Heterogeneous Globalization:
Offshoring and Reorganization∗
Andrew B. Bernard†
Teresa C. Fort‡
Frederic Warzynski¶

Valerie Smeets§

November 28, 2018

Abstract
This paper exploits a direct measure of offshoring to study how the movement of
production abroad affects the composition of firms’ domestic employment and production, as well as their innovative activities. After offshoring begins, firms increase theirimports of domestically produced goods, and retain – rather than abandon – domestic
production of those goods. We define a new measure of offshoring based on this relationship that enables us both to distinguish it from import competition and to identify
new production cost saving opportunities in foreign countries. In response to such newoffshoring opportunities, firms reallocate labor from production work to technology
and innovation-related occupations. This reallocation of workers is accompanied byincreases in offshoring firms’ product development and R&D spending. The results
suggest a link between offshoring and domestic innovation.

JEL Codes: L25,F14,F61
Keywords: offshoring, innovation, import competition, skilled workers, technology, R&D∗

We thank Lindsay Oldenski and Doireann Fitzgerald for helpful discussion comments at the NBER ITI
SI and Dallas Fed International Trade Conference. We also thank Mary Amiti, Will Dobbie, James Harrigan,
Rob Johnson, Fariha Kamal, Esteban Rossi-Hansberg, Meredith Startz, Peter Schott and participants at
the AASLE, CCER, Center for Economic Studies, CMU, Drexel, EITI, Fed Board, Georgetown, LMU/IFO,
LSE, Michigan State, NY Fed, Princeton, RIDGE, SAIS, SOLE, UCLA, University of Michigan, UQAM,
UVA, World Bank and Yale for helpful comments and suggestions.
†
Tuck School at Dartmouth, NBER, and CEPR, andrew.b.bernard@tuck.dartmouth.edu‡
Tuck School at Dartmouth, NBER, and CEPR, teresa.fort@dartmouth.edu§
Aarhus University, vas@asb.dk¶
Aarhus University, fwa@asb.dk

1

Introduction

A growing number of studies conclude that low-wage imports, and Chinese imports in particular, are reducing manufacturing employment in advanced economies.1 A potential puzzle
for these papers, however, is that even as manufacturing employment has declined, real value
added has continued to rise at about the same rate as GDP. Moreover, this output growth
has occurred in some of the same sectors in which import penetration has been rising.
One potential explanation for the role of trade in the divergence between manufacturing
employment and output is that imports reflect not only the import competition channelemphasized in existing work, but also production fragmentation decisions made by firms that
continue their domestic operations. The growth in Chinese imports to the US was driven
not only by imports of wholesale-retail firms, but also by US manufacturers’ foreign sourcing
decisions (Antràs et al., 2017). While the manufacturing employment loss in response to
Chinese imports has received considerable attention, growing evidence suggests that theselosses did not necessarily entail firm exit as manufacturers expanded their operations into
other activities (Bernard et al., 2017; Fort et al., 2018).
This paper studies how the movement of production abroad affects the composition offirms’ domestic employment and production, as well as their innovative activities. To doso, we exploit a clear measure of offshoring based on novel survey data in which Danish
firms were asked whether they relocated their core activity to foreign regions between 2001
and 2006. This relocation could occur within or outside the boundary of the firm and only
covers activities that were previously performed in Denmark. This is one of the first explicit
measures of offshoring that captures the firm decision to move existing domestic activities
to a foreign location.
The data show that nine percent of the surveyed Danish firms relocated their core ac1
Autor et al. (2013, 2014) and Pierce and Schott (2016) provide evidence for the US. Negative effects ofChinese imports are not limited to the US, see Mion and Zhu (2013) for Belgium, Ashournia et al. (2014)
for Denmark, Malgouyres (2017) for France, Balsvik et al. (2015) for Norway, and Thewissen and van Vliet(2017) for the OECD.

1

tivity to a foreign region between 2001 and 2006. Among these offshorers, countries thatjoined the European Union in 2004 and 2007, collectively referred to as New Member States(NMS), were the most popular destinations.2 54 percent of Danish offshoring firms offshoredto the NMS. One third of the offshoring firms relocated their core activity to China, making
it the second most popular destination. We combine these data with information on firm employment, sales, production, input usage, R&D expenditure, imports, exports, and matchedemployer-employee records to create a rich new dataset for studying the ramifications ofglobalization.
We first analyze the relationship between offshoring and importing. Consistent with assumptions in prior work, firms that offshore to a particular region increase their imports
from that region in both levels and shares. There are important differences, however, in thetypes of goods that offshorers import. Offshoring firms significantly increase their imports ofdetailed products (HS6) that they also produce domestically. This increase by offshorers is
relative both to their own prior import behavior and to that of non-offshorers, who increaseimports of non-produced goods instead. Furthermore, rather than hollowing out their domestic production, offshorers continue to produce the same goods that they import. In fact,
we find that offshorers’ domestic production of goods that are both produced and imported
is more resilient than their production of goods that they do not import.
While it may seem surprising that firms both produce and import the same detailed
products, we do find a clear distinction between imported and domestically-produced versions. In particular, prices, as proxied by unit values, are 50 to 60 percent higher for thedomestically-produced version compared to the imported version for the same firm-year anddetailed CN8 product. The price difference suggests that offshoring firms produce higher
quality versions of their goods at home and offshore the production of lower quality versions
to NMS countries and China. At the same time offshorers are changing the composition of
their workforce by increasing their share of highly educated workers and technology-related
2
The 12 NMS countries are Bulgaria, Cyprus, Czech Republic, Estonia, Hungary, Latvia, Lithuania,
Malta, Poland, Romania, and Slovenia, and Slovakia.

2

workers; non-offshorers have no such composition changes. While imports of produced products are rising, offshorers are also disproportionately introducing more new products relative
to non-offshorers.
This evidence is suggestive of an important role for offshoring in a firm’s allocation of
resources towards R&D and innovation, but there are other potential explanations for the
relationship. One possibility is that increased competition may lead firms to increase innovation and to offshore. Bloom et al. (2015) find evidence that increased import competition
from China led European firms to increase patenting and productivity, and existing theoryshows how increased import competition can provide new incentives for firms to innovate(e.g., Impullitti and Licandro, 2017; Fieler and Harrison, 2018). Import competition may
also lead firms to offshore (e.g., Rodriguez-Lopez, 2014). In line with this type of negative
selection, we find that increased Chinese import competition in a firm’s industry is associated not only with an increased likelihood of offshoring to China, but also with an increased
probability of offshoring to the NMS.
An alternative channel through which offshoring may affect innovation is by the formationof international production teams. In Antràs et al. (2006), production requires solving
problems. Workers of different ability sort into teams, choosing whether to be problemsolvers or production workers based on the relative returns to each activity, which in turndepend on their skill. Offshoring occurs when production teams can form across countries,
with problem-solvers in one country combining with production workers in another. The
theory predicts that new offshoring opportunities will lead to an increase in the numberof problem-solvers in skill-intensive countries, with workers in those countries shifting fromproduction to problem-solving activities as the relative return to the latter increases.
To tease apart these channels, we first propose a new offshoring measure: changes in a
firm’s share of imports of produced goods over total imports. This measure captures intensive
and extensive margin offshoring decisions at a detailed product level. We then identify
changes in firm-level offshoring due to factors external to both the firm and Denmark. In

3particular, we exploit the fact that the 12 NMS countries underwent significant changes intheir institutions when they joined the European Association Agreement (EAA) and theWorld Trade Organization (WTO).3 These changes led to increased economic growth andintegration with the rest of the world, though their impact naturally varied across goods.
We measure variation in the NMS countries’ comparative advantage growth across detailed product categories using changes in six-digit HS product export shares by the NMS
countries to the rest of the world (ROW), excluding Denmark. Using changes in NMS
export shares rather than changes in levels rules out growth that might be driven by aggregate demand or technology shocks that could increase trade in particular products acrossall countries. We construct a firm-specific measure of offshoring exposure by assigning the
product-level shocks to firms based on the firm’s pre-period production shares across products. The measure of potential offshoring opportunities is available for all manufacturingfirms, regardless of their pre-period import status.
Our IV strategy identifies changes in firm-level offshoring to the NMS countries as a resultof improved productivity in those countries in products relevant to the firm. The key identifying assumption is that the common within-product component of the relative increase
in regional productivity is due to increases in NMS productivity. The exclusion restriction
requires that the foreign region’s increased productivity only affects a firm’s innovative activities through its impact on the offshoring decision. This restriction would be violated if
improvements in NMS comparative advantage also led to increased competition from NMS
countries, and that increased competition directly affected firms’ innovative activities (e.g.,
as in Bloom et al., 2015). Fortunately, we can control for this concern directly using a comparable measure of NMS import competition into Denmark in the firm’s pre-period products.
Our instrument thus captures the portion of NMS market share growth by product in the
ROW that is orthogonal to NMS import competition in Denmark. All specifications are run
3

The Czech Republic, Hungary, Malta, Romania, Slovakia, Poland, Cyprus, and Slovenia joined the WTO
in 1995. Bulgaria joined in 1996, Latvia and Estonia joined in 1999, and Lithuania joined in 2001. Malta andCyprus had been members of the EAA since the early 1970s, while the remaining NMS all joined between
1994-1999.

