We use administrative data on the quarterly employment and earnings of Pennsylvanian workers in the 1970s and 1980s matched to Social Security Administration death records covering 1980–2006 to estimate the effects of job displacement on mortality. We find that for high-seniority male workers, mortality rates in the year after displacement are 50%–100% higher than would otherwise have been expected. The effect on mortality hazards declines sharply over time, but even twenty years after displacement, we estimate a 10%–15% increase in annual death hazards. If such increases were sustained indefinitely, they would imply a loss in life expectancy of 1.0–1.5 years for a worker displaced at age forty. We show that these results are not due to selective displacement of less healthy workers or to unstable industries or firms offering less healthy work environments. We also show that workers with larger losses in earnings tend to suffer greater increases in mortality. This correlation remains when we examine predicted earnings declines based on losses in industry, firm, or firm-size wage premiums.

In this paper we exploit a unique database that merges longitudinal earnings data on Pennsylvanian workers with national death records to study the detailed nature of the correlation between earnings and mortality. We find that the estimates typically reported in the literature, which are based on single years of earnings data, are likely to understate substantially the strength of the association between income and mortality. In particular, relative to a single year of earnings, the average of earnings over a six-year period predicts a 70 percent greater impact of income on mortality. In addition, controlling for the mean level of earnings over a period, we find that greater earnings volatility is associated with higher mortality. We also examine the lag structure of the relationship between earnings and mortality. We find that conditional on a small number of years of recent earning levels, there is little or no correlation between earnings levels in earlier years and current mortality. This runs counter to the interpretation of the earnings-mortality correlation that views workers as "buying health" by allocating a steady fraction of their earnings to the accumulation of a health stock. It is also inconsistent with interpretations of the earnings- mortality link emphasizing the correlation of both variables with an unobserved, time-invariant trait, such as the rate at which workers discount the future. We find that explaining the patterns of correlation appears to require a relatively complex theory that we leave to future research.

We exploit administrative data combining workers' earnings histories with information about their firms to estimate the magnitude and temporal pattern of displaced workers' earnings losses. We find that high-tenure workers separating from distressed firms suffer long-term losses averaging 25 percent per year. In addition, we find that displaced workers' losses: (i) begin mounting before their separations, (ii) depend only slightly on their age and sex, (iii) depend more on local labor-market conditions and their former industries, (iv) are not, however, limited to those in a few sectors, and (v) are large even for those who find new jobs in similar firms.

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We show that the largest increase in unemployment benefits in US history had large spending impacts and small job-finding impacts. This finding has three implications. First, increased benefits were important for explaining aggregate spending dynamics—but not employment dynamics—during the pandemic. Second, benefit expansions allow us to study the MPC of normally low-liquidity households in a high-liquidity state. These households still have high MPCs. This suggests a role for permanent behavioral characteristics, rather than just current liquidity, in driving spending behavior. Third, the mechanisms driving our results imply that temporary benefit supplements are a promising countercyclical tool.