.

August 2018

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Ottawa, Ontario
K1N 5V5613-233-8891
csls@csls.ca

CENTRE FOR
THE STUDY
OF LIVING
STANDARDS

Rising Import Competition in Canada and its
Employment Effect by Gender: Evidence
from the 'China Shock'

Myeongwan Kim
Prepared for Global Affairs Canada

CSLS Research Report 2018-3

1

Rising Import Competition in Canada and its Employment Effectby Gender: Evidence from the 'China Shock'

Abstract
It is well known that there has been a secular decline in the manufacturing share of total
employment in Canada, with the decline accelerating after 2000. Among the factors that
contributed to that trend, this report focuses on rising Chinese import competition in Canada,
which also accelerated after 2000. A trade-induced job loss in manufacturing is estimated bygender. We estimate that a trade-induced job loss amounted to 56.8 thousand for males and 36.1
thousand for females over the 2001-2011 period. However, females had a larger loss in relative
terms since they experienced a much smaller decline in their total manufacturing employment
over this period. We also find that the labour reallocation in response to a trade shock isimportant in offsetting the negative employment effect. However, the reallocation was lesssuccessful for females.

i

Rising Import Competition in Canada and its Employment Effectby Gender: Evidence from the 'China Shock'
Table of Contents
Abstract ............................................................................................................................................ i
Executive Summary ................................................................................................................... iv
List of Tables ................................................................................................................................ vii
List of Charts.................................................................................................................................. ix
I. Introduction ..................................................................................................................................1
II. Conceptual Framework ...............................................................................................................4
A. Decomposing the Effects of Import Shocks ............................................................................4
B. Defining Occupational Groups ................................................................................................6
1. Skill-level .........................................................................................................................6
2. Skill-type ..........................................................................................................................7
III. Employment and Occupation-specific Import Penetration in Canada .......................................7
A. Employment patterns by gender ..............................................................................................7
1. Employment patterns across skill levels ..........................................................................8
2. Employment patterns across skill types ...........................................................................9
C. Occupation-specific trade exposure.......................................................................................11
IV. Empirical Strategy and Data sources. ......................................................................................14
A. Measure of occupation-specific import exposure ................................................................14
B. Identification strategy ............................................................................................................15
C. Data Sources ..........................................................................................................................17
V. Empirical Analysis 1: Occupation-Level Direct Effect ............................................................18
A. Model.....................................................................................................................................18
B. Summary Statistics ................................................................................................................19
C. Results ...................................................................................................................................22
1. Regression results ..........................................................................................................22
2. Implied employment effects ..........................................................................................30
VI. Empirical Analysis 2: Indirect Effects Operating within Local Labour Markets ....................37
A. Model.....................................................................................................................................37
B. Summary Statistics ................................................................................................................40
C. Results ...................................................................................................................................43
1. Regression results ..........................................................................................................43
2. Implied employment effects ..........................................................................................50ii

VII. Conclusion ..............................................................................................................................54
References ......................................................................................................................................55
Appendix: Additional Tables and Charts .......................................................................................57iii

Rising Import Competition in Canada and its Employment Effectby Gender: Evidence from the 'China Shock'Executive Summary
It is well known that there has been a secular decline in the manufacturing share of total
employment in Canada. From 1991 to 2015, the manufacturing share of total Canadian
employment fell from 14.7 per cent to 9.5 per cent, with the decline accelerating after 2000.
Among the factors that contributed to that trend, this report focuses on rising Chinese importcompetition in Canada, which also accelerated after 2000.
Recent literature focusing on trade with China find evidence that manufacturing
employment in developed countries was negatively affected by rising Chinese importcompetition (e.g. Acemoglu, Autor, Dorn, Hanson, and Price, 2016, Balsvik, Jensen, andSlavanes, 2015; Murray, 2017). However, the previous literature tends to focus on the overall
employment effect within import-competing sectors (i.e. manufacturing sectors). However, it isimportant to study how the loss and gain are distributed among workers.
By constructing an occupation-specific trade exposure measure, we focus on how
occupation-level characteristics interact with import shocks over time. In particular, we classify
four-digit occupations in the National Occupation Classification (NOC) according to their skill
level (high, mid, and low) and skill type (management, professional, technical/paraprofessional,
other services, and production), respectively. We assess potential gender differences in theemployment effect of an import shock within each skill level and skill type.
Skill level and skill types are two distinct dimensions characterizing a given occupation.
Skill level is associated with the amount of education or training required to enter and performthe main duties of an occupation while skill type is the type of work performed in an occupation(not the same as industrial categorization as it is not the type of economic activity carried out byan establishment). Therefore, analyzing the effect of a trade shock in the two dimensions
separately would allow one to draw various policy implications.

Empirical Approach
We estimate differential employment effects across distinct occupational groups based on
the two following samples: occupations within manufacturing in Canada to estimate the direct
effect of rising Chinese import competition; and occupations in both manufacturing and nonmanufacturing in Census Metropolitan Areas and Census Agglomerations (CMAs/CAs) acrossCanada to account for labour reallocation and demand effects operating within local labour
markets.
An instrumental variables strategy is employed to deal with potential endogeneity ofCanadian trade exposure. Following Autor, Dorn, and Hanson (2013) and Acemoglu et al. (2016),
we exploit the fact that during 1991-2011, the growth in Chinese imports were mostly stemmediv

from factors internal to China such as urbanization, opening to foreign investment, and accession
to the WTO. To capture the variation in Chinese import penetration driven by China's expanding
exporting capacity, we instrument for changes in Chinese import to Canada using the changes inimports in eight other advanced economies.

Results
1. Direct effect of trade with China
Our main finding is that, during the period in which Chinese import penetration rosesignificantly (i.e. 2001-2011), a trade-induced job loss in manufacturing amounted to 36.1
thousand for females and 56.8 thousand for males. Females suffered a larger job loss in relative
terms. Rising Chinese import penetration accounts for 21.3 per cent of the total decline in female
employment in manufacturing (169.3 thousand). For males, China accounts for 16.8 per cent of
their total manufacturing employment (337.5 thousand).
When analyzed by skill level, we find that a trade-induced job loss at the aggregate levelis largely driven by low-skilled occupations. We find no statistical evidence that high- and midskilled were negatively affected by China for both genders. However, we find evidence of tradeinduced job loss for low-skilled occupations. Importantly, gender-difference in the trade-induced
job loss was evident here. The trade-induced job loss for low-skilled occupations was equallydistributed between male and female although the female share in the total low-skilledemployment is much smaller in manufacturing. Low-skilled occupations had a loss of 42.4
thousand for females and a loss of 42.9 thousand for males. The loss accounts for 31.9 per centof the total decline in low-skilled jobs of women (132.9 thousand) and 21.3 per cent of the total
decline in low-skilled jobs of men (201.1 thousand). Therefore, in relative terms, females had alarger job loss than males did.
We also analyze the impact by skill type. During the 2001-2011 period, rising Chinese
import competition had statistically significant effects on the employment of production
occupations for both gender. Again, females suffered as many job losses as males did despite amuch smaller female share in the total production employment in manufacturing.
Production - a loss of 32.3 thousand jobs for females and 32.7 thousand for males (28.7
per cent of the total decline in jobs of women in production and 16.8 per cent of the total
decline in jobs of men in production)

We find statistical evidence that females also experienced a substantial job loss in the following
skill types while we found no evidence for males:Technical/paraprofessional - a loss of 3.6 thousand for females (78.3 per cent of the total
decline)

Other services - a loss of 15.4 thousand jobs for females (35.2 per cent of the total
decline)v

In summary, despite a smaller female share in the total manufacturing employment acrossskill groups, females had a job loss comparable to the loss for males. We find that thisphenomenon is due to the following two factors: 1. a greater sensitivity of female employment torising import penetration; 2. a larger increase in import penetration for females due to theconcentration of female employment in highly exposed sectors.
2. Indirect effects of labour reallocation and demand spillovers
By exploiting variations in local employment rates and local trade exposure across 122
CMAs/CAs in Canada, we also assess the net effect of labour reallocation and demand effects
operating within localities. We find that the labour reallocation effect is important in offsetting
the negative direct effects but the degree of reallocation within local labour markets varies acrossgender in some cases.
For
females
workers,thelabourreallocation
toproduction
andtrades/construction/transportation occupations in unaffected sectors appears to be fully inhibitedby the negative local demand effect. However, the labour reallocation to these occupations in
unaffected sectors was quite successful for males, mitigating the job loss occurred in affected
sectors (i.e. manufacturing). As a result, the total job loss in these two groups was much larger
for females in both absolute and relative terms.

vi

Rising Import Competition in Canada and its Employment Effectby Gender: Evidence from the 'China Shock'
List of Tables
Table 1: Employment share in total employment by skill level, Manufacturing, Male, 1991-2011,
Canada .............................................................................................................................................8
Table 2: Employment share in total employment by skill level, Manufacturing, Feale, 1991-2011,
Canada .............................................................................................................................................9
Table 3: Employment share in total employment by skill type, Manufacturing, Male, 1991-2011,
Canada ...........................................................................................................................................10
Table 4: Employment share in total employment by skill type, Manufacturing, Female, 19912011, Canada .................................................................................................................................10
Table 5: Annualized percentage point change in Occupation-Specific Chinese Import Penetration
Ratio and Annual per cent change in employment for Selected 3-digit NOC-S 2006, Male,
Manufacturing, 2001-2011 ...........................................................................................................12
Table 6: Annualized percentage point change in Occupation-Specific Chinese Import Penetration
Ratio and Annual per cent change in employment for Selected 3-digit NOC-S 2006, Feale,
Manufacturing, 2001-2011 ...........................................................................................................13
Table 7: Occupation-Level Changes in Employment and Chinese Import Penetration Ratio,
Manufacturing Industries, Canada ................................................................................................21
Table 8: Effect of Chinese Import Penetration on Log Employment in 4-digit occupations in
Manufacturing Industries, Male, Canada: OLS and 2SLS Estimates ............................................24
Table 8-1: Effect of Chinese Import Penetration on Log Employment in 4-digit occupations in
Manufacturing Industries, Female, Canada: OLS and 2SLS Estimates .......................................25
Table 9: Effect of Chinese Import Penetration on Log Employment in 4-digit occupations in
Manufacturing Industries by Skill-Level, Male, Canada: 2SLS Estimates ..................................26
Table 9-1: Effect of Chinese Import Penetration on Log Employment in 4-digit occupations in
Manufacturing Industries by Skill-Level, Female, Canada: OLS and 2SLS Estimates ...............27
Table 10: Effect of Chinese Import Penetration on Log Employment in 4-digit occupations in
Manufacturing Industries by Skill-Type, Male, Canada: 2SLS Estimates ...................................28
Table 10-1: Effect of Chinese Import Penetration on Log Employment in 4-digit occupations in
Manufacturing Industries by Skill-Type, Female, Canada: 2SLS Estimates ................................29
Table 11: Implied Employment Changes Induced by Changes in Chinese Import Penetration,
thousand, by Skill level and Skill type, Manufacturing sectors, Male Canada ............................34
Table 11-1: Implied Employment Changes Induced by Changes in Chinese Import Penetration,
thousand, by Skill level and Skill type, Manufacturing sectors, Female Canada .........................35
Table 12: 2001 Employment level (thousand), share in three-digit NAICS manufacturing sectors,
annual % pt change in import penetration at three-digit NAICS industry level over 2001-2011,
male and female, Canada ..............................................................................................................36
Table 13: Summary Statistics on Changes in Employment Rates and in Chinese Import
Penetration across Local Labour Markets, Male, All Industries, 1991-2011, % point .................41
Table 13-1: Summary Statistics on Changes in Employment Rates and in Chinese Import
Penetration across Local Labour Markets, Female, All Industries, 1991-2011, % point . ............42vii

Table 14: Effect of Import Penetration on Employment in Canadian Local Labour Markets, All
Occupations, All Industries, 1991-2011 stacked model: 2SLS Estimates .....................................43
Table 15: Effect of Import Penetration on Canadian Local Labour Markets, By Skill Level, Male,
1991-2011, stacked model: 2SLS Estimates .................................................................................46
Table 15-1: Effect of Import Penetration on Canadian Local Labour Markets, By Skill Level,
Female, 1991-2011, stacked model: 2SLS Estimates ...................................................................47
Table 16: Effect of Import Penetration on Canadian Local Labour Markets, By Skill Type, Male,
1991-2011, stacked model: 2SLS Estimates .................................................................................48
Table 16-1: Effect of Import Penetration on Canadian Local Labour Markets, By Skill Type,
Female, 1991-2011, stacked model: 2SLS Estimates ...................................................................49
Table 17: Implied Employment Changes Induced by Changes in Chinese Import Penetration,
thousand, Male, All Industries, Canada ........................................................................................52
Table 17-1: Implied Employment Changes Induced by Changes in Chinese Import Penetration,
thousand, Female, All Industries, Canada ....................................................................................53

List of Appendix Tables
Table A1: Occupation group classification, skill level and skill type ...........................................57
Table A2: Occupation-Level Changes in Employment and Chinese Import Penetration Ratio, by
Skill-Level, Male, Manufacturing Industries, 1991-2011 by sub-period, Canada .......................59
Table A2-1: Occupation-Level Changes in Employment and Chinese Import Penetration Ratio,
by Skill-Level, Female, Manufacturing Industries, 1991-2011 by sub-period, Canada ...............60
Table A3: Occupation-Level Changes in Employment and Chinese Import Penetration Ratio, by
Skill-Type, Male, Manufacturing Industries, 1991-2011 by sub-period, Canada ........................61
Table A3-1: Occupation-Level Changes in Employment and Chinese Import Penetration Ratio,
by Skill-Type, Female, Manufacturing Industries, 1991-2011 by sub-period, Canada ................62viii

Rising Import Competition in Canada and its Employment Effects by
Gender: Evidence from the 'China Shock'
List of Charts
Chart 1: Import penetration ratio for Canada from China and Manufacturing Share of Total
Employment, 1992-2015..................................................................................................................2
Chart 2: Occupation-specific import exposure to China: Other advanced economies vs. Canada,
1991-2001 and 2001-2011 .............................................................................................................16

List of Appendix Charts
Chart A1: Annualized employment growth and annual change in import penetration ratio, 3-digit
occupations, Male, Manufacturing, Canada, 2001-2011 ...............................................................63
Chart A2: Annualized employment growth and annual change in import penetration ratio, 3-digit
occupations, Female, Manufacturing, Canada, 2001-2011............................................................63ix

Rising Import Competition in Canada and its Employment Effects by
Gender: Evidence from the 'China Shock' 1
I.

Introduction

It is well known that there has been a secular decline in the manufacturing share of thetotal employment in Canada. From 1991 to 2015, the manufacturing share of the total Canadian
employment fell from 14.7 per cent to 9.5 per cent, with the decline accelerating after 2000. In
light of the falling manufacturing share in total employment, researchers have paid attention torising Chinese exports, which also accelerated after 2000.
Chart 1 shows the manufacturing share in the total Canadian employment along with the
Chinese import penetration ratio in Canada. We see that the manufacturing share in total
employment recovers and stabilizes during the 1991-2001 period. In the post 2001 period,
however, the negative relationship between the two variables is evident. Consequently, thecausal relationship between the two has been studied extensively in the literature. The post 2001
period is associated with increasing trade between developing and developed economies. Theory
suggests trade could have negative effects on employment and wage for unskilled workers indeveloped economies. However, the consensus in the literature in the early 2000 seems to
support the argument that trade does not lead to adverse distributional effects.2 Recent literature
focusing on trade with China argues that it does (e.g. Acemoglu, Autor, Dorn, Hanson, and Price,
2016, Balsvik, Jensen, and Slavanes, 2015; Murray, 2017).
However, limitation of the previous literature on trade with China is that it often focuseson the overall employment effect within import-competing sectors (i.e. manufacturing sectors).
However, it is important to study how the loss and gain are distributed among workers. Kim(2018a) find that the distributional effect of rising Chinese import penetration is evident in bothskill level and skill type dimensions. He finds that rising Chinese import penetration hurt aparticular skill group disproportionately more in manufacturing. In this report, we study whether
the distribution effect is also evidence in the gender dimension.
We analyze differential employment effects by gender in two distinct dimensions ofindividual occupation's characteristics: skill type and skill level. Skill level is associated with theamount of education or training required to perform the main duties of an occupation while skill
type is the type of economic activity performed in an occupation (not the same as industrial
categorization which is about the type of economic activity carried out by an establishment).
Recent studies find that skill-level and skill-type are important characteristics in distinguishingthe impact of trade exposure (e.g. Becker, Ekholm, and Muendler, 2013, Ebenstein, Harrison,
1

This report was written by CSLS economist Myeongwan Kim under the supervision of CSLS Executive Director
Andrew Sharpe for Global Affairs Canada. The Centre for the Study of Living Standards would like to thank Global
Affairs Canada for financial support for this research. The author thanks Bert Waslander, Alexander Murray at
Finance Canada , and Aaron Sydor at Global Affairs Canada for comments. An earlier version of the report waspresented at the annual meeting of the Canadian Economic Association held in Montreal, June 1-3, 2018. Email:daniel.kim@csls.ca.
2
See Autor, Dorn, and Hanson (2016) for a comprehensive review on this literature.

1

McMillan, and Phillips, 2014, Hummels, Jørgensen, Munch, and Xiang, 2014, and Hakkala andHuttunen, 2016). Therefore, analyzing the employment effect of a trade shock in the twodimensions separately would allow one to draw various policy implications.

10

18

9

16

8

14

7

12

6

10

5

8

4

6

3
2

4

1

2

0

0
1992

1995

1998

2001

2004

2007

2010

Manufacturing share of total
employment, %Import penetration, %Chart 1: Import penetration ratio for Canada from China and Manufacturing
Share of Total Employment, 1992-2015

2013

Import Penetration, Manufacturing (left axis)
Manufacturing employment/working age population (right axis)

Source: Statistics Canada, Labour Force Survey (CANSIM Table 282-0001), CANSIM Table 304-0014, andInnovation, Science and Economic Development Canada, Trade Data Online.

