WORKERS BENEATH THE FLOODGATES: LOW-WAGE IMPORT - 麻省理工学院人工智能研究专业

WORKERS BENEATH THE FLOODGATES: LOW-WAGE IMPORT
COMPETITION AND WORKERS’ ADJUSTMENT

Hale Utar*

Abstract—Using employee-employer matched data, I analyze the impact of
a low-wage trade shock on manufacturing workers in a high-wage country,
丹麦, and how they adjust to the shock over a decade. I derive causal
effects by exploiting the dismantling of the Multiﬁber Arrangement quotas
on products from China upon its WTO accession as a quasi-natural experi-
ment and use within-industry, within-occupation heterogeneity in workers’
exposure to this shock. I ﬁnd signiﬁcant negative long-run effects on earn-
ings and employment trajectories and identify job instability in the service
sector as a main adjustment friction, concentrated among workers with
manufacturing-speciﬁc education and occupation. The results establish the
importance of speciﬁc human capital in trade adjustment and provide evi-
dence of skill upgrading as workers rebuild lost human capital through
教育.

我.

介绍

MANUFACTURING jobs, once the main income source

for the middle class, are waning, and this causes
considerable anxiety in advanced countries. How workers
and society can best adjust are important topics of cur-
rent debate. Recent research has made great progress in
understanding the consequences of the rising trade with
low-wage countries on ﬁrms and industries and documented
signiﬁcant labor reallocation as a result (Bernard, 詹森,
& Schott, 2006; Khandelwal, 2010; Autor, Dorn, & Han-
儿子, 2013; Utar & Torres-Ruiz, 2013; Utar, 2014; Pierce
& Schott, 2016; Bloom, Draca, & Van Reenen, 2016). 但
labor does not reallocate instantaneously and costlessly, 作为
predicted by traditional trade theories. The salient question
is what happens to workers when they are displaced from
their workplaces due to import competition from low-wage
countries.1 If workers can efﬁciently switch to another job
within the same industry, the earnings (and broader welfare)
consequences are small. But what options are available to
manufacturing workers when facing low-wage import com-
请愿? Are the possible paths of adjustment different for
workers depending on their individual investments in human
首都, reﬂected in their education and occupation, 以及如何
do these differences affect the cost of adjustment?

Received for publication November 13, 2015. Revision accepted for

publication December 18, 2017. Editor: Amit K. Khandelwal.

* Bielefeld University and CESIfo.
The study is sponsored by the Labor Market Dynamics and Growth Cen-
ter at the University of Aarhus. Support of the Department of Economics
and Business, Aarhus University and Statistics Denmark are acknowledged
with appreciation. I am grateful to Henning Bunzel for his support and thank
Amit Khandelwal (the editor), two anonymous referees, Wolfgang Keller,
Casper Thorning, and the participants of various seminars and conferences
for comments and suggestions. The data source used for all ﬁgures and
tables is Statistics Denmark.

A supplemental appendix is available online at http://www.mitpress

journals.org/doi/suppl/10.1162/rest_a_00727.

1 Job displacement due to plant downsizing can have a lasting negative
effect on workers’ earnings for years after the event and can even have
nonpecuniary effects, such as reduced life expectancy (Jacobson, LaLonde,
& Sullivan, 1993; Sullivan & von Wachter, 2009).

Addressing this, I study the impact of a Chinese import
shock on workers’ earnings and employment trajectories
in a high-wage country, 丹麦, and study workers’
adjustment in a quasi-natural experiment that measures the
causal effects of a trade policy change affecting a classic
manufacturing industry. China beneﬁted from trade liber-
alization in the form of import quota removals in textiles
upon entry into the World Trade Organization (WTO). 这
event constitutes a suitable setting in which to study the
effect of Chinese import competition.2 By using longitudi-
nal employee-employer matched data from 1999 到 2010
that follows individuals from job to job, sector to sec-
托尔, but also in and out of education or unemployment, 我
provide a true-to-life documentation of manufacturing work-
ers’ adjustment to the trade shock over the decade that
如下.

I measure the exposure to the trade shock at the indi-
vidual
等级. I ﬁrst use detailed product and ﬁrm-level
domestic production data to identify ﬁrms domestically pro-
ducing products subject to import quotas for China. 这
matched employee-employer data allow me to identify work-
ers employed in ﬁrms that will subsequently be hit by a surge
of cheaper imports from China. I then measure differential
labor market trajectories of the exposed workers relative to
other workers initially employed in the same industry after
controlling for potentially unobserved worker and workplace
characteristics and aggregate shocks by worker and time
ﬁxed effects.

Technological forces are important among factors that
cause decline in manufacturing employment in advanced
国家 (Machin & Van Reenen, 1998). Especially labor-
intensive industries have been restructuring since the 1960s
due to factors that include both low-wage competition and
technological changes. The empirical strategy in this paper
disentangles the effects of the trade shock from potentially
important technology and demand factors by directly utiliz-
ing a discrete change in trade policy and within-industry,
within-occupation heterogeneity in exposure to the resulting
import competition.

I show that increased competition with China leads to
substantial earnings reductions, averaging 89% 工作的-
ers’ initial annual wage over the nine years after the ﬁrst
removal of quotas for China. The effect on earnings is mainly
due to reduction in hours worked instead of hourly wages,
which is consistent with a Danish labor market combining

2 The plausibly exogenous increase in import competition due to removal
of the Multi-ﬁber Arrangement quotas for China has been used as an iden-
tiﬁcation strategy before at the industry (Bloom et al., 2016) or ﬁrm (Utar,
2014) 等级. See also Harrigan and Barrow (2009) and Khandelwal, Schott,
and Wei (2013) for price and productivity consequences of the event.

The Review of Economics and Statistics, 十月 2018, 100(4): 631–647
© 2018 由哈佛大学和麻省理工学院的校长和研究员撰写. 根据知识共享署名发布 4.0
国际的 (抄送 4.0) 执照
土井:10.1162/rest_a_00727

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632

THE REVIEW OF ECONOMICS AND STATISTICS

U.S.-style liberal hiring-ﬁring regulations with a high degree
of unionization.3

Workers exposed to the competition face a higher like-
lihood of unemployment and shorter future employment
spells. The trade shock leads to displacement from the ﬁrm
exposed to the competition and subsequent job instability.
The initial impact of trade is fairly homogeneous across
workers regardless of education or occupation. Whether a
secretary, machine operator, or manager at the exposed ﬁrm
and whether college educated or not, the trade shock affects
workers similarly at the exposed ﬁrm, causing an average
reduction in length of employment of more than a full year
over the nine years following. For workers of all educations
and occupations, the growing service sector provides the
most viable path to new employment, and the trade shock
signiﬁcantly increases the likelihood of moving there for all
types of workers. But after the move from manufacturing
to the service sector, workers’ paths of adjustment diverge,
resulting in very heterogeneous long-run outcomes. 大学-
educated workers fully recover the initial earnings losses,
but high school–educated workers suffer cumulative earn-
ings losses of 143% of a preshock annual wage over the
十年.

This paper is part of the recent literature that docu-
ments the role of low-wage country trade in the evolution
of industry and labor markets in advanced economies and
is most closely related to worker-level studies document-
ing trade adjustment costs.4 Autor et al. (2014) provide the
ﬁrst worker-level study on Chinese import competition and
document that American workers under direct threat from
Chinese import competition have lower cumulative earnings
and higher risk of exiting the labor force. The costs of adjust-
蒙特, they ﬁnd, are disproportionately borne by low-wage
工人, who stay within manufacturing, while high-wage
workers have a higher likelihood of moving out of manu-
facturing and adjust successfully. Their results imply that
a necessary condition for a successful adjustment is being
able to move out of manufacturing. But their results do not
answer whether the costs of adjustments are limited to the
frictions that slow or prevent workers’ move to new sec-
tors and whether moving out of manufacturing in itself is
a sufﬁcient condition for a smooth recovery.5 Studying the
experience of workers in a European country with active
labor market policies (ALMP) where full-time employment
outside manufacturing is within reach for all types of work-
呃, I show that adjustment costs are substantial even after
moving out of manufacturing to the service sector. 的确

3 The Global Competitiveness Report 2013–2014 ranks Denmark sixth
之中 148 countries at hiring and ﬁring practices, indicating a very dereg-
ulated market (the United States is ranked 9th in the same ranking), 尽管
it is ranked 93rd for ﬂexibility of wage determination.

4 Studies also document wage changes in response to the recent wave
of globalization within ﬁrms (Hummels et al., 2014) or within local labor
市场 (Hakobyan & McLaren, 2016).

5 Their results raise the question of why the transition out of manufactur-
ing is easier for high-wage workers than for low-wage workers and what
underlying characteristics of workers drive the difference.

it is the costs incurred after moving to the service sector
that determine the differences in workers’ outcome over the
medium to long term. And workers’ initial investment in
human capital as reﬂected in education and occupation plays
a major role in determining the distribution of these costs.
A decade after the trade shock, a typical machine opera-
tor’s earnings loss remains at one year’s annual wage, 尽管
a typical secretary fully recovers earnings despite the same
impact to both occupations at the exposed ﬁrm.

