The Surprisingly Swift Decline of U.S. Manufacturing Employment

The Surprisingly Swift Decline of U.S. Manufacturing Employment

Justin R. Pierce Board of Governors of the Federal Reserve SystemPeter 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 U.S. Census Bureau, the Board of Governors or its research staff. All results have been reviewed to ensure that no confidential information is disclosed.

2

Post-War U.S. Manufacturing Employment

3

1214

1618

20E

mpl

oym

ent (

Mill

ion)

1948 1958 1968 1978 1988 1998 2008

NBER Recessions ShadedU.S. Manufacturing Employment


4

1214

1618

20E

mpl

oym

ent (

Mill

ion)

1948 1958 1968 1978 1988 1998 2008



5

1214

1618

20E

mpl

oym

ent (

Mill

ion)

1948 1958 1968 1978 1988 1998 2008


-2.9 mill over 3 years

1214

1618

20E

mpl

oym

ent (

Mill

ion)

1948 1958 1968 1978 1988 1998 2008



6

-2.9 mill over 3 years

Introduction

• The sharp decline in US manufacturing employment since 2001 is closely linked to a change in US trade policy: – China’s receipt of Permanent Normal Trade Relations in late 2000

• PNTR did not change actual tariff rates: Chinese imports were already eligible for low NTR rates typically reserved for WTO members– But for China, NTR required contentious annual renewals– Failure would increase tariffs to Smoot-Hawley levels

• The potential for large tariff increases likely discouraged:– US firms from openings plants in China– Chinese firms from making investments to export to US

• With PNTR, the possibility of future tariff hikes was eliminated

7

Before Continuing…

8

200

400

800

1600

Rea

l Val

ue A

dded

(Bill

ion)

10

12

14

16

18

20

Em

ploy

men

t (M

illio

n)

1948 1958 1968 1978 1988 1998 2008year

BLS Employment BEA Real Value Added

Employment vs Log Real Value AddedU.S. Manufacturing

…note that manufacturing real value added continues to rise at the historical pace

Outline

• US-China Trade Policy

• Data

• Baseline results

• Alternate explanations

• Additional results

• Conclusion

9

US NTR and Non-NTR Tariffs

• NTR = Normal Trade Relations– Synonym for Most Favored Nation (MFN)

• The US has two basic tariff schedules– NTR tariffs : for WTO members; generally low– Non-NTR tariffs : for non-market economies; generally

high; set by Smoot-Hawley (1930)

• So how does China fit into these categories?

10

US-China Trade Policy, 1980-2001

11

1980 (February)China was granted temporary NTR status by the US Congress

Temporary NTR requires annual re-approval by Congress

2000 (October)U.S. Congress grants

China PNTR, eliminating the risk that a failed vote might lead to a jump in

tariffs

2001 (December)China enters WTO

Annual renewals of MFN status were uncertain

http://query.nytimes.com/mem/archive/pdf?res=F40815FC3F5F12728DDDA80B94D9405B8084F1D3

Measuring the Policy Change

• Measure the effect of the policy as:– NTR Gap = Non-NTR Tariff – NTR Tariff

• Measures extent to which tariffs could increase prior to PNTR

• Varies across industries

• We can preview the results in two simple figures that use public data

12

Preview of Findings – EmploymentPublic NBER-CES Data

13

• High- and low-gap industries follow roughly parallel trends in two decades prior to PNTR

.8

.9

1

1.1

1.2

2001

=1

1981 1986 1991 1996 2001 2006

Below Median NTR Gap Above Median NTR Gap

NBER-CES Manufacturing Industry DatabaseU.S. Manufacturing Employment

Preview of Findings – EmploymentPublic NBER-CES Data

14

• High- and low-gap industries follow roughly parallel trends in two decades prior to PNTR

• After PNTR the series diverge with employment falling most sharply in the high-gap industries most affected by PNTR

• (Note: we use the gap as a continuous variable in our regression analysis.)

.8

.9

1

1.1

1.2

2001

=1

1981 1986 1991 1996 2001 2006

Below Median NTR Gap Above Median NTR Gap

NBER-CES Manufacturing Industry DatabaseU.S. Manufacturing Employment

Preview of Findings – TradePublic Census Trade Data

15

• Divergence is also evident in trade data

01

23

2001

=1

1991 1993 1995 1997 1999 2001 2003 2005 2007year

China: Below Mean China: Above Mean

U.S. Census Bureau Foreign Trade DataU.S. Imports Excluding Natural Resources


16


• Imports from China in the more-exposed products jump after PNTR

01

23

2001

=1

1991 1993 1995 1997 1999 2001 2003 2005 2007year

China: Below Mean China: Above Mean


17



• This trend is not present in imports from rest-of-world (ROW)

