Organizational innovations and productivity: the
case of foreign outsourcing
José C. Fariñas
(U. Complutense Madrid)
Ana Martín-Marcos
(UNED)
Simposium on Business Dynamics and Innovation: The effects of agglomeration
economies
University of Barcelona
(8 October, 2008)
Introduction
•Oslo Manual (OECD, 2005):
•“… organizational innovations refer to the implementation of new
organizational methods. These can be changes in business practices, in
workplace organization and in the firm’s external relations”
•Among of the most relevant organizational methods in firm’s external
relations is outsourcing
• We use the term foreign outsourcing (offshoring) to mean the acquisition of
intermediate goods and services from foreign (affiliated and unaffiliated)
firms
•Fragmentation of production or foreign outsourcing has been a major factor
in the growth of trade and FDI
• The objective of the paper is to explore the relationship between foreign
outsourcing and productivity at the firm level
Outline
• Theoretical framework
• Descriptive evidence on foreign outsourcing
• Testing procedure and productivity measure
• Empirical results
• Robustness checks
•Other controls
•Endogeneity issue
• Main conclusions
Theoretical framework
• Antràs and Helpman (2004) offers a theoretical framework where firms
make two endogenous organizational choices:
- integration decision (integration vs. outsourcing)
- location decision (domestic vs. foreign)
• Two agents are engaged in production: final-good producers and firms
producing components that can be located at home (D) or in the foreign
country (F). Firms producing components can be vertically integrated (V) or
not: outsourcing (O)
• Fixed organizational costs of search, monitoring and communication are
ranked as follows:
fvF > foF > fvD > foD
- regardless of ownership structure, fixed costs are higher in the foreign country
- given location, costs of an V-firm > costs of an O-firm
Industry equilibrium predictions:
Location and integration decisions will depend on the level of firm productivity (λ) and
on the relative input intensity of the industry, according to the following pattern:
Component intensive industry:
Exit
Outsource in D
OF  OD
Outsource in F
(arm’s length trade)
λ, Productivity level
Headquarter intensive industry:
Exit
VF  OF  VD  OD
Either outsource or Outsource in F
(arm’s length trade)
integrates in D
Integrates in F (FDI)
(intrafirm trade)
λ, Productivity level
• Antràs and Helpman (2004) model predicts self selection:
high productivity firms outsource in international markets,
whereas low-productivity firms acquire intermediate
materials at home.
• However, from an empirical point of view, self-selection is
not inconsistent with the fact that firms engage in foreign
outsourcing in the expectation that this would improve
productivity:
firms reallocate relatively inefficient parts of their production process
to another country where they can be produced more cheaply
• Two-way relationship between foreign outsourcing and
productivity
Descriptive evidence on foreign outsourcing
• Foreign outsourcing = the import of intermediate
inputs (goods and services) by domestic firms
(Feenstra and Handson 1996).
• Measure (at the firm level):
– Share of imported intermediate inputs in the total purchase of
intermediate inputs.
Os f 
 imported intermedia te inputs of
j by firm f
j
total purchases of intermedia te inputs by f
• Estimates of foreign outsourcing at the firm level based on
information reported by Encuesta sobre Estrategias
Empresariales (ESEE):
– Firms report the value of their total imports
– Firms report the percentage of the capital stock purchased
abroad and the annul value of their investment in capital
goods
– Firms report the value of imports of similar goods coming
from affiliated companies
Imports of intermediate importsi  Total importsi - Imports of capital goodsi Imports of similar goodsi
Percent of firms importing intermediate inputs
60
53,7
55
49,6
50
45
55
43,6
40
35
30
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002
EXTENSIVE MARGIN:
Large increase in the percentage of manufacturing firms performing
foreign outsourcing over the period 1990-2002
Foreign outsourcing intensity: Imported intermediate inputs
/Total intermediate inputs (only importers)
25,00
20,10
20,00
18,80
16,50
15,00
10,00
5,00
0,00
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002
INTENSIVE MARGIN
Firms already performing foreign outsourcing have increased
their intensity, although less than the extensive margin
Table 3
Foreign outsourcing and firm size
Firm size
Percent of firms
performing foreign
outsourcing
Intensity of foreign outsourcing
(intermediate imports/total
intermediate inputs)
Only intermediate
importers
All firms
Firms with ≤ 200
employees
36,6
16,2
5,9
Firms with > 200
employees
80,2
20,1
16,1
Positive relationship between foreign outsourcing and the size of
firms. The difference is higher for the probability than for the
intensity, which suggest that performing this activity involves
significant sunk costs
Figure 2
The probability of outsourcing vs. the intensity of foreign outsourcing by industry
(2 digit manufacturing NACE and ISIC classification)
25
15
17
16
12
18
20
9
7
6
4
14
10
20
2
13
15
8
3
19
10
11
5
5
1
.2
.4
.6
Number of outsourcing firms/ Total number of firms
High degree of heterogeneity across industries.
