Does Material and Service Offshoring Improve
Domestic Productivity?
Evidence from Japanese manufacturing industries
Keiko Ito (Senshu University)
Kiyoyasu Tanaka (Institute of Developing Economies)
WIOD Conference on Industry‐Level Analyses of
Globalization and its Consequences
Technische Universitaet Wien, Vienna
May 26-28, 2010
1
Motivation
 Progress in fragmentation of production processes and
the international division of labor in East Asia
 Increase in offshoring to Asia contributed to skill-
upgrading in Japan (Ahn et al. 2008, etc.)
 Statistical evidence so far that offshoring enhances
productivity is still weak
 Particularly, on the effects of service offshoring,
empirical evidence is scarce
2
Definition of offshoring
 Olsen (2006)
 “Offshoring” refers to :
“Relocation of jobs and processes to any foreign
country without distinguishing whether the provider is
external or affiliates with the firm”
“International outsourcing”: relocation of business
activities to unaffiliated foreign firms
+
“International insourcing” : relocation of business
activities to affiliated foreign firms
3
The purpose of this study
 Utilizing the comprehensive I-O Tables, relatively
detailed industry-level data, and trade statistics, we
measure the size of offshoring of material inputs and
services inputs, and examine the trend and
characteristics of offshoring for Japanese manufacturing
 Using industry-level data, we investigate the impact of
offshoring on domestic productivity for the case of
Japanese manufacturing
 Test for the presence of productivity-enhancing effects
for both material offshoring and service offshoring
 Examine how the effects differ for offshoring to
different regions and of different activities
4
Potential impacts of offshoring on productivity
 By relocating inefficient tasks to low-cost countries, the
unit cost of the firm’s product falls (=cost savings)
 By offshoring less productive stages of production
process, firms can shift corporate resource to highproductivity activities (product development, process
innovation, etc.) (=restructuring)
 The use of new varieties of imported material or service
inputs may increase productivity (=variety effect)
 Technological innovations (ICT, transportation),
erosion of trade barriers
5
Previous studies (Industry-level studies)
 Egger & Egger (2006): EU mfg. 1992-97
Offshoring has a +tive effect on low-skilled worker
labor productivity in the long run
 Amiti & Wei (2006, 2009): US mfg. 1992-2000 (TFP & LP)
Service offshoring (++)
Material offshoring (+)
 Daveri & Jona-Lasinio (2008): Italian mfg. 1995-2003
Material offshoring (+)
Service offshoring (0)
 Lin & Ma (2008): Korean mfg. 1985-2001
Marial offshoring (+)
Service offshoring (-)
6
Previous studies (Micro-level studies)
 Görg & Hanley (2005): Irish electronics firms (1990-95)
Material offshoring (+) only for plants with low exp intensities
Service offshoring (0)
 Görg, Hanley & Strobl (2008): Irish mfg
Service offshoring (++) only for exporters
-- service offshoring requires knowledge to search for partners
 Hijzen, Inui & Todo (2006): Japanese mfg (1994-2000)