4

in first differences and also include industry fixed effects, which capture broad industry-levelchanges, such as increases in import competition.
The IV estimates point to a positive impact of offshoring on firms’ share of technology
workers. A ten percentage point increase in a firm’s share of NMS produced good imports
leads to a 6.5 point increase in the firm’s share of technology workers. This represents almost
a 40 percent increase relative to the average offshoring firm’s pre-offshoring technology worker
share. The IV results also show that offshoring firms increase their share of high skilledworkers (those with at least a Bachelor’s degree), and, perhaps most surprisingly, that they
introduce more new domestically-produced goods relative to non-offshorers. These results
are indicative of an important role for offshoring in firms’ allocation of resources towards
innovative activities.
This paper contributes to a significant empirical literature on offshoring and workforce
composition. There is evidence that offshoring is related to the rising skill premium (Feenstra
and Hanson, 1999), increased shares of high skill workers within the firm (Mion and Zhu,
2013), and to greater polarization (Harrigan et al., 2016). The paper is most closely related
to Hummels et al. (2014), who also analyze Danish firms’ importing behavior. Although theirprimary focus is on the wage responses, they also find offshoring increases high skill worker
employment and decreases low skill worker employment. We extend those results by studying
a later time period in which offshoring to low wage countries is more prevalent. Using a firm’s
pre-period production, rather than its pre-period imports, to create the instrument allows
us to capture both intensive and extensive margin offshoring decisions, the latter being
particularly relevant for offshoring to low wage locations. We also show that offshoring
does not replace domestic production, that it leads firms to increase technology-related
occupations, and that it results in increased product introductions.
This paper also adds to a growing body of work on offshoring and innovation (Bøler et al.,2015; Arkolakis et al., 2018). We provide evidence that offshoring to NMS countries induces
a firm to reallocate workers to technology-related activities, and that this occurs even when5controlling for changes in firm sales over the offshoring period. This reallocation of workers
and change in occupations in response to new offshoring opportunities is consistent withfirms organizing workers to leverage knowledge across countries, as Helpman (1984) andAntràs et al. (2006, 2008). Reallocation is also a key feature of Rodrı́guez-Clare (2010), in
which offshoring lowers real returns to production work in the north, thereby also lowering
the opportunity cost to innovate. That theory highlights the potential for worker switchingfrom production to innovation to raise aggregate productivity and growth in the offshoring
country in the longer term.
We also add to work that develops new measures of offshoring. Feenstra and Hanson(1999) introduce one of the first industry-level measures of offshoring by using input-output
tables to calculate each industry’s share of imported inputs. More explicit firm-level measuresof offshoring highlight significant heterogeneity in offshoring, even within detailed industries(Fort, 2017; Monarch et al., 2017). A number of recent papers measure offshoring as any
imports by a manufacturing firm, and Hummels et al. (2014) focus on imports of four-digit
HS products that the firm also produces domestically. Using the direct measure from theunique offshoring survey, we show that produced goods imports are a good predictor of
offshoring. Studies that exploit industry variation in import penetration changes may thus
confound the effects of import competition with those of offshoring.4
The rest of the paper proceeds as follows. In section 2 we describe the new offshoringdata and the other linked data. Section 3 documents the differences between offshoring andnon-shoring firms. Section 4 discusses how we exploit the productivity changes within NMS
countries to identify the effects of offshoring. We present results from this analysis in section
5, and in section 6 show that offshoring is also associated with increased R&D spending.
The last section concludes.
4This general finding is consistent with Kovak et al. (2017) who study US multinationals and find employment gains for those multinationals that offshore vertical tasks, but negative employment effects for domestic
firms that compete with offshorers. Antràs et al. (2017) provide a theoretical framework that captures theseeffects. Offshoring firms lower prices and expand, but the lower price index leads non-offshorers to shrink.

6

2

Data

In this section, we describe our novel measure of offshoring. We combine this measure withinformation from several other sources to construct a rich dataset of firm and employee
characteristics.

2.1

Offshoring survey

We use a 2007 offshoring survey run by Statistics Denmark that asked firms about theiroffshoring decisions between 2001 and 2006. The survey was part of a larger effort designed
by Eurostat to assess European firms’ global production decisions. While the original Eurostat survey was aimed at all private sector firms with at least 100 employees, Statistics
Denmark surveyed all firms with more than 50 employees that existed in 2005, and firms
with 20-50 employees in selected industries.5 The Danish survey achieved a response rate of
approximately 98 percent, which translates to 4,161 firms.
The survey asked firms about their decisions to relocate, either in part or entirely, ninedifferent business functions: core activity; distribution and logistics; marketing; sales andafter sales services (including help desk and call center); ICT services; administrative andmanagement functions; engineering work and other technical services; R&D; facility management (cleaning, security, food, etc...); other functions. We focus on a firm’s decision to
offshore its core business activity to a foreign location.6
The specific language in the survey asked firms whether they moved a particular activity
to one or more of seven distinct regions.7 We emphasize that this offshoring definition
includes only those functions that were previously performed domestically, either by thefirm itself or by another domestic firm. It does not include foreign locations of activities
which are new to the firm, which are covered in a separate part of the questionnaire.
5

Certain industries, such as government services were deemed less relevant for measuring offshoring.
The survey instructions specify that a firm’s core activity corresponds to its primary industry classification.
7
The actual Danish language is “...udflytning...”, which literally translates to “move out.” The precise
question is presented in the online appendix.
6

7

The survey also asked firms to identify the country or regions to which they offshored. The
survey used the following breakdown of sourcing by location: “Old” EU countries (EU15),
which comprise the countries that belonged to the EU prior to 2004; New Member States(NMS), which comprise the 12 countries that joined the EU in 2004 and 2007;8 other European countries; China; India; other Asian countries and Oceania; US and Canada; Central
America; and Africa. Firms were also asked to identify whether they offshored their core
activity to new and/or existing firms within the same business group, or to separate firms.
The survey therefore provides a direct measure of a firm’s decision to begin offshoringin the period from 2001 to 2006. We focus solely on the relocation of the firm’s activity
to a foreign country, regardless of whether this relocation occurred within or outside theboundary of the firm. In practice, the survey suggests that both integrated and outsourced
offshoring are important. Approximately 44 percent of firms that offshored their core activity
did so to other foreign companies (with no ownership or less than 50 percent ownership).
The remaining offshored to a partner with an ownership relationship.

2.2

Additional data sources

We combine the offshoring survey data with a number of different data sources on Danish
firms. We use the Firm Statistics Register (FirmStat), which is based on Value-Added
Tax (VAT) administrative data, to gather information on firm sales, value added, material
expenditures, capital, total employees, and industry (six-digit NACE). We use these data,
which are available for the population of Danish firms, to construct a firm-level panel from1996 to 2008.9 This time frame and coverage allow us to analyze potential selection into theoffshoring survey, as well as any differential trends for offshoring versus non-offshoring firms.
We augment the VAT data with product-level information about the values and quantities of firm production from manufacturing production surveys (ProdCom). These surveys
8

The 12 NMS countries are Bulgaria, Cyprus, Czech Republic, Estonia, Hungary, Latvia, Lithuania,
Malta, Poland, Romania, and Slovenia, and Slovakia.
9
Some of the firm-level data continues past 2008 but we have chosen to end the sample to avoid the greatrecession.

8

are available beginning in 1995 and cover all manufacturing firms with at least ten employees. They provide information on the value of production by ten-digit product codes, thefirst eight digits of which map to Combined Nomenclature (CN) product codes. The CN
classification system maps to the Harmonized System (HS) at the six-digit level.
We also exploit a survey conducted by Statistics Denmark that collects manufacturingfirms’ purchases of intermediate inputs. These data are available for manufacturing firms
with at least 50 employees. In principle these data are also available at the same HS6 levelof aggregation as the production data, though in practice firms often report at the moreaggregated HS4 level.
We also link our data set to the Danish Foreign Trade Statistics Register. The trade data
are based on Customs declarations and cover all international trade transactions of Danish
firms by product and destination/origin. A benefit of the Danish data is that products in the
trade data are classified using the same HS codes as the production and input use data. Thisfacilitates comparisons of Danish firms’ production, input purchase, and trade decisions.
A critical element in our analysis is to exploit detailed information about the populationof Danish individuals over the period 1991 to 2008. To do so, we use data extracted from
Integrated Database for Labor Market Research (IDA). These data cover the universe of
the Danish population aged 15-74, including the unemployed and those outside of the labor
force. They provide information on workers’ gender, age, experience, tenure, wage, educationlevel, and occupation. Workers are linked to the plant and firm where they are employed.
The dataset also provides a six-digit NACE industry code for the economic activity of eachworker’s plant.
We use the Integrated Database for Labor Market Research (IDA) data to define worker
occupation groups. Following Bernard et al. (2017), we determine the number of workers
for five different occupational categories: managers; technology workers (R&D workers andtechnicians); support activities; sales activities; and line workers. We further decompose line
workers into two separate categories: those involved in transport and warehousing (line 1)9and the others, mostly involved in the production process (line 2).10
We also add data from R&D surveys that span the period from 2000 to 2010. Thesesurveys are only available for between 3,500 and 4,500 firms depending on the year. Firms
surveyed are supposed to represent the universe of potential innovators, which means inpractice that specific innovative sectors and firms above a certain size threshold are targeted.
While the full set of questions in each survey varies by year, we construct a panel of theshare of R&D expenditure in total revenue, as well as the share of R&D workers in total
employment.

3

Offshorers versus Non-Offshorers

The availability of a new, direct measure of offshoring provides a unique opportunity toconsider the differences between offshoring and non-offshoring firms both before and after
the core activity is moved abroad. In particular, this section provides summary statisticsof the new offshoring data and descriptive evidence on how offshoring relates to changes infirms over time. A particular focus is on the interaction between offshoring and importing,with a goal of better understanding the nature of imports by offshoring firms.