Industries where the intensive and the extensive margins are higher:
15 Office machinery, computers and precision instruments
16 Electrical machinery and communication equipment
17 Motor vehicles
18 Other transport equipment
9 Chemicals and chemical products
.8
Testing procedure and productivity measurement
• Perform comparisons of productivity distributions of different groups of firms
• The procedure is based on non-parametric techniques and has been previously
used in Delgado, Fariñas and Ruano (2002)
• Let define two productivity distributions:
F, productivity distribution of firms outsourcing in foreign countries
G, productivity distribution of firms not performing foreign outsourcing
(either they integrate or outsource at home)
• According to predictions proposed in Antràs and Helpman (2004) for component
intensive industries, the distribution F should dominate the distribution G.
• Stochastic dominance of F relative to G requires two statistical conditions to be
satisfied:
- First, both distributions are not identical, i.e. the null hypothesis H0 : F(z)G(z) = 0 can be rejected;
-Second, the sign of the difference is as expected, i.e. the null hypothesis H0 :
F(z)-G(z)  0 cannot be rejected
(the variable z represents independent random samples drawn from cdf’s F and
G, of size n and m respectively)
• These two-sided and one-sided tests can be performed respectively using the
Kolmogorov-Smirnov test statistics:
• To further illustrate the comparisons between the productivity of different groups
of firms we have graphed their smooth sample distribution functions.
Productivity measurement
• Database: Encuesta sobre Estrategias Empresariales (ESEE)
• Panel of manufacturing firms containing 21,098 observations over the period
1990-2002 that correspond to an average number of 3,462 firms per year.
• The dataset is representative of the population of Spanish manufacturing firms
Large firms (more than 200 employees)
Small firm (between 10-200 employees), random sampling scheme
• Firm productivity is defined by an index of total factor productivity for each firm
over the period 1990-2002. The index proposed is an extension of the multilateral
total factor productivity index proposed by Caves, Christensen and Diewert
(1982).
•The expression of total factor productivity for firm f, at time t, in a given industry is:
ln  ft ( )
1 R
 ln y ft  ln y   ( rft   r )(ln x rft  ln xr ) 
2 r 1
1 R
ln y  ln y   ( r   r )(ln xr  ln x r );
2 r 1
Where, yft is the output of firm f at time t; xrft is the quantity of input r labor,
materials and the stock of capital, corresponding to firm f at time t; ωrτ is the cost
share of input r. Firms are classified in two size groups of small and large firms, 
= 0 ,1
• The index measures the proportional difference of TFP for firm f relative to a
given reference firm. The reference firm varies across industries (NACE
classification at the two-digit level). When observations are pooled, average TFP
differences across industries are removed.
Empirical results
1. Comparisons between productivity distributions that have been
performed:
- Foreign outsourcing firms vs. non-foreign outsourcing firms
1.1 All manufacturing firms
1.2 Component intensive industries
- Ex-ante comparisons: entering outsourcing firms vs. non-outsourcing
firms
2. Robustness checks
2.1 Additional controls: productivity premium of foreign outsourcing is
robust to other characteristics associated to productivity
2.2 Endogeneity issue
Figure 2
Productivity differences between foreign outsourcing and non-outsourcing firms
(Smooth sample distribution function)
Table 2
Productivity level differences between foreign outsourcing firms and
non- foreign outsourcing firms: hypotheses test statistics
(All firms)
Number of firms
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
Foreign
outsourcing
477
574
687
655
720
690
702
820
858
858
910
824
795
Non-foreign
outsourcing
618
768
833
787
731
678
682
782
738
741
754
674
651
Difference (%) in productivity level
between foreign outsourcing and nonforeign outsourcing firms in the:
25th
75th
Median
percentile
percentile
4.8
6.4
4.9
8.7
10.4
4.8
7.7
8.8
6.9
7.5
7.5
4.4
8.7
10.3
5.5
8.6
10.7
7.4
9.5
10.9
8.8
8.8
8.6
8.5
8.4
8.0
5.6
9.0
8.9
7.7
8.2
8.7
7.9
5.5
6.2
4.2
4.3
6.4
4.3
Average difference
at the median: 7.5 percent
Equality of
distributions
Differences favorable to
foreign outsourcing firms
P-value
P-value
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.826
0.814
0.960
0.939
0.988
1.000
0.998
1.000
0.996
0.986
0.962
0.969
0.985
Table 5
Productivity level differences between foreign outsourcing and non- foreign outsourcing firms:
hypotheses test statistics
(only component intensive industries)
Number of firms
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
Foreign
outsourcing
249
302
380
379
402
392
389
453
487
486
506
449
415
Non-foreign
outsourcing
265
336
345
328
308
275
273
319
301
308
316
276
281
