U.S. Job Flows and the China Shock
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1 U.S. Job Flows and the China Shock Appendix For Online Publication Brian Asquith, Sanjana Goswami, David Neumark, and Antonio Rodriguez-Lopez November 2017 A Supporting Figures and Tables Millions % 51% Births Expansions Births Expansions (a) Job creation decomposition (b) Job creation shares (average) Millions % 59% Deaths Contractions Deaths Contractions (c) Job destruction decomposition (d) Job destruction shares (average) Figure A.1: Employment creation and destruction in the manufacturing industry (three-year windows) 1
2 Millions % 63% Births Expansions Births Expansions (a) Job creation decomposition (b) Job creation shares (average) Millions % 68% Deaths Contractions Deaths Contractions (c) Job destruction decomposition (d) Job destruction shares (average) Figure A.2: Employment creation and destruction in the non-manufacturing industry (three-year windows) 2
3 Table A.1: Job Flows Decomposition in All Industries (in Thousands) Employment at initial year 102, , , , , , , , ,499 Employment at final year 111, , , , , , , , ,779 Change in employment Due to births 16,887 19,498 18,377 17,571 16,814 19,176 24,060 21,893 18,758 Due to deaths -8,953-9,261-10,699-11,067-11,618-12,716-12,989-14,223-16,854 Due to expansions 8,331 9,366 11,658 13,472 14,404 14,688 14,610 13,565 13,151 Due to contractions -6,995-6,896-7,739-7,338-7,417-7,184-8,347-9,946-11,775 Net changes Net extensive margin 7,933 10,237 7,678 6,504 5,196 6,460 11,071 7,670 1,904 Net intensive margin 1,336 2,471 3,919 6,134 6,987 7,505 6,263 3,620 1,376 Net employment change 9,270 12,708 11,598 12,638 12,183 13,965 17,334 11,289 3, Employment at initial year 141, , , , , , , , ,508 Employment at final year 139, , , , , , , , ,794 Change in employment Due to births 15,350 16,789 16,909 15,952 15,053 16,058 19,464 22,178 19,159 Due to deaths -17,571-17,061-14,161-12,987-12,189-21,996-23,762-26,870-19,155 Due to expansions 13,126 13,028 11,906 10,925 10,183 8,190 7,418 7,416 7,544 Due to contractions -13,532-11,041-9,559-8,040-7,124-5,618-4,256-3,924-3,262 Net changes Net extensive margin -2, ,748 2,966 2,864-5,938-4,298-4,691 3 Net intensive margin ,986 2,347 2,885 3,060 2,572 3,162 3,492 4,282 Net employment change -2,627 1,713 5,095 5,851 5,924-3,365-1,135-1,199 4,285 Notes: This table reports employment levels and three-year job flows for the overall U.S. economy. It uses NETS data from the universe of U.S. establishments with two or more employees in at least one year during the period.
4 Table A.2: Predicted U.S. Net Employment Changes due to the China Shock with NETS Data and CBP Data (in Thousands) Import exposure PNTR status Specification Exposure type Sector NETS CBP NETS CBP : Table 1, cols. 2 and 6 Direct Manufacturing ,496-4,165 Tables 4 and 5, col. 2 Combined I Total ,567-2,484-7,495 Tables 4 and 5, col. 5 Combined II Total ,918-2,825-10,200 Tables 6 and 7, col. 1 Local Exposed -2,128-2,078-3,896-3,153 Tables 6 and 7, col. 2 Nonexposed tradable ,103 Tables 6 and 7, col. 3 Nonexposed nontradable 2,225 2,331 2,792 1, : Table 1, cols. 5 and 7 Direct Manufacturing ,707-4,819 Tables 4 and 5, col. 3 Combined I Total ,549-3,693-8,345 Tables 4 and 5, col. 6 Combined II Total ,009-5,261-13,200 Tables A.5 and A.6, col. 1 Local Exposed -2,515-2,758-6,620-5,282 Tables A.5 and A.6, col. 2 Nonexposed tradable ,269-1,736 Tables A.5 and A.6, col. 3 Nonexposed nontradable 2,222 2,684 4,693 4,145 Notes: For the specifications described in the first column, and using either Chinese import exposure or China s PNTR status as the China-shock variable, this table compares predicted net employment changes with NETS data vs. predicted net employment changes with CBP data. Negative values indicate that the China-shock variable reduces employment. Equations (6) and (7) show general formulas to calculate predicted employment changes from Tables 1, 4, and 5, and equations (16) and (17) show the general formulas to calculate predicted employment changes from Tables 6, 7, A.5, and A.6. The numbers in bold denote predicted changes corresponding to statistically significant coefficients in the corresponding tables. 4