3.1

Summary statistics about offshoring

We first describe the distribution of offshoring activities across sectors. Figure 1 shows twoviews of the distribution of offshoring across broad sectors. The industries are sorted by
the share of firms that offshore in the sector between 2001 and 2006 - the solid (darker)
blue columns. Textile and Apparel has the greatest share of offshoring firms, more than
30 percent, while almost 20 percent of firms in the Machinery and Furniture sectors reportoffshoring their main activity between 2001 and 2006. At the other extreme are Business
Services and Transport where fewer than 5 percent of firms offshore.
10

See the online data appendix for the definition of these groups based on the ISCO code.

10

et
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Share of offshorers in industry(a) Across Broad Sectors

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Share of offshorers in industry

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Figure 1: Industry distribution of offshoring firms

Industry share of offshorers(b) Within Machinery

Notes: Figure plots the share of offshoring firms within each industry (first/blue bars) and the share ofoffshoring firms across industries (second/red bars). Note that the red bars do not sum to 1 since only the
top industries are presented to minimize disclosure concerns.

The (lighter) red columns show the share of that industry in total offshoring, again using
firm counts. Machinery is the largest broad manufacturing sector in Denmark and accounts
for more than half of all offshoring firms.11 While a small share of Business Services firm
offshore, the large size of the sector in the overall economy mean that it accounts for morethat 10 percent of all offshoring firms.
Panel (b) of Figure 1 takes a more disaggregated look at the Machinery sector itself.
Offshoring firms comprise about 30 to 12 percent of firms in each industry. Machinery andequipment hosts the largest share of offshorers, with over 20 percent of all offshoring firms
classified in that industry.12
The data show that just over nine percent of firms in the survey relocate their core activity
to a foreign region/country between 2001 and 2006. Table 1 presents the count of firms that
offshore, by region to which they relocated. The two most popular destinations are the newmember state (NMS) countries and China. More than one third of Danish offshorers choose11

In later sections of the paper, we are forced to restrict our sample to firm with production, thereby
increasing the importance of the Machinery sector in our results.
12
Similar patterns hold at the worker level, see the Appendix. The main difference for workers is thatthe share of workers at offshoring firms within industries in the Machinery sector ranges from 20 to over 60
percent.

11

Table 1: Offshoring of core activity by region
Offshoring of core activity by detailed region
RegionFirm count

Share

NMS
NMS & China
China
Other

139
66
60
115

0.37
0.17
0.16
0.30

Total Offshorers

380

1.00

Notes: Locations to which firms relocated their core activity.

NMS (but not China) as an offshore destination, while another 17 percent offshore to both
NMS countries and China. China, but not NMS, is a destination for just over 15 percent
of Danish offshoring firms. Almost one third of Danish firms offshore to “Other” regions,
without also offshoring to either the NMS countries or China.13

3.2

Offshorer premia

Firms that engage in international activities such as exporting, importing and foreign direct
investment are well know to be significantly different from purely domestic firms (Bernard etal. (2018)). They are usually larger, more skill- and capital intensive, and more productive.
Given the different definition of offshoring used in this paper, we compare offshoring Danish
firms to their non-offshoring counterparts in the year before offshoring activity begins.
Column 1 of Table 2 reports premia from a simple regression of the (log) characteristic
in 2000 on a future offshoring dummy including industry fixed effects. Offshorers are substantially larger in terms of sales and employment than non-offshoring firms in the same
industry. They also are more likely to either export or import. Surprisingly, labor productivity, measured as sales per worker and value added per worker, is not different at offshoringfirms compared to non-offshorers.14 These results are broadly consistent with the charac13

See the Appendix for a breakdown of the other regions. Some firms that offshore to China and NMS
also offshore to other regions, but they are too few to report separately.
14
The difference between value-added and total sales comes from the resales of goods without transformation, materials ,and the cost of subcontractors. More work is needed to see which of the last three12teristics of firms that engage in foreign markets more generally, with the exception of laborproductivity.
Table 2: Offshorer versus Non-Offshorers

log FTElog Saleslog Sales/Worker
log VA/Worker
Importer
Exporter
Imports/Sales
Exports/Sales

Level(2001)

Change(2001-2006)

0.57***
0.62***
0.06-0.03
0.18***
0.19***
0.05***
0.16***-0.17***-0.08*
0.08**
0.00
-0.02
-0.01
0.02***
0.00

Notes: Each entry is the estimated coefficient from regressing the variable in column 1 on an indicator for whether
the firm offshored its primary activity between 2001 to
2006. For the column titled “Level” the dependent variables is the (log) level of the variable in 2001 and the controls include NACE4 industry fixed effects. For the column “Change”, the dependent variable is the change from2001-2006 and the controls include NACE4 industry fixed
effects.

Column 2 of Table 2 shows the changes in these same firm characteristics from 2001
to 2006, the period when the offshoring is undertaken. While both employment and sales
growth are significantly lower at offshorers, the relative changes lead to a significant increasein sales per worker. The measure of labor productivity, value-added per worker, grows at
the same rate for both groups of firms over the interval while import shares rise at offshoringfirms.

3.3

Offshoring firms’ import behavior and domestic production

An important contribution of this paper is to document the relationship between an explicit
firm-level measure of offshoring and firms’ import behavior. Offshoring is often equated with
imported intermediates, but it can take place in a variety of forms. It is not evident that aadjustments explain the difference between the sales per worker and value-added per worker premia.

13firm relocating its main activity to a foreign country will necessarily import intermediates.
In fact, offshoring need not entail any importing by the firm back to the home country.
Many firms offshore assembly of the final product, and others offshore the entire production
activity of a product.15
For the top two sourcing locations, NMS and China, we analyze how offshoring relates tofirm import behavior. Figure 2 shows that firms re-orient the sources of their imports towards
the offshoring regions. The left panel shows that firms that offshore to NMS countries morethan double their share of imports from NMS over the offshoring period. The right panelpresents similar results for firms that offshore to China.16 These results provide reassuring
evidence that the offshoring survey is capturing real changes in firm behavior, and support
prior work that has argued for using imports as a measure for offshoring.
Figure 2: Imports from offshoring region over total imports
Chinese Import Share
By China Offshore Status

00

NMS Imports/Total Imports
.1
.2
.05
.15

China Imports/Total Imports
.05
.1
.15

.25

NMS Import Share
By NMS Offshore Status

2000

2002

2004
Year

Offshorers

2006

2008

2000

Non-Offshorers

2002

2004
Year

Offshorers

Notes: Balanced panel of firms.

2006

2008

Non-Offshorers

Notes: Balanced panel of firms.

(a) NMS(b) China

We next examine the types of goods that offshoring firms import. To do so, we use dataon produced goods from the Prodcom production survey described above to identify whether
a firm’s imports constitute domestically produced goods. We identify a firm’s production
by HS6 product and label all imports that the firm also produces in Denmark as imports ofproduced goods. The left panel in Figure 3 shows that offshoring firms increase their imports
15

For example, firms may engage in platform FDI, as modeled in Tintelnot (2017).
In the Appendix, we perform a similar analysis for firm exports. While firms’ exports to their offshore
locations grow, they do so much less than for their imports.
16

14

of goods that they also produce domestically from 20MDKK to about 35MDKK over theoffshoring period, while non-offshoring firms’ produced good imports are relatively stable.17
The right panel of Figure 3 shows the opposite pattern for imports of goods that the firm
does not produce domestically. Offshorers actually shrink their average imports of thesegoods, while non-offshorers increase their imports of non-produced goods substantially.
In the Appendix, we also present results analyzing firms’ imports of inputs, as reported in
the material purchase survey. This survey generally only provides detail at the HS4 productlevel, so we compare imports of inputs and produced goods with each defined at the HS4level. The input and produced good classifications need not be mutually exclusive since a firm
could both produce a particular product and also purchase it as an input. While offshoringfirms increase their share of produced good imports and of imports that are classified asboth produced goods and inputs, they do not seem to increase imports of goods classified
solely as inputs.
Figure 3: Average imports by good type and offshore status
By Offshore Status

50
MDKK
40
30

0

20

10

MDKK
20

30

60

Average Imports of Non-Produced Goods

By Offshore Status
40

Average Imports of Produced Goods

2000

2002
Offshorers

2004
Year

2006

2008

2000

Non-Offshorers

2002
Offshorers

Notes: Balanced panel of firms.

2004
Year

2006

2008

Non-Offshorers

Notes: Balanced panel of firms.

(a) Produced Goods(b) Non-produced Goods

A common preconception about offshoring is that firms’ foreign activities substitute for17

One question raised by figure 3 is why offshoring firms have such high levels of produced good imports
in 2001, prior to offshoring. In the Appendix, we show that offshorers in the survey have higher average
imports of produced good imports from the old EU countries in 2001. Interestingly, firms that offshore to
NMS seem to grow their old EU produced good imports as well, while firms that offshore to China but not
the NMS shrink their produced good imports from the old EU and grow their produced good imports from
China.

15

domestic production. From this perspective, an increase in imports should lead to a reductionin production in Denmark. While prior work has shown that access to foreign imports
increases domestic productivity (Amiti and Konings, 2007) and that cost reductions in foreign
affiliate locations can increase domestic employment (Kovak et al., 2017), the displacement
effects of offshoring could be particularly strong when firms import goods that they also
produce domestically.
To assess how offshoring affects domestic production, Figure 4 plots firms average production by offshore status. The left panel shows that average production for goods thatthe firm also produces domestically actually grows over the offshoring period similarly forboth types of firms. In contrast, offshoring firms see a sharp decline in the average domestic
production of the goods that they do not import. Since average production of non-imported
goods is relatively small, offshoring firms’ total average production is relatively steady over
the offshoring period, even as their imports of produced goods increase.
Figure 4: Average production by good type and offshore status
Avg Domestic Production of Produced-Only Goods

By Offshore Status

By Offshore Status

0

20

30

MDKK

MDKK
50
40

60

200

70

Avg Domestic Production of Produced & Imported Goods

2000

2002
Offshorers

2004
Year

2006

2008

2000

Non-Offshorers

2002
Offshorers

Notes: Balanced panel of firms.