Offshoring (+) 4x greater effect than domestic outsourcing
 Fariñas & Martín-Marcos (2008): Spanish mfg (1990-2002)
Offshoring (+)
7
Unclear effects of service offshoring
 McKinsey Global Institute (2005, 2008)
US service offshoring to India  + on US economy
Germany & France  -tive
 Daveri & Jona-Lasinio (2008)
- transitional adjustment costs? ( low re-employment rates, less
flexible labor mkt, low job creation)
- most productive services are offshored to escape existing
inefficiencies at home? ( insufficient liberalization)
 Lin & Ma (2008): language barriers
 MGI (2005) : wage levels of destination countries,
competitiveness of the home country, ownership
structure of affiliated offshore providers
8
Measurement of offshoring
 Offshoring =(imported intermediate inputs from all
industries) / (total non-energy intermediate inputs)
 j 1 mij
N
zi 
Yi
N
zi  
j 1
mij IM j
IM j Yi
 Material offshoring: z=MO (j=mfg. industries)
 Service offshoring: z=SO (j=offshorable services)
- telecommunications, insurance, finance, business
services, information services
 Data: 1990, 1995, 2000 I-O tables (benchmark)
Trade statistics (MOF, Japan), METI extended I-O Tables, BOP
statistics, JIP database 2009
9
Table1. Material & service offshoring in Jpn mfg
1990
(%)
Imported inputs as a percentage share of total inputs
Materials
5.95
of which:
from North America
2.16
from EU
1.21
from Asia US: 12-17 % 1.60
from China
0.29
Italy
& Korea: 20+%
from
ASEAN4
0.48
Services
of which:
from North America
from EU
from Asia
from China
from ASEAN4
10
1995
(%)
2000
(%)
2004
(%)
6.29
7.69
8.89
2.08
1.14
2.24
0.60
0.61
Change 1990-2004
(% points) (%)
2.95
49.57
2.29
1.96
-0.21
US: 0.18-0.29
% 0.35
1.32
1.56
3.23 & Korea:
4.40 1+%2.80
Italy
0.98
1.73
1.44
0.96
1.16
0.68
-9.63
28.81
175.56
505.10
140.19
0.21
0.20
0.23
0.19
-0.02
-11.50
0.09
0.06
0.04
0.01
0.01
0.09
0.04
0.05
0.01
0.01
0.11
0.05
0.05
0.01
0.01
0.08
0.06
0.04
0.01
0.01
-0.003
-0.008
-0.008
0.003
-0.002
-3.72
-11.72
-18.78
47.09
-20.16
Estimation model
 Production function
Qi,t  T SOi,t , MOi,t  F Si,t , Mi ,t , Li,t , Ki,t 
LnQi ,t  0  1SOi ,t  2 MOi ,t  1LnSi ,t  2 LnMi ,t  3 LnLi ,t  4 LnKi ,t   i   t  ei ,t
 Regression Model
LnQi ,t  0  1SOi ,t   2 MOi ,t  1LnSi ,t   2 LnMi ,t   3LnLi ,t   4 LnKi ,t
  i i   t t   i ,t
 Include industry dummies & year dummies
 Include one-year lags of offshoring variables
 Endogeneity --- Use Value added per worker as a dependent
variable
 Data for S, M, L, K --- JIP Database 2009, 1988-2004
11
Table 3. OLS estimates of the effect of
offshoring on TFP (1)
Dependent variable: Δln (Real Output)
(1)
-0.58
(1.627)
Δ Service Offshoring
Δ Service Offshoring,
0.387
(1.071)
t-1
0.408*
(0.198)
Δ Material Offshoring
Δ Material Offshoring,
(2)
t-1
Δ ln(Material Input)
Δ ln(Service Input)
Δ ln(Number of Workers)
0.542***
(0.048)
0.07
(0.036)
0.084
(0.057)
0.35
(0.296)
0.518***
(0.045)
0.068*
(0.029)
0.072
(0.055)
(3)
-0.588
(1.511)
0.374
(0.706)
0.445*
(0.183)
0.258
(0.230)
0.544***
(0.050)
0.071*
(0.035)
0.074
(0.065)
Δ ln(Number of Nonproduction
Workers)
Δ ln(Number of Production Workers)
Δ ln(Capital Stock)
Year Dummies
Industry Dummies
Observations
