The most interesting result of this paper is the strong, consistent positive contribution of several community level variables to life expectancy. Poor people tend to live longer in places with more immigrants, more expensive housing, higher local government spending, more density, and a better educated population. Consider each of the five characteristics in the category “Other factors” at the bottom of Chetty’s table above. [...]
The strongest pattern in the data was that low-income individuals tend to live longest (and have more healthful behaviors) in cities with highly educated populations, high incomes, and high levels of government expenditures, such as New York, New York, and San Francisco, California. In these cities, life expectancy for individuals in the bottom 5% of the income distribution was approximately 80 years. In contrast, in cities such as Gary, Indiana, and Detroit, Michigan, the expected age at death for individuals in the bottom 5% of the income distribution was approximately 75 years. Low-income individuals living in cities with highly educated populations and high incomes also experienced the largest gains in life expectancy during the 2000s.
As noted, these correlations don’t show causation; some of the effect may have something to do with those—like immigrants—who self-select to move to cities. But the strength of these correlations (and their absence for other variables like access to medical care) signals a need for further scrutiny. As always, this kind of broad statistical work comes with caveats: the paper takes only a first-pass, high-level look at correlations between geographic variables and life expectancy. This analysis shows the simple and direct relationship between each tested variable and life expectancy—but doesn’t measure any interactions among variables. And the standard caveat applies: correlation doesn’t prove causation. Still, by examining the correlation between selected local characteristics and life expectancy, we can begin to answer some of our questions about what aspects of place affect this aspect of quality of life.
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