2004
Year

2006

2008

Non-Offshorers

Notes: Balanced panel of firms.

(a) Imported Goods(b) Non-imported Goods

A natural question is why do firms produce and import the same products? The factthat offshoring firms’ domestic production of goods that they also import is thus more
resilient than their production of non-imported goods suggests that they may have certain
capabilities in those produced and imported goods that they can leverage across multiple
production locations. For instance, offshoring firms may maintain domestic production of16

a higher quality variety, while they offshore production of lower quality varieties. Table 3
provides evidence consistent with this story. For the sample of firm-products (CN8) from
2000-2008 with both production in Denmark and imports from abroad in the same year, we
regress unit values on a dummy for domestic production while controlling for firm-productand year fixed effects.18
The coefficient on domestically produced varieties is large, positive and significant. Column 1 in table 3 suggests that on average, domestic varieties have unit values 60 percent
higher than their imported counterparts within the same firm. A potential concern with thisestimate is that the domestic unit values and the import unit values come from different data
sources, with the latter excluding any potential mark-ups the offshoring firm may add in thedomestic market. We thus examine the extent to which this differential in domestic versus
foreign unit values is larger for offshoring firms. The second column includes an interaction
between the offshoring dummy from the survey and the domestic unit value and shows thatthe price gap is 27 percentage points higher for offshoring firms. The final column adds
country/region specific indicators for the imported varieties and shows that imports fromthe China are 42 percentage points lower than imports from all other locations, and NMS
imports are 20 percent lower. In contrast, imports from the original 15 EU countries are 12
percentage points higher that imports from other countries. These patterns suggest quality
differentiation within a detailed product category that differs systematically across countries(e.g., as in Schott, 2004), with firms offshoring production of low quality versions to China
and NMS countries.
If offshoring involves relocating production of low quality versions of particular products
abroad, we would expect to see the domestic unit value of those goods rise after firms begin
to import them. To assess the extent to which offshoring firms’ domestic quality changes
in conjunction with offshoring, we estimate how firms’ domestic unit values evolve in an
18

The unit value for the domestic variety comes from the Prodcom survey and represents the domestic
factory gate price, while the unit value for the imported variety comes from the Danish customs data andrepresents the imported price.

17

Table 3: Unit value differences for domestically-produced varieties of the same productDependent variable - the log unit value of a CN8 product

Domestic variety

(1)

(2)

(3)

0.596***(0.096)0.520***(0.093)0.268**(0.113)3.966***(0.039)
0.70
Yes
Yes
37,4503.966***(0.039)
0.70
Yes
Yes
37,4500.566***(0.117)0.205*(0.112)-0.423***(0.066)-0.200***(0.058)0.123**(0.060)3.946***(0.067)
0.70
Yes
Yes
37,450

Domestic × Offshorers
China
NMS
EU15
Constant
R2
Year Fixed Effects
Firm-by-Product Fixed Effects
Observations

Notes: The sample includes all firm-product-year combinations from 2001-2008
where there is both domestic production and importing of the same CN8 product by
the firm in the same year. The dependent variable is the log unit value. “Domestic”
is a dummy for whether the variety is produced domestically; “Offshorer” is adummy for whether the firm offshored its core activity during 2001-2006; “China”,“NMS” and ‘EU15” are dummies for whether the imported variety comes from
China, the NMS, or the EU15 respectively. Standard errors clustered by CN8
product.

18

event study setting. We focus on firms that produce the same detailed CN8 product for atleast 7 consecutive years, that also also import the product during the period, and for which
we observe at least three years of pre-importing and three years of post initial-importing
domestic production. To address differences in units across unit values, we normalize unit
values to one within each firm-CN8 product in the firm’s initial import year, and estimate

log(pf t ) = αt +X

βk ∆Impf,t+k + εf t ,(1)kwhere αt denotes year fixed effects, ∆Impf,t+k is a series of indicators that identify the firm’s
initial import year, and (pf t ) is the normalized domestic unit value. We cluster the standard
errors by CN8 product category. Figure 5 presents the event study coefficients, and shows aclear increase in domestic unit values after firms begin offshoring. This increase may reflect
offshoring firms abandoning domestic production of lower quality versions (e.g., as proposedin Schott, 2008), or quality of upgrading of their domestically-produced versions as they
reallocate domestic resources towards innovation.
Figure 5: Imports from offshoring region over total imports

Domestic Unit Value Estimates
Log Normalized Domestic Unit Value
.04
.06
-.02
0
.02

Event Study Coefficients

-3

-2

-1
0
1
2
Years Since Initial Importing from NMS or China

3

Domestic unit value normalized to 1 in initial import year. Balanced panel of pre and post years.

19

The richness of these data provides novel evidence on the relationship between offshoringand importing. While it has become common to equate a firm’s decision to relocate production to a foreign country with a decision to import intermediates, we show that offshorers
tend to import the same goods that they produce domestically. Perhaps most surprisingly,
firms’ imports of goods that they produce do not seem to decrease domestic production.
The unit values of domestically-produced goods are systematically higher and rise after
offshoring, however, suggesting a role for quality differentiation within the same detailed
product category.

3.4

Offshoring and employment composition

There has been considerable attention paid to the employment effects of offshoring. Table 4
presents summary statistics of the labor composition at offshoring and non-offshoring firms
in 2001 and 2008. The top Panel A shows that offshoring firms have seen a large decline
in their share of less-educated workers, those with less than a high school degree. These
workers fell from 37 percent of the workforce at offshoring firms in 2001, to 30 percent in2008. In contrast, the share of these workers at non-offshorers stayed constant at 38 percent
over the same period. The decline in low-education worker shares at offshorers shows up inlarge increase in the high education worker share, which almost doubles, and a more modest
rise in middle education worker shares. Non-offshorers have a small decrease in the middle
category and a small rise in the most educated group.
Panel B of Table 4 presents similar information on labor composition by occupations.
The most notable difference between offshoring and non-offshoring firms is in their sharesof technology workers. Offshorers start with technology workers comprising 17 percent of
their workforce in 2001, but the share climbs about more than 40 percent to 24 percentof the workforce by 2008. In contrast, technology workers increase slightly from 13 to 14
percent of the workforce for non-offshorers over the same interval. Both types of firms see
their production worker shares decline, with larger declines for offshorers. While offshorers
20

Table 4: Labor force characteristics by offshoring status
2001

2008

0.37
0.57
0.06

0.30
0.59
0.11

0.38
0.55
0.07

0.38
0.52
0.09

0.03
0.54
0.07
0.17
0.13
0.05
0.01

0.04
0.38
0.06
0.24
0.18
0.08
0.01

0.04
0.32
0.09
0.13
0.27
0.13
0.02

0.04
0.22
0.10
0.14
0.28
0.21
0.01

Panel A: Education
Offshoring firms
Education - low
Education - middle
Education - highNon-offshoring firms
Education - low
Education - middle
Education - highPanel B: Occupations
Offshoring firms
Managers
Production workers
Blue non-production workers
Tech workers
Support workers
Sales workers
NEC
Non-offshoring firms
Managers
Production workers
Blue non-production workers
Tech workers
Support workers
Sales workers
NEC

Notes: Offshoring firms are defined as those that relocated their core activity
to a foreign region between 2001 and 2006. Low education workers have lessthan a high school degree, middle education workers have a high school degree
but less than a bachelors degree, and high education workers have a bachelor’s
degree or above. See the online Appendix for the ISCO codes corresponding tothe occupation categories.

21

increase their technology worker shares relatively more, non-offshorers see bigger increases intheir share of sales workers. Sales worker shares increase by 3 percentage points at offshorers,
compared to 8 points at non-offshorers.19
Figure 6 plots the average number of workers at offshoring and non-offshoring firms fora balanced panel of firms from 1998 to 2008. First, it is clear that firms in the offshoring
survey are significantly larger than the average firm in Denmark. The average non-offshorer
has about 125 employees in 1999. Offshoring firms are almost twice this size, with about 250
employees in 1999. Although offshoring firms start larger, their trends in average firm size
are similar from 1998 to 2001. Starting in 2001, however, the offshoring and non-offshoringfirms’ behavior diverges significantly. The average offshoring firm size drops sharply from2001 to 2005 and then flattens out. In contrast, non-offshorers display a slight upward trend
in their average firm size.
Figure 6: Average firm employment by firm’s offshoring status
Average Workers Per Firm

100

Avg workers per firm
150
200

250

By Firms' Offshore Status

1998

2000

2002

2004

2006

2008

Year
Offshorers

Non-Offshorers

Notes: Balanced panel of firms

Notes: Figure plots average firm employment for firms in the offshoring survey. Offshoring firms are thosethat relocated their core activity to a foreign country between 2001 and 2006.

An important contribution of this paper is to show how offshoring relates to a firm’s
19

We present the level of employment shares by category, but the patterns depicted here are similar whencalculating averages relative to a firm’s industry average. The empirical analysis will be based only on
manufacturing firms and include industry fixed effects to control for compositional differences by offshore
status.

22

allocation of resources – and in particular employees – towards innovative activities. Figure
7 plots the share of technology workers in total employment for offshoring and non-offshoringfirms. Offshoring firms start with slightly higher shares of technology workers, but theirshare diverges from non-offshoring firms’ technology worker share over the offshoring period.
While offshoring firms’ tech worker growth rate increases in 2002, non-offshorers’ growthrate flattens out in about 2003.
Figure 7: Share of technology workers by firm’s offshoring status
Technology Worker Share.14

Avg tech worker share
.18
.16
.2

.22

By Firms' Offshore Status

1998

2000

2002

2004

2006

2008

Year
Offshorers

Non-Offshorers

Notes: Balanced panel of firms

Notes: Figure plots the share of technology workers over total employment for firms in the offshoring survey.
Offshoring firms are those that relocated their core activity to a foreign country between 2001 and 2006.