01

23

2001

=1

1991 1993 1995 1997 1999 2001 2003 2005 2007year

China: Below Mean ROW: Below MeanChina: Above Mean ROW: Above Mean



18



• This trend is not present in imports from rest-of-world (ROW)

• Find similar results for number of U.S. importers, Chinese exporters and importer-exporter pairs

01

23

2001

=1

1991 1993 1995 1997 1999 2001 2003 2005 2007year

China: Below Mean ROW: Below MeanChina: Above Mean ROW: Above Mean



Related Research

• Employment and trade liberalization– Lots of papers – Autor et al. (2012); Bloom et al. (2012)

• Investment under uncertainty– Lots of papers– Trade: Handley (2012); Handley and Limao (2012, 2013)

• “Jobless” recoveries– Manufacturing: Faberman (2012)– Overall: Jaimovich and Siu (2012)

• Supply-chain linkages– US manufacturing: Ellison, Glaeser and Kerr (2010)– Trade: Baldwin and Venables (2012)

19

Outline


• Data




• Conclusion

20

NTR Gaps

• NTR Gap = Non-NTR Tariff – NTR Tariff

• Compute for each HS8 product using the ad valorem equivalent NTR and non-NTR rates from Feenstra, Romalis and Schott (2003) available for 1989-2001

• The NTR Gap for industry i is the mean over the gaps of the HS8s in that industry

21

Distribution of 1999 NTR Gap

22

• The gap is large in economic terms

• Varies substantially across industries, allowing for identification of effect of PNTR

• 89 percent of the variation in the NTR gap across industries arises from variation in non-NTR rates, set in 1930

01

23

4D

ensi

ty

0 .2 .4 .6 .8

Distribution of 1999 NTR Gap

Mean: 0.32Std: 0.15

Census Data

• LBDxxxxxxxxxxxxxxxxxxxx

• CMxxxxxxxxxxxxxxxxxxxxx

• LFTTD

• Annual employment of all U.S. establishments, 1977-2009

• Employment + other attributes for all manufacturing establishments every five years, 1977(5)2007

• Transaction-level US import data: value, importer ID, foreign exporter ID

23

Outline


• Data




• Conclusion

24

Empirical Strategy

• We use a difference-in-differences strategy to examine the link between PNTR/WTO and U.S. manufacturing employment outcomes– 1st difference: industries with higher vs lower NTR Gaps– 2nd difference: outcomes after 2001 vs before

• PNTR coincides with the 2001 peak, so compare employment d years after 2001 with employment d years after the 1990 peak

25

Industry-Level OLS Diff-in-Diff Using the LBD(i=industry; t=NBER peak {1990,2001}; d=1:6 years after peak)

26

Cumulative percent change in industry i

employment d years after NBER

peak t={1981,1990,2001

}

DID TermInteraction of indicator variable for 2001 peak and continuous, time-invariant own-industry

NTR Gap

Industry and peak-year

fixed effects (control for cyclicality)

Industry attributes

• Separate regression for d=1:6 years after each peak

Basic Industry-Level RegressionsBold=statistically significant at 10% level

27

Percent Change in Industry Employment

Years After NBER Peak (LBD)

1 2 3 4 5 61{post-PNTR} x NTR Gapi -0.104 -0.187 -0.332 -0.387 -0.469 -0.482 0.058 0.082 0.105 0.114 0.149 0.147

ln(K/Lit) -0.058 -0.032 0.021 0.099 0.140 0.170 0.036 0.056 0.071 0.077 0.101 0.093

ln(S/Lit) -0.048 -0.110 -0.140 -0.131 -0.087 -0.108

0.046 0.059 0.075 0.087 0.096 0.111

Observations 652 652 652 652 652 652R2 0.67 0.70 0.70 0.70 0.66 0.66Fixed Effects i,t i,t i,t i,t i,t i,tEmployment Weighted Yes Yes Yes Yes Yes Yes

Implied Impact of PNTR -0.034 -0.060 -0.107 -0.125 -0.151 -0.156

0.019 0.026 0.034 0.037 0.048 0.047


28




ln(K/Lit) -0.058 -0.032 0.021 0.099 0.140 0.170 0.036 0.056 0.071 0.077 0.101 0.093

ln(S/Lit) -0.048 -0.110 -0.140 -0.131 -0.087 -0.108

0.046 0.059 0.075 0.087 0.096 0.111



0.019 0.026 0.034 0.037 0.048 0.047

Use LBD to examine outcomes 1:6 years after peak, e.g., compare 1981-87, 1990-96, and 2001-2007