I ﬁnd that the ﬁeld of education, independent of educa-
tion level, is also an important determinant of adjustment
成本. Workers with manufacturing-focused vocational edu-
cation face short-term frequent unemployment spells in the
service sector, while workers with service-speciﬁc voca-
tional education fully avoid trade-induced unemployment.
The adjustment problems persist for workers who lose a sub-
stantial part of their human capital in their new environment,
and the trade adjustment costs are dominated by forgone
human capital speciﬁc to the initial industry. The results
overall show that human capital speciﬁcity, 和特别之处-
larly speciﬁcity to manufacturing, is the main determinant of
workers’ cost of adjustment to an import shock from China.
Motivated by trade liberalization episodes in developing
countries with rigid markets, much of the trade adjustment
literature focuses on mobility frictions that slow down or
prevent resources from allocating efﬁciently in the new envi-
ronment.6 Focusing on labor reallocation in response to trade
liberalization and employing empirical structural models,
some studies aim at recovering mobility costs that workers
face to switch sectors (Artuç, Chaudhuri, & McLaren, 2010;
Dix-Carneiro, 2014) or analyze the relationship between
trade and wage inequality in the presence of search frictions
(Helpman et al., 2014). Among them, this paper is most
related to Dix-Carneiro (2014), who introduces human capi-
tal with differential returns across sectors, ﬁnding substantial
heterogeneity in adjustment frictions across workers. 这
paper adds quasi-experimental evidence and shows that tak-
ing workers’ occupations into account is essential to capture
the full role of industry-speciﬁc human capital.7 Contrary to
what studies so far suggested, this paper shows that trade-
induced adjustment problems do not end once workers ﬁnd
full-time jobs in the growing sectors and brings to the light
a new facet of the nature of these frictions.8

6 See Goldberg and Pavcnik (2007) for a review. Recent examples include
Menezes-Filho and Muendler (2011), who use matched data to document
sluggish labor reallocation in response to trade liberalization in Brazil. Dix-
Carneiro and Kovak (2015) focus on regional dynamics and document
transition from the formal to the informal economy in response to trade
liberalization in Brazil.

7 While Dix-Carneiro (2014) ﬁnds a dominating role for moving frictions
in Brazil, a relative abundance of labor market frictions in Brazil in com-
parison to Denmark could be one reason for a larger role of moving barriers
那里.

8 In a study of structural change induced by trade, Keller and Utar (2016)
show a strong pattern of job polarization—decline in midlevel wage jobs
and increase in high- and low-wage jobs—in Denmark over 2000 到 2009.
They ﬁnd that import competition from China played an important role
in causing polarization. In a related study, Traiberman (2017) 估计

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WORKERS BENEATH THE FLOODGATES

633

The idea that the speciﬁc aspect of human capital could be
an important barrier to labor reallocation from shrinking sec-
tors to growing ones is not new. Since Becker (1964), 学习
focus on human capital that may be speciﬁc to ﬁrm, 行业,
and occupation (Topel, 1991; Neal, 1995; Parent, 2000; Pole-
taev & 罗宾逊, 2008; Kambourov & Manovskii, 2009).
This literature either looks at plant closings regardless of
reason or focuses on job switches that are endogenous to
characteristics of workers and their employers. Exploiting
the removal of import quotas that led to a decline in labor
要求, I advance this literature by offering a plausibly
exogenous driving force for job mobility. I ﬁnd that industry
and occupation speciﬁcity of human capital interact.9 Work-
ers’ occupations are a crucial determinant of trade-induced
adjustment costs depending on the degree to which occupa-
tions are speciﬁc to manufacturing. These results show that
focusing on the occupation or the industry component of job
switching may give an incomplete picture of the underlying
determinants of reallocation costs.

Since the right skill set to the new environment is impor-
tant to recover from the trade shock, I examine whether the
import shock leads to investment in human capital through
education.10 The trade shock does cause workers to seek fur-
ther education, and this effect is stronger for lower education
级别, but also with a higher level of mismatch of the ini-
tial education with the new sector. 因此, this paper shows
the ﬁrst direct evidence that trade with low-wage countries
can lead to skill upgrading at the individual level, 从而
potentially increasing the supply of skill.11

二. Empirical Framework and Worker-Level Data

The removal of Multi-Fiber Arrangement (MFA) quotas
for China is used as identiﬁcation strategy. This section
brieﬂy introduces this empirical framework, 显示如何
the removal of import quotas led to increased competition,
describes the data used, and provides information on the
Danish labor market. Further details are provided in the
online appendix.

A. The Surge of Import Competition from China

with the Quota Removals

The MFA was introduced in 1974 to govern the world
trade in textiles with the purpose of protecting high-wage
countries against competition from low-wage countries

a structural model of the Danish labor market and ﬁnds a large role for
occupational reallocation costs in response to lower import prices.

9 See Poletaev and Robinson (2008) for a related point.
10 Bartel and Sicherman (1998) show that technological change may
induce investment in human capital. Whether trade with low-wage coun-
tries alters the demand for skill in advanced countries and their offshore
locations is an important related question. Recent evidence supports skill
upgrading at the ﬁrm and establishment level (Bloom et al., 2016; Utar,
2014; Utar & Torres-Ruiz, 2013).

11 Atkin (2016) looks at a potential effect of trade on the supply of skill
from a different angle and shows that export expansion triggered by the
trade reforms in Mexico causes school dropouts.

through quantitative restrictions. 在 1995 it was agreed that
the MFA would gradually be lifted in so-called phases
of liberalization. But China’s non-WTO status rendered it
ineligible to beneﬁt from the liberalization, which changed
only when China had joined the WTO in December 2001.
The subsequent dramatic surge of Chinese textiles and cloth-
英 (时间&C) exports to Denmark and the resulting increase in
competition provides a plausibly exogenous source of shifts
in employment trajectories among Danish workers.

As one of the smaller members of the EU, the coverage
of quotas was largely exogenous to Denmark’s industrial
结构, as it was determined in EU-level negotiations
throughout the 1960s and 1970s. The empirical strategy
focuses on China because although the removal of the import
quotas started in 1995, phase I and II removals did not effec-
tively trigger increased competition. 这是因为, 首先, 这
law allowed the EU to choose the products to be integrated
into the normal system, and the EU started with inactive,
nonbinding quotas. 然后, among the exporting countries
subject to the MFA quotas, China stood out as facing the
largest number of quotas with the highest quota utilization
rates.12

There was considerable uncertainty as to whether the
negotiations for China’s WTO membership would succeed,
which they did in December 2001. In January 2002, China’s
quotas on phase I, 二, and III goods were removed immedi-
ately, leading to a dramatic surge in Chinese T&C imports
into the formerly protected countries. Now a WTO member,
China also beneﬁted from the last phase in January 2005.13
在 1998, China’s share of T&C import in Denmark was a
little over 10% 相比 2.8%, 0.7%, 和 1.3%, 重新指定-
主动地, for India, Pakistan and Indonesia—the countries with
the highest quota utilization after China. 数字 1 shows the
evolution in T&C import shares of China throughout 1999
到 2010 compared to the total shares of all other develop-
ing countries subject to MFA quotas. 经过 2010 China’s share
reached 32%, while the respective shares of India, 巴基斯坦,
and Indonesia were 7%, 1%, 和 0.3%. The line with circles
in ﬁgure 1 illustrates the magnitude of the shock by showing
the evolution of the value of Chinese imports in MFA goods
expressed in multiples of the 1999 total T&C value added,
which was around 1.1 billion current euros. The image of
ﬂoodgates opening is an apt one.14

12 Information on MFA quotas is reported in the Système Intégré de Ges-
tion de Licenses (SIGL) database of the European Commission and is
publicly available.

13 Due to a surge of Chinese imports at EU ports in the ﬁrst few months
的 2005 after the ﬁnal quota removal phase, the EU retained a few of the
quota categories until 2008. Since the sample period extends over 2008,
these quotas are also included in the current analysis.

14 Utar (2014) employs transaction-level import data and shows that the
MFA quotas were binding for China and both the 2002 和 2005 abolish-
ments caused a signiﬁcant surge of MFA goods from China in Denmark with
associated decline in unit prices of these goods. Khandelwal et al. (2013)
ﬁnd that Chinese export prices declined due to efﬁciency gains in China.
Misallocation of the quotas by the Chinese government during the MFA
regime played an important role in the subsequent surge of lower-priced
Chinese goods.

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634

THE REVIEW OF ECONOMICS AND STATISTICS

Figure 1.—Value of Chinese imports (Left Axis) and Import Shares of
China and Other Developing Countries Subject to MFA Quotas in
Danish Textile and Clothing Imports (Right Axis)

The values of total Chinese imports of MFA quota goods are expressed in units of the 1999 total T&C

value-added in Denmark.

乙. Employee-Employer Matched Data

The main database used in this study is the Integrated
Database for Labor Market Research (IDA) of Statistics
丹麦. It contains administrative records on all indi-
viduals between 15 和 74 years old and all jobs and
establishments that are active in the last week of Novem-
ber each year. The IDA database provides a yearly snapshot
of the labor market by reporting primary positions of each
individual living in Denmark as of November. For each
个人, I observe annual labor earnings, hourly wage,
annual hours worked, 行业, and occupation in the pri-
mary employment.15 I also observe workers’ highest attained
教育, 年龄, 性别, immigration status, personal income,
and total earnings from all jobs within a year, 也
the overall position with respect to the labor market such as
employee, retiree, or in education. Occupation and education
information follows the International Standard Classiﬁcation
of Occupations (ISCO) and International Standard Classi-
ﬁcation for Education (ISCED), and these administrative
data inﬂuence workers’ wages due to a collective bargaining
系统.