Moreover, skill could be as important as industry experience in terms of readjustment inresponse to an import shock. A particular skill may be more easily employable in other(unaffected) sectors offsetting a potential negative employment effect of import shocks. On theother hand, there could be a skill not easily employable in other sectors prolonging
unemployment spell for affected workers. For example, Kim (2018a) finds that the labour
reallocation was less successful in low-skilled occupations when analyzed by skill level and in
production occupations when analyzed by skill type. In this report, we examine whether there isa significant asymmetry in the degree of labour reallocation between men and women withineach skill level and type. An analysis in this regard would have important policy implications interms of how to distribute compensation and re-training opportunities among those who lose
from international trades.
By constructing occupation-specific trade exposure following Ebenstein et al. (2014), we
capture potential employment effects by focusing on how occupation-level characteristics with
import shocks over time. In this report, we classify four-digit occupations in National
Occupation Classification (NOC) according to their skill level (high, mid, and low) and skill type(management,
professional,
technical/paraprofessional,
otherservices,
trades/construction/transportation, and production), respectively.
2The empirical approach taken in this report is largely based on Acemoglu et al. (2016),
Autor et al. (2013), and Murray (2017). Although they primarily focus on industry-level
employment effects of the China shock, their conceptual framework and the associated empiricalapproach are applicable to an occupation-level analysis. Following the work cited above, we use
an instrumental variable approach to estimate the causal impact of Chinese import penetration on
Canadian employment using four-digit occupations in NOC as the unit of analysis.3 We firstestimate the direct effect of Chinese import penetration on employment for male and female byskill group in manufacturing industries. Then, we take into account indirect effects of labour
reallocation and demand effects operating at the occupational level within local labour markets
across Canada.
Our main finding is that, during the period in which Chinese import penetration rosesignificantly (i.e. 2001-2011), a trade-induced job loss amounted to 36.1 thousand for females
and 56.8 thousand for males. Note that females experienced a much smaller decline in their
manufacturing employment than males did during this period. This implies that females suffereda larger job loss in relative terms. Rising Chinese import penetration accounts for 21.3 per centof the total decline in female employment in manufacturing. For males, China accounts for 16.8
per cent of their total manufacturing employment.
When analyzed by skill level, we find that a trade-induced job loss at the aggregate levelis largely driven by low-skilled occupations. We find no statistical evidence that high- and midskilled were negatively affected by China for both genders. However, we find evidence of tradeinduced job loss for low-skilled occupations. Importantly, gender-difference in the trade-induced
job loss was evident here. The trade-induced job loss was equally distributed between male andfemale despite the fact that the female share is much smaller in the total low-skilled employment
in manufacturing. Low-skilled occupations had a loss of 42.4 thousand for females and a loss of
42.9 thousand for males. The loss accounts for 31.9 per cent of the total decline in low-skilledjobs of women and 21.3 per cent of the total decline in low-skilled jobs of men. Hence, in
relative terms, females had a larger job loss than males did.
We also analyze the impact of Chinese import penetration in skill type dimension. During
the 2001-2011 period, rising Chinese import competition had statistically significant effects on
the employment of production occupations for both genders but females suffered a larger job loss
than males in relative terms. A trade-induced job loss for production occupations is estimated to
be 32.3 thousand and 32.7 thousand for females and males respectively. Again, this is surprisingsince the female share in the total production employment in manufacturing is much smaller. In
relative terms, Chinese import penetration can explain 28.7 per cent of the total decline in jobs offemales in production and 16.8 per cent of the total decline in jobs of males in production.

3

Following Autor et al. (2013) and Acemoglu et al. (2016), we exploit the fact that during 1991-2011, the growth inChinese imports were mostly stemmed from factors internal to China such as urbanization, rising competitiveness ofChinese manufacturing industries, and accession to the WTO. To capture the variation in Chinese import penetration
driven by China's expanding exporting capacity, we instrument for changes in Chinese import to Canada using thechanges in imports in eight other advanced economies.

3

We find statistical evidence that females also experienced a job loss in the following skill
types: Technical/paraprofessional - a loss of 3.6 thousand (78.3 per cent of the total decline);
Other services - a loss of 15.4 thousand jobs (35.2 per cent of the total decline) . We found nostatistical evidence that males in these occupations were affected by rising Chinese importpenetration.
We also find that the degree of labour reallocation within local labour markets varies
across the two genders. For females, the reallocation to production andtrades/construction/transportation occupations in unaffected sectors appears to be fully inhibitedby negative local demand effects. However, the labour reallocation to these occupations in
unaffected sectors was quite successful for males, mitigating the job loss occurred in affected
sectors (i.e. manufacturing). As a result, the total job loss in these two groups was much larger
for females in both absolute and relative terms.
We would like to emphasize, however, that the employment effect is a quite narrowlydefined criteria to assess the overall consequences of trade with China. Policymakers should take
into account a wide scope of the impact to evaluate the overall welfare implication of trade.
The remainder of the report is structured as follows. In Section II, we briefly introduce a
conceptual framework to motivate our empirical strategies. We also define skill levels and skill
types to group four-digit occupations in NOC by skill. In Section III, we summarize theemployment structure in manufacturing and the degree of import competition faced by each
occupation in Canadian manufacturing sectors. In Section IV, we describe the construction of an
occupation-specific import exposure variable along with our data sources. Section V and VI
describes the two empirical approaches and their results. Section VII concludes.

II.

Conceptual Framework
A. Decomposing the Effect of Import Shocks

In this section, we outline the conceptual framework that motivates our empiricalapproach in this report. Following Acemoglu et al. (2013), we decompose the aggregate
employment effect of an increase in Chinese import penetration as follows:

Aggregate employment effect = Direct effect on exposed occupations+ Aggregate reallocation effects+ Aggregate demand effects.
+ Indirect impact on occupations in linked industries

4The direct effect is the change in employment in occupations in sectors whose outputs
compete with Chinese imports. The reallocation effect captures the potential offsetting
employment effect of absorption (in other sectors) of factors of production released fromcontracting industries. The aggregate demand effect is associated with the impact of Keynesiantype multipliers arising from change in consumption and investment at local or national level.
Lastly, negative employment effects would be found in workers employed in industries linked toan affected industry through the input-output matrix. Using industry-level data, Murray (2017)
found that I-O linkage did not have a substantial impact of the measured employment effect inCanada. In this report, we do not estimate the effect through this channel.
The direct effect is captured in occupation-level regressions that estimate the marginal
effect of a change in import penetration on employment in occupations within manufacturing. It
is difficult to estimate the two indirect effects at the national level without a structure in ourmodel. Hence, we take a local labour market as the unit of analysis to estimate the relative effectof the two indirect effects.
Local labour markets are treated as sub-economies subject to differential import shocks
arising from the initial occupational employment structure. We define a local labour market as a
Census Metropolitan Area (CMA) or Census Agglomeration (CA) and assess the employment
impact of import shocks operating within a local labour market in Canada.4 We decompose thetotal employment effect in a local labour market as follows:

Local employment effect = Direct effect on exposed occupations+ Local reallocation effects+ Local demand effects.
+ Local impact on occupations in linked industries

It should be noted that the approach only captures the reallocation and demand effects
operating within a local labour market. It does not capture an adjustment determined in thenational and international equilibrium. If the extent of labour mobility across labour markets islarge, our estimates would underestimate the positive reallocation effect in response to the China
shock. Similarly, only the components of the demand effect operating at the local level would be
captured in our estimates since the national components would be the same across all local
labour markets. Hence, we acknowledge that local labour market is an appropriate unit ofanalysis only if a transmission of shocks across regions is small in Canada.

4

We use 122 CMAs/CAs available across all three census years (1991, 2001 and 2011) as our sample. In 2011,
those 122 CMAs/CAs accounted for 80 per cent of the total Canadian population.

5

B. Defining Occupational Groups
The primary objective of this report is to quantify the effect of Chinese importpenetration on employment by skill group. In our sample, we have 494 four-digit occupations
defined in the National Occupation Classification system (NOC). Therefore, it would be moremeaningful and convenient to aggregate the 494 occupations into some broader groups. However,such broader groups must be chosen carefully such that they represent important dimensions ofoccupation characteristics relevant for analyzing the impact of Chinese import shock.5
In this study, we classify 4-digit occupations by two criteria following a variant of NOC
developed jointly by Statistics Canada and Human Resources and Skills Development Canada(HRSDC). Occupations are classified according to either skill-level and skill-type. See Appendix
Table A1 for details.
1. Skill-level
Skill level is associated with the amount of education and training required to enter andperform the main duties of an occupation. Along with education and training, the experience
required for entry, and the complexity and responsibilities typical of an occupation are also
considered to determine skill level. Requirements for individual occupations may overlap
between the skill levels. For example, some occupations can be entered with either a university
degree or a college diploma. In this case, skill level is determined by considering several factors.
These factors include the requirements most generally demanded by employers, complexity ofoverall responsibilities and knowledge requirements, and further training and specialization
obtained on the job. In the variant of NOC, occupations are classified into 4 skill levels: skill
level A, skill level B, skill level C, and skill level D.
We define high-skilled group to include occupations in skill-level A. Mid-skilled group isdefined to include skill-level B. Lastly, we define low-skilled group to include both skill-level C
and D.6As a result, high-skilled group represents occupations that require at least Bachelor's
degree to enter and perform the tasks. Mid-skilled group represents occupations that usuallyrequire college-level education, apprenticeship training, or occupation-specific on-the-job
training. Occupations in the low-skilled group require secondary school education or shortoccupation-specific training, or no formal education (but require only on-the-job training).

5Note that the cross-sectional unit in our framework is still 4-digit occupation. It is important to analyze trade
shocks in general equilibrium but it requires researchers to empirically map trade shocks into a small number ofaggregate outcomes. With a limited number of observations at aggregate level, it would be tricky to isolate the effectof shocks due to confounding factors. Hence, we estimate the direct effect of trade shocks using individual 4-digit
occupations as the unit of analysis.
6
For occupations in skill level C, workers are usually required to have secondary school and/or occupation-specifictraining. For skill level D, only on-the-job training is usually required.

6

2. Skill-type
Skill type represents the type of work performed on the job. Note that although some skill
types tend to be associated with a particular industry, industry and occupation are two distinct
variables which can be cross-tabulated to provide detailed information on employment. Industrial
categorization is determined by the kind of economic activity carried out by an establishment(factory, mine, farm, store, etc.) while occupational categorization is determined by the kind of
economic activity carried out by an individual worker.7 An establishment can employ workers
performing a completely different type of skill. In other words, the nature of the factory, businessor service in which the worker is employed does not determine the classification of his or her
occupation, except to the extent that it allows the nature of the tasks to be more clearly defined.
The occupational categories are chosen to distinguish different dimensions of task
content of jobs that are relevant for analyzing the effects of increased importing. According to avariant of NOC developed jointly by Statistics Canada and HRSDC, the 2-digit occupations are
re-classified into 10 broader groups. However, due to the limited number of observations in eachgroup established by Statistics Canada and HRSDC, we further aggregate the 10 groups into 6
broader groups: 1. management; 2. professional; 3. technical and paraprofessional; 4. otherservices; 5. trade/construction/transportation; and 6. production.
It is important to note that a given skill level is not necessarily correlated with a specificskill type. In our classification, the high-skilled group (skill level A) is equally distributed acrossmanagement and professional rather than concentrated on one specific group. Also, mid-skilled(skill level B) and low-skilled (skill level C and D) groups are readily found across the following
three different skill types: technical/paraprofessional; other services;trades/construction/transportation; and production. Hence, the classifications by skill type and byskill level represent two distinct dimensions of a given occupation.

III.

Employment and Occupation-specific Import Penetration in
CanadaA. Employment patterns by gender
In this section, we discuss the employment structure of Canadian manufacturing. We
describe how employment is distributed across skill levels and skill types. We discuss theemployment distribution both within each gender and across the two genders. It is well known
that men account for a majority of manufacturing employment. However, it would be
informative to examine the breakdown of the employment by skill to identify the skill groups inwhich female employment is relatively more important as well as any within-gendercharacteristics in the employment structure across different skill groups.
7

However, some occupations are found almost solely within one particular industry. For example, mining or
automobile assembly occupations are found only within their respective industrial sectors. During the original
research and development of the NOC, it was realized that in many industries, occupational mobility is determined
more by internal job ladders than by functional specialization. In consequence, some unit groups include
occupations in a particular skill level within an industry..

7

1. Employment patterns across skill levels

Table 1 and 2 report the share of employment by skill level. For both genders, low-skilledoccupations account for the largest share in manufacturing. For males, roughly half of the total
manufacturing employment is attributed to low-skilled occupations. For females, low-skilledoccupations account for more than half of their manufacturing employment (62 per cent on
average).
During the period in which Chinese import penetration rose substantially (i.e. 2001-2011),
both high- and mid-skilled share of the total employment increased for each gender. In otherwords, low-skilled share declined. For males, the share of low-skilled occupations in their total
manufacturing employment declined from 48.8 per cent to 45.5 per cent over this period.
Females experienced a larger decline: from 64.9 per cent to 59.3 per cent. This is in contrast to
the previous decade (1991-2001) when low-skilled share increased while both high- and midskilled occupations declined slightly in their employment share.
The redistribution of employment from low-skilled to higher-skilled occupations could be
the result of many factors. Most notable is the skill-biased technological change which tends toincrease the demand for higher skills while decreasing the demand for low skills. However, it
could also be the result of increasing penetration of Chinese low-tech manufactured goods. In thefollowing empirical analysis, we quantify the role of Chinese import penetration in explaining
the redistribution of employment.

Table 1: Employment share in total employment by skill level, Manufacturing, Male, 1991-2011, Canada
Panel A: Employment / Total male employment (%)
Mid-skilled

Low-skilled

1991

High-skilled
16.6

35.7

47.7

2001

15.5

35.6

48.8

2011

17.3

37.2
45.5
Panel B: Employment / Aggregate (male+female) employment (%)

Total

High-skilled

Mid-skilled

Low-skilled

1991

71.1

77.8

75.3

63.5

2001

71.0

78.6

77.9

64.8

2011
72.4
76.9
78.4
Source: The 1991 and 2001 Censuses and the 2011 National Household Survey.

8

66.8

Table 2: Employment share in total employment by skill level, Manufacturing, Female, 1991-2011, Canada
Panel A: Employment / Total female employment (%)
High-skilled

Mid-skilled

Low-skilled

1991

10.8

26.7

62.5

2001

10.4

24.8

64.9

2011

13.8

26.9

59.3

Panel B: Employment / Aggregate (male+female) employment (%)
Total

High-skilled

Mid-skilled

Low-skilled

1991

28.9

22.2

24.7

36.5

2001

29.0

21.4

22.1

35.2

2011
27.6
23.1
21.6
Source: The 1991 and 2001 Censuses and the 2011 National Household Survey.

33.2

Panel B in Table 1 and 2 presents the share of each gender in the aggregate
manufacturing employment by skill level. First, the manufacturing employment is dominated bymales. They account for over 70 per cent of the total manufacturing employment. The male shareof the total manufacturing employment in Canada is higher for all three skill levels. Among thethree skill levels, the female share is the largest in low-skilled occupations. The female share in
low-skilled occupations stands at roughly 35 per cent, compared to 22 to 24 per cent share inhigh- and mid-skilled occupations.
It is interesting to note that the gender distribution of the manufacturing employment is
not static across time. During the 2001-2011 period, the female share in the aggregate
employment in high-skilled occupations increased while the female share in the aggregate lowand mid-skilled occupations decreased.
2. Employment patterns across skill types
The gender difference in the employment structure is more evident in the skill type
dimension (see Panel A in Table 3 and 4). A majority of the female employment in
manufacturing is in other services and in production while males have the employment that is
relatively more dispersed across the six skill types. It is interesting to observe that, for bothgenders, the share of production occupations in their manufacturing employment declined overthe 2001- 2011 period while the share of the remaining five skill types increased.
Panel B in Table 3 and 4 reports the gender share of the aggregate manufacturing
employment in Canada. Not surprisingly, over 90 per cent of the total manufacturing
employment in trades/construction/transportation is explained by males. Such pattern remained
quite stable over the 1991-2011 period. A similar pattern is also observed for occupations intechnical/paraprofessional.

9There are two skill groups in which females were becoming more important in terms of
employment. Roughly 80 per cent of the total management employment is accounted for bymales. However, the female share in management had increased over the 1991-2011 period.
Over the 1991-2011 period, the female share had increased by 5.1 percentage points: 17.2 percent to 22.3 per cent. The manufacturing employment in professional is somewhat equallydistributed between male and female relative to the other skill types. Nevertheless, the female
share in the total professional employment had increased by 5.7 percentage points during the
1991-2011 period.

Table 3: Employment share in total employment by skill type, Manufacturing, Male, 1991-2011, Canada

Management

Panel A: Employment / Total male employment (%)
Trades &Technical &OtherConstruction &Professional
Paraprofessional
services
Transportation

Production

1991

11.3

2.5

9.0

16.3

28.3

32.6

2001

9.8

1.3

10.7

10.3

27.2

40.6

2011

10.4

1.7

12.6

11.4

28.6

35.3

Management

Panel B: Employment / Aggregate (male+female) employment (%)
Trades &Technical &OtherConstruction &Professional
Paraprofessional services
Transportation

Production

1991

82.8

53.7

77.2

44.6

95.7

68.3

2001

79.9

49.5

77.1

44.6

94.2

67.7

2011

77.7

48.0

77.0

47.1

94.6

70.1

Source: The 1991 and 2001 Censuses and the 2011 National Household Survey.

Table 4: Employment share in total employment by skill type, Manufacturing, Female, 1991-2011, Canada

Management

Panel A: Employment / Total female employment (%)
Trades &Technical &OtherConstruction &Professional
Paraprofessional
services
Transportation

Production

1991

5.4

4.9

6.1

46.3

2.9

34.4

2001

6.1

3.4

7.8

31.4

4.1

47.3

2011

7.8

4.8

9.9

33.7

4.3

39.6

Management

Panel B: Employment / Aggregate (male+female) employment (%)
Trades &Technical &OtherConstruction &Professional
Paraprofessional services
Transportation

Production

1991

17.2

46.3

22.8

55.4

4.3

31.7

2001

20.1

50.5

22.9

55.5

5.8

32.3

2011

22.3

52.0

23.0

52.9

5.4

29.9

Source: The 1991 and 2001 Censuses and the 2011 National Household Survey.

10

In contrast, the female share in production employment declined over the 2001-2011
period, the period associated with a large increase in Chinese import penetration. Other services
is the only skill type in which females account for more than half of the aggregate manufacturing
employment. Again, the female share in these occupations declined over the 2001-2011 period.
The pattern in the changing female shares across the four skill types is somewhat
consistent with the pattern observed across the three skill levels. We find that in manufacturing,
the female shares in mid- and low-skilled occupations declined while their share increased inhigh-skilled occupations. Note that management and professional tend to be in high-skilledgroup while production and other services tend to be in either mid- or low-skilled groups. To
summarize, although the change is not substantial, we observe that females were becoming more
important in management and high-skilled professional jobs but less so in mid- and low-skilledservices and production jobs.