29




ln(K/Lit) -0.058 -0.032 0.021 0.099 0.140 0.170 0.036 0.056 0.071 0.077 0.101 0.093

ln(S/Lit) -0.048 -0.110 -0.140 -0.131 -0.087 -0.108

0.046 0.059 0.075 0.087 0.096 0.111



0.019 0.026 0.034 0.037 0.048 0.047

• Industries with higher NTR gaps experience larger employment declines following PNTR, as expected


30




ln(K/Lit) -0.058 -0.032 0.021 0.099 0.140 0.170 0.036 0.056 0.071 0.077 0.101 0.093

ln(S/Lit) -0.048 -0.110 -0.140 -0.131 -0.087 -0.108

0.046 0.059 0.075 0.087 0.096 0.111



0.019 0.026 0.034 0.037 0.048 0.047

• Absolute magnitude of DID coefficient rises over time; i.e., relative losses are persistent


31




ln(K/Lit) -0.058 -0.032 0.021 0.099 0.140 0.170 0.036 0.056 0.071 0.077 0.101 0.093

ln(S/Lit) -0.048 -0.110 -0.140 -0.131 -0.087 -0.108

0.046 0.059 0.075 0.087 0.096 0.111



0.019 0.026 0.034 0.037 0.048 0.047

• Effect attenuated in high K/L industries, magnified in high S/L industries

• But these controls generally are not statistically significant


32




ln(K/Lit) -0.058 -0.032 0.021 0.099 0.140 0.170 0.036 0.056 0.071 0.077 0.101 0.093

ln(S/Lit) -0.048 -0.110 -0.140 -0.131 -0.087 -0.108

0.046 0.059 0.075 0.087 0.096 0.111



0.019 0.026 0.034 0.037 0.048 0.047

• Multiply DID coefficient by average NTR gap to assess implied impact of PNTR

• Post-2001 growth is 3.4 to 15.6 percentage points lower than post-1990 growth

Outline

• PNTR

• Data




• Conclusion

33

Alternate Explanations

• Alternate explanations must explain:

– Timing: employment declines and Chinese imports rise with PNTR in 2001

– Variation across industries: outcomes are larger for industries most affected by the policy change

• We consider a wide range of stories…

34


• Changes in Chinese Policy – Lower import tariffs– Elimination of export licensing requirements– Elimination of production subsides– Reduced barriers to foreign investment

• Union Resistance in the US

• Popped US tech bubble

• Rising Chinese competitiveness

• End of Textile and Clothing Quotas

35


• Changes in Chinese Policy – Lower import tariffs – Brandt et al. (2013) – Elimination of export licensing requirements – Bai et al. (2007) – Elimination of production subsides – Girma et al. (2007) – Reduced barriers to foreign investment – Nunn (2007)

• Union Resistance in the US – unionstats.org

• Popped US tech bubble – IT dummy; control for prior growth

• Rising Chinese competitiveness – capital and skill intensity

• End of Textile and Clothing Quotas – Khandelwal et al. (2013)

36

Correlation of 1999 Gap with Other Industry AttributesBold=statistically significant at 10% level

NTR Gap is:

Negatively correlated with K/L, S/L, change in Chinese subsidies, and US union membership

Positively correlated with contractibility, share of Chinese firms eligible for export licenses, MFA dummy, and advanced technology indicator

Dependent variable: 1999 NTR Gapln(K/L) -0.080 -0.060 0.009 0.011ln(S/L) -0.019 -0.037 0.019 0.022Nunn ‘s Contract Intensity 0.176 -0.030 0.035 0.050DChinese Import Tariffs (1996-05) 0.001 0.000 0.002 0.002DChinese Subsidy (1999-05) -10.760 -8.509 4.909 3.969Share of Chinese Firms Eligible to Export (1999) 0.330 0.256 0.066 0.0731{MFA Apparel} 0.235 0.178 0.029 0.025Union Membership -0.006 -0.004 0.001 0.0011{Advanced Technology Products} 0.036 0.011 0.014 0.0181{Anti-Dumping Filings, 2001-07} 0.002 0.031 0.019 0.019Prior Growth -0.042 -0.014 0.077 0.063NTR 0.080 -0.139 0.221 0.172Industries 326 326 326 326 326 326 326 326 326 326 326 326 326R-squared 0.21 0.00 0.07 0.00 0.02 0.09 0.11 0.13 0.01 0.00 0.00 0.00 0.39Covariate Mean 4.61 -1.30 0.52 -6.57 -0.0002 0.50 0.04 14.11 0.15 0.16 -0.04 0.04 Covariate Std Dev 0.82 0.40 0.22 6.63 0.0016 0.13 0.20 8.52 0.36 0.36 0.12 0.05 Notes: Table reports the results of industry-level OLS regressions summarizing the relationship between the 1999 NTR gap and noted industry attributes. Coefficient for constant is suppressed. See text for a discussion of these attributes and their sources.