One possible concern is that the rising share of tech workers is due to a decrease in
offshoring firms’ average size. Figure 8 shows that this is not the case. Even as total
employment at offshoring firms falls, their level of technology workers rises. In contrast,
non-offshorers tech workers grow at about the same rate as their total employment.

3.5

Offshoring and product development

To assess outcomes related to this increase in technology workers and the declining share of
production workers at offshoring firms, we compare changes in their product-level margins.
This exercise is limited to firms with manufacturing production, since production data are23

Figure 8: Level of technology worker employment by offshoring status
Workers at Non-Offshoring Firms

2000

2002

2004
Year

All Workers

2006

75
60
65
70
Tech Workers (000s)

Workers (000s)
460
480
500

55

440
420

12

66

68

Workers (000s)
72
70

13
14
15
Tech Workers (000s)

74

76

16

520

Workers at Offshoring Firms

2008

2000

Tech Workers

2002

2004
Year

All Workers

Notes: Balanced panel of firms

2006

2008

Tech Workers

Notes: Balanced panel of firms(a) Offshorers(b) Non-Offshorers

only available for this sector. Table 5 shows that in 2000, offshorers produce an average of
4.85 distinct products, compared to only 2.89 by non-offshorers. The difference is even larger
by 2007, with offshoring firms producing 6.26 products relative to only 3.05 for non-offshorers.
The right panel shows that this disproportionate increase in products by offshorers is driven
by the fact that almost half of their products in 2007 are new, while less than one third of
the products sold by non-offshorers are new introductions after 2000.
Table 5: Product switching by offshore status

Non-offshorers
percent
Offshorers
percent
Total
percent

No. of Products

Product changes from 2000-2007

2000

2007

Continued

DroppedIntroduced

2.89

3.05

4.85

6.26

2.15
74.4%
3.41
70.3%

0.74
25.6%
1.44
29.7%

0.90
29.5%
2.85
45.5%

3.22

3.60

2.36
73.3%

0.86
26.7%

1.24
34.4%

0.95
1.22

0.91
1.46

0.81
1.94

Relative to firm’s industry average
Non-offshorers
Offshorers

0.94
1.28

0.90
1.46

Notes: There are 1,220 firms (207 offshorers) with production data.

24

The evidence in table 5 suggests that product development may be an important new
activity for offshorers. Since offshorers are more concentrated in certain industries, we also
calculate within-industry statistics for product counts. The bottom panel of table 5 presents
average product counts by offshore status, normalized by each firm’s industry average. In
both 2000 and 2007, non-offshorers produced fewer products than the average firm in theirindustry. Offshorers produced 28 percent more products than their industry average in 2000,
and almost 50 percent more by 2007. As in the raw count data, new products represent themost important margin of adjustment for these differences. While non-offshorers introduced
only 81 percent of their industry average, offshoring firms introduced almost twice as many
new products over the period.
The descriptive evidence here is suggestive of a casual relationship between offshoring anda firm’s allocation of resources towards innovative activities. In the next section, we discuss
potential theoretical channels that might drive this evidence and outline an empirical strategy
to analyze the relationship more rigorously.

4

Theoretical motivation and empirical approach

In this section, we first describe the key theoretical channel through which we expect therelocation of domestic production abroad to affect firms’ organization of its domestic workforce. We then discuss several alternative channels and challenges in identifying the impact
of offshoring on innovation-related activities, and explain how we will assess or control for
their impact in our analysis. Finally, we present an identification strategy to address theseissues and to provide information on the various potential channels.

4.1

Theoretical channels for offshoring and innovation

We investigate how offshoring affects innovation by allowing firms to leverage knowledge
through the formation of international production teams. In Antràs et al. (2006), production25requires solving problems. Workers of different ability sort into teams, choosing whether tobe problem-solvers or production workers based on the relative returns to each activity,
which in turn depend on their skill. Offshoring occurs when production teams can form
across countries, with problem-solvers in one country combining with production workers inanother. The theory predicts that new offshoring opportunities will lead to an increase in
the number of problem-solvers in skill-intensive countries, with workers in those countries
shifting from production to problem-solving activities as they form teams with production
workers in lower wage countries.
In a related fashion, offshoring also leads production workers in the north to switch
into innovation-related activities in Rodrı́guez-Clare (2010). Since offshoring lowers the real
production worker wage in the north, it also lowers the opportunity cost to innovate. Workers
that were previously indifferent between production or innovation in the north will thus
switch into innovation. The key mechanism in both these models is a change in the relative
return to production work versus innovation that leads workers to change what they do.
When new offshoring opportunities arise, for example as a result of the EU accession process
in the NMS or China’s WTO entry, this lowers the return to production work in Denmark
for those firms that can offshore. The relative return to innovation thus rises, providing an
incentive for the firm to reallocate resources towards innovation, and for workers to switchfrom production to innovation-related occupations.
Heterogeneous firms models with fixed costs to offshore and to innovate provide an alternative channel through which offshoring may affect innovation. Bøler et al. (2015) develop
a model in which there are strong complementarities between firms’ sourcing decisions andtheir R&D investment. In their model, trade and technology are complementary activities
because they both lead firms to become more profitable and thus cover associated fixed
costs. Analogously in our work, if firms find offshoring more profitable, this may facilitate
an increase in their innovative activities. One way to assess the importance of this channel is
to control for changes in firm sales over the offshoring period. If the impact of offshoring on26

innovation is due to a firm scale effect, controlling for growth in firm output should eliminate
the offshoring effect on innovation.
Offshoring and innovation may also be related if both are optimal responses to increased
competitive pressure from abroad, as in Bloom et al. (2015). Bloom et al. (2014) present
a framework in which firms that face increased import competition reallocate “trapped”
resources within the firm towards R&D activities. In that model, increased competition
lowers the opportunity cost to innovate so that firms decrease production and shift workers
into innovative activities. A key feature of their theoretical channel is the presence of labormarket frictions that make it infeasible (or suboptimal) for the firm to fire workers in responseto the increased competition. Denmark has a particularly flexible labor market and it seems
unlikely that Danish firms face these types of firing frictions reducing the likelihood of atrapped factors explanation.20
Import competition may also lead firms to innovate by reducing x-inefficiencies (Schmitz,
2005), by changing managerial incentives (Schmidt, 1997; Aghion et al., 2005), or by incentiving firms to invest in new product varieties that do not compete with foreign imports(Impullitti and Licandro, 2017; Fieler and Harrison, 2018). We therefore focus on empirical
specifications in which we control for industry-level import penetration separately from afirm’s decision to offshore.
Offshoring and innovation may also be related if firms’ decisions to relocate overseas increase their access to new ideas or inputs. A number of papers document an important rolefor imported intermediates in improving firm productivity (Amiti and Konings, 2007; Goldberg et al., 2010; Halpern et al., 2011), and for imports in spreading ideas across countries(Coe and Helpman, 1995; Acharya and Keller, 2009). These channels may be quite important for offshoring by developing countries to more developed countries, but are likely lessimportant when considering Danish firms’ offshoring decisions to low wage countries, suchas China and NMS countries. In addition, we focus on Danish firms’ decision to offshore
20

Andersen and Svarer (2007) document the flexibility of the Danish labor market.

27their main activity, which is potentially distinct from the decision to offshore IT and R&D
activities.

4.2

Empirical approach

An important contribution of this paper is to show that offshoring leads firms to reallocate
their domestic workers towards innovative activities. A primary concern with estimating
this relationship is that firms may offshore production in response to other shocks. One
might expect a downward bias on the estimated coefficient of the effect of offshoring on
innovation if firms start offshoring in response to negative demand or productivity shocks,
for example as in Monarch et al. (2017). In this scenario, firms may seek to lower costs notjust by relocating production offshore, but also by reducing domestic expenditure on higher
wage occupations. Alternatively, one might expect an upward bias on the OLS estimatesif firms offshore their main activities so that they can re-orient domestic resources towards
innovation.
Perhaps one of the most obvious challenges to estimating the effect of offshoring to NMS
or China is that production cost saving opportunities in these locations may also entail
increased import competition. We assess this potential concern by estimating the probabilityof offshoring to China or NMS as a function of increased import penetration from thoseregions. Table 6 shows that this concern is empirically relevant for China. Increased importpenetration from China in a firm’s sector is associated not only with an increased likelihoodthat a firm will offshore to China, but also that it will offshore to NMS. In contrast, increased
import penetration from NMS does not seem to influence firm’s offshoring decisions.
The inter-relatedness between import competition and offshoring opportunities is thus anadded challenge to distinguishing the effects of a negative demand shock that differs acrossindustries (increased import competition in a firm’s industries) from a positive offshoringshock (increased production cost savings opportunities). The results presented in Table 6
also highlight a potential omitted variable concern in prior work. For instance, Bloom et al.
28

Table 6: Probability of Offshoring to China or NMS
Dep var is indicator equal to one if firm i offshores from 2001-2006 to:
China∆ChImpP en2001−2006
j1.111**(0.537)0.029**(0.011)-0.487**(0.186)1.225*(0.594)0.393(0.266)0.029**(0.011)-0.503**(0.184)-0.006(0.652)0.035**(0.013)-0.540**(0.227)2.543***(0.613)0.329(0.430)0.038***(0.012)-0.644***(0.212)

0.03
1,679

0.03
1,679

0.02
1,682

0.04
1,679

∆N M SImpP en2001−2006
jlogSales2001
i
Constant
R2
Observations

NMS

Notes: Import penetration measured at 2-digit NACE industry. Standard errors
clustered by industry.