B. Occupation-specific trade exposure
Based on equation (2) in Section IV, we compute import exposure for 140 three-digit
NOC occupations for each gender in the manufacturing industry in Canada. Table 5 and 6
present the occupations with the ten largest and ten smallest changes in Chinese import exposure
over the 2001-2011 periods along with the employment growth for each occupation.
Males and females appear to have a similar pattern in occupation-specific import
exposure. Seven of the ten most exposed occupations for females are also found in the ten most
exposed occupations for males. There are less overlapped occupations in the ten smallest but
they tend to be in a similar occupational group. For example, both genders have occupations
unique to primary industry such forestry and mining, oil, and gas.
More importantly, for both genders, the occupations with large annual increases in theimport penetration ratio tend to have their employment concentrated in highly exposed sectors inmanufacturing. For example, the occupation that experienced the largest increase in importpenetration for both genders was Managers in communication (except broadcasting). Note that
more than half of their total manufacturing employment was in Communications equipment
manufacturing (NAICS 3342) for both genders. Among the manufacturing sectors, it
experienced the largest increase in import penetration (7.23 percentage-point increase per year)
over the period 2001-2011. Another example is Machine operators and related workers in fabric,
fur and leather products manufacturing. Their employment tended to in Clothing knitting mills(NAICS 3151) in 2001. The sector experienced a 5.22 percentage-point increase per year overthe 2001-2011 period.
It is interesting to note that, for the ten largest occupations, females tend to experiencelarger annual increases in import penetration ratio. Moreover, the annual employment growth for
those occupations tend to be lower for females. As we show in the following empirical analysis,
this pattern is observed not only in the ten most exposed occupations but also in most of theoccupations at 4-digit level. Females are subject to a greater degree of import exposure to China.
We show in the following section that this is due to the fact that female manufacturing
employment is concentrated in highly exposed sectors.
11

Table 5: Annualized percentage point change in Occupation-Specific Chinese Import Penetration Ratio and Annual
per cent change in employment for Selected 3-digit NOC-S 2006, Male, Manufacturing, 2001-2011
Employment∆ in Import
growthPenetration
Ten largest(%)
Ratio (% pt)
A31 Managers in communication (except broadcasting)

4.41-11.77C07 Computer and Information Systems Professionals

2.29

-0.61

H51 Upholsterers, tailors, shoe repairers, jewellers and related occupations

2.10

-6.14

J16 Machine operators and related workers in fabric, fur and leather products manufacturing

2.07

-9.53

G98 Other elemental service occupations

2.06-17.32

C18 Technical occupations in computer and information systems

1.98

-1.43

G81 Childcare and home support workers

1.91

12.04

C14 Technical Occupations in Electronics and Electrical Engineering

1.73

-3.82

H12 Carpenters and Cabinemakers

1.66

-2.03

A12 Managers in Engineering, Architecture, Science, and Information Systems
Ten smallest

1.62

-0.67

G96 Food Counter Attendants, Kitchen Helpers and Related Occupations

0.19

8.91

I12 Supervisors, Mining, Oil and Gas

0.19

-1.44

G71 Occupations in Travel and Accommodation

0.16

-5.71

G73 Other Occupations in Travel, Accommodation, Amusement and Recreation

0.12

19.46

I11 Supervisors, Logging and Forestry

0.11-10.49I15 Logging Machinery Operators

0.10-11.15

G94 Butchers and Bakers

0.09

-0.42

I17 Fishing Vessel Masters and Skippers and Fishermen

0.06

27.85

D03 Assisting Occupations in Support of Health Services

0.05

15.16

E02 Psychologists, Social Workers, Counsellors, Clergy and Probation Officers
0.01
11.53
Source: Author's calculation based on the online trade data base maintained by Innovation, Science, and Economic
Development Canada and the 1991 and 2001 censuses and 2001 National Household Survey.
Note: D04 (Therapy and Assessment Professionals) has an annualized percentage point change in OIP of 0.00 as we have zeromale employment in 2001 and 2011 for the occupation. Hence, we excluded it in this table.

For both genders, we observe the occupations in the bottom ten exhibit only a negligible
annual increase in their import exposure to China. Most of them are not directly related toeconomic activities carried out in establishments in manufacturing. They include: 1.
Psychologists, Social Workers, Counsellors, Clergy and Probation Officers; 2. Assisting
Occupations in Support of Health Services; 3. Police Officers and Firefighters Police Officers
and Firefighters; 4. Other Occupations in Travel, Accommodation, Amusement and Recreation.
Interestingly, for both male and female, there are occupations included in the bottom ten
in mining, oil, and gas extraction: Mine service workers and operators in oil and gas drilling;
Supervisors, Mining, Oil and Gas; and Underground Miners, Oil and Gas Drillers and RelatedWorkers Underground Miners, Oil and Gas Drillers and Related Workers. These occupations
tend to have a large employment share in Petroleum and coal product manufacturing (NAICS
12

3241). This sector was one of only few manufacturing sectors that faced a declining importpenetration ratio during the 2001-2011 period.
To examine a correlation between the two variables among all 140 three-digit
occupations, we plot employment growth against changes in import penetration ratio. Appendix
Chart A1 and A2 depicts a scatter plot between annualized employment growth and the annualchange in import penetration ratio over the 2001-2011 period for male and female respectively.
We observe that occupations with lower growth rates (or higher rates of decline) in theiremployment tend to experience larger increases in Chinese import competition and vice versa.

Table 6: Annualized percentage point change in Occupation-Specific Chinese Import Penetration Ratio and Annual
per cent change in employment for Selected 3-digit NOC-S 2006, Female, Manufacturing, 2001-2011
Employment∆ in Import
growthPenetration
Ten largest(%)
Ratio (% pt)
A31 Managers in communication (except broadcasting)

4.36-12.32

H21 Electrical Trades and Telecommunication Occupations

2.61

-8.28

C14 Technical Occupations in Electronics and Electrical Engineering

2.43

-4.01

J16 Machine operators and related workers in fabric, fur and leather products manufacturing

2.22-11.99H51 Upholsterers, Tailors, Shoe Repairers, Jewellers and Related Occupations

2.12

-9.40

H43 Other Mechanics

2.11

-4.47

G98 Other elemental service occupations

2.11-18.70

C05 Architects, Urban Planners and Land Surveyors

2.10

0.61

C07 Computer and Information Systems Professionals

2.03

-3.71

H12 Carpenters and Cabinemakers
Ten smallest

1.84

-1.87

G71 Occupations in Travel and Accommodation

0.15

0.00

C17 Transportation Officers and Controllers

0.15

-2.88

A33 Managers in Public Administration Managers in Public Administration

0.14

0.00

D04 Therapy and Assessment Professionals

0.11

13.87

D03 Pharmacists, Dietitians and Nutritionists

0.11

8.47

I14 Mine Service Workers and Operators in Oil and Gas Drilling

0.09

4.70

G94 Butchers and Bakers
I13 Underground Miners, Oil and Gas Drillers and Related Workers Underground Miners,
Oil and Gas Drillers and Related Workers

0.07

1.89

0.02

2.88

G61 Police Officers and Firefighters Police Officers and Firefighters

0.00

4.05

G73 Other Occupations in Travel, Accommodation, Amusement and Recreation
0.00
12.53
Source: Author's calculation based on the online trade data base maintained by Innovation, Science, and Economic
Development Canada and the 1991 and 2001 censuses and 2001 National Household Survey.

13

IV.

Empirical Strategy and Data Sources
A. Measure of occupation-specific import exposure

Following Ebenstein et al. (2014), we construct occupation-specific exposure tointernational trade using the distribution of workers employed in an occupation across industries.
Specifically, this is done by weighting industry-specific exposure by an industry's start-of-period
share in the total number of employed workers in a given occupation.
First, industry-level import exposure can be defined as follows:∆𝐼𝑃𝑗 ,𝜏 ≡ 𝑌∆𝑀𝑗𝑐𝑐,𝜏
𝑗 ,92 +𝑀𝑗 ,92 −𝐸𝑗 ,92(1)where 𝑗 denotes subsectors in the manufacturing industry. 𝜏 denotes the two sub-periods: 19922001 and 2001-2011. 𝑌𝑚𝑎𝑛𝑢 ,92 + 𝑀𝑚𝑎𝑛𝑢 ,92 − 𝐸𝑚𝑎𝑛𝑢 ,92 = 𝐽𝑗 =1(𝑌𝑗 ,92 + 𝑀𝑗 ,92 − 𝐸𝑗 ,92 ). 𝑌𝑗 ,92 isindustry shipments of sector 𝑗 in 1992, 𝑀𝑗 ,92 and 𝐸𝑗 ,92 are imports and exports in sector 𝑗 in
1992.8 Hence, 𝑌𝑗 ,92 + 𝑀𝑗 ,92 − 𝐸𝑗 ,92 represents the domestic absorption in sector 𝑗 in the initial
𝐽
𝑐𝑐
𝑐𝑐
𝑐𝑐
period. ∆𝑀𝑚𝑎𝑛𝑢,𝜏 = 𝑗 =1 ∆𝑀𝑗 ,𝜏 and ∆𝑀𝑗 ,𝜏 is the change in import from China in subsector 𝑗 over𝜏.9
All nominal values are converted to chained 2007 Canadian dollars using the household
consumption expenditure deflator. Variation in ∆𝐼𝑃𝑗 over time reflects only the change in thereal value of Chinese imports, while the domestic market size is held constant at its initial value.
A motivation for normalizing by initial domestic absorption is that variation in import exposure
occurs only from changes in Chinese imports, not from other factors that might affect domestic
market size during the period in which Chinese import rose.
Following Ebenstein et al. (2014), the change in trade exposure for occupation 𝑘 (4-digit
occupation) for a Canadian manufacturing industry over period 𝜏 is defined as follows:∆𝑂𝐼𝑃𝑘,𝜏 ≡𝐽
𝑗 =1 𝛼𝑘𝑗 ,𝜏 ∙ ∆𝐼𝑃𝑗 ,𝜏8(2)

Our starting year for ∆𝐼𝑃𝑗 ,𝜏 is 1992 instead of 1991 which is the starting year for our dependent variable. Trade databy industry for China are available only from 1992. Note that we annualize the change during 1992-2001 and mostof the increase in Chinese import competition occurred after 2000. Therefore, this would not cause any serious
problem.
9Note that our model based on Equation (1) would not account for the effect of manufacturing imports from othercountries being replaced by Chinese imports. This effect could be non-negligible according to Chart 3. To the extent
our model fails to account for such effect, one could expect that our estimate of the employment effect of the China
shock is understated.

14

𝐿𝑚𝑎𝑛𝑢𝑘,𝑗 ,𝜏

where 𝛼𝑘𝑗 ,𝜏 ≡ 𝐿𝑚𝑎𝑛𝑢 . 𝐿𝑚𝑎𝑛𝑢
𝑘𝑗 ,𝜏 is the number of employed workers in occupation 𝑘 in sector 𝑗 at the𝑘,𝜏

start of 𝜏. 𝐿𝑚𝑎𝑛𝑢
is the number of workers in occupation 𝑘 across all sectors in manufacturing𝑘,𝜏industry at the start of 𝜏. 10
The above represents percent change in trade exposure of occupation 𝑘 in the
manufacturing industry over 𝜏. Variation in ∆𝑂𝐼𝑃 across occupations arises from variations in
the initial distribution of occupations across manufacturing sectors.11

B. Identification strategy
One issue with our estimation using (2) is that realized imports from China could becorrelated with import demand shocks resulting in a biased OLS estimate (underestimate the true
impact). This is due to the possibility that both Canadian employment and imports are correlatedwith unobserved shocks to demand for Canadian product.
Hence, an instrumental variable strategy is employed to deal with potential endogeneityof trade exposure. Following Autor et al. (2013) and Acemoglu et al. (2016), we exploit the factthat during 1991-2011, the growth in Chinese imports stemmed mostly from the risingcompetitiveness of Chinese manufacturing industries and lowering of trade barriers andaccession to the WTO. To capture the variation in (2) driven by China's expanding exporting
capacity, we instrument for changes in Chinese imports to Canada using the changes in importpenetration in eight other advanced economies.12∆𝐼𝑃𝐸𝑗 ,𝜏 ≡ 𝑌

∆𝑀𝑗𝐸𝐴
,𝜏
𝑗 ,92 +𝑀𝑗 ,92 −𝐸𝑗 ,92(3)

where ∆𝑀𝑗𝐸𝐴,𝜏 represents the change in the Chinese imports of eight other advanced economies inindustry 𝑗 over 𝜏. The nominal values of imports of the eight economies are converted from
USD to Canadian dollars using annual PPPs for personal consumption expenditure from theOECD, deflated to chained 2007 Canadian dollars using the Canadian PCE deflator.
Then, we obtain the following for occupation 𝑘.
∆𝑂𝐼𝑃𝐸𝑘,𝜏 ≡𝐽
𝑗 =1 𝛼𝑘𝑗 ,𝜏 ∙ ∆𝐼𝑃𝐸𝑗 ,𝜏

(4)

The motivation for our identification strategy is that the eight advanced economies would
have been exposed to China in a similar way in that Chinese import growth was driven by supply
shocks in the country. Then, the key identifying assumptions are: 1. product demand shocks are
10

Note that 1991 data are available rather than 1992. This is not consistent with industry-specific import penetration
whose starting year is 1992. We assume employment structure in 1991 within locality was not fundamentallydifferent from 1992. Hence, we use 1991 value for the employment.
11
Variation may not be significant at a broader level (skill-type and skill-level). However, at the 4-digit occupationlevel, variation is substantial.
12
The eight economies are Australia, Denmark, Finland, Germany, Japan, New Zealand, Spain and Switzerland. We
exclude the United States because its economy is highly integrated with Canada and is likely to have experienced
similar demand patterns.

15

uncorrelated across the eight countries; and 2. there are no strong increasing returns to scale in
Chinese manufacturing such that Canadian demand shocks might increase efficiency in the
Chinese manufacturing industries and lead them to export more to the eight other economies.13
Although the former might contaminate (downwardly) our estimates of the impact of the China
shock on employment, we think the latter is not likely to be a major concern since the size ofCanadian economy is too small relative to the global economy.
Our data suggest that approximately 82 per cent of the variation in occupation-specificimport penetration is driven by exogenous supply shocks.14 This suggests that import growth in
the eight advanced economies has strong predictive power for Chinese import growth in Canada(see Chart 5). As a comparison, Acemoglu et al. (2016) find that 62 per cent of the total variationin Chinese imports to U.S. was driven by supply shocks. Balsvik et al. (2015) find thatexogenous supply shocks can explain about 91 per cent of the total variation in Chinese imports
to Norway.
Chart 5: Occupation-specific import exposure to China: Other advanced economies vs.
Canada, 1991-2001 and 2001-2011

Source: Author's calculation based on the online trade data base maintained by Innovation, Science, andEconomic Development Canada and the 1991 and 2001 censuses and 2001 National Household Survey.
13

As pointed out in Goldsmith-Pinkham et al. (2018), in this IV setting, there could be a small number ofoccupations driving a large share of the identifying variations in our sample. Autor et al.(2013) also point out thatthe electronic computer industry in their sample could be a major source of endogeneity stemmed from correlated
demand shocks across the U.S and eight other countries due to common innovations in the use of information
technology. In our case, a group of occupations related to ICT (e.g. Information system analysts and consultants,
Database analysts and data administrators, Software engineers and designers, Web designers and developers) may
be a source of a similar endogeneity problem. As a crude test, we estimated the equation after we excluded ICTrelated occupations in our sample. The estimated marginal effect was found to be slightly larger. This is consistent
with our prediction that those occupations would contaminate the estimate downwardly.
13
See Autor et al. (2013) for further discussion.
14
This is based on regressing (2) on (4) for all 4-digit occupations in the Canadian manufacturing industries(equivalent to first-stage regression in our subsequent 2SLS estimation). The R-squared from such regression is
0.82.

16

A. Data Sources
Trade data required to construct the industry-level import penetration ratio and its
instrument are provided by Alexander Murray. In Murray (2017), trade data for Canada are
drawn from the Trade Data Online database maintained by Innovation, Science and Economic
Development Canada (ISED). The database provides import and export statistics by detailed
four-digit NAICS industry. Data are available for nominal values of total imports, total exports,
and imports from China for 85 four-digit NAICS manufacturing industries for the 1992-2015
period. The import penetration measures are normalized by the industry's total domestic
absorption (total industrial shipment plus imports minus export). Data on total shipments by
four-digit NAICS manufacturing industry are drawn from CANSIM Table 304-0014.
In order to construct the instrumental variable, we need data on the Chinese imports ofeight other advanced economies by four-digit NAICS industry. In Murray (2017), the data wereobtained on each country's Chinese imports by six-digit HS product code from the UN Comtrade
database. Then, the data are mapped into 85 four-digit NAICS manufacturing industries using aprocedure developed in Pierce and Schott (2012).15
To construct the occupation-specific import penetration ratio, we need employment data
for each occupation across all manufacturing industries in Canada. We draw measures of
employment by four-digit NOC occupations across 85 NAICS manufacturing industries from the1991 and 2001 censuses and the 2011 National Household Survey. For our local-level analysis,
we extract the employment data by industry and by occupation for each of 122 CMAs/CAs fromthe censuses.
However, industries and occupations are coded based on different classification systems
across the three censuses. In the 1991 census, industries and occupations are coded according to
the Standard Industrial Classification System (SIC) 1980 and NOC 1991; in the 2001 census,
NAICS 1997 and NOC-S 2001; and in the 2011 census, NAICS 2007 and NOC-S 2006.
Concordance of the NOC (𝑡 year) -NOC (𝑠 year) (or SIC-NAICS) is a research questionand some methods are suggested in the literature. Conveniently, in the 2001 census, both SIC
1980 and NOC 1991 are available. Hence, we use employment shares in the 2001 census basedon the year's cross-tabulation of NOC 1991 - NOC-S 2001 and SIC 1980 -NAICS 1997
respectively. Based on the cross-tabulation, we can compute the share of each occupation in the
NOC-S 2001 and each industry in NAICS-1997 across the occupations in NOC-1991 and theindustries in SIC-1980, respectively. In other words, we get an employment share for each pairof NOC-1991 and NOC-S 2001 occupations and for each pair of SIC 1980 - NAICS 1997
industries for Canada and for each CMA/CA.

15

There are 86 four-digit NAICS manufacturing industries. However, the mapping from HS products to NAICS
industries had no products into NAICS 3328 (Coating, engraving, cold and heat treating and allied activities).
Hence, the industry is dropped, leaving us with a sample of 85 manufacturing industries. We think that our analysis
would not be sensitive to the exclusion; in the data from ISED, imports in this industry are close to zero.

17

We apply the employment shares to the 1991 data assuming that the employment
structure was the same in 1991 and 2001. This ignores a different distribution of occupations
within each industry. However, it requires an infeasible number of computations to take into
account an individual industry.16 Thus, we take a more parsimonious approach by taking into
account only the difference in the occupational distribution of employment across CMAs/CAs
and across the two genders (i.e. we carry out concordance for each CMA/CA and for each maleand female). This should not distort our analysis greatly because a major Chinese importpenetration occurred only after the 2000s.17

V.