37

Full Specification

• Where possible, we include all these covariates and their interactions with a post-PNTR dummy to allow for potential changes in relationships after 2001

• These interactions yield a very flexible specification

38

Now Includes1999 NTR Gap (as before)

&All other industry attributes

40

Percent Change in Industry Employment Years After NBER Peak (LBD) 1 2 3 4 5 61{post-PNTR} x NTR Gapi -0.128 -0.219 -0.362 -0.352 -0.395 -0.366 0.076 0.121 0.152 0.158 0.196 0.1851{post-PNTR} x Contract Intensityi 0.051 0.006 -0.021 0.035 -0.019 -0.059 0.049 0.065 0.080 0.092 0.118 0.1211{post-PNTR} x DChina Import Tariffsi -0.046 0.051 0.174 0.273 0.298 0.241 0.065 0.093 0.112 0.124 0.159 0.1721{post-PNTR} x DChina Licensingi 0.033 0.015 0.006 -0.105 -0.039 -0.030 0.091 0.139 0.173 0.190 0.235 0.2181{post-PNTR} x DChina Subsidiesi -2.019 -3.227 -2.023 -4.158 -9.861 -4.904 4.869 7.558 9.007 9.717 12.360 12.160Anti-Dumping Filingsi -0.015 -0.017 -0.023 0.016 0.048 0.052 0.014 0.021 0.025 0.027 0.037 0.0421{post-PNTR} x Anti-Dumping Filingsi -0.011 -0.016 -0.026 -0.049 -0.112 -0.113 0.018 0.027 0.032 0.034 0.047 0.0561{post-PNTR} x 1{Advanced Techi} -0.031 -0.044 -0.030 -0.021 -0.013 -0.045 0.024 0.033 0.038 0.041 0.051 0.0521{post-PNTR} x 1{MFA Apparel}i -0.007 0.069 0.115 0.066 0.081 0.074 0.039 0.041 0.043 0.037 0.046 0.052ln(K/Lit) -0.038 -0.011 0.031 0.079 0.068 0.100 0.034 0.050 0.059 0.067 0.083 0.0901{post-PNTR} x ln(K/Lit) -0.005 -0.002 -0.031 -0.041 -0.034 -0.026 0.011 0.014 0.016 0.018 0.022 0.028ln(S/Lit) -0.073 -0.132 -0.226 -0.244 -0.175 -0.219 0.039 0.057 0.074 0.080 0.095 0.1091{post-PNTR} x ln(S/Lit) -0.013 0.015 0.064 0.092 0.141 0.166 0.023 0.026 0.033 0.037 0.048 0.054Union Membershipit -0.106 -0.139 -0.498 -0.397 -0.430 -0.515 0.165 0.204 0.248 0.275 0.362 0.4191{post-PNTR} x Union Membershipit 0.012 -0.009 0.077 0.246 0.378 0.362 0.084 0.117 0.138 0.157 0.196 0.250Prior Growthit 0.112 0.092 0.290 0.354 0.429 0.279 0.096 0.123 0.176 0.202 0.263 0.2901{post-PNTR} x Prior Growthit -0.035 -0.023 -0.273 -0.450 -0.596 -0.598 0.124 0.162 0.210 0.254 0.310 0.372DNTRi -0.243 -0.240 0.126 0.199 -0.112 0.158 0.280 0.449 0.479 0.507 0.602 0.643Observations 652 652 652 652 652 652R2 0.70 0.72 0.73 0.74 0.71 0.70Fixed Effects i,t i,t i,t i,t i,t i,tEmployment Weighted Yes Yes Yes Yes Yes Yes