(2015) find that European firms that faced increased Chinese import competition increased
their domestic innovation. One possibility is that those firms offshored production to NMS,
and that offshoring was actually the channel through which they increased innovation.
To address these issues, we implement an instrumental variables (IV) strategy in which we
identify changes in a firm’s offshoring decisions due to factors external to both the firm and
Denmark. Given the strong correlation between Chinese import competition and offshoring,
we focus on firms’ offshoring to NMS. We focus on NMS both because it is the main offshoring
destination for Danish firms, and because we are better able to distinguish between importcompetition and offshoring opportunities.
In order to exploit the most detailed product-level data available, and to control for broad
industry changes, we do not use the offshoring dummy in this section. Instead we rely on theevidence of the strong relationship between changes in a firm’s import share of domestically
produced goods and its offshoring decision. The change in the import share of produced
goods from the NMS is used as a proxy for firm offshoring to the NMS. The benefit of usingchanges in firm’s produced good import shares is that these can be measured at the detailed
six-digit product level and this measure can be employed by researchers without access to29comparable direct surveys on offshoring. Figure 9 shows that this measure is indeed a goodpredictor of offshoring to NMS, while increased shares of non-produced goods are not.
Figure 9: Average marginal effects of import shares on predicted offshoring to NMS
AMEs on Predicted Probability of Offshoring to NMS

AMEs on Predicted Probability of Offshoring to NMS

Growth in Non-Produced Good Imports from NMS over Total Imports

0-.3

Effects on Pr(Offshoring).51

Effects on Pr(Offshoring)
-.2
-.1

0

1.5

Growth in Produced Good Imports from NMS over Total Imports

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
Log Firm Sales in 2001(a) Produced good import share

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
Log Firm Sales in 2001(b) Non-produced good import share

Notes: Panel (a) plots the average marginal effects of growth in a firm’s produced good imports over total
imports share from 2001 - 2006 on its predicted probability of offshoring. Panel (b) plots a comparable figure
for non-produced good import share growth. Produced goods are defined as goods produced domesticallyby the firm in 2000 or 2001.

With this detailed product-level measure of offshoring in hand, we can exploit the factthat the 12 new EU member states underwent significant productivity growth and changes incomparative advantage across products during the offshoring period due to internal changes
required for accession to the EU. We measure variation in their comparative advantagechanges across detailed product categories using changes in six-digit HS product export
shares by the NMS countries to the rest of the world (ROW), excluding Denmark. Thisapproach is similar to Hummels et al. (2014), although we use changes in NMS’s export
shares rather than changes in levels to rule out growth driven by aggregate demand or
technology shocks that increase demand for particular products across all countries.
The export share growth rates are a product-level measure, but we require a firm-level
instrument to predict changes in offshoring. Since offshoring involves imports of goods also
produced domestically by the firm, we use each firm’s production across six-digit HS products
in 2000 and 2001 to assign the product-level shocks to the firm. Specifically, we aggregate30

the change in the export share in product k, ∆ExpShare2001−2006, to the firm level accordingkto:∆ExportShiN M S =Xshik ∆ExpShare2001−2006
,
k

(2)

k

where shik is firm i’s share of production of product k in 2000 and 2001.21 Single productfirms will therefore be assigned the change in the NMS export share for their single product,
while multi-product firms, which comprise the majority of the sample, will have a firmspecific shock based on the distribution of their pre-offshoring production.
One concern is that firms within industries may not be different according to their productmix. We find substantially product-share variation across firms within industries. The
average NMS offshoring firm produces 5.3 unique products, while the average non-NMS
offshorer produces 3.4 products. For all firms, the average of the firm-level median productshare is 0.48 for NMS offshorers and 0.57 for non-NMS offshorers.22
Our IV strategy identifies firms that began offshoring to the NMS as a result of improved NMS exports in products relevant to the firm. The key identifying assumption isthat the common within-product component of the relative increase in regional exports isdue to relative increases in NMS productivity. The exclusion restriction requires that theforeign region’s increased productivity only affects a firm’s innovative activities through its
impact on the offshoring decision. This restriction would be violated if improvements in
NMS comparative advantage also led to increased competition from the NMS, and that increased competition directly affected firms’ innovative activities (e.g., as in Bloom et al.,2015). We therefore construct a comparable measure of import competition from the NMS
into Denmark in the firm’s pre-period products. We measure import penetration at the HS6level as imports from NMS over total imports and domestic production, but excluding each21

We use production data in two years to ensure that we do not miss pre-offshoring production of lumpy
goods.
22
As an example of the variation we exploit, consider a hypothetical firm in the two-digit NACE industry“Manufacture of electrical equipment (27).” Potential HS6 products that firm could produce include: 850110(Electric motors; of an output not exceeding 37.5W), 850151 (Electric motors; AC motors, multi-phase, ofan output not exceeding 750W), and 850161 (Generators; AC generators (alternators), of an output notexceeding 75kVA).

31

firm’s own imports and production. We calculate changes from 2001 to 2006 and constructa weighted average based on the firm’s pre-period production shares. Our identification
strategy thus precisely exploits important distinctions between offshoring and import competition. In our first stage, we estimate how 2001 to 2006 changes in a firm’s produced good
imports from NMS over total imports are predicted by NMS export share growth in thefirm’s pre-offshoring product mix:

∆P P ImpShi,N M S = α + βSh ∆ExportShi,N M S + βImp ∆ImpP eni,N M S + εi ,(3)where P P ImpShi,N M S is the change firm import share of produced products from the NMS,
∆ExportShiN M S is the firm-specific change in NMS export shares in markets outside Denmark, and ∆ImpP eniN M S is a firm-specific measure of the change in the import penetration
to Denmark from NMS in a firm’s pre-period product mix. All variables are changes from2001 to 2006. Note that estimation of equation (3) is thus similar to a first differences approach since we exploit changes in foreign comparative advantage to identify changes in a
firm’s offshoring status. All specifications also include two-digit NACE industry fixed effects. Since the regressions are in differences, these fixed effects capture broad industry-levelchanges in import competition. We weight the regressions by firm employment and winsorize
the top and bottom one percent of outliers.
In the second stage regressions, we estimate how firm-level outcomes such as employment
and workforce composition change in response to a firm’s offshoring decisions according to:∆yi2001−2008 = α + βP P ∆P P ImpShi,N M S + βImp ∆ImpP eniN M S + εi2001−2008(4)

where ∆yi2001−2008 is the change in the firm-level outcome variable from 2001 to 2008 and theother variables are as described in equation (3). These specifications again include two-digit
NACE industry fixed-effects to control for broad sectoral changes over time. We weight the
regressions by firm employment and winsorize the top and bottom one percent of outliers.

32

5Offshoring and Firm Outcomes

In this section, we present results from estimating Equation (4) via OLS and when instrumenting for offshoring decisions using the instrument described in section 4.2. We alsopresent the reduced-form results from regressing the firm-level employment outcome variables directly on the instrument described in equation (2).

5.1

OLS and Reduced form results

Table 7 presents OLS results for the IV sample for offshoring to the NMS. The sample size
drops substantially to 1,149 firms due to the need for product-level data to construct themeasure of firm produced product imports and the instrument itself.
Table 7: OLS results for offshoring to NMS and workforce changes
Dependent variable is 2001-2008 change in :
(1)
log
empl
∆P GimpSh2001−2006
i,N M S
∆ImpP en2001−2006
i,N M S
Constant
R2
Observations

(2)
Tech
Share

(3)
Edu Hi
Share(4)
Edu LowShare-0.398*0.081***(0.204)(0.026)-0.3200.044(0.537)(0.068)-0.229*** 0.030***(0.018)(0.002)

0.066***(0.015)-0.044(0.041)0.027***(0.001)-0.127*** 3.776*
0.338***(0.025)(1.984)(0.109)-0.033-10.319** -0.495*(0.065)(5.088)(0.279)-0.048*** 2.752*** 0.131***(0.002)(0.172)(0.009)

0.09
1,149

0.22
1,149

0.12
1,149

0.14
1,149

(5)
New
Prods

0.12
1,026

(6)
New
Prod Sh

0.12
1,026

Notes: ∆P GimpSh2001−2006
is the share of produced goods in total NMS imports for the firm fromi,N M S
2001−2006
2001-2006. ∆ImpP eni,N M S
is a firm-specific measure of product import penetration with firm
production shares as weights. Regressions are weighted by employment and include 2-digit NACE
industry fixed effects. * p<0.10, ** p<0.05, *** p<0.01

Column 1 reports the results for log firm employment. The coefficient on the offshoring
variable is negative and significant at the 10 percent level and the magnitude is comparable
to that for the firm-level import penetration measure. Columns (2)-(4) report results for33

measures of labor force composition within the firm. Offshoring is positively and significantly
correlated with the firm’s share of technology workers in total employment and the share ofworkers with a college degree or higher. The share of workers with less than a high school
degree is negatively and significantly correlated with offshoring.
The final two columns examine a firm-level measure of innovative activity through theintroduction of new products. The dependent variable is the number of new products andthe share of new products in the firm product portfolio in columns (5) and (6) respectively.
The number of new products is positively related to offshoring, although weakly significant,while the new product share is also positive and significant at the one percent level. While
the relationship between offshoring and innovation is positive in these specifications, importcompetition is associated with relatively fewer new product introductions and shares. TheseOLS regressions largely conform to the stylized facts presented previously and suggest an
important distinction between import competition and offshoring.
Table 8 presents the reduced-form results for the same sample of firms. The main variableof interest is now the change in export share by NMS countries weighted by the firm’s preperiod production shares, ∆ExportShi,N M S . The biggest change occurs in the employment
regression where the instrument is essentially zero, in contrast to the negative and significant
coefficient in the OLS regression. This result is consistent with the premise that firms offshore
in response to a negative shock. The coefficient on import penetration remains negative andessentially unchanged, although still not significant.
For the labor force variables, the results are consistent with the OLS findings with smaller
coefficients. Offshoring has a positive effect on tech worker and high education workers
shares and a negative effect on the share of the lowest education group. The proxies forinnovative activity, new product introductions and new product shares, both have positiveand significant coefficients on the offshoring variable.