Empirical Analysis 1: Occupation-Level Direct Effect

A. ModelTo assess the direct effect of the China shock on Canadian employment across skill levels
and skill types, we estimate the following regression equation.
∆𝐿𝑘,𝜏 = 𝛼𝜏 + 𝛽∆𝑂𝐼𝑃𝑘,𝜏 + 𝜀𝑘,𝜏(5)where ∆𝐿𝑘,𝜏 is 100 times the log change (annualized) in employment level in 4-digit occupation
𝑘 over 𝜏.18∆𝑂𝐼𝑃𝑘,𝜏 is 100 times the annual change (percentage-point change) in the Chinese
import penetration for 4-digit occupation 𝑘 over 𝜏. 𝛼𝜏 is a period-specific constant and 𝜀𝑘,𝜏 is anerror term.
To estimate the marginal impact of trade exposure on each skill group, we estimate thefollowing two fully-interacted regressions.19∆𝐿𝑠𝑘,𝜏 = 𝛼𝑠,𝜏 + 𝛽1 ∆𝑂𝐼𝑃𝑘,𝜏 ∙ 𝕀 𝑠 = 𝑕𝑖𝑔𝑕 𝑠𝑘𝑖𝑖𝑙𝑒𝑑 + 𝛽2 ∆𝑂𝐼𝑃𝑘,𝜏 ∙ 𝕀 𝑠 = 𝑚𝑖𝑑 𝑠𝑘𝑖𝑖𝑙𝑒𝑑+𝛽3 ∆𝑂𝐼𝑃𝑘,𝜏 ∙ 𝕀{𝑠 = 𝑙𝑜𝑤 𝑠𝑘𝑖𝑖𝑙𝑒𝑑} + 𝜀𝑘,𝜏(6)
∆𝐿𝑝𝑘,𝜏 = 𝛼𝑝,𝜏 + 𝛽1 ∆𝑂𝐼𝑃𝑘,𝜏 ∙ 𝕀 𝑝 = 𝑚𝑎𝑛𝑎𝑔𝑒𝑚𝑒𝑛𝑡 + 𝛽2 ∆𝑂𝐼𝑃𝑘,𝜏 ∙ 𝕀 𝑝 = 𝑝𝑟𝑜𝑓𝑒𝑠𝑠𝑖𝑜𝑛𝑎𝑙 + ⋯ +𝑘6∆𝑂𝐼𝑃𝑘,𝜏∙𝕀{𝑝=𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛}+𝜀𝑘,𝜏
(7)where 𝑠 and 𝑝 indicate skill level and skill type, respectively. Estimated coefficient 𝛽 represent
the marginal impact of import penetration on employment in a given skill group.
16

The number of computations required to take into account different distributions across industries is 13.3 billion(692 occupations in NOC 1991 x 520 in NOC-S 2001 x 300 industries in NAICS 1997 x 122 CMAs/CAs plus
Canada total).
17
The concordance between NAICS 1997 and NAICS 2007 and that between NOC-S 2001 and NOC-S 2006 are
relatively straightforward for our purpose. Hence, we do not concord them using the same method described here.
Instead, we refer to the concordance tables provided by Statistics Canada.
18
We use employment data from a cross-tabulation of 85 four-digit NAICS manufacturing industries and 494 fourdigit NOC occupations. The cross-tabulations referred here are the ones created after we carry the concordance
between SIC-NAICS and SOC-NOC in our census files.
19
Note that fully-interacted regressions are analogous to regressions on split samples.

18

We estimate equation (5), (6), and (7) by two-stage least squares (2SLS) using ∆𝑂𝐼𝑃𝐸𝑘,𝜏
on a pooled sample of occupation-level changes in employment in manufacturing and import
exposure over the two sub-periods: 1991-2001 and 2001-2011. Observations are weighted by
employment levels in 1991, so that occupations with large initial employment receive greater
weight. Standard errors are clustered within 140 three-digit NOC categories.
In order to quantify the direct effect of the China shock, we use our estimated coefficientsfrom the above equations. Based on the coefficients, we compute an estimate of the direct
employment effect for each skill group in Canadian manufacturing sectors.
To benchmark the impact of supply-driven Chinese import shocks on the employment
level in Canada, we use the estimated coefficients to estimate changes in log employment
induced by supply-driven Chinese import penetration over the periods 1991-2001 and 2001-2011,
respectively.
In order to capture the variation induced by supply shocks, we discount the change intrade exposure to China by R-squared from the first stage regression. We define Δ𝑂𝐼𝑃𝑘,𝑡 to be
the portion of the change in occupation 𝑘 's exposure to Chinese import attributable to theChinese export supply shocks. Lastly, we use the observed end-of-period employment level toconvert from logs to levels. Hence, the implied employment effect can be seen as the causal
effect of supply-driven increase in Chinese import penetration ratio over the period of interest.
The implied employment effect can be written as the following:
𝐾
𝑐𝑓
Δ𝐿𝑡 =

𝑐𝑓

(𝐿𝑘,𝑡 − 𝐿𝑘,𝑡 )𝑘=

𝐾−𝛽 Δ𝑂𝐼𝑃 𝑘,𝑡)𝑘 𝐿𝑘,𝑡 (1 − 𝑒(8)𝑐𝑓

where 𝐿𝑘,𝑡 is the actual employment level for occupation 𝑘 at time 𝑡 and 𝐿𝑘,𝑡 is thecounterfactual level of employment for occupation 𝑘 at time 𝑡.

B. Summary Statistics
Table 7 reports summary statistics for the three key variables used in the estimation ofequation (5). First, the rising growth of Chinese import competition after 2001 is evident. The
mean annual increase in import penetration is higher for the 2001-2011 period than the mean
increase observed in the 1991-2001 period. The turnaround in the employment growth inmanufacturing after 2001 is also shown. The mean employment growth turns negative for bothgenders for the latter half of the full 1991-2011 period.
According to the data, females experienced a larger increase in Chinese import exposureand a larger decline in employment in manufacturing during the 2001-2011 period. Notice thatfemales have a larger mean increase in the annual change in import penetration. For the stacked
1991-2011 sample, the mean for females is 0.63 percentage-point, compared to 0.48 percentage19

point observed for males. This is also true in each of the two sub-periods. Note also that, during
the 2001-2011 period, females experienced a larger mean decline in their employment in
manufacturing. The mean rate of decline in female employment is -3.41 percentage-points,
compared to the mean of -2.99 percentage-points for males. Note that the median rate of decline
in employment is also larger for females.
Appendix Table A2 and A2-1 report the summary statistics by skill-level. During the
2001-2011 period, females experience a larger mean increase in Chinese import penetration in all
skill levels but particularly in mid- and low-skilled. Females also have a larger mean rate of
decline in employment in mid- and low-skilled occupations than males do during this period. For
example, female low-skilled occupations had a mean rate of decline of 4.25 percentage points intheir employment. For males, the mean rate of decline for low-skilled employment is 3.52
percentage-points. However, note that the median rates of decline in the employment are similar
for males and females implying that females had some occupations with particularly large rates
of decline in employment during this period.
Appendix Table A3 and A3-1 report the summary statistics for the variables by skill type.
First, females have a larger mean annual increase in Chinese import penetration for all the skill
types except for professional over the 2001-2011 period. Most notable istrades/construction/transportation. Even though the female share in its total employment is verysmall, they have a mean annual increase of 0.81 percentage-point, compared to 0.33 percentagepoint for males. Interestingly, Chinese import penetration ratio declined on average forprofessional occupations. Both genders experienced a decline in Chinese import penetration inthis skill group on average with females having a larger mean decline.
Mean annual changes in import penetration and mean employment growth do not appear
to be closely (negatively) correlated. Except for production occupations, males tend to have asmaller mean employment growth than females during the 2001-2011 period despite the fact thatthey tend to have a slightly smaller mean increase in import penetration ratio annually. However,
we show in the previous section that the two variables are negatively correlated across individual
occupations (see Appendix Chart A1 and A2).

20

Table 7: Occupation-Level Changes in Employment and Chinese Import Penetration Ratio, Manufacturing Industries, Canada
1991-2011 stacked

Sub-periods
1991-2001

2001-2011

1991-2011

Male
Mean

MedianMean/Median

Mean/Median

Mean/Median

Annual∆ in Chinese Import Penetration (% pt)

0.48

0.38

0.35 / 0.31

0.61 / 0.63

0.52 / 0.48

Instrument for Chinese Import Penetration (% pt)

0.43

0.26

0.23 / 0.19

0.63 / 0.60

0.48 / 0.42

100 x Annual log change in Employment (%)

-1.98

-1.70

-0.97 / 0.58

-2.99 / -2.46-3.78 / -2.35

FemaleMeanMedianMean/Median

Mean/Median

Mean/Median

Annual ∆ in Chinese Import Penetration (% pt)

0.63

0.55

0.45 / 0.41

0.80 / 0.80

0.67 / 0.62

Instrument for Chinese Import Penetration (% pt)

0.58

0.38

0.32 / 0.26

0.84 / 0.78

0.65 / 0.57

100 x Annual log change in Employment (%)
-1.22
-0.48
0.92 / 2.34
-3.41 / -2.63-2.21 / -0.47
Note: The annual change in Chinese import exposure is 100 x annual change in import penetration for occupation 𝑘. The instrument is 100 x annual change inimport penetration for occupation 𝑘 based on the average annual absolute change in imports from China in a set of eight comparator countries over the period
indicated. The comparator countries are Australia, Denmark, Finland, Germany, Japan, New Zealand, Spain and Switzerland. Annual growth in employmentis
the annualized per cent change in employment level for each 494 four-digit occupations between 1991-2001 and 2001-2011 based on data from the 1991 and2011 census and the 2011 National Household Survey. Observations are weighted by occupation-level employment in 1991.

21

C. Results
1. Regression results
We start by estimating the marginal effect of the China shock on the overall employment
by gender in Canadian manufacturing industries. Here, we estimate Equation (5), (6), and (7) but
on split samples (male and female). Table 8 and Table 8-1 report our estimates for the total direct
effect on manufacturing employment for males and females respectively (Equation 5). Column(1) in both tables only includes time dummies for the two sub-periods. We observe that females
experienced a larger mean rate of annual decline in their manufacturing employment than males
did.
Column (2) estimate the equation by OLS but we find no statistically significant
employment effect of rising Chinese import penetration. As noted earlier, the OLS estimate
could be biased since growth in import could have been driven partly by changes in domestic
supply and demand. Hence, in column (3) we mitigate the simultaneity bias by instrumenting thechange in import penetration in Canada by the changes in import penetration in the eightcomparison countries.
Our 2SLS estimates from the stacked models (column 3) suggest that there is statisticallysignificant effect of rising import penetration on manufacturing employment for both male andfemale. Nevertheless, there was essentially no difference in the sensitivity of employment growth
to trade between male and female workers over the 1991-2011 period (-0.95 for male and -0.96
for female). Focusing on the two sub-periods does not change the story. Both genders exhibit avery similar degree of marginal effect of trade on their employment growth.
Table 9 and Table 9-1 report 2SLS estimates of the marginal effect by skill level. We findthat for both genders, only low-skilled occupations are negatively affected by rising Chinese
import penetration in Canadian manufacturing. The estimates from the stacked model suggestthat female low-skilled occupations faced a slightly larger marginal effect of rising importpenetration on their employment. A one-percentage-point increase in import penetration leads toa 1.57 percentage-point decline in annual employment for males and 1.75 percentage-point for
females. The estimates based on the 2001-2011 period also suggest that the marginal effect ofChinese import competition on low-skilled employment growth is slightly larger for females but
the difference is very small.20

20With the total sample (male+female), we find that rising Chinese import penetration leads to a higher employment
growth for low-skilled occupations during the 1991-2001 period (see Kim, 2018a). Column (2) in Table 9 indicatesthat this was driven by male low-skilled workers. As pointed out in Kim (2018a),such positive relationship is driven
by few influential observations in the male sample. A negative but statistically insignificant relationship is found if
we exclude them.

22

Again, skill level is just one way to characterize occupations. We find above that themarginal employment effect is the greatest for low-skilled occupations. However, low-skilledoccupations consist of more than one skill type (e.g. technical/paraprofessional, other service,trades/construction/transportation and production). Estimating the marginal employment effect inskill-type dimension would be informative.
In the skill-type dimension, we see a quite different response of employment growth toChinese imports. First, female production occupations exhibit a greater sensitivity to Chinese
import competition. Column (1) in Table 10-1 shows that annual employment growth in female
production occupations is reduced by 2.33 percentage points in response to a 1 percentage-point
increase in import penetration ratio. This compares to 1.60 percentage-point reduction for maleproduction workers as suggested in column (1) in Table 10.
In Kim (2018a), we find that the negative impact of China on the employment fortechnical/paraprofessional and other services in the total sample (male+female). Here, it appears
that such negative impact found at the aggregate level is mostly driven by female workers inthose occupations. Column (1) in Table 10 indicates that male workers in those occupations
receive no statistically significant impact from the China shock. Lastly, we find that male
employment growth in professional occupations increased in response to a rise in Chinese importpenetration (see column 1).21 However, such effect disappears at the aggregated sample as shownin Kim (2018a).
Column (2) and (3) in Table 10 and 10-1 report the results based on the two sub-periods.
For both genders, the results based on the 2001-2011 period are generally consistent with those
based on the stacked model. In Kim (2018a), we find that the positive marginal effect on
production occupations observed in the total sample (male+female) based on the 1991-2001 subperiod. Note that such positive relationship is driven by males as shown in column (2) of Table
10. Male employment in production exhibits a positive and statistically significant response to arise in Chinese import penetration while female does not. However, similar to what we find in
Kim (2018a), the positive relationship is driven by few influential observations in the malesample. If we exclude them, we find a negative but statistically insignificant relationship.

21

The negative relationship is driven by some influential outliers (e.g. Registered nurses - D112 in NOC-S 2006).
Note that we do not exclude all influential outliers in the regression analysis in this report. Most of the influential
outliers exist in the sample period 1991-2001 (except for male professional). Therefore, they do not fundamentally
alter our conclusion in this report.

23

Table 8: Effect of Chinese Import Penetration on Log Employment in 4-digit occupations in Manufacturing Industries, Male, Canada: OLS
and 2SLS Estimates
Stacked Differences, 1991-2011

By Sub-periods

1991-2001 and 2001-2011(1)

1991-2001-1.31*(0.71)-3.28***(0.95)(2)-0.47(0.35)-1.14(0.70)-3.16***(0.95)(3)-0.95**(0.45)-0.98(0.71)-3.03***(0.94)

Constant

-

-

Obs.

829

Estimation Method

OLS

Annual change in Chinese Import Penetration
1{1991-2001}
1{2001-2011}

2001-2011(4)
1.69(1.06)(5)0.90(1.24)(6)-0.75*(0.42)(7)-1.11**(0.55)

-

-

-

-

-

-1.90***(0.72)-1.62**(0.77)-4.13***(0.61)-3.91***(0.64)

829

829

437

437

394

394

OLS

2SLS

OLS

2SLS

OLS

2SLS

First-stage F Statistic170.3671.45
310.94
Note: In all specifications, the dependent variable is the average annual growth rate of employment by four-digit occupation over the specified period. Some ofthe observations are dropped as they have zero employment in all manufacturing sectors across the census years we consider. Note that, for some occupations,the sum of employment for male and female reported in census tables is not necessarily equal to the total employment reported for those occupations. Hence, forsome occupations, employment level is zero for both male and female although it is positive for the total sample. Hence, the number of observation in regressions
by gender does not match up with the one reported in the regressions for the total. Standard errors in parentheses are clustered on 140 three-digit occupationgroups. Observations are weighted by occupation employment in 1991.
* p<0.10** p <0.05*** p<0.01

24

Table 8-1: Effect of Chinese Import Penetration on Log Employment in 4-digit occupations in Manufacturing Industries, Female, Canada:
OLS and 2SLS Estimates
Stacked Differences, 1991-2011

By Sub-periods

1991-2001 and 2001-2011(1)
Annual change in Chinese Import Penetration
1{1991-2001}
1{2001-2011}
Constant

1991-2001

0.78(0.72)-6.27***(0.90)(2)-0.41(0.43)
0.96(0.75)-6.10***(0.90)(3)-0.96*(0.57)
1.21(0.76)-5.87 ***
(0.91)---

2001-2011(4)
2.61**(1.02)(5)
0.59(1.15)(6)-0.91*(0.48)

-

-

-

-0.42
(0.89)

0.51(0.90)-4.70***(0.61)(7)-1.13*(0.63)-4.49***(0.70)

Obs.

754

754

754

410

410

344

344

Estimation Method

OLS

OLS

2SLS

OLS

2SLS

OLS

2SLS

First-stage F Statistic
884.3868.03
297.82
Note: In all specifications, the dependent variable is the average annual growth rate of employment by four-digit occupation over the specified period. Some ofthe observations are dropped as they have zero employment in all manufacturing sectors across the census years we consider. Note that, for some occupations,the sum of employment for male and female reported in census tables is not necessarily equal to the total employment reported for those occupations. Hence, forsome occupations, employment level is zero for both male and female although it is positive for the total sample. Hence, the number of observation in regressions
by gender does not match up with the one reported in the regressions for the total. Standard errors in parentheses are clustered on 140 three-digit occupationgroups. Observations are weighted by occupation employment in 1991.
* p<0.10** p <0.05
*** p

25

Table 9: Effect of Chinese Import Penetration on Log Employment in 4-digit occupations in Manufacturing Industries by Skill-Level, Male, Canada:
2SLS Estimates
Stacked Differences, 1991-2011

1991-2001

2001-2011

(1)`

(2)

(3)

0.40
(0.43)-0.26(0.22)-1.57*(0.80)

3.29(2.86)-0.79(2.25)
2.79***(1.05)

0.35(0.46)-0.24(0.20)-2.12**(0.99)

829

437

394

Annual change in Chinese Import Penetration
High-skilled
Mid-skilled
Low-skilled
Obs.

First-stage F Statistic
5746.117334.797652.72
Note: In all specifications, the dependent variable is the average annual growth rate of employment by four-digit occupation in the specified skill group over the
specified period. Some of the observations are dropped as they have zero employment in all manufacturing sectors across the census years we consider. Note that,for some occupations, the sum of employment for male and female reported in census tables is not necessarily equal to the total employment reported for those
occupations. Potentially due to measurement errors, for some occupations, employment level is zero for both male and female although it is positive for the total
sample. Hence, the number of observation in regressions by gender does not match up with the one reported in the regressions for the total reported in Kim(2018a). For (1), we also control for the period dummy interacted with the dummy for skill levels. For (2) and (3), the constant term is interacted with the dummy
for skill levels. Standard errors in parentheses are clustered on 140 three-digit occupation groups. Observations are weighted by occupation employment in 1991.
* p<0.10** p <0.05*** p<0.01

26

Table 9-1: Effect of Chinese Import Penetration on Log Employment in 4-digit occupations in Manufacturing Industries by Skill-Level, Female,
Canada: OLS and 2SLS Estimates
Stacked Differences, 1991-2011

1991-2001

2001-2011

(1)`

(2)

(3)

0.54
(0.90)-0.68(0.49)-1.75*(1.00)

8.85(9.13)-0.38(1.93)
1.07(1.06)-0.02(0.62)-0.71(0.46)-2.38**(1.19)

759

415

346

Annual change in Chinese Import Penetration
High-skilled
Mid-skilled
Low-skilled
Obs.