5 Table A.3: IV Estimation of the Effects of Chinese Import Exposure on U.S. Employment with Higher-Order Upstream and Downstream Linkages Across Industries Combined measure I (direct+upstream) Combined measure II (direct+upstream+downstream) (1) (2) (3) (4) (5) (6) Net employment growth -0.35** -0.42*** -0.47*** -0.31** -0.36*** -0.38*** (0.15) (0.15) (0.16) (0.14) (0.13) (0.11) Job flows Births (0.09) (0.07) (0.09) (0.08) (0.06) (0.07) Deaths 0.33*** 0.40*** 0.47*** 0.33*** 0.38*** 0.42*** (0.10) (0.10) (0.12) (0.09) (0.09) (0.10) Expansions (0.03) (0.02) (0.02) (0.05) (0.03) (0.04) Contractions 0.12** 0.11* 0.08* 0.11** 0.12** 0.08** (0.06) (0.06) (0.05) (0.06) (0.06) (0.04) Net extensive margin -0.25** -0.33*** -0.43*** -0.24*** -0.29*** -0.36*** (0.12) (0.11) (0.15) (0.09) (0.08) (0.10) Net intensive margin (0.07) (0.08) (0.05) (0.08) (0.07) (0.05) Job creation * 0.12 (0.10) (0.07) (0.09) (0.10) (0.07) (0.08) Job destruction 0.44*** 0.52*** 0.55*** 0.44*** 0.50*** 0.50*** (0.14) (0.14) (0.13) (0.13) (0.12) (0.10) CBP data: Net employment growth -0.94*** -1.31*** -1.34*** -0.85*** -1.14*** -1.21*** (0.25) (0.35) (0.39) (0.22) (0.30) (0.36) Sector period controls Yes Yes Yes Yes Yes Yes Manf. sector controls Yes No No Yes No No Include No No Yes No No Yes Observations Notes: This table reports results for the effects of direct + upstream, and direct + upstream + downstream higher-order Chinese import exposure on annualized log-employment changes and job flows. All regressions include 479 industries, two subperiods ( and either or ), and are weighted by 1992 employment. The net growth regression with CBP data is weighted by 1992 CBP employment, and is reported for the purpose of comparison with the net growth regression with NETS data. Standard errors (in parentheses) are clustered at the three-digit industry level. The coefficients are statistically significant at the *10%, **5%, or ***1% level. 5
6 Table A.4: OLS Estimation of the Effects of China s PNTR Status on U.S. Employment with Higher-Order Upstream and Downstream Linkages Across Industries Combined measure I (direct+upstream) Combined measure II (direct+upstream+downstream) (1) (2) (3) (4) (5) (6) Net employment growth ** ** (0.14) (0.12) (0.17) (0.12) (0.10) (0.14) Job flows Births (0.14) (0.12) (0.16) (0.11) (0.10) (0.12) Deaths 0.24*** 0.28*** 0.44*** 0.17*** 0.22*** 0.39*** (0.05) (0.05) (0.10) (0.06) (0.05) (0.09) Expansions (0.03) (0.03) (0.03) (0.04) (0.03) (0.03) Contractions (0.04) (0.03) (0.03) (0.04) (0.03) (0.03) Net extensive margin ** *** (0.14) (0.12) (0.18) (0.11) (0.10) (0.14) Net intensive margin (0.05) (0.04) (0.04) (0.05) (0.04) (0.04) Job creation (0.14) (0.12) (0.15) (0.11) (0.10) (0.11) Job destruction 0.26*** 0.30*** 0.45*** 0.18** 0.24*** 0.39*** (0.07) (0.06) (0.10) (0.07) (0.06) (0.09) CBP data: Net employment growth -0.52*** -0.70*** -0.90*** -0.43*** -0.66*** -0.97*** (0.11) (0.11) (0.16) (0.10) (0.11) (0.16) Sector period controls Yes Yes Yes Yes Yes Yes Manf. sector controls Yes No No Yes No No Include No No Yes No No Yes Observations Notes: This table reports results for the effects of direct + upstream, and direct + upstream + downstream higher-order exposure to China s PNTR status on annualized log-employment changes and job flows. All regressions include 479 industries, two subperiods ( and either or ), and are weighted by 1992 employment. The net growth regression with CBP data is weighted by 1992 CBP employment, and is reported for the purpose of comparison with the net growth regression with NETS data. Standard errors (in parentheses) are clustered at the three-digit industry level. The coefficients are statistically significant at the *10%, **5%, or ***1% level. 6
