We estimate the causal effects of acute fine particulate matter (PM 2.5) exposure on mortality and health care use among the US elderly using Medicare administrative data and a novel instrument for air pollution: changes in the local wind direction. We then develop a new methodology that uses machine learning to estimate the number of life-years lost due to PM 2.5. We find that, while unhealthy individuals are disproportionately vulnerable to air pollution, the largest aggregate burden is borne by those with medium life expectancy, who are both vulnerable and comprise a large share of the elderly population.
|Original language||English (US)|
|Number of pages||46|
|State||Published - Nov 8 2016|
|Name||NBER Working Paper|