First-stage F statistic1659.65
1293.17
1907.18
Note: In all specifications, the dependent variable is the average annual growth rate of employment by four-digit occupation in the specified skill group over the
specified period. Some of the observations are dropped as they have zero employment in all manufacturing sectors across the census years we consider. Note that,for some occupations, the sum of employment for male and female reported in census tables is not necessarily equal to the total employment reported for those
occupations. Potentially due to measurement errors, for some occupations, employment level is zero for both male and female although it is positive for the total
sample. Hence, the number of observation in regressions by gender does not match up with the one reported in the regressions for the total reported in Kim(2018a). For (1), we also control for the period dummy interacted with the dummy for skill levels. For (2) and (3), the constant term is interacted with the dummy
for skill levels. Standard errors in parentheses are clustered on 140 three-digit occupation groups. Observations are weighted by occupation employment in 1991.
* p<0.10** p <0.05*** p<0.01

27

Table 10: Effect of Chinese Import Penetration on Log Employment in 4-digit occupations in Manufacturing Industries by Skill-Type, Male,
Canada: 2SLS Estimates
Stacked Differences, 1991-2011

1991-2001

2001-2011

(1)`

(2)

(3)

-0.67
(2.22)
1.14***(0.30)-0.32(0.36)-1.92(1.93)-0.49(0.59)-1.60*(0.95)-1.21(6.45)-12.58(19.21)1.18(1.45)
2.62(5.07)-5.06*(2.89)
2.53**(1.26)-0.64(2.34)
1.19***(0.28)-0.43(0.40)-2.46(1.95)-0.25(0.54)-2.19**(0.99)

829

437

394

Annual change in Chinese Import Penetration
Management
Professional
Technical and Paraprofessional
Services
Trades, Construction, and Transportation
Production
Obs.

First-stage F Statistic
5201.8121184.103844.66
Note: In all specifications, the dependent variable is the average annual growth rate of employment by four-digit occupation in the specified skill group over the
specified period. Some of the observations are dropped as they have zero employment in all manufacturing sectors across the census years we consider. Note that,for some occupations, the sum of employment for male and female reported in census tables is not necessarily equal to the total employment reported for those
occupations. Potentially due to measurement errors, for some occupations, employment level is zero for both male and female although it is positive for the total
sample. Hence, the number of observation in regressions by gender does not match up with the one reported in the regressions for the total reported in Kim(2018a). For (1), we also control for the period dummy interacted with the dummy for skill levels. For (2) and (3), the constant term is interacted with the dummy
for skill levels. Standard errors in parentheses are clustered on 140 three-digit occupation groups. Observations are weighted by occupation employment in 1991.
* p<0.10** p <0.05*** p<0.0128

Table 10-1: Effect of Chinese Import Penetration on Log Employment in 4-digit occupations in Manufacturing Industries by Skill-Type, Female,
Canada: 2SLS Estimates
Stacked Differences, 1991-2011

2001-2011

1991-2011

(1)`

(2)

(3)

3.48
(3.59)
3.97(2.75)-1.48***(0.56)-4.71**(2.05)
0.51(0.96)-2.33***(0.88)

12.16(15.58)63.70(54.22)-0.59(1.46)-0.44(6.28)
0.70(1.49)
1.03(1.41)

2.32(3.03)
2.51(2.59)-1.56**(0.65)-5.46***(1.88)
0.50(0.98)-3.15***(0.76)

759

415

346

Annual change in Chinese Import Penetration
Management
Professional
Technical and Paraprofessional
Services
Trades, Construction, and Transportation
Production
Obs.

First-stage F statistic
1992.51428.421487.36
Note: In all specifications, the dependent variable is the average annual growth rate of employment by four-digit occupation in the specified skill group over the
specified period. Some of the observations are dropped as they have zero employment in all manufacturing sectors across the census years we consider. Note that,for some occupations, the sum of employment for male and female reported in census tables is not necessarily equal to the total employment reported for those
occupations. Potentially due to measurement errors, for some occupations, employment level is zero for both male and female although it is positive for the total
sample. Hence, the number of observation in regressions by gender does not match up with the one reported in the regressions for the total reported in Kim(2018a). For (1), we also control for the period dummy interacted with the dummy for skill levels. For (2) and (3), the constant term is interacted with the dummy
for skill levels. Standard errors in parentheses are clustered on 140 three-digit occupation groups. Observations are weighted by occupation employment in 1991.
* p<0.10** p <0.05*** p<0.0129

1. Implied employment effects
Using the estimated coefficient in column (3) in Table 8 and 8-1, we estimate the total
number of manufacturing jobs in Canada that did not exist in 2011 as a result of the increase in
Chinese import competition over the 1991-2011 period. Here, we rely on Equation (8) along with
the R-squared from the first-stage regression. We also estimate the employment effect by skill
level and by skill type based on the estimated coefficient from column (1) in Table 9, 9-1 andTable 10, 10-1.22
We provide our estimates of employment effect of the China shock for each gender.
Table 11 and Table 11-1 present employment changes induced by Chinese import penetration formales and females, respectively. First, the total employment effect was greater for males than it
was for females both during the full 1991-2011 span and the 2001-2011 period. However, notethat female share in the total employment is much smaller and the total decline in theiremployment is smaller than males over this period. This implies that females had a larger job
loss in relative terms.
For example, during the 2001-2011period when Chinese import penetration rose
substantially, the job loss estimated for females is 36.1 thousand and the loss for males is 56.8
thousand. However, in relative terms, females experienced a larger decline in their employment
due to the China shock. For them, 21.3 per cent of the total decline was induced by the shock.
For males, the share was 16.8 per cent.
It would be useful to assess the total employment effect broken down into different skill
groups. In relative terms, females tend to experience a larger job loss than males but is it true forall skill groups? We first assess the implied employment effect by skill level. Over the full 19912011 span, female low-skilled workers had a slightly higher net loss than male workers: a loss of
82.1 thousand for female compared to a loss of 77.0 thousand for male. Also, female had a larger
proportional decline compared to male. Of the total decline in low-skilled jobs for female, 79.6
per cent was caused by rising import competition from China. For male, the share was 69.5 per
cent.
Similarly, the job loss in female low-skilled occupations was larger in relative terms
during the period in which import penetration from China rose significantly. Over 2001-2011,
males and females experienced essentially the same level of job loss (42.4 thousand loss forfemale and 42.9 thousand loss for males). We estimate that had import penetration from China
remained unchanged, then female low-skilled jobs would have declined by 90.5 thousand insteadof 132.9 thousand. In other words, of the total decline in the low-skilled jobs, 31.9 per cent was
induced by Chinese imports. For male, the share was 21.3 per cent.

22

Following Acemoglu et al. (2016) and Murray (2017), we compute employment effects using both statisticallysignificant and insignificant coefficients from the stacked model.

30

Our estimates suggest a quite large employment effect for female low-skilled occupations
despite the fact that low-skilled occupations in manufacturing are predominately held by male.23
This is due to: 1. greater observed increases in trade exposure for female low-skilled occupations;and 2. a larger estimated marginal effect (𝛽 ) of import competition on female employment
growth in low-skilled occupations.
During the 2001-2011 period, the mean annual increase in import penetration ratio forfemale low-skilled occupations was 0.82 percentage point, compared to 0.63 percentage point for
male low-skilled. Moreover, the estimated marginal employment effect of import competition on
female low-skilled employment growth is -1.75 (vs. -1.57 for male low-skilled). These two
factors lead to a large implied employment effect for female despite a small female share in the
total low-skilled manufacturing employment.24
We emphasize again that skill level and skill type are not necessarily correlated (i.e. noskill level is found exclusively in a particular skill type and vice versa). They each reflects a
distinct characteristics of a given occupation. Analyzing the gender difference in employment
effect by skill type would also be informative. In which skill type do we observe a substantial
gender difference in the direct employment effect of the rising Chinese import penetration?
Across the skill types, we find that female production workers experienced a similar
degree of job loss to male production workers. Focusing on the 2001-2011 period, the net loss
for female was 32.3 thousand while that for male was 32.7 thousand. During this period,
production jobs for females and males declined by 112.5 thousand and 194.6 thousand
respectively. Therefore, females had a larger proportional job loss due to rising importpenetration. The job loss accounts for 28.7 per cent of the total decline in female production
employment during this period. For males, the share is 16.8 per cent.
Note that occupations in production were mostly held by male in manufacturing.25 Again,
despite this fact, having a higher estimated marginal female employment effect results in a quite
large employment effect for them (-2.33 vs. -1.60). In addition, the observed increase in trade
exposure for female production occupations was greater than that for the corresponding maleoccupations. For example, the mean annual increase in import penetration ratio for female
production workers was 0.86 percentage point while that for male was 0.62 percentage point
during the 2001-2011 period.
Females also had a notable trade-induced job loss in occupations in other services during
the 2001-2011 period. We estimate that rising Chinese import penetration led to a loss of 15.4
thousand for other services. This accounts for 35.2 per cent of the total decline in theemployment for this skill group. It appears that males also had a comparable job loss in otherservices but the estimates are based on insignificant coefficients. This is less surprising than the23

Of the total low-skilled occupations in manufacturing, 36.6 per cent was held by female in 1991, 33.2 per cent in2001, and 35.2 per cent in 2011.
24
One can refer to Equation (8) to examine the role of each factors in determining the implied employment effect.
Another factor is the R-squared from our first-stage. However, male and female samples exhibit a very similar Rsquared.
25
Note that, of the total production employment in manufacturing, 31 per cent was held by female on average overthe 1991-2011 period.

31

findings for female production occupations since females accounted for more than half of thetotal employment in other services in manufacturing. On average, females accounted for 55 percent of the total employment in other services in manufacturing during the 1991-2011 period.
Lastly, we find statistical evidence that females also experienced a job loss in technicaland paraprofessional. Although the job loss is small in the absolute term (a loss of 3.6 thousand),it accounts for 78.3 per cent of the total decline in the female employment for that skill group. In
contrast, we find no statistical evidence that Chinese import penetration affected the male
employment in this skill group.
In summary, females had a larger loss in relative terms in low-skilled occupations whenanalyzed by skill level and in production and technical/paraprofessional, and other services whenanalyzed by skill type. It is interesting to find that we observe comparable job losses found forfemales in low-skilled and production occupations despite the fact that they accounted for asmaller share of the total manufacturing employment in those skill groups. These patterns reflect:
1.larger increases in trade exposure for female; and 2. larger marginal effects of importpenetration from China on female employment across skill levels and skill types.
One explanation for the above pattern can be found in Table 12. The table reports theemployment structure of three-digit manufacturing sectors across male and female. In 2001,
female accounted for 29.0 per cent of the total manufacturing employment in Canada (maleaccounted for 71.0 per cent). However, female tended to have high shares in sectors withrelatively large annual increases in import penetration ratio over the 2001-2011.26 Most notable
is the female share in Textile Product Mill (NAICS 314), Clothing Manufacturing (NAICS 315),
Leather and Allied Product Manufacturing (NAICS 316), and Miscellaneous Manufacturing(NAICS 339).These sectors experienced quite large increases in import penetration over the
2001-2011 period. For example, Clothing Manufacturing (NAICS 315) had an annual increase of
2.6 percentage points in their import exposure over the 2001-2011. In this sector, female
accounted for 75.0 per cent of the sectoral employment in 2001.
Autor and Dorn (2013) find that technological progress led to "employment polarization"in the United States such that low-skilled labour moved from goods (involving routine-tasks) toservices while high-skilled labour remained where they are. Hence, we observe a strong U-shapeemployment growth in skill level leaving the mid-skilled labour with relatively low employment
growth. In Kim (2018a), we find that trade did not play a role in "employment polarization" in
Canada since it was only the low-skilled group that experienced a significant trade-induced job
loss. In this report, we find that such result is true for both genders.
We end this section with two caveats worth noting. First, the estimates presented in Table
11 and 11-1 are based on the estimated marginal effect over the 1991-2011 period. This meansthat we impose the same marginal effect on employment growth in both the 1991-2001 and2001-2011 sub-periods. However, we know from Tables 8 to 10 that the marginal effect ofChinese import competition is estimated to be different across the two sub-periods for both maleand female. During the 1991-2001 period, for both genders, we find no statistical evidence that26

We find that this pattern is quite stable over the three census years we consider. General patterns in employment
structures and changes in import penetration ratio at the three-digit industry level are very stable over time.

32

employment growth in most of the skill groups were affected by Chinese import penetration (ifwe exclude few influential observations as discussed earlier). However, some skill groups
experienced a very large marginal employment effect of Chinese import competition during the
2001-2011 period. Hence, we acknowledge that the total direct effect on the employment of thetwo groups over the two decades may be smaller than our estimates reported in Table 11 and 111. However, this does not affect our conclusion that during 2001-2011.
Another caveat is that total employment effect in row (1) in Table 11 and 11-1 is notnecessarily equal to the sum of the employment effect across the three skill levels in row (2) oracross the six skill types in row (3). The reason is that in row (1), we impose the same marginal
effect of trade on all occupations regardless of skill levels or skill types while in row (2) or row(3), we allow the marginal effect to differ across skills based on the estimated coefficients incolumn (1) in Table 9 and 9-1 for skill level and Table 10 and 10-1 for skill type respectively.
Hence, the sum of implied employment effects reported in each row would not necessarily be thesame (see Equation 8).

33

Table 11: Implied Employment Changes Induced by Changes in Chinese Import Penetration, thousand, by Skill level and Skill type, Manufacturingsectors, Male Canada
Counterfactual ∆Actual ∆Implied Employment EffectOccupation Group(s)in employment levelin employment level1991200119911991200119911991200119912001
2011
2011
2001
2011
2011
2001
2011
2011
(1) All occupations

194.7-280.7

-86.0

154.6

-337.5-182.9

-40.1

-56.8

-96.9

High-skilled

6.3

-39.6

-33.3

9.9

-33.0

-23.1

3.6

6.6

10.2

Mid-skilled

57.9

-99.0

-41.1

54.4

-103.4

-49.0

-3.5

-4.4

-7.9

Low-skilled

124.3-158.2

-33.8

90.2

-201.1-110.8

-34.1

-42.9

-77.0

Management

-0.6

-21.8

-22.4

-4.1

-27.5

-31.6

-3.5

-5.7

-9.2

Professional

-13.5

-1.6

-15.0

-12.8

-0.6

-13.3

0.7

1.0

1.7

Technical/Paraprofessional

41.5

-11.8

29.7

39.1

-15.9

23.2

-2.4

-4.1

-6.5

Other services

-52.2

-8.2

-60.4

-61.3

-22.7

-84.0

-9.1

-14.5

-23.6

Trades/Construction/Transportation

31.0

-71.2

-40.2

27.7

-76.2

-48.5

-3.3

-5.0

-8.3

(2) By Skill Level(3) By Skill Type

Production
193.5-161.931.6
165.8-194.6
-28.8
-27.7
-32.7
-60.4
Note: Counterfactual changes represent the changes in employment level if there had been no change in Chinese import penetration. Following Acemoglu et al.
(2016) and Murray (2017), the quantity is computed based on both statistically significant and insignificant coefficients from our stacked models. Note that eachrow represents a different specification: row (1); row (2); and row (3). An implied effect is computed (separately) using the 2SLS estimates from thecorresponding row specification. Thus, implied effects on individual groups do not sum exactly to the quantities based on row (1) specification. Predictions for
1991-2011 is equal to the sum of the predictions for the two sub-periods. The unit of analysis is 4-digit NOC occupations.

34

Table 11-1: Implied Employment Changes Induced by Changes in Chinese Import Penetration, thousand, by Skill level and Skill type, Manufacturingsectors, Female Canada
Counterfactual ∆Actual ∆Implied Employment EffectOccupation Group(s)in employment levelin employment level1991200119911991200119911991200119912001
2011
2011
2001
2011
2011
2001
2011
2011
(1) All occupations

56.3-133.2

-76.9

25.4

-169.3-143.9

-30.9

-36.1

-67.0

High-skilled

-1.4

-6.5

-8.0

0.2

-3.6

-3.5

1.6

2.9

4.5

Mid-skilled

0.7

-26.4

-25.7

-4.6

-32.7

-37.3

-5.3

-6.3

-11.6

Low-skilled

69.6

-90.5

185.2

29.9

-132.9-103.1

-39.7

-42.4

-82.1

Management

1.8

-9.2

-7.4

5.4

-3.0

2.4

3.6

6.2

9.8

Professional

-10.3

-3.5

-13.8

-7.9

0.6

-7.3

2.4

4.1

6.5

Technical/Paraprofessional

14.6

-1.0

13.6

12.0

-4.6

7.4

-2.6

-3.6

-6.2

Other services

-64.6

-28.4

-93.0

-76.0

-43.8

-119.8

-11.4

-15.4

-26.8

Trades/Construction/Transportation

7.1

-6.8

0.3

7.6

-6.1

1.5

0.5

0.7

1.2

(2) By Skill Level(3) By Skill Type

Production
118.5
-80.2
38.3
84.5
-112.5
-28.0
-34.0
-32.3
-66.3
Note: Counterfactual changes represent the changes in employment level if there had been no change in Chinese import penetration. Following Acemoglu et al.
(2016) and Murray (2017), the quantity is computed based on both statistically significant and insignificant coefficients from our stacked models. Note that eachrow represents a different specification: row (1); row (2); and row (3). An implied effect is computed (separately) using the 2SLS estimates from thecorresponding row specification. Thus, implied effects on individual groups do not sum exactly to the quantities based on row (1) specification. Predictions for
1991-2011 is equal to the sum of the predictions for the two sub-periods. The unit of analysis is 4-digit NOC occupations.