41

Percent Change in Industry Employment Years After NBER Peak (LBD) 1 2 3 4 5 61{post-PNTR} x NTR Gapi -0.128 -0.219 -0.362 -0.352 -0.395 -0.366 0.076 0.121 0.152 0.158 0.196 0.1851{post-PNTR} x Contract Intensityi 0.051 0.006 -0.021 0.035 -0.019 -0.059 0.049 0.065 0.080 0.092 0.118 0.1211{post-PNTR} x DChina Import Tariffsi -0.046 0.051 0.174 0.273 0.298 0.241 0.065 0.093 0.112 0.124 0.159 0.1721{post-PNTR} x DChina Licensingi 0.033 0.015 0.006 -0.105 -0.039 -0.030 0.091 0.139 0.173 0.190 0.235 0.2181{post-PNTR} x DChina Subsidiesi -2.019 -3.227 -2.023 -4.158 -9.861 -4.904 4.869 7.558 9.007 9.717 12.360 12.160Anti-Dumping Filingsi -0.015 -0.017 -0.023 0.016 0.048 0.052 0.014 0.021 0.025 0.027 0.037 0.0421{post-PNTR} x Anti-Dumping Filingsi -0.011 -0.016 -0.026 -0.049 -0.112 -0.113 0.018 0.027 0.032 0.034 0.047 0.0561{post-PNTR} x 1{Advanced Techi} -0.031 -0.044 -0.030 -0.021 -0.013 -0.045 0.024 0.033 0.038 0.041 0.051 0.0521{post-PNTR} x 1{MFA Apparel}i -0.007 0.069 0.115 0.066 0.081 0.074 0.039 0.041 0.043 0.037 0.046 0.052ln(K/Lit) -0.038 -0.011 0.031 0.079 0.068 0.100 0.034 0.050 0.059 0.067 0.083 0.0901{post-PNTR} x ln(K/Lit) -0.005 -0.002 -0.031 -0.041 -0.034 -0.026 0.011 0.014 0.016 0.018 0.022 0.028ln(S/Lit) -0.073 -0.132 -0.226 -0.244 -0.175 -0.219 0.039 0.057 0.074 0.080 0.095 0.1091{post-PNTR} x ln(S/Lit) -0.013 0.015 0.064 0.092 0.141 0.166 0.023 0.026 0.033 0.037 0.048 0.054Union Membershipit -0.106 -0.139 -0.498 -0.397 -0.430 -0.515 0.165 0.204 0.248 0.275 0.362 0.4191{post-PNTR} x Union Membershipit 0.012 -0.009 0.077 0.246 0.378 0.362 0.084 0.117 0.138 0.157 0.196 0.250Prior Growthit 0.112 0.092 0.290 0.354 0.429 0.279 0.096 0.123 0.176 0.202 0.263 0.2901{post-PNTR} x Prior Growthit -0.035 -0.023 -0.273 -0.450 -0.596 -0.598 0.124 0.162 0.210 0.254 0.310 0.372DNTRi -0.243 -0.240 0.126 0.199 -0.112 0.158 0.280 0.449 0.479 0.507 0.602 0.643Observations 652 652 652 652 652 652R2 0.70 0.72 0.73 0.74 0.71 0.70Fixed Effects i,t i,t i,t i,t i,t i,tEmployment Weighted Yes Yes Yes Yes Yes Yes

DID term remains negative and significant

Implied Impact of PNTR

42

Estimated impact of PNTR is reduced when controlling for alternate explanations but remains substantial

0-.1

-.2-.3

2002 2004 2006 2002 2004 2006

Baseline Baseline + Additional Covariates

Rel

ativ

e G

row

th (%

)

Note: Each panel displays implied impact plus 90% confidence interval.

By SpecificationImplied Impact of PNTR

Outline


• Data

• Baseline results & Alternate explanations

• Additional results– Other Countries– Other Outcomes– Margins of Adjustment– Plant-level– Supply-chain Exposure– Trade

• Conclusion52

Other Countries

• Our paper focuses on effects of a U.S. trade policy

• Now we compare employment outcomes in the U.S. to those in EU

• Useful test case because EU did not have the policy change that took place in U.S.– EU granted permanent NTR status to China in 1980, did not have

annual renewals

• We estimate relationship between NTR gap in EU and again in US using an alternative data source (UNIDO) and an alternate specification

53

54

Dependent Variable: ln(Empit) EU US1{year=1998} x NTR Gapi -0.019 -0.079 -0.148 -0.2851{year=1999} x NTR Gapi -0.010 -0.189 -0.120 -0.2381{year=2000} x NTR Gapi 0.007 -0.304 -0.112 -0.2241{year=2001} x NTR Gapi 0.032 -0.395 -0.112 -0.2221{year=2002} x NTR Gapi 0.015 -0.636 -0.115 -0.2351{year=2003} x NTR Gapi 0.041 -0.128 1{year=2004} x NTR Gapi 0.010 -1.057 -0.136 -0.2961{year=2005} x NTR Gapi -0.042 -1.078 -0.144 -0.334Observations 686 999R2 0.99 0.99Employment Weighted Yes YesFixed Effects i,t i,tNotes: Each column displays the results of an ISIC-industry (i) level OLS regression of the log of manufacturing employment on year (t) fixed effects, industry fixed effects and interactions of year fixed effects with the 1999 U.S. NTR gap. Coefficient estimates for all but the latter are suppressed. Data are from the UNIDO INDSTAT4 database (see text) for 1997 to 2005. U.S. data for 1993 are missing from this dataset. Industries for which data are not available in all years for a particular country are dropped. Regressions are weighted by 1997 employment. Robust standard errors are displayed below each coefficient. Coefficients in bold are statistically significant at the 10 percent level.

