INTRA-INDUSTRY TRADE: PROGRESS AND CHALLENGES

INTRA-INDUSTRY TRADE:
PROGRESS AND CHALLENGES
Chris Milner
University of Nottingham
Presentation to INTECO Workshop at the
University of Valencia, Dec 1st-2nd, 2005
Introduction
• Intra-industry trade is a topic I return to
with gaps
• Given the increasing heterogeneity of
international interactions and emergence of
new theoretical and empirical approaches,
thought some stock-taking would be useful
– what progress has been made to resolve ‘old’
issues?
– has IIT analysis a role to play in new context?
Organisation of the Presentation
• Progress
– On measurement
– On modelling
• theoretical
• empirical
• Overall Evaluation
– Challenges
Measurement of IIT
• Starting with measurement contrary to usual
preference to start with theory, but
– how the literature started also!
• Issues of aggregation effects and heterogeneity
still critical
– ‘statistical artefact’ concerns may no longer be
expressed, but
– empirical challenge of categorical aggregation
remains, perhaps even more challenging
– now have a strand of literature that represents
industries as heterogeneous (in terms of
technology/productivity of firms)
Measurement Issues
• Industry definition
– official classification v. selective regrouping
• Aggregation bias
– sensitivity analysis and use of amended indices
• Adjustment for trade imbalance
• Bilateral v. multilaterally
• Degree of matching v. extent of two-way trade
– Grubel-Lloyd v. Fontagne-Freudenberg
• depends on purpose at hand
Grubel-Lloyd (GL) Index
• GL index measures share of IIT in gross
trade (GT) ie IIT/GT where:
– IIT = 2 min (Xj, Mj)
– GT = (Xj + Mj) = IITj + NTj
(NTj = net trade)
• can be applied for any level of aggregation
• offers a comprehensive decomposition of net and
matched trade
• does not measure the amount of IIT
• does not distinguish between H-O and non-H-O
industries
Other Developments on
Measurement
• Marginal or dynamic measures of IIT
– if interested in adjustment effects of changes in IIT,
then better to use something other than traditional GL
indices (see Greenaway et al, 1994)
• Extended measures of IIT
– can allow for servicing of markets through overseas
production as well as armslength trade (see Greenaway,
Lloyd and Milner, 2001)
• Decomposition of IIT
– into IIT in horizontally and vertically differentiated
goods
Decomposition of IIT
• Decomposition based on unit value dispersion
criterion (eg Abd-el Rahman, 1991; Greenaway et
al. (1994, 1995)
– concerns over arbitrary nature of dispersion criterion,
use and quality of unit values, sensitivity of results to
level of disaggregation used, and instability of
decomposition across countries (e.g. Nielson and
Luthje, 2002), but offers a comprehensive methodology
• On this basis Vertical IIT is the dominant form of
IIT
– in both N-N and N-S trade
Table 1
Shares1 of Horizontal and Vertical2 IIT in USA’s Bilateral Trade in Manufactures
Country
Horizontal IIT
Vertical IIT
Canada
0.15
0.20
Germany
0.03
0.22
Switzerland
0.03
0.18
UK
0.03
0.25
Norway
0.01
0.04
Luxembourg
0.02
0.04
Austria
0.00
0.08
Sweden
0.02
0.14
New Zealand
0.00
0.03
Australia
0.00
0.04
Spain
0.01
0.07
Finland
0.01
0.07
Ireland
0.01
0.13
Italy
0.02
0.19
Japan
0.03
0.09
Source: Taken from Durkin and Krygier (1997)
France
0.03
0.27
(1) Grubel-Lloyd
index
(2) Using +/Denmark
0.01 the study reports also results
0.11 of a +/-25% differential
15% unit value differential, though
whichBelgium
are very similar to the above results.
0.02
0.11
Table 2
Relative Importance of Vertical and Horizontal IIT in UK’s bilateral Intra-Industry
Trade (1988) (in Manufactured Goods)
Share (%) in Total IIT
Horizontal
Vertical
With EU Countries
33%
67%
With OECD Countries
33%
67%
With Developing/ Industrialising Countries
9%
91%
including
Singapore
10%
90%
Korea, Rep.
9%
91%
China
7%
93%
Malaysia
6%
94%
Thailand
9%
91%
32%
68%
With All Countries
Source: Information for groups of countries taken from Grubel and Lloyd indices in Greenaway, Milner
and Elliot (1997) and for individual countries from SITC product coverage data in Greenaway, Hine
and Milner (1994).