35

Table 12: 2001 Employment level (thousand), share in three-digit NAICS manufacturing sectors, annual % pt change in import penetration at three-digit
NAICS industry level over 2001-2011, male and female, Canada
Male share
Female share
Annual Δ in import
Male
Female(%)(%)
penetration (% pt)
Total manufacturing1441.3

589.5

71.0

29.0

1.1

311: Food Manufacturing

136.6

90.0

60.3

39.7

0.1

312: Beverage and Tobacco Product Manufacturing

23.5

7.8

75.1

24.9

0.0

313: Textile Mills

15.8

9.9

61.5

38.5

0.0

314: Textile Product Mills

10.5

10.5

50.0

50.0

1.8

315: Clothing Manufacturing

25.2

75.8

25.0

75.0

2.6

316: Leather and Allied Product Manufacturing

4.3

5.7

43.1

56.9

3.0

321: Wood Product Manufacturing Wood Product Manufacturing

124.4

20.5

85.8

14.2

0.4

322: Paper Manufacturing

83.0

17.3

82.8

17.2

0.2

323: Printing and Related Support Activities
324: Petroleum and Coal Product Manufacturing Petroleum and Coal
Product Manufacturing

57.1

33.6

62.9

37.1

0.2

11.9

3.0

80.0

20.0

0.0

325: Chemical Manufacturing Chemical Manufacturing326: Plastics and Rubber Products Manufacturing Plastics and Rubber
Products Manufacturing

60.6

34.2

63.9

36.1

0.2

76.5

36.8

67.5

32.5

0.9

327: Non-Metallic Mineral Product Manufacturing

44.0

10.8

80.2

19.8

0.6

331: Primary Metal Manufacturing

81.7

9.9

89.2

10.8

0.7

332: Fabricated Metal Product Manufacturing

141.7

31.6

81.8

18.2

0.9

333: Machinery Manufacturing Machinery Manufacturing

107.4

21.4

83.4

16.6

0.9

334: Computer and Electronic Product Manufacturing335: Electrical Equipment, Appliance and Component Manufacturing
Electrical Equipment, Appliance and Component Manufacturing

71.9

40.3

64.1

35.9

3.8

38.2

18.4

67.4

32.6

1.9

336: Transportation Equipment Manufacturing
337: Furniture and Related Product Manufacturing Furniture and Related
Product Manufacturing

204.5

55.1

78.8

21.2

0.3

77.2

25.2

75.4

24.6

2.1

339: Miscellaneous Manufacturing

45.3

31.6

58.9

41.1

2.1

Source: The 2001 census and author's calculation based on the online trade data base maintained by Innovation, Science, and Economic Development Canada.

36

VI.

Empirical Analysis 2: Indirect Effect Operating within Local LabourMarkets
A. ModelIt is important to realize that an analysis based on the manufacturing industries would
miss some important spillover effects on industries beyond manufacturing. As discussed in
Section II, a trade-induced reduction in manufacturing employment may lead to an increase inemployment in another industry as labour is reallocated. At the same time, a trade shock may
reduce the incomes of displaced workers. This may lead to a decline in demand for output
produced in other industries and hence, a decline in employment in those industries as well.
In this section, we are interested in assessing the net effect of the China shock on
employment for each occupation group, taking into account possible spillovers to unaffectedindustries. Following Autor et al. (2013) as a general framework, we estimate how theemployment of each occupation group in manufacturing and non-manufacturing sectors
responded to the import shock over time within local labour markets.27 It will shed some light on
how resilient a given occupation group had been in the face of rising Chinese import competition
within local labour markets.28
We treat local labour markets as subeconomies subject to differential trade exposure
according to initial patterns of employment across different occupations. Then, we exploit
variations in local employment rate and locality's trade exposure across the local labour markets
in Canada to estimate the marginal employment effect of import competition. Here, the sample is
no longer restricted to the occupations in the manufacturing industries. We first present ourbaseline specification to measure employment rate response at the local level:𝑗𝐿∆𝐸𝑙,𝜏 = 𝛼𝜏 + 𝛽∆𝐼𝐸𝑙,𝜏
+ 𝛾𝑋𝑙,𝜏 + 𝜖𝑙,𝜏(9)where ∆𝐸𝑙,𝜏 is the annual percentage-point change in the employment rate (i.e. the ratio of total
employment to the working-age population, defined as the population aged 15 or over) in sector𝐿𝑗 (manufacturing or non-manufacturing) in locality 𝑙 over time period 𝜏. 29 ∆𝐼𝐸𝑙,𝜏
is the annual
percentage-point change in locality 𝑙's exposure to Chinese import over 𝜏. 𝑋𝑙,𝜏 is a vector of
locality-specific control variables which we will specify later.

27

Our definition of locality is the census metropolitan area or census agglomeration (CMA/CA).
Note that our framework can capture but cannot explicitly show the effect of individual worker being re-employed
in different skill group from the group in which he or she was previously employed. A worker-level panel structure
in our data would be necessary for such study.
29
We use a cross-tabulation of 494 four-digit NOC occupations and 300 four-digit NAICS industries (303 industries
for 2011) for each of 122 CMAs/CAs as well as working-age population in each CMAs/CAs from the censuses. The
cross-tabulations referred here are the ones created after we carry the concordance between SIC-NAICS and SOCNOC in our census files.
2837

To estimate the marginal effect by skill group, we estimate the following equations:𝑗𝐿𝐿∆𝐸𝑠,𝑙,𝜏 = 𝛼𝑠,𝜏 + 𝛽1 ∆𝐼𝐸𝑙,𝜏
∙ 𝕀 𝑠 = 𝑕𝑖𝑔𝑕 𝑠𝑘𝑖𝑙𝑙𝑒𝑑 + ⋯ + 𝛽3 ∆𝐼𝐸𝑙,𝜏
∙ 𝕀 𝑠 = 𝑙𝑜𝑤 𝑠𝑘𝑖𝑙𝑙𝑒𝑑+𝛾𝑋𝑠,𝑙,𝜏 + 𝜀𝑠,𝑘,𝜏
(10)

𝑗

𝐿
𝐿
∆𝐸𝑝,𝑙,𝜏 = 𝛼𝑠,𝜏 + 𝛽1 ∆𝐼𝐸𝑙,𝜏
∙ 𝕀 𝑝 = 𝑚𝑎𝑛𝑎𝑔𝑒𝑚𝑒𝑛𝑡 + ⋯ + 𝛽6 ∆𝐼𝐸𝑙,𝜏
∙ 𝕀 𝑝 = 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛+ 𝛾𝑋𝑝,𝑙,𝜏 + 𝜀𝑝,𝑘,𝜏
(11)

where 𝑗 represents industry (manufacturing or non-manufacturing); 𝑠 and 𝑝 represent skill leveland skill type of a given occupation, respectively. 𝑋 includes fixed effects for six regions (theAtlantic region, Quebec, Ontario, the Prairie region, British Columbia, and the Northern region)and the initial share of a locality's employment that is in manufacturing.
Local labour markets differ in their trade exposure due to variation in the importance of𝐿
different occupations (in manufacturing sectors) for local employment. The variation in ∆𝐼𝐸𝑙,𝜏
across local labour markets stems entirely from variation in local occupational employment
𝐿structure at the start of period 𝜏. Specifically, we construct ∆𝐼𝐸𝑙,𝜏
as the following:𝐿∆𝐼𝐸𝑙,𝜏
=𝐾 𝐿𝑙,𝑘 ,𝜏∆𝑂𝐼𝑃𝑘,𝜏
𝑘=1 𝐿
𝑙,𝜏

(12)

where 𝐿𝑙,𝑘,𝜏 is the number of employed workers in occupation 𝑘 in manufacturing sectors inlocality 𝑙 at the start of 𝜏 and 𝐿𝑙,𝜏 is the number of employed workers in locality 𝑙 at the start of𝐿𝜏.30 The instrument for ∆𝐼𝐸𝑙,𝜏
is obtained by replacing ∆𝑂𝐼𝑃𝑘,𝜏 with ∆𝑂𝐼𝑃𝐸𝑘,𝜏 in Equation (4).
If the degree of mobility response of working-age population is small to an adverse trade
shock, then a trade-induced decline in manufacturing employment should yield a corresponding
rise in either non-manufacturing employment, unemployment, labour force exit, or somecombination of the three. By estimating equation (9), (10), and (11) separately for manufacturing
and non-manufacturing, we pay particular attention to how much of the change in nonmanufacturing employment is induced by the China shock.31 This will represent the combinationof labour reallocation and negative demand effect of Chinese import penetration operating within
a local labour market. In other words, we assess the relative importance of the two effects.
Together with the degree of change in manufacturing employment due to the same shock,we can then assess the degree of resiliency of each occupation group. For example, if a given
skill group had a decline in its employment in manufacturing but had a comparable increase in
the employment in non-manufacturing, we can say that the labour reallocation to that skill group𝐿
We also constructed the ∆𝐼𝐸𝑙,𝜏
as the employment-weighted average of our industry-level import competition
measure following Murray (2017). Statistical properties of the two variables are very similar and our general resultsin this section is not altered when we adopt the one from Murray (2017).
31
We assume that no industry in non-manufacturing industries faced a direct exposure to Chinese importpenetration. This is a plausible assumption since the manufacturing share of total imports from China is 98.4 percent on average over the 1992-2015 period.
30

38

in unaffected sectors was successful mitigating the aggregate job loss in response to a trade
shock.32 On the other hand, if there was no corresponding increase (or even a reduction) in
employment in other sectors, this implies that negative demand effects presumably inhibit labour
reallocation to that group in unaffected sectors to some extent. Some portion of the displaced
workers would either stay unemployed or exit the labour force. Note, however, that the above
interpretation requires the assumption that local labour markets are not well-integrated such thatan initial local impact does not rapidly diffuse across regions.33
Similarly, using our estimated coefficient (𝛽 ), we compute the implied employment
effect as follows. Let Δ𝐼𝐸𝑙 𝑡 denote the portion of the change in import penetration to locality 𝑙over time period 𝑡 that is attributable to the Chinese export supply shocks:
𝐿
𝑐𝑓
Δ𝐿𝑡 =

𝑐𝑓

Δ𝐿𝑙,𝑡
𝑙

=

𝐿
𝑙 𝑃𝑂𝑃𝑙,𝑡 𝛽 Δ𝐼𝐸𝑙 𝑡 ∙ 0.01

(13)

where 𝑃𝑂𝑃𝑙,𝑡 is the working-age population in locality 𝑙 at the end of period 𝑡. We measure
Δ𝐼𝐸𝑙 𝑡 by discounting the observed change in local trade exposure by the R-squared from our
first-stage regression. We multiply the quantity by 𝑃𝑂𝑃𝑙,𝑡 and 0.01 since 𝛽 Δ𝐼𝐸𝑙 𝑡 represent a
percentage-point change in employment rate over period 𝑡.
The implied employment effect estimated by Equation (13) capture not only the direct
impact of Chinese but also the net effect of inter-industry labour reallocation and demand
spillover effects operating within local labour markets. Again, it will not capture the effects
operating at a broader level (at the provincial or national levels).

B. Summary Statistics
Summary statistics for the variables are reported in Table 13 and 13-1 for each genderrespectively. First, the rising Chinese import competition after 2001 is evident: the mean annualchange in Chinese import penetration ratio over the 1991-2001 period is lower than that over the
2001-2011 period for both genders. It also shows the turnaround in employment growth after
32

Note that the reallocation to this skill group can occur from not only the same skill group but also from other skill
groups in manufacturing.
33
We ran a crude regression in which we regressed annual growth of local working-age population (population aged
15 or over) on annual change in local's trade exposure to China controlling for regional difference in time trend as
well as initial manufacture share of the local employment. We find no statistically significant response of local
working-age population growth to an increase in trade exposure (based on 2SLS). Hence, the mechanism describedin the text is valid for most of the labour markets across Canada on average. However, there could be some local
labour markets for which across-localities reallocation is important. For example, depending on the performance ofgas and oil sectors, there could be a large degree of labour reallocation between British Columbia and Alberta.

39

2001 we discussed in the earlier section; across all industries, the annual change in theemployment rate is positive for both genders over the 1991-2001 period but it become negative
over the 2001-2011 period.
During 2001-2011 period, the mean annual increase in local trade exposure is quite
similar for males and females. However, the mean decline in local employment rate (allindustries) is lower for males during this period. Across the 122 CMAs/CAs, the employment
rate declined by 0.29 percentage-point on average for males while it declined by 0.17
percentage-point for females. On average, females appear to have experienced a larger decline in
the employment rate for a given rise in local trade exposure during this period.
During the first half of the 1991-2011 period, occupations in all three skill levels had
positive mean increase in their employment except for male mid-skilled occupations. During theperiod when Chinese import penetration rose substantially (i.e. 2001-2011), all three skill levels
had a decline in their local employment rate on average across the 122 CMAs/CAs. For bothgenders, the mean decline in the employment rate was the largest for low-skilled occupations andlowest for high-skilled occupations during this period. Across the two genders, we find thatmales experienced a larger mean decline in the employment rate for all three skill groups during
the 2001-2011 period.
A similar pattern is found in the skill type dimension. The local employment rate for mostof the skill types rose on average during the 1991-2001 period but fell in the following subperiod. Similarly, males tend to experience a larger mean decline in the employment rates in all
skill types except for other services. For occupations in other services, females had a notably
larger mean decline. The employment rate of other services fell by 0.33 percentage-point on
average for females during the 2001-2011 period. This is almost twice as large as the mean
decline experienced by males.

40

Table 13: Summary Statistics on Changes in Employment Rates and in Chinese Import Penetration across Local Labour Markets, Male, All Industries,
1991-2011, % point
1991-2011

1991-2001

2001-2011

Mean

S.D.

Median

Mean

SD

Mean

SD

Annual change in Chinese Import Penetration

0.08

0.05

0.08

0.05

0.03

0.11

0.05

Instrument for annual change in Chinese Import Penetration

0.07

0.06

0.05

0.03

0.02

0.11

0.06

-0.13

0.27

-0.11

0.03

0.21

-0.29

0.22

High-skilled

0.06

0.22

-0.06

0.08

0.14

-0.21

0.19

Mid-skilled

-0.15

0.26

-0.14

-0.01

0.23

-0.29

0.21

Low-skilled

-0.17

0.30

-0.16

0.02

0.23

-0.37

0.23

Management

-0.08

0.12

-0.06

0.00

0.07

-0.15

0.11

Professional

-0.03

0.08

-0.01

0.01

0.06

-0.06

0.08

Technical/Paraprofessional

0.00

0.14

-0.01

0.10

0.09

-0.11

0.10

Other services

-0.11

0.18

-0.10

-0.03

0.15

-0.18

0.18

Trades/Construction/Transportation

-0.10

0.19

-0.10

-0.01

0.17

-0.19

0.16

Annual change in Employment Rate
(1) All occupations(2) By Skill Level(3) By Skill Type

Production
-0.08
0.19
-0.08
0.02
0.18
-0.18
0.14
Note: The annual change in Chinese import exposure is the employment-weighted mean (within the locality) of the occupation-level import exposure penetration
ratio. The instrument is computed similarly but using imports to the eight advanced economies as described in the main text. The employment rates by locality
are measured as 100 x the locality's total employment in each skill group divided by the locality's population aged fifteen and over. The variables in the table are
the annual percentage-point differences over the time periods specified. The samples are 122 CMAs/CAs. Observations are weighted by the locality's workingage population in 1991.

41

Table 13-1: Summary Statistics on Changes in Employment Rates and in Chinese Import Penetration across Local Labour Markets, Female, All
Industries, 1991-2011, % point
1991-2011

1991-2001

2001-2011

Mean

S.D.

Median

Mean

SD

Mean

SD

Annual change in Chinese Import Penetration

0.07

0.05

0.07

0.05

0.03

0.09

0.05

Instrument for annual change in Chinese Import Penetration

0.07

0.06

0.06

0.04

0.02

0.11

0.06

-0.06

0.23

-0.04

0.05

0.19

-0.17

0.21

High-skilled

0.03

0.17

-0.01

0.13

0.16

-0.06

0.13

Mid-skilled

-0.06

0.17

-0.05

0.03

0.14

-0.14

0.16

Low-skilled

-0.16

0.28

-0.14

0.00

0.24

-0.31

0.24

Management

0.00

0.09

0.00

0.05

0.07

-0.05

0.07

Professional

0.05

0.10

0.00

0.07

0.11

0.01

0.08

Technical/Paraprofessional

0.03

0.08

0.00

0.07

0.08

-0.02

0.06

Other services

-0.20

0.34

-0.12

-0.07

0.28

-0.33

0.35

Trades/Construction/Transportation

-0.01

0.02

-0.01

0.01

0.02

-0.02

0.02

Annual change in Employment Rate
(1) All occupations(2) By Skill Level(3) By Skill Type

Production
-0.04
0.09
-0.03
0.01
0.08
-0.09
0.07
Note: The annual change in Chinese import exposure is the employment-weighted mean (within the locality) of the occupation-level import exposure penetration
ratio. The instrument is computed similarly but using imports to the eight advanced economies as described in the main text. The employment rates by locality
are measured as 100 x the locality's total employment in each skill group divided by the locality's population aged fifteen and over. The variables in the table are
the annual percentage-point differences over the time periods specified. The samples are 122 CMAs/CAs. Observations are weighted by the locality's workingage population in 1991.

42

C. Results
1. Regression results
First, we report the results from estimating Equation (9), our baseline specification.
Again, we find a negative relationship between changes in local employment rate in
manufacturing and changes in local trade exposure for both genders. Our 2SLS estimatesindicate that a 1-percentage-point-increase in local trade exposure leads a decline in the local
employment rate by 2.73 percentage points for females and 2.11 percentage points for males.
Importantly, the local employment rate in non-manufacturing increases for both genders
in response to a rise in local trade exposure to China, thereby mitigating the decline observed in
manufacturing. This indicates that there had been successful labour reallocation frommanufacturing to non-manufacturing in response to a rise in local trade exposure. In other words,
local demand effects appear to be too weak to offset the labour reallocation effect operating
within local labour markets. This is the opposite of what Acemoglu et al. (2016) find. They findthat negative local demand effects appear to fully offset the labour reallocation operating within
local labour markets.
Table 14: Effect of Import Penetration on Employment in Canadian Local Labour Markets, All Occupations,
All Industries, 1991-2011 stacked model: 2SLS Estimates
Employment Rate (all occupations)FemaleAll industries

ManufacturingNon-manufacturing-0.16 (0.50)-2.73*** (0.27)

2.42** (0.98)

Obs.

488

244

244

First-stage F statistics

929.82908.37908.37All industries

ManufacturingNon-manufacturing0.10 (0.50)-2.11*** (0.67)

2.31** (1.03)

488

244

244

CMA/CA import exposure

Male
CMA/CA import exposure
Obs.

First-stage F statistics
727.67710.89710.89Note: The number of observation is 488 (122 CMA/CA's x two sectors x two time periods). The dependent variable
is the annual percentage-point change in the employment rate within a CMA/CA over the 1991-2001 and 2001-2011
periods. We include period and region dummies (the Atlantic region, Quebec, Ontario, the Prairie region, British
Columbia, and the Northern region) as well as the initial share of a locality's employment that is in manufacturing.
Standard errors in parentheses are clustered on 122 CMAs/CAs.

