Transcript Outsourcing, Productivity, and Input Composition at the Plant Level Catherine J. Morrison Paul and Mahmut Yaşar World Congress, Washington D.C., May 2008

Outsourcing, Productivity, and Input
Composition at the Plant Level
Catherine J. Morrison Paul and Mahmut Yaşar
World Congress, Washington D.C.,
May 2008
Make-or-Buy
“It is the maxim of every prudent master of a family,
never to attempt to make at home what it will cost him
more to make than to buy.” Smith (1776, pp.485-486)
“… quite apart from the question of diminishing
returns the costs of organizing certain transactions
within the firm may be greater than the costs of
carrying out the exchange transactions in the open
market.” Coase (1937, pp. 7-8)
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Productivity drivers
Firms’ productivity depends on their potential to minimize
production costs by substituting among a variety of inputs
Studies used to focus on “value added” capital and labor inputs
but now recognize substitution of processed (materials) for
processing (capital and labor) inputs
More generally, input choices include purchasing rather than
producing goods and services (implies outsourcing or
subcontracting)
Affects the productivity & competitiveness of outsourcing firms
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Outsourcing drivers
Firms would be expected to use their own inputs for activities they
have a comparative advantage for and outsource others
Roodhooft and Warlop (1999)
A firm’s comparative advantage depends on trade, price, and
technical conditions
E.g., import competition from lower wage countries encourages
foreign outsourcing, reducing the wages of less skilled laborers
Feenstra and Hanson (1999, 2003), Hanson et al. (2005)
In reverse, lower wage countries may subcontract output
Both specialized tasks and lower productivity/skill processes may be
outsourced to other domestic or foreign firms
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Our goal
We explore how outsourcing or subcontracting is related to
plant productivity and input composition/substitution
from the perspective of a developing country
We consider the productivity effects of:
domestic outsourcing, through the share of inputs that are subcontracted
receiving contracts, through the share of output that is subcontracted
foreign outsourcing, through the share of imported intermediate inputs
represented as production frontier shifts and twists
from diff shares of subcontracted inputs/outputs or imported materials
and find this aspect of input choice important to recognize
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Literature
Outsourcing/subcontracting has not been a focus of the production literature
But some studies suggest (domestic or foreign) outsourcing results if producing
inputs or services in-house is at least as costly as subcontracting them
Involves two types of costs
production costs: labor costs, scale economies, clustering of special skills or
expertise, or production smoothing
transactions costs: negotiating, monitoring, and enforcing contracts, or searching
for outside suppliers
Also may be benefits from foreign technology transfer through outsourcing
importing: R&D embodied in materials/capital imports and learning from their
use (input subcontracting through input imports)
FDI/exports: increased demand for exports from host country suppliers (output
subcontracting)
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Data: output and inputs
Plant data collected by the State of Statistics in Turkey for the
Annual Surveys of Manufacturing Industries
International Standard Industrial Classification, Apparel & Textiles
Output (Y): total value of shipments plus changes in inventories of
finished goods and work-in-progress
Material (M): expenditures, allowing for changes in stocks
Energy (E): value of fuel+electricity
Y,M and E nominal values are divided by corresponding price deflators
to get constant value quantities at 1987 prices
Labor input (LT and LN): technical and administrative workers,
production workers
Capital (K): perpetual inventory method using gross investment
data
Seven regions distinguished
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Data: outsourcing and technology transfer
Our domestic outsourcing variables are:
subcontracted input (the share of a plant’s inputs
subcontracted to supplier plants, in total inputs)
subcontracted output (the share of output subcontracted by
other plants, in total output)
Klicaslan and Taymaz (2005)
Our foreign outsourcing variable is:
the share of imported materials in total materials use
Our foreign technology transfer variables include:
the share of exports in total sales
the share of foreign firm ownership (FDI)
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Table 1. Shares of SUBI, SUBO, and IMPM for Different Group of Plants (%)
SUBI
SUBO
IMPM
13.49
17.45
1.48
11.96
15.10
15.11
22.40
14.45
10.44
0.77
1.42
2.90
11.63
14.69
30.64
8.92
0.32
2.22
13.32
19.64
17.19
26.56
1.39
4.50
1.58
6.02
0.00
12.18
4.16
3.75
14.99
9.12
21.80
12.95
12.45
16.36
34.37
0.88
3.22
0.52
1.66
3.23
Overall
A&T Industries
By Size
Small
Medium
Large
By Export Status
Non-Exporters
Exporters
By Ownership
Domestic
Foreign
By Region
South-East Anatolian and East
Anatolian
Agean Sea
Black Sea
C. Anatolian
Marmara
Mediterranean
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Empirical framework
First look at premia/correlations
for Pit = performance indicators (t=time and i=plant)