The Danish production database, VARES, is used to iden-
tify ﬁrms domestically producing goods that were subject
to the import quotas for China. VARES provides informa-
tion on industrial goods produced within the country at the
detailed product level and is the basis for the industrial com-
modity production statistics of Denmark. Firms that in 1999
domestically produce eight-digit Combined Nomenclature
(CN) goods subject to the MFA quota removal for China are
identiﬁed and mapped to worker-level information through
the unique ﬁrm identiﬁcation numbers.16

15 The primary employment of a worker is the worker’s most important

job in terms of earnings and hours worked.

16 See the online appendix for details on the mapping of the quotas to CN

产品.

在 1999, textile manufacturing constituted 3% of total
manufacturing in terms of employment, turnover, and export
和 6% in terms of the number of establishments. 那里
were around 13,000 workers employed in the T&C sector
在 1999. I focus here on workers of working age (17 到 67
年) throughout the whole sample period. 桌子 1 presents
sample information from the 1999 cross-section of workers
and reports demographic, 教育, occupation, 和工作-
place characteristics of treated workers in comparison to
other workers in the same industry. With an average age
的 39, the average worker was roughly in the middle of
his or her career span. The share of female workers was
57%, 和 6% were immigrants. 在 1999, about half of the
工人 (47%) were exposed to increased import competi-
tion by being employed at a ﬁrm that would subsequently
be affected by quota removals when China joined the WTO.
Workers had similar age, 经验, 教育, and wage
levels in both the treated and untreated groups. The percen-
tage of machine operators in both groups was the same,
在 35%, showing that production workers make up a sub-
stantial part of the workforce in both groups. 桌子 1 还
shows that workers’ initial ﬁrms faced similar employment
trends before the shock regardless of whether they produced
quota products.

数字 1 in the online appendix shows the distribution
of workers at the end of the sample period over different
labor market positions by exposure to the trade shock. 经过
2010, 33% of the control group had primary employment
in the service sector whereas among exposed workers, 这
ratio was much higher at 44%. Twenty-ﬁve percent, of both
groups were outside the labor market in 2010. The ﬁgure
makes clear that the analysis controls for the secular declin-
ing trend of the industry and concentrates on the pure trade
effect even if this may underestimate the effect of trade,
since the secular declining trend in the industry may in part
be caused by globalization.

C. Labor Market

The labor market in Denmark is characterized by lib-
eral hiring and ﬁring regulations for ﬁrms combined with
a high level of publicly provided social protection for work-
呃. Denmark is one of a few countries with no estimated
redundancy/ﬁring costs (世界经济论坛, 2013).
The hiring and ﬁring ﬂexibility in combination with a high
level of tax-funded social protection is often described as a
“ﬂexicurity” system. 尤其, Denmark has a compre-
hensive and large-scale ALMP with a history back to the
20世纪70年代末. Any unemployed worker is subject to the ALMP
措施, which include job search assistance. 因此, 这
long-term unemployment rate (in total unemployment) 是
generally low in Denmark compared to the OECD average.
在 2008, 它是 13.5%, 相比, 例如, 52.5%
和 10.6% for Germany and the United States, 分别
(OECD Employment Database, 2013). Wage determination
is less ﬂexible. There is no minimum wage, but reference

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WORKERS BENEATH THE FLOODGATES

635

Table 1.—Worker Characteristics, 1999

意思是
标清
氮

年龄

38.78
10.26
10,511

女性

0.57
0.49
10,511

Immigrant

0.06
0.24
10,511

联盟
Membership

0.80
0.40
10,511

Unemployment
Insurance
Membership

0.90
0.31
10,511

大学
教育

0.11
0.32
10,511

Vocational
教育

0.35
0.48
10,511

Number of observations
年龄
Immigrant
Experiencea
Past unemployment spellsa
Negative trend at workplace
With college education
With vocational education
Machine operator (ISCO 82)
Annual (primary) wage
Total annual wages
1996–1999 average Annual Wage

Treated

控制

意思是

4,917
38.88
0.05
14.71
1.13
0.43
0.13
0.35
0.35
214,968
228,866
203,870

标清

10.19
0.22
5.88
1.62
0.50
0.33
0.48
0.48
132,948
134,376
122,648

意思是

5,594
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0.45
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0.35
215,047
228,930
204,146

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0.26
5.79
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0.48
0.48
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128,441
122,658

意思是
Difference

0.18
−0.02b
0.56乙
−0.27b
−0.02
0.03乙
0.00
−0.00
−79.32
−64.07
−276.18

t-test

0.89
−4.36
4.85
−7.53
−1.93
4.07
0.47
−0.17
0.03
0.02
0.12

a Expressed in years.
b Indicates signiﬁcance at the 5% 等级.
Values are expressed in year 2000 Danish kroner. Negative trend at workplace is an indicator variable that takes 1 if the total employment of worker i’s workplace declined at least 5% compared to year 1998.
A worker is “treated” or “exposed” if she or he holds a primary employment in a ﬁrm with domestic production of MFA goods as of 1999. A worker is in the control group if employed in other T&C ﬁrms as of 1999.

wages are to a great extent determined by collective wage
bargaining agreements, covering 85% of all wage and salary
earners (Visser, 2013).

三、. Empirical Strategy

A causal relationship between trade and workers’ out-
comes is derived by exploiting the exogenous trade shock
due to China’s accession to the WTO, which triggered the
removal of the MFA quotas for China. I start with mea-
suring differential labor market outcomes among workers
under direct threat of increased competition through the
quota removals in comparison to other textile workers using
a simple difference in differences (DID) analysis as follows:

ln Xit = α0 + α1CompExpZ
我

× Post02t

+ δi + τt + (西德:5)它,

(1)

where Post02t = 1 when year (西德:2) 2002 和 0 否则. Xit
is worker i’s outcome in year t. CompExpZ
is the worker-
我
level measure of exposure to competition where superscript
Z = {D, C} indicates whether it is deﬁned as a discrete, D,
or a continuous, C, variable. 那一年 1999 is used to deter-
mine workers’ subsequent exposure to the quota removal to
limit any anticipation effects. The discrete treatment vari-
有能力的, CompExpD
我 , takes the value of 1 if in 1999, worker i
was employed in a ﬁrm that domestically manufactured a
product that with China’s entry into the WTO was subject
to the abolishment of the MFA quotas for China, 和 0 oth-
erwise. The continuous treatment variable, CompExpC
我 , 是
the revenue share of these goods at worker i’s employer in
1999. 这边走, exposed workers employed at ﬁrms domesti-
cally producing quota products with a small share of revenue

would be given less weight than exposed workers whose
workplaces concentrated heavily on domestic MFA good
生产. The treatment variable is interacted with a time
indicator for China’s post-WTO accession years, Post02t, 到
capture the variation in the outcome variable between pre-
and postshock years speciﬁc to exposed workers compared
to other textile workers.17

The aggregate trends in the industry and the labor market
are controlled for by using year ﬁxed effects, τt. 有可能的
that workers employed by the exposed ﬁrms were system-
atically different from the rest of the T&C workers or that
the exposed ﬁrms were different from other T&C ﬁrms. 全部
time-invariant differences across workers and across their
initial ﬁrms such as gender, occupation, 年龄, 教育, 这-
tial wage, and organizational and technological structure of
the initial ﬁrms were controlled for by worker ﬁxed effects,
δi. The coefﬁcient estimates for α1 measure the impact of the
trade shock on workers’ outcomes due to the textile quota
abolishments for China in the years after its entry into the
WTO.

In a ﬁrm-level analysis, Utar (2014) shows that the MFA
quota removal for China leads to a signiﬁcant decline in
就业. In the presence of labor market frictions, 这
displaced workers from these ﬁrms are likely the ones who
experience disproportionate decline in their earnings. 但
they will also switch to other jobs and subsequently partially
or fully compensate for their initial loss. 方程 (1) is at
the worker level, following workers who were employed in

17 The empirical strategy builds on the observation that ﬁrms affected by
the two removals largely overlapped. Utar (2014) reports that 87% 的
ﬁrms that produced goods subject to 2002 quota removal (phases I to III)
also produced goods subject to phase IV removal.

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636

THE REVIEW OF ECONOMICS AND STATISTICS

the sector as of 1999 wherever they go as they adjust to the
震惊. 然而, if workers leave the labor market altogether,
the logarithmic transformation of the dependent variables
potentially leads to underestimation of the average impact
captured by α1. In order to address this and disentangle the
impact across different jobs that workers hold subsequently
in different sectors and examine the nature of adjustment
frictions, I divide the sample into pre- (1999–2001) and post-
(2002–2010) WTO accession periods and use the following
baseline regression:

˜Xis = β0 + β1CompExpZ
我
+ β2Post02s + δi + (西德:5)是, s = 0, 1,

× Post02s

(2)

where s = 0 and s = 1 indicate the pre- and postshock
periods, 分别. In this regression, ˜Xis is the cumula-
tive outcome variable (例如, the wage earnings of worker i
over the 1999–2001 [s = 0] and 2002–2010 [s = 1] peri-
消耗臭氧层物质). Since zero observations are potentially an important
part of the adjustment analysis, instead of taking logarith-
mic transformations of the earnings and hours variables, 全部
long-run earnings and hours worked variables are expressed
in multiples of worker i’s own 1996–1999 average annual
earnings and hours worked, 分别. 更具体地说,
2010
t=2002 Xi
˜Xi0 =
, where Xi is the average
席
of Xi over 1996 到 1999. As before, Post02s takes 1 期间
the postshock period (s = 1), and δi denotes worker ﬁxed
effects.