43

Next, we discuss the results by skill level. Column (2) in Table 15 and 15-1 reports theestimates for manufacturing for each gender. All skill levels are negatively affected by trade
shocks in terms of their annual change in employment rate. Here, low-skilled occupations havethe largest marginal effect among the three skill groups for both genders.
Note, however, that female low-skilled occupations exhibit a greater degree of sensitivity
to Chinese import competition. For females, a 1-percentage-point China shock to localities
reduces the low-skilled employment rate by 2.68 percentage points. This compares to 1.51
percentage-point reduction of male low-skilled employment rate for a 1-percentage-point
increase in local trade exposure.
Based on column (3), the reallocation to non-manufacturing sector did occur for all threeskill levels in response to a rise in Chinese import penetration for both genders. However, thereallocation occurred at a varying degree across the three skill levels.
Both male and female exhibit an equivalent rise in non-manufacturing employment rate
for high- and mid-skilled occupations. This implies that the reallocation to both high and midskilled occupations were quite successful within local labour markets. 34 For both genders,
however, negative demand effects presumably prevent low-skilled occupations from achieving
an equivalent rise in their employment rate in non-manufacturing. The labour reallocation to
low-skilled occupations in non-manufacturing appears to be less successful than the reallocation
to high- and mid-skilled occupations.
Next, we present the results from estimating Equation (12) in which we assess theemployment effect by skill type. Table 16 and Table 16-1 report the results for each gender.
Based on column (1) in each table, we find that a 1-percentage-point China shock to localities
reduces the change employment rate in male production occupations by 0.40 percentage points
per year in all industries. For females, the same shock reduces the employment rate ofproduction occupations by 1.03 percentage points. Hence, females exhibit a larger marginal
effect of a rise in Chinese import penetration in local labour markets. Additionally, a 1percentage-point rise in local import exposure reduces the employment rate oftrades/construction/transportation by 0.12 percentage points for females. In contrast, theemployment rate of the same occupation group increases for males although the increase is notstatistically significant.
The breakdown by the two sectors reveals that the labour reallocation to production andtrades/construction/transportation jobs in non-manufacturing was somewhat successful for males
but not for females. Column (2) in each table shows that for both genders, the employment rate
for the two skill types in manufacturing declined in response to a rise in local trade exposure to
China. However, in column (3), we find no statistical evidence for females that the employment
rates of those two skill types in non-manufacturing rise in response to a trade shock while we do

34

Note that the coefficient for each skill group in non-manufacturing reflects the reallocation from not only the sameskill group but also the other skill groups in manufacturing. For example, a positive response of the employment
rate in mid-skill group in non-manufacturing could be driven by the employment being reallocated from low-, mid-,and high-skilled in manufacturing. The same logic applied to the analysis by skill type.

44

for male.35 One explanation for this pattern is that there is a smaller number of jobs in those skill
groups available for female workers outside manufacturing within local labour markets than it isfor male workers, potentially prohibiting re-employment in response to an import shock.
Interestingly, we observe that the employment rate in female management occupations in
all industries is positively affected by a rise in local's trade exposure. The breakdown by
manufacturing and non-manufacturing indicates that such relationship is driven by the marginal
effect observed in non-manufacturing. The female employment rate in management for
manufacturing is indeed reduced by a rise in local trade exposure. However, it appears that suchdecline in the employment rate in manufacturing is more than offset by an increase in nonmanufacturing. This indicates that a trade shock might have induced previously unemployedworkers to be re-employed in management occupations in non-manufacturing or induced
workers in those occupations to exit the labour force.36

35

We conjecture that, within local labour markets, we would see a rise in either unemployment rate or the share offemale workers not in the labour force for those two skill types in response to the China shock.
36
In order to examine a more complete mechanism, we would need data for labour force, unemployment rate, andout-of-labour-force by skill type so that we assess the responses of four mutually exclusive categories (those three
categories plus the employment rate) with respect to a trade shock as in Autor et al. (2013).

45

Table 15: Effect of Import Penetration on Canadian Local Labour Markets, By Skill Level, Male, 1991-2011, stacked model: 2SLS Estimates
Employment Rate (all industries)

Manufacturing Employment Rate

Non-Manufacturing Employment Rate

CMA/CA import exposure x {Low-skilled}

(1)`
0.02
(0.10)
0.09(0.22)-0.42**(0.21)(2)-0.42***(0.10)-0.62**(0.28)-1.51***(0.39)(3)
0.46**(0.21)
0.81**(0.38)
0.67*(0.36)

Obs.

1,464

732

732

CMA/CA import exposure x{High-skilled}
CMA/CA import exposure x {Mid-skilled}First-stage F statistics
1644.01
1608.441608.44
Note: For (1), the number of observation is 1,464 (122 CMA/CA's x two industries x three types of occupations x two time periods). For (2), (3), and (4), N=732(122 CMA/CA's x three types of occupations x two time periods).The dependent variable is the annual percentage-point change in the employment rate within a
CMA/CA over the 1991-2001 and 2001-2011 periods. In columns (2) and (3), the dependent variable is the annual percentage-point change in the ratio ofsectoral employment to the total working-age population within a CMA/CA over the 1991-2001 and 2001-2011 periods and for high-, mid-, and low-skilledoccupations in each sector. In all specification, we include period, region dummies, and the locality's initial manufacturing employment share interacted with skill
dummies. Standard errors in parentheses are clustered on 122 CMAs/CAs.
* p<0.10** p <0.05*** p<0.01

46

Table 15-1: Effect of Import Penetration on Canadian Local Labour Markets, By Skill Level, Female, 1991-2011, stacked model: 2SLS Estimates
Employment Rate (all industries)

Manufacturing Employment Rate

Non-Manufacturing Employment Rate

CMA/CA import exposure x {Low-skilled}

(1)`
0.25
(0.17)-0.07(0.24)-0.66*(0.35)(2)-0.23***(0.07)-1.06***(0.14)-2.68***(0.33)(3)
0.72**(0.34)
0.92**(0.46)
1.35**(0.57)

Obs.

1,464

732

732

CMA/CA import exposure x{High-skilled}
CMA/CA import exposure x {Mid-skilled}First-stage F statistics
1624.35
1589.211589.21
Note: For (1), the number of observation is 1,464 (122 CMA/CA's x two industries x three types of occupations x two time periods). For (2), (3), and (4), N=732(122 CMA/CA's x three types of occupations x two time periods).The dependent variable is the annual percentage-point change in the employment rate within a
CMA/CA over the 1991-2001 and 2001-2011 periods. In columns (2) and (3), the dependent variable is the annual percentage-point change in the ratio ofsectoral employment to the total working-age population within a CMA/CA over the 1991-2001 and 2001-2011 periods and for high-, mid-, and low-skilledoccupations in each sector. In all specification, we include period, region dummies, and the locality's initial manufacturing employment share interacted with skill
dummies. Standard errors in parentheses are clustered on 122 CMAs/CAs.
* p<0.10** p <0.05*** p<0.01

47

Table 16: Effect of Import Penetration on Canadian Local Labour Markets, By Skill Type, Male, 1991-2011, stacked model: 2SLS Estimates
Employment Rate
Manufacturing
Non-Manufacturing(all industries)
Employment Rate
Employment Rate

CMA/CA import exposure x {Production}

(1)`
-0.08
(0.07)
0.03(0.05)
0.08(0.08)-0.05(0.12)
0.11(0.15)-0.40**(0.19)(2)-0.31***(0.05)-0.03*(0.02)-0.23**(0.10)-0.33***(0.08)-0.56***(0.17)-1.09***(0.40)(3)
0.14(0.13)
0.09(0.10)
0.39**(0.16)
0.24(0.24)
0.78**(0.31)
0.29*(0.16)

Obs.

2,928

1,464

1,464

CMA/CA import exposure x {Management}
CMA/CA import exposure x {Professional}
CMA/CA import exposure x {Technical/Paraprofessional}
CMA/CA import exposure x {Other Services}
CMA/CA import exposure x {Trades/Construction/Transportation}

First-stage F statistics
1644.58
1609.59
1609.59
Note: For (1), the number of observation is 2,928 (122 CMA/CA's x two industries x six types of occupations x two time periods). For (2), (3), and (4), N=1,464(122 CMA/CA's x six types of occupations x two time periods). The dependent variable is the annual percentage-point change in the employment rate within a
CMA/CA over the 1991-2001 and 2001-2011 periods. In columns (2) and (3), the dependent variable is the annual percentage-point change in the ratio ofsectoral employment to the total working-age population within a CMA/CA over the 1991-2001 and 2001-2011 periods and for occupation in the six skill groups
in each sector. In all specification, we include period, region dummies, and the locality's initial manufacturing employment share interacted with skill dummies.
Standard errors in parentheses are clustered on 122 CMAs/CAs.
* p<0.10** p <0.05*** p<0.01

48

Table 16-1: Effect of Import Penetration on Canadian Local Labour Markets, By Skill Type, Female, 1991-2011, stacked model: 2SLS Estimates
Employment Rate
Manufacturing
Non-Manufacturing(all industries)
Employment Rate
Employment Rate

CMA/CA import exposure x {Production}(1)`
0.30***(0.09)-0.02(0.12)
0.13(0.10)
0.27(0.38)-0.12 **
(0.05)-1.03***(0.15)(2)-0.11***(0.03)-0.09***(0.03)-0.24***(0.06)-1.09***(0.14)-0.22***(0.05)-2.22***(0.27)(3)
0.70***(0.18)
0.04(0.23)
0.50**(0.23)
1.62**(0.74)-0.02(0.06)
0.15(0.14)

Obs.

2,928

1,464

1,464

CMA/CA import exposure x {Management}
CMA/CA import exposure x {Professional}
CMA/CA import exposure x {Technical/Paraprofessional}
CMA/CA import exposure x {Other Services}
CMA/CA import exposure x {Trades/Construction/Transportation}

First-stage F statistics
1624.92
1590.35
1590.35
Note: For (1), the number of observation is 2,928 (122 CMA/CA's x two industries x six types of occupations x two time periods). For (2), (3), and (4), N=1,464(122 CMA/CA's x six types of occupations x two time periods). The dependent variable is the annual percentage-point change in the employment rate within a
CMA/CA over the 1991-2001 and 2001-2011 periods. In columns (2) and (3), the dependent variable is the annual percentage-point change in the ratio ofsectoral employment to the total working-age population within a CMA/CA over the 1991-2001 and 2001-2011 periods and for occupation in the six skill groups
in each sector. In all specification, we include period, region dummies, and the locality's initial manufacturing employment share interacted with skill dummies.
Standard errors in parentheses are clustered on 122 CMAs/CAs.
* p<0.10** p <0.05*** p<0.0149

2. Implied employment effects.

In this section, we summarize the implied employment effects computed based on theestimated coefficients analyzed in the previous section. Specifically, we assess the implied
employment effect by skill level and skill type based on Equation (13).
The total implied employment effect for each gender is reported in Table 17 and Table
17-1. The total implied effect in all industries across CMAs/CAs is -138.0 thousand for female
and -90.5 thousand for male over the full 1991-2011 span. In other words, total employment for
male would have increased by 5.4 per cent more over the period had there been no Chinese
import shock (given other factors are held constant). For females, the employment would havegrown by 6.5 per cent more without the China shock. Of the total implied effect over the full
1991-2011 period, a loss of 65.4 thousand and 96.0 thousand occurred during the 2001-2011
period for males and females respectively. This implies that, over the 2001-2011 period, the total
employment would have grown by 7.5 per cent more for males and 9.0 per cent more for females
without the China shock. In any case, the net job loss was greater for females in both absoluteand relative terms.
How is the aggregate job loss distributed across different skill levels? Let us focus on the
period in which Chinese import penetration rose significantly (i.e. 2001-2001). During thisperiod, low-skilled occupations for females had a net job loss of 131.1 thousand while male lowskilled occupations had a net loss of 89.4 thousand. To put it in a context, we estimate thatfemale low-skilled employment would have grown by 73.5 per cent more over this period if they
had not been hit by local trade shocks. On the other hand, the employment in male low-skilledoccupations would have grown by 36.6 per cent more without the shocks.
We estimate that female production occupations experienced a net job loss of 204.5
thousand across all industries in CMAs/CAs in Canada during the 2001-2001 period (see Table
17 and Table 17-1). On the other hand, males had a loss of 84.3 thousand in production jobs.
Note that the employment in production declined for both genders over the 2001-2011 period.
During this period, production employment declined by 213.8 thousand for males and by 141.8
thousand for females. This implies that China can explain about 39.4 per cent of the total decline
in jobs of males in production. For females, trade-induced job loss is greater than the actual
decline. Had there been no change in Chinese import penetration, then the production
employment would have increased by 63.5 thousand for females in production.
A larger absolute and relative job loss for female production can be partly attributed tounsuccessful labour reallocation for them. Males were able to have somewhat successful
reallocation to production occupations in non-manufacturing in response to a rise in local trade
exposure. Although the reallocation did not fully offset the job loss in manufacturing, it
mitigated the loss to a significant extent.
Females also experienced a job loss of 23.6 thousand in trades/construction/transportation
due to China during the 2001-2011 period while males experienced a job gain (but based on a
statistically insignificant coefficient). As we show in the previous subsection, this is due to the50

fact that the labour reallocation to this group in unaffected sectors was completely inhibited bynegative demand effects for females. The reallocation to unaffected sectors for males was quite
successful.
We found statistical evidence that females also experienced an aggregate job loss in thefollowing skill types: Technical/paraprofessional - a loss of 3.6 thousand (78.3 per cent of thetotal decline); Other services - a loss of 15.4 thousand jobs (35.2 per cent of the total decline).
We found no statistical evidence that males in these groups were affected by rising Chinese
import penetration.
In summary, the greater aggregate job loss for females can be attributed to not only larger
marginal impacts estimated for them but also the unsuccessful labour reallocation to unaffected
sectors. The negative effect on male production employment in manufacturing was partly offset
by the job gain in non-manufacturing due to the labour reallocation. However, we find nostatistical evidence that this was true for females. For female, the labour reallocation to
production occupations in non-manufacturing was completely inhibited by the negative local
demand effect. Additionally, our estimates imply that the female reallocation to
trades/construction/transportation in non-manufacturing was also completely inhibited bynegative demand effects operating within local labour markets. For males, the reallocation to thatskill group was quite successful. In contrast, we find no evidence for the gender difference in the
degree of labour reallocation in the skill level dimension.

51

Table 17: Implied Employment Changes Induced by Changes in Chinese Import Penetration, thousand, Male, All Industries, Canada
Counterfactual ∆Actual ∆Implied Employment EffectOccupation Group(s)in employment levelin employment level1991199119911991200119911991200119912001
2001
2011
2001
2011
2011
2001
2011
2011
(1) All occupations

755.1

942.4

1781.2

730.0

877.0

1690.7

-25.1

-65.4

-90.5

High-skilled

327.6

290.6

621.9

329.1

294.6

627.4

1.5

4.0

5.5

Mid-skilled

156.2

378.4

553.2

163.9

398.5

581.0

7.7

20.1

27.8

Low-skilled

271.3

333.7

522.4

236.9

244.3

398.6

-34.4

-89.4

-123.8

Management

92.8

82.8

159.5

86.1

65.4

135.4

-6.7

-17.4

-24.1

Professional

86.5

174.5

266.8

88.9

180.8

275.5

2.4

6.3

8.7

Technical/Paraprofessional

256.0

205.0

477.2

262.7

222.5

501.4

6.7

17.5

24.2

Other services

111.9

341.4

443.8

108.0

331.2

429.7

-3.9

-10.2

-14.1

Trades/Construction/Transportation

111.4

250.7

383.2

120.2

273.5

414.8

8.8

22.8

31.6

(2) By Skill Level(3) By Skill Type

Production
96.4-129.5-33.1
64.0-213.8-149.8-32.4-84.3-116.7
Note: Counterfactual changes represent the changes in employment level if there had been no change in Chinese import penetration. Following Acemoglu et al.
(2016) and Murray (2017), the quantities in row (1) - row (3) is computed based on both statistically significant and insignificant coefficients from thecorresponding stacked models. Predictions for 1991-2011 is equal to the sum of the predictions for the two sub-periods.

52

Table 17-1: Implied Employment Changes Induced by Changes in Chinese Import Penetration, thousand, Female, All Industries, Canada
Implied Employment Effect
Counterfactual ∆Actual ∆Occupation Group(s)in employment levelin employment level1991199119911991200119911991200119912001
2001
2011
2001
2011
2011
2001
2011
2011
(1) All occupations

1096.91165.72262.61054.91069.72124.6

-42.0

-96.0

-138.0High-skilled

421.5

455.4

876.9

442.8

504.0

946.8

21.3

48.6

69.9

Mid-skilled

272.3

400.8

673.1

266.4

387.3

653.7

-5.9

-13.5

-19.4

Low-skilled

403.0

309.4

712.4

345.7

178.3

524.0

-57.3

-131.1-188.4

Management

144.7

50.3

195.0

170.3

108.9

279.2

25.6

58.6

84.2

Professional

285.8

429.2

715.0

283.7

424.5

708.2

-2.1

-4.7

-6.8

213.7

248.7

462.4

224.9

274.2

499.1

11.2

25.5

36.7

Other services

275.3

346.3

621.7

298.4

399.0

697.5

23.1

52.7

75.8

Trades/Construction/Transportation

38.7

27.6

66.3

28.4

4.0

32.4

-10.3

-23.6

-33.9

(2) By Skill Level(3) By Skill TypeTechnical/Paraprofessional

Production
138.6
63.5
202.1
49.2
-141.0-91.8-89.4-204.5-293.9Note: Counterfactual changes represent the changes in employment level if there had been no change in Chinese import penetration. Following Acemoglu et al.
(2016) and Murray (2017), the quantities in row (1) - row (3) is computed based on both statistically significant and insignificant coefficients from thecorresponding stacked models. Predictions for 1991-2011 is equal to the sum of the predictions for the two sub-periods.

53

VII.

Conclusion

This report estimates the impact of the Chinese import shock on Canadian labour markets
over the period 1991-2011. By constructing a measure of occupation-specific trade exposure, we
focus on differential employment effect by gender across distinct occupational groups bothwithin manufacturing in Canada and the broader industrial sectors within CMAs/CAs. An
instrumental variable strategy is employed to deal with potential endogeneity of Canada trade
exposure. This way, we capture the causal impact of Chinese import penetration on Canadian
employment.
In this report we estimate that within manufacturing, females lost more jobs than males
did in relative terms. Females experienced a trade-induced job loss of 36.1 thousand which
accounts for 21.3 per cent of the total decline in female employment in manufacturing during thisperiod. Males experienced a loss of 56.8 thousand jobs which accounts for 16.8 per cent of thetotal decline in male employment in manufacturing.
We find that gender differences are also evident within skill groups. When analyzed byskill level, we find that a trade-induced job loss was statistically significant for only low-skilledoccupations. Although the trade-induced job loss was equally distributed between males andfemales, females had a proportionally larger loss. Low-skilled occupations had a loss of 42.4
thousand for females and a loss of 42.9 thousand for males. The loss accounts for 31.9 per centof the total decline in low-skilled jobs of women and 21.3 per cent of the total decline in lowskilled jobs of men.
When analyzed by skill type, we find that rising Chinese import competition had statisticallysignificant effects on the employment in the following skill types:
Production - a loss of 24.3 thousand jobs for females and 5.8 thousand for males (21.6
per cent of the total decline in jobs of women in production and 3.0 per cent of the total
decline in jobs of men in production);Technical/paraprofessional - a loss of 6.2 thousand for females (if no trade shock, wewould have seen an increase of 1.6 thousand instead of a decline of 6.1 thousand) and
4.1 thousand for males (25.8 per cent of the total job losses of men with theseoccupations);

Other services - a loss of 16.5 thousand jobs for females and 2.2 thousand jobs for males(37.7 per cent for women with these occupations, compared to 9.7 percent for men).

