate at which health declines late in life. A single-crossing restriction on preferences implies that lower income seniors will choose to live in lower quality neighborhoods, become sicker sooner, and spend more on health care. We test these predictions using a 10% random panel sample of Medicare beneficiaries that includes more than 7 million seniors from 2001-2013. Regression analysis reveals that poorer seniors tend to live in neighborhoods that expose them to higher concentrations of fine particulate air pollution (PM2.5); they are diagnosed with more chronic medical conditions; they spend more on health care; and they die sooner. We also find that medical spending and migration rates increase following health shocks that are associated with elevated PM2.5 exposures, such as cancers, hip fractures, strokes, heart attacks, and dementia. Finally, we observe that when lower-income seniors move, they tend to move to more polluted neighborhoods. The average move increases the PM2.5 exposure gap between high-income and low-income seniors by 17% of the gap that existed in 2001. Overall, our findings are suggestive of an “illness-poverty-amenity trap” in which sicker, poorer seniors are exposed to worse environmental conditions that degrade their health, increase their medical spending, and induce them to move to neighborhoods that are less expensive and more polluted. This sorting process generates pollution exposure gaps by age and health that parallel the gaps by race and income that have been the primary focus of environmental justice literature. Our findings also suggest that policies targeting environmental quality may have important fiscal implications for Medicare programs because seniors are the fastest growing age group in the U.S. and among the most vulnerable to air pollution and heat stress.
Work in Progress
Sorting for Life: New Evidence on the VSL for Seniors
(joint work with Kelly Bishop, Nicolai Kuminoff, and Alvin Murphy)
Abstract. Senior citizens are the main beneficiaries of many regulations targeting human health and environmental quality. For instance, 70% of monetary benefits that the Environmental Protection Agency attributes to its Clean Air Act regulations are based on reducing mortality among people over age 65. However, these benefit measures are calculated by multiplying the number of deaths avoided by the value of a statistical life (VSL) derived from wage hedonic studies of younger, healthier workers. A well-known caveat to such calculations is that life-cycle theory suggests the VSL will evolve with age and health. However, there is virtually no revealed preference evidence on this evolution after people exit the labor market. We address this knowledge gap by leveraging the fact that seniors may increase their life expectancies by paying to move to neighborhoods where residents tend to live longer, for example because of access to higher-quality health care, better environmental conditions,and more opportunities for social interaction. Based on this logic, we use a hedonic property value model to estimate the implicit cost of statistical life extension in the housing market and use these implicit-cost estimates to estimate the VSL for seniors. We assess the sensitivity of our estimates to different beliefs that seniors may have about how their residential location affects their longevity. Specifically, we compare VSL estimates based on the “naïve” belief that observed spatial differentials in average longevity reflect purely a causal relationship with the “sophisticated” belief that these spatial differentials in average longevity reflect both a causal relationship and a non-causal correlation created by spatial sorting on health in equilibrium.