1. 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

2. 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.

3. 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

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

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

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

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

8. 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

9. 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

10. 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)

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

12. 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)

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

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

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

16. 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

17. “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
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

18. 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 changes in Chinese import tariffs
Labor weighted average exposure to 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?

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

20. 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?)

21. 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

22. 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

23. 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

24. 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 ~ ,000, or ~7 percent of average rate across counties in 2000.

25. 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

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

27. Aggregate Deaths of Despair for Whites, by Age

28. Disaggregate results for suicide, poisoning and ARLD

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

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

31. 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

32. Prior Trends?

33. “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

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

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

36. 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

37. 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

38. First Stage: PNTR and Unemployment Rate Annual Panel Specification

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

40. 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

41. 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?

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

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

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

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

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

47. 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

48. Thanks!