R-squared
12
0.262*
(0.105)
yes
no
800
0.641
0.279*
(0.105)
yes
no
800
0.621
0.267*
(0.109)
yes
no
750
0.635
(4)
-0.588
(1.497)
0.31
(0.753)
0.380*
(0.152)
0.207
(0.191)
0.542***
(0.050)
0.075*
(0.035)
0.159
(0.130)
-0.079
(0.131)
0.267*
(0.109)
yes
no
750
0.637
Table 3. OLS estimates of the effect of
offshoring on TFP (2)
Dependent variable: Δln (Real Output)
(5)
-0.613
(1.716)
Δ Service Offshoring
Δ Service Offshoring,
0.268
(1.066)
t-1
0.151
(0.132)
Δ Material Offshoring
Δ Material Offshoring,
(6)
t-1
Δ ln(Material Input)
Δ ln(Service Input)
Δ ln(Number of Workers)
0.479***
(0.049)
0.062
(0.032)
0.104
(0.057)
0.139
(0.193)
0.467***
(0.046)
0.061*
(0.029)
0.109
(0.055)
(7)
-0.635
(1.603)
0.136
(0.674)
0.19
(0.130)
0.101
(0.171)
0.484***
(0.052)
0.062
(0.033)
0.09
(0.068)
Δ ln(Number of Nonproduction
Workers)
Δ ln(Number of Production Workers)
Δ ln(Capital Stock)
Year Dummies
Industry Dummies
Observations
13R-squared
0.124*
(0.055)
yes
yes
800
0.700
0.142**
(0.050)
yes
yes
800
0.688
0.152**
(0.056)
yes
yes
750
0.693
(8)
-0.658
(1.604)
0.095
(0.691)
0.175
(0.129)
0.092
(0.163)
0.486***
(0.052)
0.063
(0.033)
0.103
(0.136)
-0.012
(0.133)
0.149*
(0.057)
yes
yes
750
0.693
Robustness checks
 Labor productivity (VA per worker) specification
Material offshoring  +tive & significant (Table 4)
 TFP growth specification
Material offshoring  +tive & significant
 Additional controls (Table)
 Material offshoring: +tively associated with domestic
productivity
 Service offshoring: insignificant
14
Table 5. OLS estimates of the effect of material
offshoring to Asia on TFP
Dependent variable: Δln (Real Output)
(1)
-0.638
Δ Service Offshoring
(1.649)
Δ Service Offshoring, t-1
Δ Material Offshoring to Asia
Δ Material Offshoring to Asia, t-1
Δ ln(Material Input)
Δ ln(Service Input)
Δ ln(Number of Workers)
Δ ln(Capital Stock)
Year Dummies
Industry Dummies
Observations
15
R-squared
(2)
(3)
(4)
(5)
(6)
(7)
(8)
-0.481
-0.489
-0.637
-0.565
-0.575
(1.528)
(1.523)
(1.720)
(1.613)
(1.615)
0.304
0.034
0.031
0.232
-0.027
-0.037
(1.033)
(0.674)
(0.691)
(1.048)
(0.652)
(0.652)
1.037**
1.015*** 0.966**
0.466*
0.622*
0.606*
(0.303)
(0.220)
(0.288)
(0.225)
(0.234)
(0.287)
1.242*
0.963** 0.915**
0.728
0.690*
0.675*
(0.547)
(0.356)
(0.310)
(0.425)
(0.337)
(0.320)
0.536*** 0.509*** 0.530*** 0.530*** 0.480*** 0.465*** 0.484*** 0.484***
(0.045)
(0.044)
(0.046)
(0.046)
(0.047)
(0.045)
(0.049)
(0.048)
0.071*
0.074**
0.077*
0.078*
0.063
0.064*
0.066*
0.067*
(0.035)
(0.027)
(0.032)
(0.032)
(0.032)
(0.028)
(0.031)
(0.031)
0.091
0.091
0.094
0.105
0.116*
0.098
(0.061)
(0.051)
(0.067)
(0.060)
(0.053)
(0.069)
0.258*
0.268*
0.260*
0.261*
0.127*
0.141** 0.156** 0.154**
(0.104)
(0.102)
(0.105)
(0.105)
(0.055)
(0.049)
(0.056)
(0.055)
yes
yes
yes
yes
yes
yes
yes
yes
no
no
no
no
yes
yes
yes
yes
800
800
750
750
800
800
750
750
0.641
0.621
0.635
0.637
0.7
0.688
0.693
0.693
Table 6. OLS estimates of the effect of
information services offshoring on TFP
Dependent variable: Δln (Real Output)
(1)
Δ Information Services
10.75
(21.480)
Offshoring
Δ Information Services
Offshoring, t-1
0.409*
Δ Material Offshoring
(0.197)
Δ Material Offshoring, t-1