2001
t=1999 Xi
席

, ˜Xi1 =

(西德:2)

The cumulative outcome contains the sum of shocks over
the periods of abolishment and afterward. The estimates of
β1 will capture the cumulative impact of the low-wage import
shock speciﬁc to exposed workers over the nine postshock
years in comparison to other workers employed in the same
initial industry. Once the long-run effect is captured with an
estimate of β1, I examine workers’ adjustment by decom-
posing β1 across different jobs or labor market positions that
workers hold subsequent to the shock.

An important challenge for empirical strategies relying
on industry-wide import measures to identify the impact of
trade with China is that industries subject to greater import
competition may be exposed to other shocks that can be
correlated with trade with China. 例如, advances in
communication technology or in transportation that lower
the cost of offshoring would affect labor-intensive industries
更多的, driving up their import from China disproportion-
ately. The empirical strategy here is free from this potential
contamination because it uses within-industry across-ﬁrm
differences in exposure to trade with China due to a dis-
crete policy change. 此外, I separately estimate
方程 (2) across smaller subsamples and use only within-
occupation, within-education group differences in exposure
to the shock among the textile workers. 这些估计
can be viewed as a lower bound of the impact of low-wage
competition because they are conditioned out of the general

declining trend of the industry, even if this is partly caused
by trade factors.18

IV.

Import Competition from China and
Workers’ Adjustment

A. Average Impact on Workers’ Earnings and Employment

桌子 2 presents two DID coefﬁcient estimates of equation
(1), discrete and continuous, for every dependent variable.
The estimation sample contains workers born between 1943
和 1982 with primary employment in the textile and cloth-
ing sector in 1999. I focus on workers with nonzero annual
earnings in this analysis and use logarithmic transformation
of the dependent variables. These are annual labor earnings,
annual income, hourly wages, annual hours worked, 和
fraction of time spent as unemployed within a year. 这
unemployment variable is adjusted by adding 1 before tak-
ing the logarithm so that workers with no unemployment
are included. The analysis addresses whether workers in the
labor market experience decline in earnings due to the shock
and if this is through decline in hourly wages or reduced
hours worked, 或两者. 然而, to the extent that the import
shock leads to long-term unemployment or pushes workers
out of the labor market, the selection will lead to underes-
timation of the full impact in equation (1). 而方程
(2) will address this, to limit the effect of selection in this
speciﬁcation, 桌子 2 presents estimation of equation (1) 和
data averaged across pre- and postshock periods (panel B) 在
addition to the estimation with yearly data (panel A). Zero
valued income and earnings are included when calculating
the averages.19

Results in panel A show that workers directly threatened
by the removals of import quotas for China experienced a
signiﬁcant decline in annual earnings relative to other tex-
tile workers. Focusing on panel B, the decline in annual
earnings from workers’ primary employment is 5.4% (坳-
umn 1). When utilizing additional cross-sectional variation
in the degree of exposure to the shock with the contin-
uous treatment variable, the coefﬁcient −0.15 (panel B,
柱子 2, hence forth B, 2) shows that a worker in a ﬁrm
with half its revenue from products subject to the quota
removal experiences a 7.5% decline in annual wage com-
pared to a worker whose ﬁrm was not producing these
产品. (Henceforth all letter and number notations, 例如,
乙, 2, refer to table panel number and column number.) 这
impact on total labor earnings, the sum of all wages from
all jobs held within a year, is also signiﬁcant, showing a
3.7% decline on average (乙,3). Unemployed workers receive

18 It is also possible that the decline in prices of quota goods as a result of
the shock depresses prices of nonquota goods or that labor shed by the quota-
producing ﬁrms causes decline in labor market opportunities of other textile
工人. All of these factors would potentially lead to underestimation of
the effect.

19 See the online appendix, 部分 4, for an alternative approach, 在哪里
the analysis is conducted with the dependent variables normalized by the
workers’ own preshock values of the outcome variables.

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WORKERS BENEATH THE FLOODGATES

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638

THE REVIEW OF ECONOMICS AND STATISTICS

compensating beneﬁts from unions and the government, 和
adjustment to the shock could also involve self-employment
or early retirement. Examining the impact on personal
收入 (columns 5 和 6), which includes self-employment,
personal business income, pension income, 失业
insurance, government transfers, and other cash beneﬁts, 作为
well as labor income, shows around a 1% decline and indi-
cates that these compensating beneﬁts, 一般, 大部分
cover the loss in annual labor earnings caused by the trade
震惊.

The negative effect on labor earnings could be due to
a decline in hourly wages or a decline in the number of
hours worked within a year or both. Results on annual hours
worked and hourly wages (columns 7–10) show that the trade
shock causes decline in labor earnings through a decline
in hours worked, not of hourly wages. The reduction in
the number of hours worked is not a voluntary develop-
蒙特, as evidenced by the signiﬁcant increase in the annual
失业 (columns 11 和 12).

To ascertain that the results are not driven by potential
existing trends that for some reason are felt disproportion-
ately among quota-producing ﬁrms or among their employ-
ees, I follow the workers backward in time and estimate
方程 (1) in a presample period of 1990 到 1999. 在这个
分析, every variable is deﬁned as before except the post-
shock dummy, which is replaced with a dummy, Dum95, 那
需要 1 on and after 1995. The period 1995 到 1999 跨度
phase I and II removals, as well as the import liberalization
for Eastern European goods, so any potential effects of these
events would be captured. As shown in panel C of table 2,
there is no disproportionate impact of such events on work-
ers subsequently exposed to the competition with China. 在
panel D, the same analysis is executed with data averaged
over the two periods (pre- and post-1995). The results are
not driven by potential pretrends.20

The literature on trade adjustment (Artuc et al., 2010;
Utar, 2009; Autor et al., 2014) emphasizes frictions that slow
workers’ movement toward growing sectors. It is also pos-
sible that workers face hurdles after making the transition to
a growing sector. It is a friction that has not been in focus in
the literature so far. In the following, we take a closer look
at displaced workers’ experience to understand the relative
importance of both types of friction.

乙. Trade-Induced Moving across Jobs within

and between Sectors

I now separate the initial effect of the shock from the
subsequent adjustment of workers and focus on workers’
adjustment to the shock. In the remainder of the paper, I use
the continuous treatment measure to assess the economic
magnitudes of the impact of import competition and compare

20 These results are conﬁrmed by the alternative approach in the online

appendix, 部分 4.

workers at the 25th and the 75th percentile of exposure.21
第一的, cumulative variables are constructed for each worker
by summing workers’ annual earnings, 就业, 和
annual hours worked in their primary employment over the
pre- and postshock years of the sample period.22 To sep-
arate the initial impact of the trade shock from workers’
subsequent adjustment to it, I decompose the cumulative
earnings, 就业, and annual hours across different
jobs that workers hold throughout the period: at their ini-
tial employers, at other employers in the T&C industry, 在
other manufacturing industries, in the service sector, 并在
all other sectors, which includes agriculture, ﬁshing, 矿业,
and construction. Changes in workers’ cumulative outcomes
due to trade are estimated via equation (2). 桌子 3 节目
the estimates of the DID coefﬁcient β1 in equation (2) 为了
the dependent variables indicated in the panel and column
headings. If a worker has kept her initial job throughout
2000 到 2010, the dependent variables in columns 2 到 6
are all 0 for this worker. Since all potential sources of
employment and labor earnings are covered, coefﬁcients
of the cumulative outcome variables in columns 2 通过
6 will sum to the overall trade effect in column 1 经过
建造.

The results show that the competition from China causes
a decline in earnings over the nine years of −3.133 ×
0.284 = 89% of a preshock annual wage (A,1 of table 3).23
Results in column 2 show that a much stronger negative
effect on earnings of 130% of a preshock annual wage was
experienced at the initial employer, which was then partly
compensated for over the decade. The partial recovery hap-
pened mainly by workers’ movement to service sector jobs
(A,5). Competition leads to higher earnings from services
amounting to 2.376 × 0.284 = 67% of a preshock annual
wage. Earnings recovery within the initial industry, 在
另一方面, is quite limited (柱子 3) and statistically
insigniﬁcant.

To disentangle intersectoral movement frictions from
adjustment frictions experienced within the destination sec-
托尔斯, I use two employment measures. The main variable is
cumulative hours worked, the sum of annual hours worked in
primary employment over pre- and postshock years. Then I
use an employment indicator variable that takes 1 if a worker
is registered with a primary employment with positive earn-
ings in the November record. The cumulative employment
variable shows the number of years a worker is employed

21 这 75/25 percentile difference compares a textile worker initially
employed at a ﬁrm with 28.4% 的 1999 revenue in domestically pro-
duced quota goods with another textile worker whose ﬁrm does not produce
any quota product. The remainder of the paper uses the 75/25 percentile
difference in assessing the magnitude of estimates from the continuous
treatment.

22 Descriptive statistics of these variables are presented in table 3 在里面

online appendix.