34

Table 8: Reduced-form results for offshoring to NMS and workforce changes
Dependent variable is 2001-2008 change in :
(1)
log
empl
∆ExportSh2001−2006
i,N M S
∆ImpP en2001−2006
i,N M S
Constant
R2
Observations

(2)
Tech
Share

(3)
Edu Hi
Share(4)
Edu LowShare-0.006
0.038***(0.045)(0.006)-0.3180.024(0.538)(0.067)-0.236*** 0.017***(0.024)(0.003)0.026***(0.003)-0.058(0.040)0.018***(0.002)-0.017*** 0.969**
0.093***(0.005)(0.434)(0.024)-0.024-11.751** -0.629**(0.066)(5.089)(0.279)-0.044*** 2.504*** 0.106***(0.003)(0.230)(0.013)

0.09
1,149

0.25
1,149

0.1
1,149

0.17
1,149

(5)
New
Prods

0.12
1,026

(6)
New
Prod Sh

0.12
1,026

Notes: ∆ExportSh2001−2006
is a firm-specific measure of the change in product export shares fromi,N M S
the NMS excluding exports to Denmark from 2001-2006 with firm production shares as weights.
2001−2006∆ImpP eni,Nis a firm-specific measure of product import penetration with firm production
MSshares as weights. Regressions are weighted by employment and include 2-digit NACE industry fixed
effects. * p<0.10, ** p<0.05, *** p<0.01

5.2

IV results

The first stage results are given in Table 9. The instrument is significant with the expected
sign for both samples. The first-stage F-statistic on the excluded instruments is 87.7 and110.7, respectively.
Table 10 presents the results from estimating equation (4), while instrumenting forchanges in the firm’s share of produced good imports using growth in the NMS’s export
shares in the firms’ pre-offshoring product mix. As in the reduced form results, the effectof offshoring on firm employment is not significantly different from zero. The IV estimatesagain confirm a positive impact of offshoring on firms’ share of technology workers. Theysuggest that a ten percentage point increase in the share of NMS imports of goods initially produced domestically leads to a 6.5 point increase in the firm’s share of technology
workers.23 This represents an almost 40 percent increase relative to the average offshoringfirm’s pre-offshoring technology worker share. The IV results also show that offshoring firms
23

The mean (standard deviation) of the change in the produced good import share at non-offshorers is
0.006 (0.065) versus 0.05 (0.136) at offshorers.

35

Table 9: First Stage Results
Dependent variable is ∆P GimpSh2001−2006:
i,N M S
∆ExportSh2001−2006
i,N M S
∆ImpP en2001−2006
i,N M S
Constant
R2
FStat on Excl Ins
Observations

(1)

(2)

0.059***-0.006-0.029-0.0760.001-0.0030.069***-0.007-0.217***-0.0770.006-0.003

0.23
87.74
1,149

0.22
110.701,026

Notes: ∆P GimpSh2001−2006
is the share of produced goods in totali,N M S
2001−2006
imports for the firm from 2001-2006. ∆ExportShi,Nis aMS
firm-specific measure of the change in product export shares fromthe NMS excluding exports to Denmark from 2001-2006 with firm
production shares as weights. ∆ImpP en2001−2006
is a firm-specifici,N M S
measure of product import penetration with firm production sharesas weights. Regressions are weighted by employment and include
2-digit NACE industry fixed effects. * p<0.10, ** p<0.05, ***p<0.01increase their share high skilled workers and reduce their low skilled worker share.
Offshoring also increases the number of new domestically-produced goods relative to nonoffshorers. A ten percentage point increase in the firm’s produced good import share leads
to a 1.4 new product introductions. In contrast, increased import penetration from NMS
is associated with fewer new products at the firm. As is typical, the IV coefficients aresubstantially larger than the OLS estimates which in turn are larger than the reduced form
coefficients.

5.3

Robustness

We report a wide variety of robustness checks on our main specification.24 First we check forthe possibility that omitted firm characteristics are driving the results. We include initial
firm size to check if the findings are driven by differential changes at large (small) firms
24

These results are not yet disclosed, but will be added to the Appendix.

36

Table 10: IV results for offshoring to NMS and workforce changes
Dependent variable is 2001-2008 change in :
(1)
log
empl
∆P GimpSh2001−2006
i,N M S
∆ImpP en2001−2006
i,N M S
Constant
Observations

(2)
Tech
Share

(3)
Edu Hi
Share(4)
Edu Low
Share

(5)
New
Prods

-0.101 0.648*** 0.436***(0.742) (0.113)(0.069)-0.321 0.042-0.045(0.529) (0.081)(0.049)-0.326 -0.11-0.066(0.817) (0.124)(0.076)-0.284***(0.092)-0.032(0.066)-0.051(0.101)13.980** 1.341***(6.250)(0.353)-8.724*-0.338(5.158)(0.291)-2.687-0.213(7.175)(0.405)

1,149

1,149

1,026

1,149

1,149

(6)
New
Prod Sh

1,026

Notes: ∆P GimpSh2001−2006
is the share of produced goods in total imports for the firm from 2001i,N M S
2001−2006
2001−2006
2006 and is instrumented by ∆ExportShi,N. ∆ImpP eni,Nis a firm-specific measureMSMSof product import penetration with firm production shares as weights. Regressions are weighted by
employment and include 2-digit NACE industry fixed effects. * p<0.10, ** p<0.05, *** p<0.01

which are more likely to offshore. The results are all quite similar when we control for initial
firm size in the regressions. To account for the possibility that offshorers are inherently more
likely to use technology, we include a proxy for IT use by the firm and find that the results
are also robust. The results are also robust to controlling for pre-trends in the dependent
variable, which we do using changes in the dependent variable from 1996 to 2001. Finally,
although the two-digit NACE fixed effects capture broad industry trends, we also control for
firm-specific changes in Chinese import competition and find that our estimates are robust
to this control.
To assess whether the effects we estimate are likely driven by changes in scale at offshorers,
we run a specification with growth in firm sales as an additional control. Our results are
generally robust to adding this variable, which suggests that the channel driving our findings
is not simply a scale effect.

37

6Innovation

In this section, we consider the nature of the increases in technology worker shares andask whether these increase are driven by external hiring or reallocation of workers within
the firm. We also provide additional evidence on innovative activity by offshoring firms by
exploiting R&D survey data, available for a subset of firms, to show that offshoring firms
increase their R&D expenditures.

6.1

Margins of worker adjustment

The results in Sections 3 and 5 show that offshoring firms are reallocating their activities awayfrom those performed by production workers towards those performed by technology workers.
Here we provide descriptive evidence on the nature of those occupation shifts. These changes
may mask a large amount of churning of workers inside the firm. Figure 10 shows that theshares of technology workers in firm hires and separations are both higher and increasingfrom 1998 to 2008 for offshoring firms. In Figure 10a, we show that offshoring firms are
increasing their hiring of technology workers relative to overall hires during the period, while
non-offshoring firms have relatively constant hiring shares of technology workers. Similarly,
Figure 10b shows that separations at offshorers are disproportionately in technology workers,
and that prevalence is rising during the period. For non-offshorers, the share of tech workers
in separations is lower and constant.
We also examine the composition of workers employed at the same firm from year t to
t + 1. Figure 11 shows that for workers that remain at the firm, the share of technology
workers is higher and steadily rising at offshorers. This stands in sharp contrast to thepattern in non-offshorers, where the share of retained workers in technology occupations
remains relatively constant over the period. Approximately one third of the tech stayers
within the firm over this period switch into technology occupations from non-technology
occupations within the firm. Traiberman (2018) documents high switching costs for workers

38

Figure 10: Tech worker shares of hires and separations by offshore status(a) Share of tech worker hires(b) Share of tech worker separations

Notes: Figure plots the share of technology worker hires over total hires and share of technology worker
separations over total separations for firms in the offshoring survey. Offshoring firms are those that relocatedtheir core activity to a foreign country between 2001 and 2006.

switching occupations in response to import competition. The results here highlight thepossibility that within-firm switching may mitigate some of these costs.

6.2

R&D Expenditure

We conclude this section with simple descriptive evidence on firms’ R&D activities. Figure
12 shows (average) total R&D expenditures and R&D worker shares for offshoring and nonoffshoring firms from 2001 to 2008. Figure 12a plots average R&D expenditure in thousandsof Danish Kroner by firms’ offshore status. Beginning in 2004, there is a clear divergencein R&D spending trajectories, as offshoring firms significantly increase their expenditures,
both in level terms and relative to non-offshorers.25 A similar stark shift is seen in the shareof R&D workers at offshoring firms in Figure 12b. These results provide additional evidence
that firms’ shift in their workforce composition towards technology workers is indeed related
to changes in their innovative efforts.
We further exploit the richness of the R&D survey information to shed light on which25
The share of expenditures shows a comparable divergence starting in 2004, rising from just under 3 toover 4 percent of total expenditures at offshorers.

39

Figure 11: Share of tech worker stayers by offshore status

Notes: Figure plots the share of continuing technology worker over all continuing workers for firms in theoffshoring survey. Offshoring firms are those that relocated their core activity to a foreign country between
2001 and 2006.