Again, females tend to have a proportionally larger job loss than males.

54

By exploiting variations in local employment rates and local trade exposure across 122
CMAs/CAs in Canada, we also assess the effects of labour reallocation and demand effects
operating within localities. We find that the labour reallocation effect proved important inoffsetting the negative direct effects but the degree of reallocation within local labour markets
varies across gender.
We find that for females, the labour reallocation to production andtrades/construction/transportation occupations in unaffected sectors appears to be fully inhibitedby the negative local demand effect. For males, the negative demand effect on those occupationalgroups were offset by the labour reallocation to unaffected sectors, therefore mitigating thenegative employment effect of rising Chinese import penetration. As a result, the total job loss inthese two groups was much larger for females in both absolute and relative terms.

References
Acemoglu, Daron, David H. Autor, David Dorn, Gordon H. Hanson, and Brendan Price (2016)"Import Competition and the Great US Employment Sag of the 2000s," Journal of Labor
Economics, Vol. 34, No. S1, Part 2, pp. S141-S198
Autor, David H., David Dorn and Gordon H. Hanson (2013) "The China Syndrome: Local Labor
Market Effects of Import Competition in the United States," American Economic Review, Vol.
103, No. 6, pp. 2121-2168
Autor, David H. and David Dorn (2013) "The Growth of Low-Skill Service Jobs and thePolarization of the U.S. Labour Market," American Economic Review, Vol.103, No.5, pp15531597
Autor David H., David Dorn, Gordon H. Hanson, Gary Pisano, and Pian Shu (2017) "Foreign
Competition and Domestic Innovation: Evidence from U.S. Patents," MIT Working Paper,
February
Balsvik, Ragnhild, Sissel Jensen, and Kjell G. Salvanes (2015) "Made in China, Sold in Norway:
Local Labour Market Effects of an Import Shock," Journal of Public Economics, Vol. 127,
pp137-144
Becker, Sascha O., Karolina Ekholm, Marc-Andreas Muendler(2013), "Offshoring and the
Onshore Composition of Tasks and Skills," Journal of International Economics, Vol. 90, No.1,
pp. 91-106
Ebenstein, Avraham, Ann Harrison, Margaret McMillan, and Shannon Phillips (2014)"Estimating the Impact of Trade and Offshoring on American Workers Using the Current
Population Surveys," The Review of Economics and Statistics, Vol.96 ,No.4, pp.581-595
Goldsmith-Pinkham, Paul, Isaac Sorkin, and Henry Swift (2018), "Bartik Instruments: What,
When, and How," National Bureau of Economic Research, Working Paper 24408, March 201855

Hakkala, Katriina Nilsson, KristiinaHuttunen (2016), "Worker-Level Consequences of Import
Shocks," the Institute for the Study of Labour Discussion Paper, No.10033, July.
Hummels, David, RasmusJørgensen, Jakob Munch, and Chong Xiang (2014) "The Wage Effectsof Offshoring Evidence from Danish Matched Worker-Firm Data," American Economic Review,Vol.104, No.6, pp. 1597-1629
Kim, Myeongwan (2018a) "Rising Import Competition in Canada and its Employment Effect bySkill Group: Evidence from the 'China Shock'," CSLS Research Report 2018-02, August.
http://www.csls.ca/reports/csls2018-02.pdf
Koopman, Robert and Zhi Wang (2008) "How Much of Chinese Exports is Really Made in
China?: Assessing Foreign and Domestic Value-Added in Gross Exports," Working Paper, 200803-B. Washington D.C.: Office of Economics, U.S. International Trade Commission
Murray, Alexander (2017) "The Effect of Import Competition on Employment in Canada:
Evidence from the 'China Shock'," CSLS Research Report 2017-03, July.
http://www.csls.ca/reports/csls2017-03.pdf

56

VIII.

Appendix: Additional Tables and Charts
Table A1: Occupation group classification, skill level and skill type(1)
Skill TypeManagement

Professional

Technical andparaprofessional(2)
Stats Can/HRSDC
re-classification

Management

Professional

Technical andparaprofessional

Administration andadministrative
supportOther services
Sales

(3)
2-digit NOC(4)
Skill Level

00 Senior management occupations
01-05 Specialized middle management
occupations
06 Middle management occupations inretail and wholesale trade and customer
services
07-09 Middle management occupations in
trades, transportation, production andutilities
11 Professional occupations in businessand finance
21 Professional occupations in natural andapplied sciences
30 Professional occupations in nursing
31 Professional occupations in health(except nursing)
40 Professional occupations in education
services
41 Professional occupations in law andsocial, community and government
services
51 Professional occupations in art andculture22 Technical occupations related tonatural and applied sciences
32 Technical occupations in health
42 Paraprofessional occupations in legal,social, community and education services
43 Occupations in front-line public
protection services
52 Technical occupations in art, culture,
recreation and sport
12 Administrative and financial
supervisors and administrative
occupations
13 Finance, insurance and related businessadministrative occupations
14 Office support occupations
15 Distribution, tracking and schedulingco-ordination occupations
62 Retail sales supervisors and specialized
sales occupations
64 Sales representatives and salespersons- wholesale and retail trade

Skill level A
Skill level A

57

Skill level A

Skill level A

Skill level A
Skill level A
Skill level A
Skill level A
Skill level A
Skill level A

Skill level A
Skill level B
Skill level B
Skill level B
Skill level B
Skill level B
Skill level B

Skill level B
Skill level C

Skill level B
Skill level C

Personal andcustomer
information
services

Industrial,construction andequipment
operation trades
Trades,construction, andtransportation
Workers andlabourers intransport andconstruction

Natural resources,
agriculture andrelated production
occupations

66 Sales support occupations
63 Service supervisors and specialized
service occupations
65 Service representatives and othercustomer and personal services
occupations
67 Service support and other service
occupations, n.e.c.
34 Assisting occupations in support ofhealth services
44 Care providers and educational, legal
and public protection support occupations
72 Industrial, electrical and construction
trades73 Maintenance and equipment operation
tradesSkill level D
Skill level B

74 Other installers, repairers and servicers
and material handlers
75 Transport and heavy equipment
operation and related maintenanceoccupations
76 Trades helpers, construction labourers
and related occupations

Skill level C

82 Supervisors and technical occupationsin natural resources, agricultural andrelated production
84 Workers in natural resources,
agriculture and related production
86 Harvesting, landscaping and natural
resources labourers

Skill level C

Skill level D
Skill level C
Skill level C
Skill level B
Skill level B

Skill level C

Skill level D

Skill level B

Skill level C
Skill level D

Production
92 Processing, manufacturing and utilities Skill level B
supervisors and central control operators
Occupations in
94 Processing and manufacturing machine Skill level C
manufacturing and operators and related production workers
utilities
95 Assemblers in manufacturing
Skill level C
96 Labourers in processing,
Skill level D
manufacturing and utilities
Note: We choose to display 2-digit occupations due to the space limit. In this report, we re-classify
individual 4-digit occupations belonging to each of the 2-digit occupations according to column (1)and column (4). In column (1), we aggregate the ten skill types in column (2) to have 5 types.
Source: Column (2)-(4) are based on a variant of NOC available at Statistics Canada website.
http://www.statcan.gc.ca/eng/subjects/standard/noc/2011/index

58

Table A2: Occupation-Level Changes in Employment and Chinese Import Penetration Ratio, by Skill-Level, Male, Manufacturing Industries, 19912011 by sub-period, Canada
1991-2001
High-skilled

Mid-skilled

Low-skilled

Mean/Median

Mean/Median

Mean/Median

Annual ∆ in Chinese Import Penetration (% pt)

0.40 / 0.42

0.34 / 0.26

0.34 / 0.30

Instrument for Chinese Import Penetration (% pt)

0.25 / 0.26

0.22 / 0.18

0.23 / 0.16

100 x Annual log change in Employment (%)-1.77 / 0.23

-0.92 / 1.05

-0.66 / 0.58

2001-2011
High-skilled

Mid-skilled

Low-skilled

Mean/Median

Mean/Median

Mean/Median

Annual ∆ in Chinese Import Penetration (% pt)

0.73 / 0.87

0.56 / 0.59

0.63 / 0.64

Instrument for Chinese Import Penetration (% pt)

0.76 / 0.92

0.59 / 0.55

0.65 / 0.55

100 x Annual log change in Employment (%)-1.80 / -2.20-2.63 / -2.41-3.52 / -3.85

1991-2011 stacked
High-skilled

Mid-skilled

Low-skilled

Mean/Median

Mean/Median

Mean/Median

Annual ∆ in Chinese Import Penetration (% pt)

0.57 / 0.48

0.45 /0.36

0.48 / 0.33

Instrument for Chinese Import Penetration (% pt)

0.51 / 0.30

0.40 / 0.23

0.44 / 0.21

100 x Annual log change in Employment (%)-1.79 / -1.27-1.77 / -1.62-2.08 / -1.83
Note: The annual change in Chinese import exposure is 100 x annual change in import penetration for occupation 𝑘 in a given skill group. The instrument is 100
x annual change in import penetration for occupation 𝑘 based on the average annual absolute change in imports from China in a set of eight comparator countries
over the period indicated. The comparator countries are Australia, Denmark, Finland, Germany, Japan, New Zealand, Spain and Switzerland. Annual growth in
employmentis the annualized per cent change in employment level for each 494 four-digit occupations between 1991-2001 and 2001-2011 based on data fromthe 1991 and 2011 census and the 2011 National Household Survey. Observations are weighted by occupation-level employment in 1991.

59

Table A2-1: Occupation-Level Changes in Employment and Chinese Import Penetration Ratio, by Skill-Level, Female, Manufacturing Industries, 19912011 by sub-period, Canada
1991-2001
High-skilled

Mid-skilled

Low-skilled

Mean/Median

Mean/Median

Mean/Median

Annual ∆ in Chinese Import Penetration (% pt)

0.51 / 0.49

0.46 / 0.42

0.43 / 0.39

Instrument for Chinese Import Penetration (% pt)

0.36 / 0.33

0.30 / 0.25

0.32 / 0.25

100 x Annual log change in Employment (%)

1.12 / 3.73

1.81 / 3.05

0.46 / 1.42

2001-2011
High-skilled

Mid-skilled

Low-skilled

Mean/Median

Mean/Median

Mean/Median

Annual ∆ in Chinese Import Penetration (% pt)

0.79 / 1.20

0.89 / 0.80

0.82 / 0.74

Instrument for Chinese Import Penetration (% pt)

0.85 / 1.24

0.93 / 0.80

0.85 / 0.75

100 x Annual log change in Employment (%)-1.08 / -1.13-3.00 / -2.41-4.25 / -3.84

1991-2011 stacked
High-skilled

Mid-skilled

Low-skilled

Mean/Median

Mean/Median

Mean/Median

Annual ∆ in Chinese Import Penetration (% pt)

0.65 / 0.67

0.67 /0.55

0.63 / 0.47

Instrument for Chinese Import Penetration (% pt)

0.61 / 0.52

0.62 / 0.33

0.58 / 0.34

100 x Annual log change in Employment (%)
0.04 / 0.05
-0.56/ -0.39-1.88 / -0.96
Note: The annual change in Chinese import exposure is 100 x annual change in import penetration for occupation 𝑘 in a given skill group. The instrument is 100
x annual change in import penetration for occupation 𝑘 based on the average annual absolute change in imports from China in a set of eight comparator countries
over the period indicated. The comparator countries are Australia, Denmark, Finland, Germany, Japan, New Zealand, Spain and Switzerland. Annual growth in
employmentis the annualized per cent change in employment level for each 494 four-digit occupations between 1991-2001 and 2001-2011 based on data fromthe 1991 and 2011 census and the 2011 National Household Survey. Observations are weighted by occupation-level employment in 1991.

60

Table A3: Occupation-Level Changes in Employment and Chinese Import Penetration Ratio, by Skill-Type, Male, Manufacturing Industries, 1991-2011 by subperiod, Canada
1991-2001
Management

Professional

Technical andParaprofessional

Other services

Trades, Construction,
Transportation

Production

Mean/Median

Mean/Median

Mean/Median

Mean/Median

Mean/Median

Mean/Median

Annual change in Chinese Import Penetration (% pt)

0.41 / 0.43

0.32 / 0.33

0.53 / 0.39

0.38 /0.35

0.21 / 0.18

0.37 / 0.21

Instrument for Chinese Import Penetration (% pt)

0.26 / 0.27

0.20 / 0.22

0.31 / 0.23

0.27 / 0.21

0.12 / 0.12

0.28 / 0.14

100 x Annual log change in Employment (%)-2.00 / -1.05-7.25 / -1.71

1.37 / 2.86

-5.21 / -3.64-0.18 / 1.91

2.14 / 2.75

Management

Professional

Technical andParaprofessional

Other services

Trades, Construction,
Transportation

Production

Mean/Median

Mean/Median

Mean/Median

Mean/Median

Mean/Median

Mean/Median

Annual change in Chinese Import Penetration (% pt)

0.85 / 0.91

-0.04 / 0.51

0.91 / 0.88

0.71 / 0.76

0.33 / 0.46

0.62 / 0.41

Instrument for Chinese Import Penetration (% pt)

0.88 / 0.97

-0.03 / 0.55

0.97 / 0.82

0.77 / 0.77

0.30 / 0.42

0.65 / 0.38

100 x Annual log change in Employment (%)-2.54 / -2.40-0.13 / -1.32-1.52 / -1.27-2.43 / -2.38-2.36 / -2.41-4.50 / -4.27

Trades, Construction,
Transportation

Production

2001-2011

Management

Professional

1991-2011 stacked
Technical andParaprofessional Other services

Mean/Median

Mean/Median

Mean/Median

Mean/Median

Mean/Median

Mean/Median

Annual change in Chinese Import Penetration (% pt)

0.63 / 0.48

0.14 / 0.33

0.72 / 0.56

0.55 / 0.43

0.27 / 0.22

0.48 / 0.28

Instrument for Chinese Import Penetration (% pt)

0.57 / 0.30

0.08 / 0.22

0.64 / 0.39

0.52 / 0.30

0.21 / 0.13

0.45 / 0.19

100 x Annual log change in Employment (%)-2.27 / -1.48-3.77 / -1.71-0.06 / -0.03-3.83 / -3.64-1.27 / -1.83-1.18 / -0.03
Note: The annual change in Chinese import exposure is 100 x annual change in import penetration for occupation 𝑘 in a given skill group. The instrument is 100 x annualchange in import penetration for occupation 𝑘 based on the average annual absolute change in imports from China in a set of eight comparator countries over the period
indicated. The comparator countries are Australia, Denmark, Finland, Germany, Japan, New Zealand, Spain and Switzerland. Annual growth in employmentis the annualized
per cent change in employment level for each 494 four-digit occupations between 1991-2001 and 2001-2011 based on data from the 1991 and 2011 census and the 2011
National Household Survey. Observations are weighted by occupation-level employment in 1991.

61

Table A3-1: Occupation-Level Changes in Employment and Chinese Import Penetration Ratio, by Skill-Type, Female, Manufacturing Industries, 1991-2011 by
sub-period, Canada
1991-2001
Management

Professional

Technical andParaprofessional

Other services

Trades, Construction,
Transportation

Production

Mean/Median

Mean/Median

Mean/Median

Mean/Median

Mean/Median

Mean/Median

Annual change in Chinese Import Penetration (% pt)

0.54 / 0.60

0.35 / 0.39

0.59 / 0.47

0.46 /0.41

0.41 / 0.38

0.43 / 0.32

Instrument for Chinese Import Penetration (% pt)

0.40 / 0.44

0.24 / 0.25

0.37 / 0.32

0.34 / 0.27

0.24 / 0.25

0.32 / 0.17

100 x Annual log change in Employment (%)

1.86 / 3.73

-7.35 / -0.14

4.24 / 5.38

-4.54 / -3.11

3.44 / 3.40

3.38 / 4.29

Management

Professional

Technical andParaprofessional

Other services

Trades, Construction,
Transportation

Production

Mean/Median

Mean/Median

Mean/Median

Mean/Median

Mean/Median

Mean/Median

1.11 / 1.20

-0.53 / 0.63

1.07 / 1.20

0.80 / 0.78

0.81 / 0.83

0.86 / 0.54

2001-2011

Annual change in Chinese Import Penetration (% pt)
Instrument for Chinese Import Penetration (% pt)

1.21 / 1.24

-0.59 / 0.69

1.18 / 1.18

0.88 / 0.78

0.77 / 0.80

0.89 / 0.45

100 x Annual log change in Employment (%)-1.29 / -1.13-0.01 / -0.58-1.34 / -1.20-3.02 / -2.63-2.48 / -1.90-5.62 / -4.93

Trades, Construction,
Transportation

Production

Management

Professional

1991-2011 stacked
Technical andParaprofessional Other services

Mean/Median

Mean/Median

Mean/Median

Mean/Median

Mean/Median

Mean/Median

Annual change in Chinese Import Penetration (% pt)

0.83 / 0.68

-0.09 / 0.39

0.83 / 0.64

0.63 / 0.56

0.61 / 0.55

0.64 / 0.39

Instrument for Chinese Import Penetration (% pt)

0.80 / 0.52

-0.18 / 0.25

0.77 / 0.39

0.61 / 0.48

0.51 / 0.33

0.61 / 0.30

100 x Annual log change in Employment (%)
0.30 / 0.29
-3.88 / -0.58
1.46 / 0.52
-3.78 / -2.63
0.53 / -0.35-1.09 / 0.10
Note: The annual change in Chinese import exposure is 100 x annual change in import penetration for occupation 𝑘 in a given skill group. The instrument is 100 x annualchange in import penetration for occupation 𝑘 based on the average annual absolute change in imports from China in a set of eight comparator countries over the period
indicated. The comparator countries are Australia, Denmark, Finland, Germany, Japan, New Zealand, Spain and Switzerland. Annual growth in employmentis the annualized
per cent change in employment level for each 494 four-digit occupations between 1991-2001 and 2001-2011 based on data from the 1991 and 2011 census and the 2011
National Household Survey. Observations are weighted by occupation-level employment in 1991.

62

Chart A1: Annualized employment growth and annual change in import penetration
ratio, 3-digit occupations, Male, Manufacturing, Canada, 2001-2011

Source: Author's calculation based on the online trade data base maintained by Innovation, Science, andEconomic Development Canada and the 1991 and 2001 censuses and 2001 National Household Survey.

Chart A2: Annualized employment growth and annual change in import penetration
ratio, 3-digit occupations, Female, Manufacturing, Canada, 2001-2011

Source: Author's calculation based on the online trade data base maintained by Innovation, Science, andEconomic Development Canada and the 1991 and 2001 censuses and 2001 National Household Survey.

63