23 Since the coefﬁcients obtained with the discrete exposure variable show
the economic magnitudes transparently, I provide these coefﬁcients in
brackets in table 3. In column 1, the coefﬁcient −0.81 in brackets means
that on average, exposed workers have 81% of a preshock annual wage less
cumulative earnings over the postshock years because of competition.

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WORKERS BENEATH THE FLOODGATES

639

Table 3.—Workers’ Recovery across Jobs within and between Sectors

All Employers
(1)

Initial Firm
(2)

Other T&C
(3)

Other Manufacturing
(4)

A. Cumulative labor earnings (in initial annual wage)

CompExpC × Post02

−3.133∗∗∗
(0.761)
[−0.810]

乙. Cumulative employment
CompExpC × Post02

−0.184
(0.174)
[−0.011]

C. Cumulative hours worked (in initial annual hours worked)

CompExpC × Post02

−4.555∗∗∗
(0.324)
[−1.191]

−3.721∗∗∗
(0.180)
[−0.924]

−4.180∗∗∗
(0.223)
[−1.062]

−1.857∗∗∗
(0.373)
[−0.456]

0.256
(0.245)
[0.039]

0.474∗∗∗
(0.135)
[0.098]

0.329
(0.187)
[0.055]

−0.593
(0.335)
[−0.145]

−0.032
(0.143)
[0.008]

−0.297
(0.211)
[−0.068]

Service
(5)

2.376∗∗∗
(0.671)
[0.602]

3.213∗∗∗
(0.200)
[0.823]

2.483∗∗∗
(0.342)
[0.655]

其他
(6)

−0.617∗∗
(0.200)
[−0.115]

−0.118
(0.064)
[−0.016]

−0.192
(0.100)
[−0.036]

Estimations of equation (2). DID coefﬁcient estimates for CompExpD × Post02 are provided in brackets. All regressions include worker ﬁxed effects, the post-WTO accession period indicator, Post02, and a constant.
In panels A and B, the number of observations is 21,022. In panel C, the number of observations is 20,860. Cumulatie effect estimates across all jobs are shown in bold and broken down into its components in columns
2 到 6. Robust standard errors clustered at the worker level are reported in parentheses. Signiﬁcant at *5%, **1%, 和 ***0.1%.

regardless of how long that employment is within a year,
while the measure for cumulative hours worked takes into
account the length of that employment if shorter than one
full year. The result in B,1 shows that competition makes
no signiﬁcant difference to the number of years employed
over nine years after the ﬁrst abolishment of quotas. 在
另一方面, the estimate in B,2 shows that the compe-
tition from China causes a signiﬁcant loss of employment
of workers at their initial (裸露) employers amounting
to one year. Affected workers offset their employment loss
at the initial ﬁrm by moving across jobs within their ini-
tial industry, but to a much larger extent by moving to the
service sector (乙,3 和乙,5). Switching jobs within the ini-
tial industry does not help recovery of earnings losses either
(panel A).

Though there is no signiﬁcant impact on the cumulative
years of employment, the coefﬁcient in C,1 shows that the
China shock causes a signiﬁcant decline in the cumulative
number of hours worked, amounting to 53% (1.857 × 0.284)
of initial annual hours worked.24 What is the reason for that?
Exposed workers experience a disproportionate decline in
hours worked at the initial, exposed ﬁrms amounting to 1.2
preshock years of hours worked, which is similar to the loss
experienced at the initial ﬁrm in terms of years of employ-
蒙特. Exposed workers also work relatively more hours in
service sector jobs following the trade shock. 然而, com-
paring the estimates in B,5 和C,5 indicates that exposed
workers work fewer hours per year of employment in the
service sector. Results presented in the online appendix on
hours worked per year of employment conﬁrm this. 工作-
ers’ earnings per year of employment also decreases once
workers move to the service sector due to competition, 作为一个
comparison of the earnings and employment effects at the
initial ﬁrm and at the service sector indicates. 虽然
service sector is the main destination for the displaced work-
呃, workers move to a less well-paying situation there. 他们

earn less due to a lower number of hours worked in service
sector jobs (A,5 和C,5).25

下一个, 方程 (2) is estimated separately for each post-
shock year from 2002 在. In these regressions, 库姆-
lative outcome variable for the preabolishment years is the
same as before, but the cumulative outcome for the post-
WTO accession years is the cumulative sum of the outcome
variables from 2002 until the year of the regression. 这
DID coefﬁcient estimates from the decomposition analysis
are displayed in Figure 2a. After the ﬁrst few years, 找到-
ing employment in the initial industry is not a viable option
for workers to compensate for their initial employment loss,
和来自 2005 向前, the service sector rises as the main
absorber of displaced workers. It is also clear that other man-
ufacturing jobs are never, even initially, an important source
of employment recovery.

Figure 2b shows that as opposed to the effect of trade
on cumulative employment, the overall effect on cumu-
lative hours worked declines continuously over the nine
postshock years. When the effects on cumulative employ-
ment and hours worked at the service sector in ﬁgure 2 是
seen together, the important adjustment friction comes into
sharper focus. Moving to the service sector is not a smooth
过渡. It does not secure a full recovery in hours worked.
Where do workers move within the service sector? 在里面
online appendix (桌子 6), I show that workers overwhelm-
ingly move to the wholesale and retail trade sectors. 结果
in the online appendix on reallocation between detailed man-
ufacturing industries show that there is no major reallocation
toward any speciﬁc manufacturing industry.

C. The Service Sector: A Safe Shore, Fraught with Perils

Despite increased employment in the service sector in
response to increased import competition, workers experi-
ence reduced hours worked per year of employment in these
工作, so either the service jobs that exposed workers take

24 The discrete difference between exposed and nonexposed workers
amounts to 46% of initial annual hours worked (the coefﬁcient −0.46 in
the brackets).

25 Also see table 5 in the online appendix.

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640

THE REVIEW OF ECONOMICS AND STATISTICS

Figure 2.—Year-by-Year Impact of Trade on the Cumulative Employment

Estimation of equation (2) using the continuous exposure measure, CompExpC .

Table 4.—Part-Time Jobs or Frequent Unemployment Disruptions in the Service Sector?

(1)

(2)

(3)

Panel A

All Types
Service Jobs

Full-Time
Service Jobs

Part-Time
Service Jobs

Dependent variable: Cumulative earnings in the service sector

CompExpC × Post02

Dependent variable: Cumulative employment in the service sector

CompExpC × Post02

Dependent variable: Cumulative total labor income in the service sector

2.508∗∗∗
(0.650)

3.128∗∗∗
(0.193)

3.296∗∗∗
(0.614)

−0.134
(0.106)

0.076
(0.055)

−0.146
(0.124)

2.376∗∗∗
(0.671)

3.213∗∗∗
(0.200)

3.265∗∗∗
(0.647)

3.368∗∗∗
(0.677)

Panel B

All Unemployment Spells

Textile

Depending on the sector of last employment
Manufacturing

Service

Dependent variable: Cumulative Unemployment Spells (expressed in months)

CompExpC × Post02

0.671
(0.455)

−0.323
(0.236)

3.185∗∗∗
(0.451)

Estimations of equation (2). The number of observations is 21,022 in all regressions. All regressions include a constant, the postshock period indicator, and worker ﬁxed effects. Robust standard errors clustered at

worker level are reported in parentheses. Signiﬁcant at *5%, **1%, 和 ***0.1%.

must be mostly part-time or the displaced exposed work-
ers must experience frequent unemployment in the service
sector, or both.26 I use IDA information on job types to fur-
ther decompose the cumulative earnings and employment
obtained in the service sector into full-time and part-time
service jobs and estimate the effect of import competition
on these job types using equation (2) (桌子 4, panel A).
这里, estimates in column 1 will be equivalent to column
5 of table 3 for the respective variables. Since part-time
workers may hold several jobs simultaneously, 此外
to primary earnings, the total labor income in the service
sector is also added in this analysis. This shows that the

26 Farber (2005) uses the U.S. Displaced Workers Survey and documents
that from 2001 到 2003, 13% of workers displaced from full-time jobs were
reemployed in part-time jobs.

competition-induced earnings and employment gain in the
service sector is entirely driven by full-time jobs. The trade
shock thus leads to movement of workers toward full-time,
not part-time, service sector jobs.

Next I estimate the impact on cumulative unemployment
spells: the summation of unemployment spells within a year
(measured in months) during pre- and postshock years for
each worker (panel B of table 4). The competition causes
失业 (乙,1). The increase in cumulative unemploy-
ment spells for a textile worker at the 75th percentile of
exposure a decade after the shock amounts to one month
more than the increase experienced by a textile worker at
the 25th percentile. I then decompose the cumulative unem-
ployment spells depending on the last sector of employment
before the unemployment spell and estimate the effect sepa-
rately across sectors (columns 2 到 4). This shows that import

(4)

Unknown
Types
Service Jobs

0.002
(0.002)

0.008
(0.005)

0.054
(0.033)

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WORKERS BENEATH THE FLOODGATES

641

competition induces unemployment spells especially within
the service sector.27

In the online appendix, ﬁgure 2 shows the yearly evo-
lution of the impact of the trade shock on the cumula-
tive unemployment spells. Trade-induced cumulative un-
employment increases until 2007 and then starts declining.
This shows that the trade effect is not convoluted by the
effects of the Great Recession. Unemployment after mov-
ing to the service sector increases rapidly through 2003
到 2005 and becomes the only source of trade-induced
unemployment by 2010.28

因此, the results so far show that import competition
causes (A) workers to move to the service sector, predom-
inantly to (乙) full-time jobs in the service sector, 和 (C)
fewer hours worked annually in the service sector, 和 (d)
with spells of unemployment within the service sector. A pic-
ture emerges that exposed workers have difﬁculty in keeping
stable employment in the service sector and that the main
problem is frequent unemployment spells between full-time
service sector jobs. These ﬁndings put a spotlight on the
adjustment frictions that workers face, as they seek to adapt
to a new type of work following a trade shock and highlight
the difﬁculty in making such a transition even in an environ-
ment with a relatively low unemployment rate and full-time
jobs available.