US versus EUEmployment Data from UNIDO; Bold indicates statistical significance

55



• U.S.• No effect of NTR gap

prior to PNTR

56




prior to PNTR• Negative and

significant after PNTR

57






• E.U.• No effect of NTR gap

on employment

58






• E.U.• No effect of NTR gap

on employment

• The disparity in outcomes provides further evidence against competing explanations: • technological change• aggregate shocks in

China

Outline


• Data



• Conclusion59

Examine Other Industry Outcomes Using CM

60

Now turn to CM

Only available in years ending in 2, 7 but a rich set of characteristics is available

Post-PNTR period is 1997-2007; pre-PNTR period is 1987-1997

Total Non-Prod Production Production Capital Capital SkillEmployment Workers Workers Hours Stock Intensity Intensity

1{post-PNTR} x NTR Gapi -0.606 -0.346 -0.728 -0.582 -0.475 0.379 0.3870.150 0.173 0.154 0.174 0.264 0.343 0.126

ln(K/Lit) 0.253 0.202 0.231 0.326 -0.447 -0.0970.091 0.093 0.096 0.130 0.202 0.041

ln(S/Lit) 0.061 -0.693 0.406 0.531 0.164 0.2300.176 0.201 0.184 0.201 0.379 0.481

Observations 652 652 652 652 652 652 652R2 0.78 0.73 0.78 0.58 0.65 0.50 0.70Fixed Effects i,t i,t i,t i,t i,t i,t i,tEmployment Weighted Yes Yes Yes Yes Yes Yes YesImplied Impact of PNTR -0.195 -0.112 -0.234 -0.187 -0.153 0.122 0.125

0.048 0.056 0.050 0.056 0.085 0.111 0.041

Percent Change Across CM Decades


61

Effect on employment is similar to that in primary specification



ln(K/Lit) 0.253 0.202 0.231 0.326 -0.447 -0.0970.091 0.093 0.096 0.130 0.202 0.041

ln(S/Lit) 0.061 -0.693 0.406 0.531 0.164 0.2300.176 0.201 0.184 0.201 0.379 0.481


0.048 0.056 0.050 0.056 0.085 0.111 0.041



62


Effect on production workers nearly twice as large as non-production workers



ln(K/Lit) 0.253 0.202 0.231 0.326 -0.447 -0.0970.091 0.093 0.096 0.130 0.202 0.041

ln(S/Lit) 0.061 -0.693 0.406 0.531 0.164 0.2300.176 0.201 0.184 0.201 0.379 0.481


0.048 0.056 0.050 0.056 0.085 0.111 0.041



63


Effect on production workers nearly twice as large as non-production workers

Capital intensity increases, but effect not statistically significant

Skill intensity (share of non-production workers) does increase

Trade-induced skill-biased technical change?



ln(K/Lit) 0.253 0.202 0.231 0.326 -0.447 -0.0970.091 0.093 0.096 0.130 0.202 0.041

ln(S/Lit) 0.061 -0.693 0.406 0.531 0.164 0.2300.176 0.201 0.184 0.201 0.379 0.481


0.048 0.056 0.050 0.056 0.085 0.111 0.041


Outline


• Data



• Conclusion64

Margins of Adjustment

• Job Destruction (JD)– PC: plant contraction at continuing firms– PD: plant death at continuing firms– FD: firm death

• Job Creation (JC)– PE: plant expansion at continuing firms– PB: plant birth at continuing firms– FB: firm birth

65

-.15

-.1

-.05

0

Cha

nge

from

Pea

k Y

ear

2001-2 2001-3 2001-4 2001-5 2001-6 2001-7

By Job Creation vs DestructionDecomposition of Implied Impact of PNTR

Job Desctruction (PC+PD+FD) Job Creation (PE+PB+FB)

Implied Impact of PNTR

66

Contribution of exaggerated job destruction

Contribution of anemic job creation

• JC contributes 17 to 41 percent across 2001-2007

• Relates to research by Faberman (2012), who notes changes in manufacturing JC and JD rates after 2001

Outline


• Data



• Conclusion67

Plant-Level OLS Diff-in-Diff Using the CM

68

Non-Total Production Production Production Capital Capital Skill Plant

Employment Workers Workers Hours Stock Intensity Intensity Death1{post-PNTR} x NTR Gappt -0.748 -0.493 -0.959 -0.843 -0.785 -0.057 0.152 0.288

0.118 0.190 0.134 0.141 0.235 0.336 0.140 0.045ln(K/L)pt 0.093 0.134 0.080 0.076 -1.406 -0.017 0.033

0.021 0.025 0.027 0.027 0.036 0.020 0.0071{post-PNTR} x ln(K/L)pt 0.030 -0.009 0.030 0.003 -0.205 -0.001 -0.048

0.015 0.019 0.019 0.020 0.022 0.014 0.005ln(S/L)pt -0.014 -1.236 0.412 0.336 -0.068 0.018 0.039