Percent difference in productivity
level between foreign outsourcing and
non- foreign outsourcing firms:
25th
75th
Median
Percentile
Percentile
2.3
5.4
3.7
7.1
8.4
2.6
8.7
6.7
6.3
7.6
6.8
4.7
9.3
8.7
6.3
8.1
10.4
7.1
8.1
9.6
7.8
7.3
7.0
6.0
7.9
5.3
5.8
7.0
5.3
7.3
6.1
3.6
6.1
3.7
3.7
4.6
0.2
1.6
4.5
6.5 percent
Equality of
distributions1
Differences favorable to
foreign outsourcing firms2
P-value
P-value
0.059
0.001
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.026
0.124
0.708
0.612
0.895
0.965
0.996
1.000
0.998
1.000
0.974
0.994
0.928
0.915
0.864
Table 6
Ex-ante productivity differences between entering outsourcing firms and non-foreign outsourcing firms:
hypotheses test statistics
Number of firms
Starters
Year to foreign
outsource
1990
74
1991
102
1992
81
1993
106
1994
59
1995
67
1996
74
1997
118
1998
78
1999
86
2000
76
2001
105
Non- starters
to foreign
outsource
516
644
620
552
574
546
548
585
590
595
587
542
Percent difference in ex-ante productivity level
between starters to foreign outsource and nonstarters
Equality of
distributions1
Differences favorable to
starters firms2
Median
25th percentile
75th percentile
P-value
P-value
4.6
8.0
0.8
6.4
1.2
3.7
5.8
7.8
4.8
2.6
3.9
3.2
0.7
1.8
5.1
3.7
3.9
4.4
3.8
7.9
4.3
5.3
5.5
2.8
3.8
6.2
-1.6
4.6
-0.7
1.0
3.4
6.6
6.6
2.2
0.5
3.9
0.403
0.009
0.807
0.044
0.516
0.129
0.018
0.000
0.080
0.319
0.064
0.139
0.936
0.882
0.793
0.883
0.862
0.720
0.998
0.919
0.968
0.984
0.954
0.911
4.4 percent.
Robustness checks
i) Additional controls:
– We check whether the productivity premium of foreign
outsourcing firms is robust to other characteristics that are
associated with firm productivity.
– Foreign outsourcing can be correlated with omitted
variables such as size, innovation, human capital, which
may be inflating the magnitude of the productivity premium.
ii) Endogeneity issues
– Potential endogeneity of foreign outsourcing could lead to
biased estimates
i) Additional controls
ln TFPit     FOit   Z it  eit
• ln TFPit is the log of TFP, where average productivity differences across
industries are removed
• FOit is a dummy variable for the current outsourcing status (1 if firm i out
sources in year t, 0 else);
• Zit is a vector of control variables that includes:
– the log of number of employees and its squared value to measure firm size
– a dummy variable indicating Foreign ownership (1 if firm has 50 percent or more of
equity owned by foreign capital)
– the log of firm age
– a full set of year dummies to control for common shocks to all firm
– the log of the ratio of labour cost per hour to proxy human capital
• Additionally, to control for unobserved firm heterogeneity due to timeinvariant firm characteristics, the equation is estimated with fixed firm
effects.
ii) Endogeneity issues
• Potential endogeneity of foreign outsourcing could lead to biased
estimates
• More productive firms might self select into foreign outsourcing,
and/or alternatively firms engage in this activity with the objective to
improve productivity.
• To address this issue: GMM estimation
ln TFPit    1 FOI it   2 NFOit   Z it  eit
 1, if the firm stops outsourcing abroad

dNFOit   0, if the firm does not change their decision
 1, if the firm starts outsourcing abroad

FOI it  FOI it 1 , if the firm continues outsourcing abroad
dFOI it  
0, otherwise
• Total effect of foreign outsourcing on productivity using the
coefficients from the GMM estimation:
• Coefficient ≈ 0.16
• As foreign outsourcing increased by 0.025 percentage points
over the sample (from 0.165 to 0.188), the coefficient implies
that foreign outsourcing lead to an increase of 0.4 percent of
TFP.
• Given that firms increase their average TFP by 18 percent over
the period, foreign outsourcing accounted for almost 2.5 percent
of the growth of TFP at the firm level.
Main conclusions
• Productivity differences between firms engaged in foreign outsourcing of
intermediate inputs and firms non-outsourcing abroad are consistent with
the predictions of Antrás and Helpman (2004)
• High productivity firms are more likely to engage in global production
strategies.
• Evidence is consistent with self-selection of the most productive firms into
the practice of outsourcing abroad. The ex-ante productivity distribution of
firms that engage into foreign outsourcing stochastically dominates the
distribution of firms non-outsourcing abroad
• The productivity premium of foreign outsourcing by firms is robust to other
characteristics associated to productivity
• Foreign outsourcing accounted for 2.5 percent of TFP growth at the firm
level over the period.
Final comment:
Offshoring in the conventional sense of reallocation of processes to
an external provider, has been very intensive in the footwear
industry.
A case study (Fuster, Martinez and Pardo, 2007) of this industry in
the province of Alicante shows that firms that engage in global
production strategies have higher productivity than firms nonoutsourcing from abroad.