V. Heterogeneity in Workers’ Adjustment

to the Trade Shock

A broad sector switch is likely to render the part of a
worker’s human capital tied to the original sector obsolete
(Neal, 1995; Parent, 2000; Poletaev & 罗宾逊, 2008), 和
this may be behind the problem experienced after moving
to the service sector. To pin down the determinants of work-
ers’ adjustment frictions, in this section I study heterogeneity
in the adjustment paths of workers with different sensitiv-
ity to the potential loss of human capital reﬂected in their
education and occupation.29

A. Education and Workers’ Adjustment

Workers are sampled according to their highest attained
教育, and equation (2) is estimated separately across
workers with different education levels: college education,
vocational education, and at most a (nontechnical) 高的
学校文凭. The DID coefﬁcient estimates are presented
in column 1 of table 5. As in section IVB, the impact on
cumulative earnings and hours worked is decomposed into

27 Additional analysis, 要求可以办到, shows that most of the

unemployment spells experienced in the service sector are short term.

28 The online appendix also contains average annual evolutions of unem-
ployment spells across sectors (see ﬁgures 5 和 6), showing that the
trade-induced unemployment within the initial industry started subsiding
后 2003.

29 Results on additional dimensions of heterogeneity including workers’

age are presented in the online appendix.

its additive components at the initial ﬁrm, other T&C jobs,
non-T&C manufacturing jobs, service sector jobs, 和别的
部门 (columns 2–6).

The impact of the low-wage import shock is not homo-
geneous across workers with different education levels. 这
negative impact increases with lower education (panels A–C,
柱子 1). College-educated textile workers exposed to the
shock do not have signiﬁcant long-run changes in earn-
ings and hours worked, but exposed workers with vocational
and high school education experience signiﬁcant declines in
cumulative earnings of 44% 和 143% of a pre–shock annual
wage.

The impact of the shock at the initial employer is neg-
ative and signiﬁcant for workers of all levels of education
(柱子 2). In fact college-educated workers incur larger
earnings losses at the initial employer than workers with less
教育 (桌子 5, A.I,2). The coefﬁcient −7.10 means that
if not for the trade shock, exposed college-educated work-
ers would have earned an additional 200% of a preshock
annual wage at their initial ﬁrms. For workers with voca-
tional and high school education, the effects are 122% 和
111%, 分别. The effect on earnings may be larger for
the college educated because, absent the shock, 他们会
have experienced a steeper earnings proﬁle at the initial
workplace.30

For all education levels, the main reason for the negative
effect on earnings at the initial ﬁrm is shortened tenure there,
as evidenced by the results on the cumulative hours worked.
For college-educated workers, the trade shock causes a
decline in hours at the exposed ﬁrm of 140% of preshock
annual hours worked (A.II,2), and for vocational and high-
school-educated workers, the effects are 120% 和 110%,
分别.

If the shock affects workers similarly at their exposed
employer regardless of education level, the difference in out-
come over the following decade stems from their ability to
compensate afterward. The shock increases the likelihood
of switching to service sector jobs regardless of workers’
教育 (柱子 5), and service sector employment is the
main source of employment recovery for workers at all edu-
cation levels. For the college educated, the estimates in A.I,2
and A.I,5 indicate that the trade-induced sector switch may
even be a blessing in disguise, as the earnings gain in the
service sector due to competition amounts to 235% of a
preshock annual wage, slightly more than the wage loss
due to shortened tenure in the initial ﬁrm (200%). But for
workers without a college education, employment in the ser-
vice sector does not offer a full recovery from the initial
impact. As the broad sector switch involves organizational
and technological changes, these results are in line with
the idea that highly educated workers have a comparative
advantage in adjusting to new knowledge and technologies

30 Topel (1991) emphasizes the importance of ﬁrm-speciﬁc human capital
and the idea that such ﬁrm-speciﬁc knowledge is more important among
the higher-educated workers.

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THE REVIEW OF ECONOMICS AND STATISTICS

Table 5.—Trade Adjustment Costs and Workers’ Education

(1)
All Employers

(2)
Initial Firm

(3)
Other T&C

(4)
Other Manufacturing

(5)
Service

(6)
其他

Sample: College Educated Workers (N= 2,398)
A.I Cumulative Labor Earnings (in initial annual wage)

CompExpC × Post02

−7.10∗∗∗
(1.350)
A.II Cumulative Hours Worked (in initial annual hours worked)
−4.98∗∗∗
(0.694)

CompExpC × Post02

0.18
(2.323)

1.03
(1.453)

Sample: Workers with Vocational Schooling (N= 7,352)
B.I Cumulative Earnings (in initial annual wage)

CompExpC × Post02

−4.30∗∗∗
(0.435)
B.II Cumulative Hours Worked (in initial annual hours worked)
−4.14∗∗∗
(0.365)

CompExpC × Post02

−2.08∗∗∗
(0.456)

−1.55∗
(0.636)

Sample: Workers with at most a High School Diploma (N= 10,774)
C.I Cumulative Earnings (in initial annual wage)

CompExpC × Post02

−3.91∗∗∗
(0.372)
C.II Cumulative Hours Worked (in initial annual hours worked)
−3.91∗∗∗
(0.305)

CompExpC × Post02

−2.66∗∗∗
(0.554)

−5.04∗∗∗
(1.264)

0.84
(1.453)

0.51
(1.037)

0.56
(0.343)

0.60∗
(0.286)

−0.25
(0.277)

−0.00
(0.215)

Sample: Workers with Manufacturing Speciﬁc Vocational Schooling (N= 2,590)
D.I Cumulative Earnings (in initial annual wage)

−2.67
(1.644)

CompExpC × Post02

−5.04∗∗∗
(0.694)
D.II Cumulative Hours Worked (in initial annual hours worked)
−4.43∗∗∗
(0.592)

−2.65∗
(1.133)
Sample: Workers with Service Related Vocational Schooling (N= 5,366)
E.I Cumulative Earnings (in initial annual wage)

CompExpC × Post02

−3.80∗∗∗
(0.538)
E.II Cumulative Hours Worked (in initial annual hours worked)
−3.71∗∗∗
(0.439)

CompExpC × Post02

−0.40
(0.589)

0.70
(0.767)

−0.63
(1.322)

−0.40
(0.975)

0.95∗
(0.373)

0.85∗∗
(0.313)

−1.92∗
(0.900)

−0.77
(0.817)

−0.20
(0.382)

−0.31
(0.288)

−0.70
(0.539)

−0.25
(0.293)

−1.64∗∗
(0.624)

−1.20∗∗
(0.452)

0.01
(0.455)

0.08
(0.445)

8.36∗∗∗
(1.634)

6.21∗∗∗
(1.060)

2.66∗∗∗
(0.570)

2.06∗∗∗
(0.429)

0.79
(1.168)

1.68∗∗
(0.539)

4.64∗∗∗
(1.052)

3.41∗∗∗
(0.755)

3.67∗∗∗
(0.736)

2.49∗∗∗
(0.538)

0.01
(0.173)

0.06
(0.162)

−0.26
(0.196)

−0.29
(0.183)

−0.97∗∗
(0.358)

−0.17
(0.145)

−0.01
(0.212)

−0.02
(0.181)

−0.13
(0.213)

−0.12
(0.176)

All regressions include worker ﬁxed effects, the post-WTO accession period indicator, Post02, and a constant. Cumulatie effect estimates across all jobs are shown in bold and broken down into its components in

columns 2 到 6. Robust standard errors clustered at the worker level are reported in parentheses. Signiﬁcant at *5%, **1%, 和 ***0.1%.

(Bartel & Lichtenberg, 1987). This all suggests that results
at the region, 行业, and ﬁrm level can lead to the erro-
neous conclusion that college-educated workers are immune
to the negative employment effect of trade shocks. What I
show here is that successful adjustment to the shock is the
primary reason for the different long-run outcomes between
college and non-college-educated workers.31

Vocationally educated workers adjust better in the service
sector than high-school-educated workers. They compen-
sate for 50% (2.06/4.14) of their initial earnings losses and
62% (2.66/4.30) of their initial employment in terms of
hours worked; these numbers are 43% 和 20% 为了
high-school-educated. As in many other European coun-
尝试, vocational education is an important institution for
nonacademic education in Denmark. After nine years of

31 Autor, Dorn, and Hanson (2015) show at the aggregate level that the
effect of Chinese imports on local labor markets tends to be stronger for non-
college-educated employment. At the ﬁrm level, Utar (2014) ﬁnds that the
negative effect of the import shock is concentrated on non-college-educated
雇员.

obligatory schooling, typically three to four years of edu-
cation is offered in a wide variety of vocations. It combines
formal school periods with practical apprenticeships, giv-
ing an intermediate level of education for speciﬁc vocations.
While college education increases the adaptability of work-
呃, vocational education carries a risk for workers of losing
their investment in human capital if it is speciﬁc to their ini-
tial industry. But these are highly skilled workers, 和
education could help them adapt to new environments, 埃斯佩-
cially if their training is not speciﬁc to the manufacturing
行业.