0.028 0.040 0.043 0.046 0.045 0.062 0.0121{post-PNTR} x ln(S/L)pt 0.128 -0.139 0.218 0.229 0.206 -0.102 -0.031

0.033 0.044 0.051 0.050 0.042 0.059 0.010ln(Age)pt -0.069 -0.120 -0.054 -0.110 -0.088 0.127 -0.125 0.028

0.176 0.185 0.219 0.192 0.201 0.233 0.167 0.0531{post-PNTR} x ln(Age)pt 0.474 0.304 0.484 0.383 0.474 0.135 -0.370 -0.007

0.337 0.372 0.423 0.388 0.391 0.480 0.313 0.100ln(TFP)pt -0.072 -0.080 -0.053 -0.052 -0.059 0.114 0.007 0.004

0.021 0.026 0.022 0.024 0.023 0.038 0.020 0.0051{post-PNTR} x ln(TFP)pt 0.021 0.039 0.012 -0.003 0.023 -0.004 0.004 -0.006

0.012 0.022 0.011 0.011 0.013 0.021 0.007 0.004Observations 140,735 140,735 140,735 140,735 140,735 140,735 140,735 272,183R2 0.76 0.80 0.75 0.73 0.84 0.51 0.58 0.79Fixed Effects p,t p,t p,t p,t p,t p,t p,t p,tEmployment Weighted Yes Yes Yes Yes Yes Yes Yes YesImplied Impact of PNTR -0.239 -0.158 -0.307 -0.270 -0.251 -0.018 0.049 0.092

0.038 0.061 0.043 0.045 0.075 0.108 0.045 0.015

Log Change Across CM Decades (Continuing Plants Only)

• Examine effect of PNTR at plant-level– See if industry results are driven by death– Control for heterogeneity within industries

• Similar specification, but now include plant attributes as controls – TFP, age, capital and skill intensity as well as their interaction

with post-PNTR indicator

• Use plant-level NTR gap– Weighted average gap across the products a plant produces

• Focus on continuing plants


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0.118 0.190 0.134 0.141 0.235 0.336 0.140 0.045ln(K/L)pt 0.093 0.134 0.080 0.076 -1.406 -0.017 0.033


0.015 0.019 0.019 0.020 0.022 0.014 0.005ln(S/L)pt -0.014 -1.236 0.412 0.336 -0.068 0.018 0.039


0.033 0.044 0.051 0.050 0.042 0.059 0.010ln(Age)pt -0.069 -0.120 -0.054 -0.110 -0.088 0.127 -0.125 0.028


0.337 0.372 0.423 0.388 0.391 0.480 0.313 0.100ln(TFP)pt -0.072 -0.080 -0.053 -0.052 -0.059 0.114 0.007 0.004



0.038 0.061 0.043 0.045 0.075 0.108 0.045 0.015


• Effect on total employment is similar to the effect found in the industry specification


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0.118 0.190 0.134 0.141 0.235 0.336 0.140 0.045ln(K/L)pt 0.093 0.134 0.080 0.076 -1.406 -0.017 0.033


0.015 0.019 0.019 0.020 0.022 0.014 0.005ln(S/L)pt -0.014 -1.236 0.412 0.336 -0.068 0.018 0.039


0.033 0.044 0.051 0.050 0.042 0.059 0.010ln(Age)pt -0.069 -0.120 -0.054 -0.110 -0.088 0.127 -0.125 0.028


0.337 0.372 0.423 0.388 0.391 0.480 0.313 0.100ln(TFP)pt -0.072 -0.080 -0.053 -0.052 -0.059 0.114 0.007 0.004



0.038 0.061 0.043 0.045 0.075 0.108 0.045 0.015


• Effect on production workers is again about twice as large as that for non-production workers

• Production hours decline at a similar magnitude to production employment

• I.e., the decline in employment is not due to making remaining workers work more


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Non-Total Production Production Production Plant

Employment Workers Workers Hours Death1{post-PNTR} x NTR Gappt -0.748 -0.493 -0.959 -0.843 0.288

0.118 0.190 0.134 0.141 0.045ln(K/L)pt 0.093 0.134 0.080 0.076 0.033

0.021 0.025 0.027 0.027 0.0071{post-PNTR} x ln(K/L)pt 0.030 -0.009 0.030 0.003 -0.048

0.015 0.019 0.019 0.020 0.005ln(S/L)pt -0.014 -1.236 0.412 0.336 0.039

0.028 0.040 0.043 0.046 0.0121{post-PNTR} x ln(S/L)pt 0.128 -0.139 0.218 0.229 -0.031

0.033 0.044 0.051 0.050 0.010ln(Age)pt -0.069 -0.120 -0.054 -0.110 0.028

0.176 0.185 0.219 0.192 0.0531{post-PNTR} x ln(Age)pt 0.474 0.304 0.484 0.383 -0.007