Figure 12: Total R&D spending and R&D workers
R&D Worker Shares

By Offshore Status

By Offshore Status and Year

.02

.04

Employment Share
.06
.08
.1

.12

DKK (000s)
5000 10000 15000 20000 25000 30000

Average Total R&D Spending

2000

2002

2004
Year
Offshorers

2006

2008

Non-Offshorers

2000

2002

2004
Year
Offshorers(a) Total R&D spending

2006

2008

Non-Offshorers(b) R&D worker share

Notes: Figure plots average product and process R&D expenditure for firms in the offshoring and R&D
surveys. Offshoring firms are those that relocated their core activity to a foreign country between 2001 and2006.

types of expenditures drive these changes. The survey records process and product R&D
expenditures separately every other year. Figure 13 plots firms’ average R&D expenditures
broken apart by product versus process R&D from 2001 to 2007. The left panel, Figure 13ashows that offshoring firms sharply increase their process innovation spending after 2005.
40

Non-offshoring firms show little or no process innovation spending throughout the period.
This suggests that offshoring entails changes in firms’ physical production process which
require additional research to implement.
Figure 13: Average product and process R&D expenditure
By Offshore Status

5000

DKK (000s)
10000
15000

20000

Average Product R&D Spending

By Offshore Status

DKK (000s)
2000 4000 6000 8000 10000 12000

Average Process R&D Spending

2000

2002

2004
Year
Offshorers

2006

2008

Non-Offshorers

2000

2002

2004
Year
Offshorers(a) Process R&D

2006

2008

Non-Offshorers(b) Product R&D

Notes: Figure plots average product and process R&D expenditure for firms in the offshoring and R&D
surveys. Offshoring firms are those that relocated their core activity to a foreign country between 2001 and2006.

In contrast, Figure 13b shows that expenditure on product innovation, which is muchhigher on average than process innovation, rises for offshoring firms towards the end of theoffshoring period and stays up in 2007. Non-offshoring firms have much lower levels of
product R&D spending and it trends up steadily over the entire period.
This evidence supports the premise that offshoring allows firms to reallocate both workers
and financial resources towards innovation, and highlights its potential to increase future
growth with the advent of potentially more and better varieties of goods.

7

Conclusion

This paper exploits new information on Danish firms’ offshoring to construct a rich dataset
on firms’ global production decisions. We use these data to analyze how firms’ decisions to
relocate their primary activities to foreign countries affect not only their aggregate employ41

ment, but also their employment across activities. We find that over time, offshoring firms
change their employment composition significantly so that they ultimately employ a muchhigher share of technology and research-related workers.
The results in this paper point to important long-term implications of offshoring. We
show that firms that relocate their main activities to a foreign country are more likely to shift
their domestic resources into innovative activities. Since innovation is a major determinant of
future performance, this shift has important potential implications for the long-term effects
of offshoring on productivity and growth.

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45

A

Data appendix

A.1

Offshoring data details

Table A.1 presents all the offshoring location regions to which Danish firms relocate theircore activities.
Table A.1: Offshoring of core activity by region
RegionFirm count

Share

EU-12
China
EU-15
Other Asian countries and Oceania
Other European countries
India
US and Canada

205
126
109
60
46
30
25

0.54
0.33
0.29
0.16
0.12
0.08
0.07

Total offshoring firms

380

0.091

Notes: Locations to which firms relocated their core activity.

s
et

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&
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si
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oo

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ile
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xt
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st
s

0

.2

.2

.4

.4

.6

.6

.8

Figure A.1: Industry distribution of offshoring workers

Share of offshorers’ workers in industry
Industry share of offshorers’ workers

Share of offshorers’ workers in industry
Industry share of offshorers’ workers(a) Across Broad Sectors(b) Within Machinery

Notes: Figure plots the share of workers at offshoring firms within each industry (first/blue bars) and theshare of workers at offshoring firms across industries (second/red bars). Note that the red bars do not sum
to 1 since only the top industries are presented to minimize disclosure concerns.

A.2

Imports of produced goods by region

This section decomposes the produced good imports by region of the imports, for firms that
offshore to NMS and China. The left panel of Figure A.2 shows that firms that offshore46

to the NMS countries between 2001 to 2006 grow their produced good imports from the
NMS countries the most over the period. It is also evident that NMS offshorers start withrelatively high levels of average produced good imports from the old EU countries, comparedboth to their produced good imports from other regions, or to non-offshorers’ produced good
imports which Figure 3 shows is only about 5 MDKK. The right panel of Figure A.2 shows
similar patterns for firms that offshore to China, with even higher levels of produced good
imports from the old EU in 2001, and slight declines in those imports between 2001 to 2006.
Figure A.2: Average produced good imports by region and offshore status
By Import Region
Avg PG Imports (MDKK)
10
20
0

0

Avg PG Imports (MDKK)
10
15
20
5

30

Average Produced Good Imports by Chinese Offshorers

By Import Region
25

Average Produced Good Imports by NMS Offshorers

2000

2002

2004
Year
NMS
Old EU

2006

2008

2000

China
Other

2002

2004
Year
NMS
Old EU

Notes: Balanced panel of firms. PG are HS6 prods made by firm in 1999/2000.

2006

2008

China
Other

Notes: Balanced panel of firms. PG are HS6 prods made by firm in 1999/2000.

(a) NMS offshorers(b) China Offshorers

To understand how firms’ offshoring decisions may be interrelated across space, Figure
A.3 presents similar figures for firms that offshore to NMS but not China and for China, but
not the NMS countries. Here, the patterns are more stark. While both sets of firms havehigh levels of produced good imports from the old EU in 2001, the NMS offshorers growthose imports as they also increase their produced good imports from the NMS countries.
In contrast, firms that offshore to China but not the NMS see considerable declines in theiraverage produced good imports from the old EU. These figures not only show how closely
produced good imports match with an explicit relocation of production as identified by firms,
but also highlight the potential for produced good imports to show how global value chainsare structured across space.

A.3

Imports of produced goods versus intermediates

In this section, we use the Prodcom data at the HS4 level and the input purchase data, which
are generally available at the HS4 level, to assess the extent to which offshoring firms import
inputs and/or domestically produced goods. Figure A.4 shows that firms that offshore to
the NMS increase their share of produced good imports, as well as their share of imports ofproducts that they both produce and purchase as inputs (“Both”). In contrast, their shareof imported inputs of HS4 products that they do not produce domestically is low and fairly
stable.
Given the lack of detail for firms’ input purchases, we cannot rule out the possibility
that they are importing both inputs and produced goods. It is also possible, however, that47

Figure A.3: Average produced good imports by region and offshore status
Average Produced Good Imports by China Only Offshorers

By Import Region

By Import Region00

Avg PG Imports (MDKK)
10
5

Avg PG Imports (MDKK)
5
10
15
20

15

Average Produced Good Imports by NMS Only Offshorers

2000

2002

2004
Year
NMS
Old EU

2006

2008

2000

China
Other

2002

2004
Year
NMS
Old EU

Notes: Balanced panel of firms. PG are HS6 prods made by firm in 1999/2000.

2006

2008

China
Other

Notes: Balanced panel of firms. PG are HS6 prods made by firm in 1999/2000.

(a) NMS offshorers(b) China Offshorers

HS6-level detail on inputs would lead to much smaller shares of imported inputs (whereas
the main text shows that firms import the same detailed HS6 products they produce). Given
the low share and small changes for imported inputs, it seems that offshoring may be more
related to imports of produced goods rather than inputs. Figure A.5 presents similar patterns
for firms that offshore to China.

A.4

Offshoring and exporting

Here we show that offshoring firms shift their exports somewhat towards offshore regions, butthat these changes and levels are considerably smaller than the comparable changes observed
for firm imports. Offshoring thus seems to entail imports from the offshore location back to
Denmark, without considerable exporting of inputs from Denmark to the offshore location.
Figure A.6 depicts these patterns.

48

Figure A.4: NMS imports of inputs and produced goods
NMS Imports Over Total Imports
By Imported-Product Type and Offshore StatusNMS Offshorers.15
EU12 Imports/Total Imports
.05
.1
0

0

EU12 Imports/Total Imports
.05
.1

.15

Non-Offshorers

2000

2002

2004
2006
year

2008

Produced Good

2010

2000

2002

2004
2006
year

2008

Produced Good

InputsBoth

2010

InputsBoth

Inputs and produced goods based on HS4 input use and production in 2000/2001.

Notes: Figure plots the share of imports from NMS of HS4 products that are “Produced goods”, “Purchased
inputs”, or HS4 products classified as “Both” produced goods and purchased inputs over total imports ofthe firm.

Figure A.5: Chinese imports of inputs and produced goods
China Imports Over Total Imports
By Imported-Product Type and Offshore Status
China Offshorers.06
China Imports/Total Imports
.02
.04
0

0

China Imports/Total Imports
.02
.04

.06

Non-Offshorers

2000

2002

2004
2006
year

Produced Good

2008

2010

2000

2002

2004
2006
year

Produced Good

Inputs2008

2010

InputsBoth

Both

Inputs and produced goods based on HS4 input use and production in 2000/2001.

Notes: Figure plots the share of imports from NMS of HS4 products that are “Produced goods”, “Purchased
inputs”, or HS4 products classified as “Both” produced goods and purchased inputs over total imports ofthe firm.

49

Figure A.6: Exports to offshoring region over total exports
China Exports over Total Exports

By Firms' Offshore Status

By Firms' Offshore Status

0.02

EU12 Exports/Total Exports
.04
.06
.08

China Exports/Total Exports
.02
.04

.1

.06

NMS Exports over Total Exports

2000

2002

2004

2006

2008

2010

2000

2002

2004

year
China

NMS

2006

2008

2010

year
CN&NMS

None

China

(a) NMSNMS(b) China

50

CN&NMS

None