Trade Liberalization and Mortality: Evidence from U.S. Counties June 2017 Justin R. Pierce Board of Governors of the Federal Reserve System Peter K. Schott Yale School of Management & NBER

Disclaimer Any opinions and conclusions expressed herein are those of the authors and do not necessarily represent the views of the National Center for Health Statistics, the Board of Governors of the Federal Reserve System or its research staff.

Introduction A large literature investigates the effect of economic shocks on health Research in public health (e.g. Case and Deaton 2015) identifies an increase in U.S. mortality among middle-aged whites after 1999 This paper examines the relationship between county-level mortality rates and a plausibly exogenous change in U.S. trade policy – U.S. granting of Permanent Normal Trade Relations (PNTR) to China in 2000 – that differentially exposed U.S. counties to increased competition from China

Motivation: Case and Deaton (2015) Case and Deaton (2015) Figure 2 Crude Death Rates, Whites 45-54

Extending Case-Deaton (2015) Back in Time Accidental Poisoning Suicide Alcohol-Related Liver Disease (ALRD)

Extending Case-Deaton (2015) Back in Time Accidental Poisoning Suicide Alcohol-Related Liver Disease (ALRD)

Extending Case-Deaton (2015) Back in Time Accidental Poisoning Suicide Alcohol-Related Liver Disease (ALRD)

Introduction A large literature investigates the effect of economic shocks on health Public health researchers (e.g. Case and Deaton 2015) have identified an increase in mortality among middle-aged whites in the U.S. after 1999 This paper examines county-level relationship between mortality and the U.S. granting of Permanent Normal Trade Relations (PNTR) to China in Oct 2000 Two identification strategies Difference in Differences: do counties more exposed to the trade liberalization (first difference) experience greater changes in mortality after it was implemented (second difference)? Instrumental Variables: does mortality rise with the unemployment rate, using exposure to PNTR as an instrument? Note: this is not a welfare analysis of PNTR This paper examines the relationship between county-level mortality rates and a plausibly exogenous change in U.S. trade policy – U.S. granting of Permanent Normal Trade Relations (PNTR) to China in 2000 – that differentially exposed U.S. counties to increased competition from China

Preview of Results Mortality: Exposure to PNTR associated with higher mortality from “deaths of despair”, in particular suicide and accidental poisoning Implied impacts are strongest for whites, especially white males, and tail off as workers age Mechanisms: Exposure to PNTR associated with persistently higher unemployment, lower labor force participation and lower per capita personal income

Literature Business cycle, mass layoffs, plant closings g Mortality Cyclicality: Ruhm (2000, 2015), Stevens et al. (forthcoming) Layoffs: Jacobson et al. (1993), Sullivan and von Wachter (2009), Browning and Heinesen (2012) China/low-wage countries g U.S. labor market Imports: Bernard et al. (2006), Ebenstein et al. (2011), Autor et al. (2013), PNTR: Pierce and Schott (2016), Handley and Limao (2016), Feng, Li and Swenson (2016) Import competition g crime, public goods, health, marriage, fertility Dix-Carneiro et al. (2015), Feler and Senses (2015), McManus and Schaur (2015), Autor, Dorn and Hanson (2015)

Outline Data Mortality rates Trade policy DID empirical strategy and results 2SLS empirical strategy Robustness Conclusion

Data: County-Level Mortality Rates CDC microdata containing all U.S. death certificates filed between 1990 and 2013 Observe age, gender, race, county of residence, year of death and underlying cause of death Match year x county x gender x race x age bin death counts to NCI’s SEER population estimates to compute death rates Rates conventionally expressed per 100,000 population Two types of county-level death rates Crude: just divide deaths by population Age-adjusted: weighted average crude death rate across age categories, using the year 2000 overall population shares as weights for all counties; (baseline results use 5-year age bins)

Age-Adjusted Death Rates, 2000 Population-Weighted Averages Across Counties Source: CDC.

Distribution of All-Cause Death Rates Over Time Population-weighted averages across counties in year 2000 are Overall 858 Male 1047 Female 719 f_ar_all.emf Figures, section A.2

Outline Data DID empirical strategy and results 2SLS empirical strategy Robustness Conclusion

DID Empirical Strategy Focus on aggregate “deaths of despair” Suicide Accidental poisoning Alcohol-related liver disease (ARLD) Rationale: Highlighted in Case and Deaton (2015), etc. More likely to respond quickly to change in policy More easily observable (suicide and accidental poisoning) More likely to be accurately recorded on death certificate Concordance of death codes across time is straightforward First look at aggregate deaths of despair Then look at each underlying cause separately

“Post” Difference-in-Differences Specification c=county; t=year Death Ratect = q 1{Post-PNTR} * NTR Gapc + b Xct + g 1{Post-PNTR} * Xc + dc + dt + a + ect DID term: post x county exposure Time-varying county attributes (e.g., NTR Tariff Rate, MFA exposure) Post x time-invariant county attributes (e.g., Change in Chinese import tariffs, education attainment) County and year fixed effects Notes Sample period 1990-2013 Standard errors clustered by county Economic significance: move a county from the 25th to the 75th percentiles of the NTR gap distribution, i.e., q*8.3

County-Level Controls Policy Labor-weighted average U.S. NTR tariff Labor-weighted average exposure to end of MFA/ATC quotas Labor-weighted average exposure to 1997-2002 changes in Chinese import tariffs Labor weighted average exposure to 1996-2005 reduction in Chinese production subsidies County attributes 1990 county median household income Spurious change in healthcare? 1990 county share of population with no college education Spurious change in technology? 1990 county share of population that are veterans Return of Gulf-War veterans?