labor productivity (LProd), wage, employment, skilled
labor, and capital intensity
O/Sjit (j=SUBI, SUBO, IMPM)
D=regional (r) and time (t) dummies and EMP=size
Estimate:
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R 1
T 1
j 1
r 1
t 1
ln Pit  0    j OS jit   r Dr   t Dt   EMP EMPit  uit
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Table 2. Percentage Differences between Groups, A&T Industries
Dependent
SUBI &
SUBI-DUM SUBO-DUM IMP-DUM
SUBI & IMP SUBO&IMP
variable
SUBO
0.643
-0.852
0.632
0.079
1.036
0.656
ln LProd
(0.039)*** (0.046)*** (0.119)*** (0.040)** (0.064)*** (0.065)***
0.146
-0.084
0.24
0.088
0.413
0.295
ln WAGE
(0.019)*** (0.022)*** (0.058)*** (0.019)*** (0.031)*** (0.032)***
0.349
-0.042
0.605
0.535
0.834
1.258
ln EMP
(0.037)***
(0.043)
(0.112)*** (0.037)*** (0.060)*** (0.061)***
0.664
-0.368
0.831
0.544
1.286
1.544
ln LADM
(0.047)*** (0.055)*** (0.141)*** (0.047)*** (0.076)*** (0.077)***
0.094
-0.019
0.210
0.170
0.444
0.62
ln LTECH
(0.056)*
(0.069)
(0.144)
(0.056)*** (0.082)*** (0.080)***
0.323
-0.294
0.932
0.465
0.813
1.023
ln K/EMP
(0.070)*** (0.081)*** (0.208)*** (0.071)*** (0.113)*** (0.115)***
0.108
-0.552
0.632
0.108
0.588
0.299
ln INV/EMP
(0.096)
(0.118)*** (0.273)**
(0.096)
(0.139)*** (0.136)**
Percentage
27.2
15.2
2.1
23.0
4.8
3.9
of plants
Notes: (1) Robust standard errors are in parentheses. *Significant at the 10% level. ** Significant at the 5% level.
***Significant at the 1% level. (2) The independent variables for the different regressions include time, size, and
region dummies. (3) The base group is the plants that do not engage in any of these activities.
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Econometric Framework
We assume that the plant production function Y = f(X,r,t) can be
represented by a translog approximation:
ln Yit = 0 + j j ln Xjit + t t + m m rmit + j jt ln Xjit t + mj mj rmit ln Xjit
+ .5 (jk jk ln Xjit ln Xkit + tt t2) + it ,
where Xj ( j = K,LT,LN,E,M) is the jth input, the rm include the O/S,
technology transfer, characteristics and dummy variables
distinguishing the plants, and  is a error term
Use Olley and Pakes (OP) method to estimate
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Table 4. Elasticities at the Mean Values Calculated by the Delta Method
Variables
Elasticity
SUBI
SUBO
IMPM
M
LT
LN
0.086
-0.092
0.593
0.716
0.071
0.198
0.040
0.033
0.626
0.851
1.059
K
E
EXP
FDI
RTS
Standard
Error
0.052
0.051
0.241
0.010
0.011
0.016
0.018
0.009
0.134
0.378
0.042
T-Statistic
P-Values
1.66
-1.80
2.46
73.21
6.37
12.05
2.24
3.58
4.67
2.250
25.54
0.097
0.072
0.014
0.000
0.000
0.000
0.025
0.000
0.014
0.024
0.000
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SUBI Results
βSUBI is positive and significant (at 10%)
positive first order productivity effect of SUBI
βLT,SUBI is positive and significant (at 1%)
a strong positive LT bias
a higher share of subcontracted inputs implies greater
administrative and technical (skilled) labor intensity
βLN,SUBI is significantly negative (at 5%)
more SUBI is associated with less use of unskilled labor
SUBI substantively affects only the labor shares
all other cross-effects are insignificant
The positive SUBI output elasticity is driven entirely by the
positive first-order and LT effects
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Interpretation
SUBI-LT complementarity and SUBI-LN substitutability
implies that subcontracting inputs reduces in-house
“production” of lower-productivity and -skill activities or
processes or services
e.g., those provided by unskilled production line
workers or janitorial workers
rather than services of skilled workers
e.g., legal or accounting services
Perhaps because input subcontracting requires
administrative and technical expertise due to greater
required supervision or support of contractors.
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SUBO Results
By contrast, more SUBO implies significantly less reliance
on skilled labor (LT)
implies subcontract-receiving plants are more “low-tech”
SUBO is also associated with lower M levels
suggests more use of lower value primary rather than processed
materials
but a greater energy share
perhaps required for the additional processing
The lower M and LT levels for subcontract-receiving plants
underlie the negative SUBO output elasticity.
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IMPM Results
More IMPM also implies lower (but not sig)
domestic materials and skilled labor use
The only sig IMPM bias is a positive E effect
The dominant effect of IMPM is therefore from the
first order coefficient IMPM
imports have little effect on input composition
the primarily negative input biases are too small to
counteract the strong positive overall effect
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Tech Trans Results,
Linkages of trade factors with O/S vary by mechanism
no significant productive relationships between SUBI
and EXP, FDI, IMPM
but effects between SUBO and trade variables are sig
with EXP is negative, and with FDI and IMPM positive
IMP or FDI firms do not have as low productivity as other SUBO
plants, but EXP firms actually have worse productivity
conversely, the productive contributions of trade factors are
smaller for EXP and larger for IMP or FDI plants with SUBO
a higher EXP share is associated with a lower LN share
supports that internationally best practice production requires
more skilled and less unskilled workers
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