Δ ln(Material Input)
Δ ln(Service Input)
Δ ln(Number of Workers)
Δ ln(Capital Stock)
Year Dummies
Industry Dummies
Observations
16
R-squared
(2)
(3)
(4)
(5)
(6)
(7)
(8)
48.84
43.99
-0.341
65.72
65.40
(27.71)
(32.42)
(24.46)
(43.04)
(47.45)
82.62** 116.4** 108.5**
84.85** 146.5** 145.9*
(24.36)
(33.40)
(37.80)
(25.02)
(49.01)
(55.44)
0.377*
0.343*
0.152
0.13
0.129
(0.164)
(0.144)
(0.132)
(0.124)
(0.126)
0.347
0.204
0.178
0.148
0.056
0.055
(0.285)
(0.213)
(0.184)
(0.186)
(0.160)
(0.155)
0.542*** 0.517*** 0.542*** 0.541*** 0.480*** 0.465*** 0.482*** 0.482***
(0.049)
(0.044)
(0.050)
(0.050)
(0.049)
(0.045)
(0.052)
(0.052)
0.071
0.068*
0.074*
0.076*
0.063
0.061*
0.066
0.066
(0.036)
(0.030)
(0.036)
(0.036)
(0.032)
(0.030)
(0.034)
(0.034)
0.084
0.07
0.071
0.105
0.105
0.082
(0.057)
(0.057)
(0.068)
(0.057)
(0.057)
(0.072)
0.261*
0.272*
0.258*
0.259*
0.124*
0.130*
0.135*
0.135*
(0.105)
(0.107)
(0.112)
(0.111)
(0.055)
(0.052)
(0.062)
(0.061)
yes
yes
yes
yes
yes
yes
yes
yes
no
no
no
no
yes
yes
yes
yes
800
800
750
750
800
800
750
750
0.641
0.621
0.635
0.637
0.700
0.688
0.693
0.693
Summary of the results
 Material offshoring: +tively associated with domestic
productivity
 Service offshoring overall: insignificant
 Material offshoring to Asia : +tive & significant
 Material offshoring to NA & EUR: insignificant
 Characteristics of destination country do matter
 Offshoring to low-cost region brings greater productivity gains
 Information service offshoring: +tive & significant
 Business service offshoring: insignificant
17
Effect of service offshoring on productivity
 Business services involve a substantial amount of judgment
& communication b/w clients & professionals
 These tasks need to be standardized & reorganized in order
for foreign firms to provide them from a distance
 Peculiarities of Japanese language & business culture may
be a barrier
18
Conclusion
 Material offshoring has a positive effect on productivity while




19
service offshoring does not. (in line with previous results of Italy &
Korea, but at odds with results of U.S.)
Although the level of service offshoring is still low, increase in info
service offshoring would improve productivity.
However, it has been pointed out that the corporate organization of
Jpn firms is not well suited to standardized IT systems. (decisionmaking processes require substantial interdivisional comm. )
(Motohashi 2008)
Firms which restructure their IT management method would be
able to benefit from offshoring of services.
Material offshoring to Asia has a positive effect on productivity. The
large differences b/w factor prices at home & Asian countries,
coupled with geographic proximity, appears to have yielded a
productivity-enhancing effect.
Future research
 Peculiarities of the Japanese business practice or peculiarities of
the Japanese langugage & culture?  examine effects of
“international” outsourcing and “domestic” outsourcing of
business services
 Effects of offshoring on various types of workers (low-skilled or
high-skilled workers)
 Productivity effect of service offshoring by region
20
Thank you!
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