I further partition the sample of vocationally educated
workers and analyze their adjustment depending on whether
the ﬁeld of vocational education is speciﬁc to manufactur-
英 (例如, textile operator, cutting machine operator, garment
technician) or service related (例如, ofﬁce worker, 技术的
设计师, decorator, IT technician).32 The results in the last
four rows of table 5 reveal substantial heterogeneity among

32 Not all vocational education topics can be unambiguously classiﬁed as

manufacturing or service focused, and the analysis excludes such cases.

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WORKERS BENEATH THE FLOODGATES

643

Figure 3.—Trade-Induced Unemployment and Workers’ Education

occupational experience component of workers’ human
capital on their adjustment to the trade shock is studied next.

乙. Occupation-Speciﬁc Human Capital and

Workers’ Adjustment

The sample is partitioned according to workers’ 1999
occupations, and equation (2) is estimated separately for
managers, professionals and technicians, clerks, craft work-
呃, machine operators, and laborers. Figure 4a presents the
DID coefﬁcient estimates for cumulative earnings from all
就业 (顶部) and from the initial employer (底部).33
Over the decade following the import shock, competition
from China causes large signiﬁcant declines in earnings
among craft workers and machine operators, but not among
clerks and service workers or managers (顶部). Professionals
and technicians even beneﬁt from this shock, as witnessed by
signiﬁcantly higher cumulative earnings amounting to 120%
of a preshock annual wage. Workers with elementary occu-
pations incur large negative earnings losses, but the effect is
statistically insigniﬁcant, implying heterogeneous outcomes
within the group. These results reveal substantial heterogene-
ity in the impact of the low-wage import shock on workers
with different occupations.

The overall effect of the shock on workers with differ-
ent occupations clearly depends on differences in success of
adjustment to the initial shock rather than differences in ini-
tial impact (compare top and bottom of Figure 4a). The initial
impact of the shock ranges across all occupations between
84% 和 200% of an initial annual wage. The effects of the
shock experienced by clerks and service workers, 还有
as operators and assemblers, at their initial exposed work-
places are, 例如, almost all the same—around 130%
of a preshock annual wage. But while clerks recover this ini-
tial loss over the decade, machine operators incur an overall
loss of 100% of a preshock annual wage (coefﬁcient −3.7).34
Competition also causes a signiﬁcant decline in cumu-
lative employment at the initial ﬁrm for all occupations
(Figures 4b and 4c, 底部). Craft workers experience the
smallest employment decline at the initial ﬁrm of 88% 的
preshock annual hours worked (Figure 4c, 底部). 这
largest effect is on manufacturing laborers with a decline
的 150% of preshock annual hours worked.35 At the same
时间, movement to the service sector is strong and similar
across all occupations (图4b, 顶部). 然而, the success
of workers in these service sector jobs varies across occu-
pations. Professionals and technicians as well as clerks and
service workers fully recover the hours lost at the exposed

33 Occupation classiﬁcations follow International Standard Occupational
Classiﬁcation (ISCO-88) major groupings. Details are provided in the
online appendix.

34 Clerks and service workers include secretaries, ofﬁce clerks, and secu-
rity service personnel. Operators and assemblers include weaving, knitting,
cutting operators, other machine operators, and assemblers. The vast
majority are operators.

35 This is in line with trade-induced decline in mass production and

increased customization as documented in Utar (2014).

The dependent variable is the cumulative unemployment spells expressed in months. Estimation of
方程 (2) with the continuous exposure measure, CompExpC , across education samples as indicated
by bar headings. Bars with solid frames indicate statistical signiﬁcance at or below the 5% 等级. 全部
regressions include worker and period ﬁxed effects.

vocationally trained workers. Workers educated for manu-
facturing speciﬁc vocations incur large earnings losses due
to forgone opportunities not only at the initial ﬁrm but also
at other manufacturing jobs, where their human capital is
a better ﬁt. A decade after the shock, these workers still
have signiﬁcantly less employment because of the competi-
的, amounting to 75% of preshock annual hours worked.
相比之下, workers with service-focused vocational educa-
tion suffer no signiﬁcant change in cumulative hours despite
a substantial loss of employment at the initial ﬁrm. 这
is not only because of more successful adjustment in the
service sector but also because other T&C jobs provide
a path of compensation for them, which resonates with
the trade-induced restructuring in this industry away from
manufacturing toward service activities (Utar, 2014).

数字 3 shows the effect of the shock on the cumu-
lative unemployment spells across workers with different
教育. Workers with service-focused vocational edu-
cation fare best in avoiding unemployment, 其次是
college-educated workers. Competition-induced unemploy-
ment is the most severe not on the least educated (工人
with at most a high school diploma) but on workers with
manufacturing-focused vocational education. Results pre-
sented in the online appendix decompose the unemployment
effect depending on the last sector of employment and
show that unemployment is mainly experienced following a
service sector employment, and only workers with service-
speciﬁc vocational education fully escape the trade-induced
unemployment in the service sector. These results establish
that not only the level (Dix-Carneiro, 2014) but also the ﬁeld
of education are important determinants of trade-induced
adjustment costs.

Education is not the only component of human capi-
的; occupational experience is another. The effect of the

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644

THE REVIEW OF ECONOMICS AND STATISTICS

Figure 4.—Workers’ Occupation and Their Adjustment

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Estimation of equation (2) with the continuous exposure measure, CompExpC , across occupation samples as indicated by bar headings. Bar heights show the value of the DID coefﬁcient for the corresponding sample.
The dependent variables are given as the plot titles. Bars with solid frames indicate statistical signiﬁcance at or below the 5% 等级. The numbers of observations are 1,066, 2,948, 2,730, 1,780, 9,106, 和 1,812 从
左边 (managers) to right (labourrs), 分别. All regressions include worker and period ﬁxed effects. The right axis shows the coefﬁcient values based on the 75/25 percentile exposure difference.

employer (Figure 4c), while machine operators and craft
workers suffer signiﬁcant cumulative loss of hours worked.
The occupations with the most successful recoveries are
clerks and service workers. They were affected as badly as
machine operators and assemblers at the exposed workplace,
and yet their subsequent recovery was much better. Workers
in this group compensate for their initial loss similarly well in
other T&C jobs, other manufacturing ﬁrms, or in the service
sector, as shown in detail in the online appendix. If the human
capital accumulated through work experience is substantially
speciﬁc to a ﬁrm or an industry, workers displaced from
their jobs are likely to experience larger losses. Clerks are
probably the occupation with the least industry-speciﬁc skills
and have a high level of transferability especially compared
to craftsmen and machine operators.36

The dependent variable in Figure 4d is the cumulative
unemployment spells experienced within the service sector

measured in months. It shows that unemployment after mov-
ing to the growing sector is concentrated among machine
operators, craft workers, and managers—occupations sensi-
tive to losing industry-speciﬁc human capital.

Autor et al. (2014) show that low-wage workers tend
to stay within manufacturing, where they are repeatedly
exposed to the import shock and identify being able to move
out of manufacturing jobs as an important factor in deter-
mining the success of American workers’ adjustment to the
Chinese import shock. I show here that even if workers are
able to move out of manufacturing jobs, they continue to
incur signiﬁcant costs in the form of job instability. That the
match of workers’ occupation-speciﬁc skills to subsequent
service jobs is important to their recovery suggests that poli-
cies such as ALMP, which could facilitate entry into a new
sector, may not be enough to provide smooth adjustments
for all workers.

36 Neal (1995) ﬁnds industry-speciﬁc knowledge to be an important part
of human capital. My results show that the importance of industry-speciﬁc
human capital in trade adjustment is occupation dependent. Some occu-
pations are more sensitive to the loss of industry-speciﬁc knowledge than
其他的.

Industry-Speciﬁcity of Occupation

The previous results show that how speciﬁc a worker’s
occupation is to the exposed industry is critical to recov-
埃里. To pin down this effect, I construct a measure of

WORKERS BENEATH THE FLOODGATES

645

Table 6.—Trade Adjustment and Speciﬁc Human Capital

Cumulative Labor Earnings (expressed in preshock annual wage)
Obtained From:

All Employers
(1)

Initial Firm
(2)

Service
(3)

Panel A

CompExpC × Post02 (β1)

Post02 × ManuSpec (β3)

CompExpC × Post02 ×

ManuSpec (β4)

氮
Panel B

CompExpC × Post02 (β1)

Post02 × TexSpec (β3)

CompExpC × Post02 ×

TexSpec (β4)

氮

1.42
(1.79)
−3.69∗∗∗
(0.57)
−7.33∗∗
(2.54)
19,550

−0.52
(1.03)
−4.26∗∗∗
(0.42)
−5.28∗
(2.10)
19,550

−5.39∗∗∗
(0.82)
−1.22∗∗∗
(0.27)
0.75
(1.16)
19,550

−4.75∗∗∗
(0.46)
−1.08∗∗∗
(0.22)
−0.45
(1.00)
19,550

6.23∗∗∗
(1.61)
−2.98∗∗∗
(0.48)
−6.61∗∗
(2.23)
19,550

4.47∗∗∗
(0.92)
−3.03∗∗∗
(0.35)
−4.78∗∗
(1.85)
19,550

Estimation of equation (3). All regressions include worker ﬁxed effects, the postshock period indica-
托尔, Post02, and a constant. Robust standard errors clustered at worker level are reported in parentheses.
Signiﬁcant at *5%, **1%, 和 ***0.1%.

industry speciﬁcity for each four-digit ISCO occupation, j. 我
deﬁne an occupation’s speciﬁcity to workers’ initial indus-
尝试, IndSpecj, as the ratio of the number of workers with
occupation j in the industry to the total number of workers
with occupation j in the overall economy in the initial year,
1999. Since the adjustment frictions are mainly observed
to be associated with the switch from the manufacturing to
the service sector, I deﬁne two measures: one for the T&C
行业, TexSpecj, and the other for the overall manufactur-
ing sector, ManuSpecj.37 I then map this information to the
workers via their four-digit occupation in 1999 and estimate
the following triple-difference equation.38

˜Xis = β0 + β1CompExpi × Post02s + β2Post02s

+ β3Post02s × IndSpeci + β4CompExpi
× Post02s × IndSpeci + δi + (西德:5)是, s = 0, 1.