Baseline Results: Aggregate Deaths of Despair Higher exposure to PNTR associated with higher mortality rates from deaths of despair

Baseline Results: Aggregate Deaths of Despair Higher exposure to PNTR associated with higher mortality rates from deaths of despair Larger declines in Chinese production subsidies associated with lower mortality (greater export access?)

Baseline Results: Aggregate Deaths of Despair Higher exposure to PNTR associated with higher mortality rates from deaths of despair Larger declines in Chinese production subsidies associated with lower mortality (greater export access?) Counties with higher shares of veterans or citizens with less education experience greater mortality in the 2000s versus the 1990s

Baseline Results: Aggregate Deaths of Despair Higher exposure to PNTR associated with higher mortality rates from deaths of despair Higher exposure to PNTR associated with higher mortality rates from deaths of despair Larger declines in Chinese production subsidies associated with lower mortality (greater export access?) Counties with higher shares of veterans or citizens with less education experience greater mortality in the 2000s versus the 1990s Economic significance: interquartile shift in NTR gap distribution associated with a 6-10% increase in mortality rates versus 2000

Baseline Results: Aggregate Deaths of Despair Higher exposure to PNTR associated with higher mortality rates from deaths of despair Higher exposure to PNTR associated with higher mortality rates from deaths of despair Larger declines in Chinese production subsidies associated with lower mortality (greater export access?) Counties with higher shares of veterans or citizens with less education experience greater mortality in the 2000s versus the 1990s Economic significance: interquartile shift in NTR gap distribution associated with a 6-10% increase in mortality rates versus 2000

Aggregate Deaths of Despair: Economic Significance Implied Impact of an Interquartile Shift in Exposure to PNTR Implied impact of an interquartile shift in county explosure to PNTR is an increase in “deaths of despair” mortality of ~1.5 100,000, or ~7 percent of average rate across counties in 2000.

Aggregate Deaths of Despair by Race and Gender Implied Impact of an Interquartile Shift in Exposure to PNTR 9% increase vs 2000 13% increase vs 2000

Why Whites, White Males? Share of Males, Whites and White Males in Manufacturing Employment, 1999 Source: www.bls.gov.

Aggregate Deaths of Despair for Whites, by Age

Disaggregate results for suicide, poisoning and ARLD

Implied Impact Within Deaths of Despair Positive and statistically significant associations except for alcohol related liver disease

Implied Impact Within Deaths of Despair All Races, Genders 4% increase vs 2000 28% increase vs 2000

Implied Impact Within Deaths of Despair White Males and Females Suicide Accidental Poisoning ARLD 5% increase vs 2000 4% increase vs 2000 23% increase vs 2000 37% increase vs 2000 6% increase vs 2000

Prior Trends?

“Annual” Difference in Differences Specification c=county; z=commuting zone; t=year DID term for own county DID term for surrounding counties Time-varying county attributes Initial (time-invariant) county attributes County and year fixed effects

Prior Trends and Timing: Whites 95% Confidence Interval of Estimated DID Coefficients

Outline Data DID empirical strategy and results 2SLS empirical strategy Robustness Conclusion

Comparison with Other Estimates Large literature examining cyclicality of mortality rates Ruhm (2000) finds that a 1sd increase in state unemployment rate is associated with 2.7% increase in suicide rate Here, use PNTR as IV for unemployment rate to compare economic magnitudes

First Stage: PNTR and Labor Market Outcomes DID Post Specification An interquartile shift in exposure to PNTR is associated with 0.4 percent decline in employment 28 percent increase in the unemployment rate 2.7 percent decline in the labor force participation rate 0.5 percent decline in per capita personal income

First Stage: PNTR and Unemployment Rate Annual Panel Specification

NTR Gap as IV for Unemployment Rate 1sd increase in u-rate implies 16% increase in suicide

NTR Gap as IV for Unemployment Rate 1sd increase in u-rate implies 16% increase in suicide 1sd increase in u-rate implies 46% increase in accidental poisoning

NTR Gap as IV for Unemployment Rate 1sd increase in u-rate implies 16% increase in suicide 1sd increase in u-rate implies 46% increase in accidental poisoning Why Do We Find Stronger Impact than Ruhm?

Why Do We Find Stronger Impact that Ruhm? Source: Pierce and Schott (2012)

Outline Data Empirical strategy and results 2SLS empirical strategy Robustness and other causes of death Conclusion

Robustness Exercises 10% increase vs 2000 8% increase vs 2000

Other Causes of Death Baseline “Post” DID Specification Percent of Year 2000 Death Rate

Outline Data Empirical strategy and results 2SLS empirical strategy Robustness and other causes of death Conclusion

Conclusions We examine whether the rise in deaths of despair among middle-age whites is related to a shock to labor markets induced by trade liberalization We find that counties more exposed to import competition from China via the change in policy exhibit increases in both suicides and accidental poisonings, particularly among whites and white males Exposure is also associated with persistent increases in unemployment rates and decreases in labor force participation Next step: use firm-worker level data to examine the labor-market shock more closelyThese trends coincide with persistent increases in the unemployment rate and declines in employment, labor force and personal income

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