0.337 0.372 0.423 0.388 0.100ln(TFP)pt -0.072 -0.080 -0.053 -0.052 0.004

0.021 0.026 0.022 0.024 0.0051{post-PNTR} x ln(TFP)pt 0.021 0.039 0.012 -0.003 -0.006

0.012 0.022 0.011 0.011 0.004Observations 140,735 140,735 140,735 140,735 272,183R2 0.76 0.80 0.75 0.73 0.79Fixed Effects p,t p,t p,t p,t p,tEmployment Weighted Yes Yes Yes Yes YesImplied Impact of PNTR -0.239 -0.158 -0.307 -0.270 0.092

0.038 0.061 0.043 0.045 0.015


• Plants with the average NTR gap are 9.2 percent more likely to exit

Outline


• Data


• Additional results– Other Countries– Other Outcomes– Margins of Adjustment– Plant-level– Supply-chain exposure– Trade

• Conclusion72

Supply chain exposure

• For each plant p we compute upstream and downstream NTR gaps using data from the 1997 US input-output table

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Plant p

UpstreamWeighted average NTR gap of industries j that supply the industries

produced by p, using the values from the IO total requirements table as

weights

DownstreamWeighted average NTR gap of industries k that make use of industries produced by p, using

values from the IO total requirements table as

weights


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• Upstream and downstream effects are positive and significant for plant death

• Could reflect supply chain co-location (Baldwin and Venables 2013)

• In total, own-, up- and downstream NTR gaps associated with a relative increase in the probability of death of 15.4 percent

Employment PlantGrowth Death

1{post-PNTR} x NTR Gappt -0.701 0.1490.147 0.057

1{post-PNTR} x NTR Upstream Gappt -0.556 0.5700.353 0.183

1{post-PNTR} x NTR Downstream Gappt 0.200 0.3930.226 0.091

ln(K/L)pt 0.097 0.0330.021 0.008

1{post-PNTR} x ln(K/L)pt 0.024 -0.0480.015 0.005

ln(S/L)pt -0.014 0.0360.028 0.012

1{post-PNTR} x ln(S/L)pt 0.125 -0.0260.034 0.010

ln(Age)pt -0.071 0.0240.177 0.053

1{post-PNTR} x ln(Age)pt 0.466 -0.0170.339 0.100

ln(TFP)pt -0.073 0.0040.022 0.005

1{post-PNTR} x ln(TFP)pt 0.022 -0.0060.013 0.004

Observations 140,735 272,183R2 0.76 0.79Fixed Effects p,t p,tEmployment Weighted Yes Yes

Across CM Decades

Outline


• Data



• Conclusion75

Effect of PNTR on U.S. Imports from China(c=country; h=HS product)

• Trade data not available till 1990s

• So, amend DID specification and estimate a triple difference:– 1st difference: products with higher vs lower NTR Gaps– 2nd difference: imports from China versus other trading partners– 3rd difference: 1997-2001 vs. 2001-2005

• Examine import value, number of US importers, number of Chinese exporters, and number of importer-exporter pairs

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Triple difference estimator

Country and product fixed

effects

Growth rate of value or number

of importer, exporters, or

pairs from country c

Interactions of difference variables

Effect of PNTR on U.S. Imports from China(LFTTD; Bold=statistically significant at 10% level)

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• Post-PNTR US imports from China increase in same goods where domestic employment is lost

• Growth in number of trading firms is consistent with greater incentives to invest in trading relationships as uncertainty declines

Value

Number of U.S.

Importers

Number of Chinese Exporters

Number of Importer-Exporer Pairs

1{post-PNTR} x 1{c=China} x NTR Gapi 0.427 0.381 0.361 0.3340.104 0.086 0.088 0.088

Observations 341,239 341,239 341,239 341,239R2 0.06 0.07 0.07 0.07Robust SE Yes Yes Yes YesFixed Effects h,c h,c h,c h,c

Normalized Change2001-2005 versus 1997-2001

Outline

• PNTR

• Data




• Conclusion

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Conclusions

• Strong link between US manufacturing job loss and PNTR

• U.S. imports from China increase in same industries where employment declines occur, along with number of U.S. importers, Chinese exporters and importer-exporter pairs

• Results are robust to inclusion of proxies for wide array of alternate explanations, as well as alternate specifications

• Our measure of the effect of the policy change (NTR Gap) has no relationship with manufacturing employment in the EU, which was not subject to policy change

• Effects of PNTR experienced through both elevated job destruction and suppressed job creation, and effect is somewhat magnified through supply chain linkages

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Thanks

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The Surprisingly Swift Decline of U.S. Manufacturing Employment

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