7 Table A.5: IV Estimation of the Effects of Chinese Import Exposure on U.S. Commuting Zones by Sectoral Employment ( ) Chinese Import Exposure Bartik Shock Exposed Nonexposed Nonexposed Exposed Nonexposed Nonexposed tradable nontradable tradable nontradable (Employment/Population) -1.12*** * 0.19*** -0.04** 0.73*** (0.22) (0.09) (0.51) (0.04) (0.02) (0.11) Job flows Births * 1.89*** 0.22*** 0.03*** 1.36*** (0.12) (0.07) (0.55) (0.03) (0.01) (0.11) Deaths 1.05*** -0.17* 1.16** 0.17*** 0.05*** 0.84*** (0.18) (0.09) (0.51) (0.03) (0.01) (0.07) Expansions ** 0.46* 0.15*** 0.02** 0.37*** (0.08) (0.06) (0.27) (0.02) (0.01) (0.05) Contractions 0.26*** -0.15* *** 0.15*** (0.06) (0.08) (0.18) (0.01) (0.01) (0.04) 7 Net extensive margin -0.86*** ** -0.02** 0.52*** (0.20) (0.06) (0.46) (0.03) (0.01) (0.09) Net intensive margin -0.25*** *** *** (0.08) (0.05) (0.19) (0.02) (0.01) (0.04) Job creation ** 2.35*** 0.37*** 0.05*** 1.72*** (0.18) (0.12) (0.69) (0.05) (0.02) (0.14) Job destruction 1.31*** -0.32** 1.37** 0.18*** 0.09*** 0.99*** (0.18) (0.15) (0.64) (0.03) (0.02) (0.10) CBP data: (Employment/Population) -1.42*** * 0.15*** *** (0.23) (0.11) (0.74) (0.02) (0.01) (0.09) Notes: Using subperiods , , and import exposure as the China shock, this table reports ˆβ k, ˆγ k, ˆβ F k, and ˆγ F k, for k {1(exposed), 2(nonexposed tradable), 3(nonexposed nontradable)}, from the estimation of specifications (14) and (15). All regressions include 4,332 observations (722 commuting zones, three sectors, and two subperiods) and the following controls: sectortime fixed effects, the commuting zone s manufacturing share (at the beginning of each period) interacted with sector dummies, and regional Census division dummies interacted with sector dummies. Regressions are weighted by 1992 commuting-zone population. The net regression with CBP data is reported for the purpose of comparison with the net regression with NETS data. Standard errors (in parentheses) are clustered at the commuting-zone level. The coefficients are statistically significant at the *10%, **5%, or ***1% level.
8 Table A.6: OLS Estimation of the Effects of China s PNTR Status on U.S. Commuting Zones by Sectoral Employment ( ) PNTR Status Bartik Shock Exposed Nonexposed Nonexposed Exposed Nonexposed Nonexposed tradable nontradable tradable nontradable (Employment/Population) -0.73*** -0.14*** 0.52** 0.14*** -0.04** 0.77*** (0.08) (0.05) (0.21) (0.04) (0.02) (0.11) Job flows Births -0.13*** *** 0.21*** 0.03*** 1.40*** (0.04) (0.02) (0.16) (0.03) (0.01) (0.12) Deaths 0.47*** 0.10*** 0.40** 0.21*** 0.06*** 0.87*** (0.06) (0.02) (0.16) (0.03) (0.01) (0.08) Expansions -0.13*** *** 0.14*** 0.02* 0.39*** (0.03) (0.02) (0.12) (0.02) (0.01) (0.05) Contractions * *** 0.16*** (0.03) (0.02) (0.05) (0.01) (0.01) (0.05) 8 Net extensive margin -0.60*** -0.11*** *** 0.53*** (0.06) (0.03) (0.16) (0.02) (0.01) (0.09) Net intensive margin -0.13*** ** 0.13*** *** (0.04) (0.03) (0.11) (0.02) (0.02) (0.04) Job creation -0.25*** *** 0.36*** 0.05*** 1.80*** (0.07) (0.03) (0.22) (0.05) (0.02) (0.14) Job destruction 0.47*** 0.11*** 0.49*** 0.22*** 0.09*** 1.03*** (0.07) (0.03) (0.18) (0.04) (0.02) (0.11) CBP data: (Employment/Population) -0.56*** -0.18*** 0.44* 0.15*** *** (0.06) (0.03) (0.26) (0.02) (0.01) (0.09) Notes: Using subperiods , , and PNTR status as the China shock, this table reports ˆβ k, ˆγ k, ˆβF k, and ˆγ F k, for k {1(exposed), 2(nonexposed tradable), 3(nonexposed nontradable)}, from the estimation of specifications (14) and (15). All regressions include 4,332 observations (722 commuting zones, three sectors, and two subperiods) and the following controls: sectortime fixed effects, the commuting zone s manufacturing share (at the beginning of each period) interacted with sector dummies, and regional Census division dummies interacted with sector dummies. Regressions are weighted by 1992 commuting-zone population. The net regression with CBP data is reported for the purpose of comparison with the net regression with NETS data. Standard errors (in parentheses) are clustered at the commuting-zone level. The coefficients are statistically significant at the *10%, **5%, or ***1% level.
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