(3)

The coefﬁcient of interest, β4, measures the variation in
the cumulative outcome variable, ˜Xis, of worker i particular
to exposed workers with an initial occupation that is spe-
ciﬁc to the initial industry (relative to exposed workers with
an industry nonspeciﬁc occupation) in the period after the
震惊.

桌子 6 presents these results for cumulative earnings.
Workers under direct exposure to the import shock have
signiﬁcantly larger losses the more speciﬁc their occupa-
tions are to the entire manufacturing sector. Columns 2
和 3 present the effect at the initial ﬁrm and the service
sector. The impact at the initial ﬁrm does not depend on

37 更正式一点, TexSpecj = Number of workers in occupation j employed in T&C as of 1999

Total number of workers in occupation j in 1999

and ManuSpecj = Number of workers in occupation j employed in manufacturing as of 1999

Total number of workers in occupation j in 1999

38 The number of observations is fewer than the whole sample in this anal-
ysis because not all workers’ four-digit occupation codes can be identiﬁed
by administrative sources.

whether a worker’s occupation is speciﬁc to manufactur-
英, but the earnings recovery at the service sector does not
materialize with a purely manufacturing speciﬁc occupation.
The signiﬁcant differences in cumulative earnings between
manufacturing speciﬁc occupations and other, less speciﬁc,
occupations are entirely due to the difference in adjustment
to the shock. Results in panel B on the T&C speciﬁcity of
occupations show similar but not stronger patterns.

These results show that an occupation’s speciﬁcity to man-
ufacturing in general is a more important determinant of
adjustment costs than the speciﬁcity of occupations to their
initial industry within manufacturing.39 They establish that
a worker’s successful adjustment depends crucially on the
degree to which her human capital is either relevant to work
in the service sector or is lost because of the trade shock.

D. Trade-Induced Skill Upgrading at the Worker Level

So far I have shown that workers’ adjustment costs are
very heterogeneous with respect to workers’ educations and
occupations, and the lack of the right skill set is an impedi-
ment to recovery for workers whose human capital is speciﬁc
to the sector they left. As the opportunity costs of time spent
out of the labor market decrease for workers with depreciated
人力资本, this may induce workers to rebuild human
capital through education. Workers can enroll in short-term
or part-time education while partly being in the labor mar-
ket or enroll in full-time education outside the labor market.
In Denmark, workers receive an education allowance from
the unemployment insurance (UI) if they enroll in school
to increase their job prospects. Making use of this informa-
的, I analyze the effect of increased import competition
with China on the number of years with school enrollment
and estimate equation (2) with the dependent variable being
cumulative years with education allowance. These results are
shown in ﬁgure 5 with full results presented in the online
appendix.

The ﬁrst bar in Figure 5a shows that trade causes an
increase in workers’ school enrollment amounting to about a
月. The dependent variable is then decomposed depend-
ing on the worker’s primary labor market position in a given
year and equation (2) is estimated separately across mutu-
ally exclusive positions. Trade induces workers to further
their education mostly after they move to the service sec-
托尔 (ﬁgure 5a). This suggests that workers seek education
to become better suited for jobs in their new work envi-
ronment and implies that the trade shock’s effect on school
enrollment may depend on their existing education and skill
gap. I test that by partitioning workers according to educa-
tion and conducting the analysis separately across college,
vocational, and high-school-educated workers (ﬁgure 5b).
Workers increasingly seek further education the less edu-
cated they are initially. To further examine the role of skill

39 See the online appendix for the full decomposition result, as well as the
results on the cumulative years of employment and annual hours worked.

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646

THE REVIEW OF ECONOMICS AND STATISTICS

Figure 5.—Impact of Trade Shock on School Enrollment

In both panels, the height of each bar represents the value of the DID coefﬁcient estimate of equation (2)
with the continuous exposure variable. (A) The dependent variables are the cumulative years with education
allowance conditional on worker’s primary labor market position in that year. (乙) 方程 (2) is run across
different education samples with the dependent variable is the cumulative years with education allowance.
Bars with solid frames indicate statistical signiﬁcance at or below the 5% 等级. All regressions include
worker and period ﬁxed effects.

mismatch, the sample of vocationally educated workers is
divided as in section VA according to ﬁeld of education,
and the analysis is conducted separately for the manufac-
turing focused and service focused vocationally educated
(the last two bars in the ﬁgure). Indeed the skill mismatch
with the service sector is the main driver of trade-induced
school enrollment. The import shock induces signiﬁcantly
more school enrollment among workers with manufacturing-
speciﬁc vocational education, while it does not cause an
increase among workers who already have service-focused
vocational education. The impact among manufacturing-
speciﬁc vocationally educated workers is almost twice the
average effect. The incentive to rebuild human capital is
strongest for those who are least able to retain their human
capital in the service sector.

While recent studies provide evidence of skill upgrading at
the ﬁrm level as a result of increased Chinese imports (Bloom
等人。, 2016; Utar, 2014), whether import competition can
lead to skill upgrading at the individual level is an important
unanswered question. My ﬁndings here point to a new and
interesting channel through which imports from low-wage
countries can shape the structure of advanced economies as
not only ﬁrms but also individuals respond by upgrading
their skills. Looking at a potential effect of trade on the sup-
ply of skill from a different angle, a recent study shows that
export expansion triggered by the trade reforms in Mexico
causes school dropouts (Atkin, 2016). Complementing this,
my results provide evidence that the decline in labor demand
due to increased import competition has caused increased
school enrollment in Denmark.

An important question, which is out of scope of this paper,
is what policies could ease such a response to a trade shock.
Education is free in Denmark, and workers receive income
support when unemployed. 桌子 2 indicates that workers
were compensated by government transfers despite signiﬁ-
cant earnings losses. This is further conﬁrmed by estimating
方程 (2) on personal income and government transfers
across different labor market positions of workers (看到
online appendix). Together these ﬁndings suggest that trade
adjustment policies should particularly target workers with
outdated skills. The role of such policies, 然而, 会
be best evaluated in a comparative study using harmonized
cross-country data.

六、.

Summary and Conclusion

The effect of increasing trade with China and other low-
wage countries on advanced-country manufacturing indus-
tries and workers is a prominent topic of current public
debate. With the decline of manufacturing employment in
advanced economies, whether and how the transition of the
most affected workers can be eased has become an important
economic policy question. This paper studies the impact of a
Chinese import shock on workers’ earnings and employment
trajectories in a European country with a generous social net
and active labor market policies in a quasi-natural experi-
ment that measures the causal effects of a trade policy change
affecting a classic manufacturing industry. By directly com-
paring a clerk to a clerk or a machine operator to a machine
operator that are all initially employed in the same industry
but differ only by exposure to the trade shock, this study
disentangles the effects of the trade shock from potentially
important technology factors.

The increased import competition resulting from the abol-
ishment of quotas for China had substantial negative effect
on Danish workers’ earnings and employment trajectories.
Shorter employment spells at the initial ﬁrm and unstable
subsequent employment interrupted by frequent unemploy-
ment are the main channels through which workers are
affected by the trade shock. The service sector is the main
absorber of displaced workers, and the ability of workers to

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WORKERS BENEATH THE FLOODGATES

647

recover from the trade shock depends on how well suited
they are for service sector jobs. Adjustment problems do
not end once workers ﬁnd full-time jobs in the growing sec-
托尔斯. Workers’ ability to recover from the shock depends on
the degree to which their human capital is either relevant
to work in the service sector or is lost because of the trade
震惊. The results bring the distributional consequences of
trade with low-wage countries into light. By showing that the
trade shock increases incentives to acquire further education,
this paper also provides the ﬁrst worker-level evidence on
skill acquisition in response to increased competition from
中国.

ALMPs combined with a relatively well-functioning
unemployment insurance system may be one reason behind
the mobility of Danish workers. The results suggest that
effective ALMPs may ensure faster movement toward grow-
ing sectors, but this itself does not guarantee smooth adjust-
蒙特. These ﬁndings shed light on the nature of difﬁculties
that advanced countries face on the path of employment
deindustrialization and inform policy makers about the most
vulnerable.

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