Modelling IIT
• Comprehensive explanations usually based on
‘large’ numbers (competitive market
structures) rather than ‘small’ numbers
(oligopolistic) models
• Variety of monopolistic competition/neoChamberlinian models, but all include:
– ‘love of variety’ specification of demand for
differentiated goods (i.e. IIT in horizontally
differentiated goods)
– decreasing costs of production inducing product
specialisation at the firm level
Chamberlinian-Heckscher-Ohlin
(C-H-O) Model
• A model of simultaneous inter- and intraindustry trade, assumes:
-
-
homogenous/constant cost (Y) and
differentiated/decreasing cost (X) goods
sectors
factor endowment (K and L) differences
between countries (H and F) - home (foreign)
country K (L) abundant
demand for all varieties at home and abroad
(CES-type utility function)
each (relatively capital-intensive) variety
produced only by one firm
• Basis for ‘similarity thesis’
Empirical Evidence on C-H-O
Model
• Early empirical literature provided informal
documentary support for ‘similarity thesis’
• Development of more formal econometric testing
of key similarity hypothesis (ie b < 0 in eq 1)
using (initially) cross section estimation method:
– Bjk = a + b(percapdiffjk) + cVjk + ejk (1)
– where Bjk = G-L index of IIT
– percapdiff = absolute per capita income
differential between countries j, k
– and
V = vector of control variables
C-H-O Testing (cont)
• Leamer (1994) critical of imprecise derivation of
test of per capita similarity thesis, and of ad hoc
addition of control variables
• Helpman (1987) cited as one of few early attempts
to link empirics directly to theory (ie to C-H-O
model)
X1 = log | (GDPi/POPi) – (GDPj/POPj) |
X2 = min (log(GDPi), log(GDPj))
X3 = max (log(GDPi), log(GDPj))
The results for the extreme years are given in table 4.6
Table 3 Regressions for Intra-industry Trade from Helpman Study
1970
1981
X1
X2
X3
R2
-0.044
0.055
-0.014
0.266
(-3.141)
(4.153)
(-1.105)
-0.006
0.027
-0.020
(-0.370)
(1.686
(-1.283)
The t-values are in parentheses; n = 14 x 13/2 = 91.
Source: Helpman (1987)
0.039
C-H-O Testing (cont)
• Leamer (1994) critical of imprecise derivation of
test of per capita similarity thesis, and of ad hoc
addition of control variables
• Helpman (1987) cited as one of few early attempts
to link empirics directly to theory (ie to C-H-O
model)
• But other support for similarity thesis and C-H-O
model
– though stronger support in All Trade and N-S
trade than N-N trade
Limitations of Early Econometric
Analysis
• Use of per capita differential to proxy factor
proportions or endowment differences
rather than use of direct measure
• Use of cross section estimation means that
country- specific or fixed effects abstracted
from
Table 6 Panel Equation Tests of C-H-O Model for US-OECD Trade (1962-83)
Fixed Effects Estimates
(1)
Per-capita income differential
(2)
0.038
(3.609)
Capital-labour differential
0.029
(3.235)
Min. GDP
1.315
(18.483)
1.327
(18.666)
Max. GDP
-0.005
(-0.079)
-0.013
(-0.197)
R2 (with country dummies)
0.524
(0.965)
0.523
(0.966)
[t ratios in brackets]
Source: Hummels and Levinsohn (1995), Table V.
Limitations of Early Econometric
Analysis
• Use of per capita differential to proxy factor
proportions or endowment differences
rather than use of direct measure
• Use of cross section estimation means that
country- specific or fixed effects abstracted
from
• Use of a measure of total IIT rather than
ITT in horizontally differentiated goods
( being explained by C-H-O model)
Theoretical Explanation for
Vertical IIT
• Incorporation of technological (factor proportion)
differences across countries to account for
possibility of product quality differences within
industries, and of income differences within
countries that creates demand for different qualities
(eg neo- H-O-S model of Falvey, 1981)
• Original motivation for this type of model was to
explain IIT in N-S trade (North specialising &
exporting capital or design-intensive varieties and
South exporting standard/labour intensive varieties,
and consumers in the N & S consuming both ‘high’
& ‘low’ quality varieties)
Limitations of Theory
• Although the theory provides no basis for a
‘similarity’ thesis, it explains only that IIT is
induced by some endowments differential not that
there is a continuous positive relationship between
vertical IIT and income/endowment differences
• Involved with some work with Falvey/Cabral in
trying to model possible simultaneous existence of
vertical IIT, horizontal IIT and net trade
– pattern depending on endowment differences
between different trading partners
– vertical IIT increases only for initial increases in
endowment differences
Econometric Modelling of
Vertical IIT
• Limited direct modelling, especially that
combines:
– use of VBj rather than total IIT measure
– use of direct measure of factor proportions
differential(s)
– and, use of panel estimation to capture countryspecific effects
• Mixed evidence on the nature of vertical IIT
- economy similarity/dissimilarity
relationship
Table 7 Summary of Cross Section and Panel Testing of Vertical IIT Model for
USA – OECD Trade (1989-92)
Cross Section / OLS
Panel / Fixed Effects
(± 15%)
(± 25%)
(± 15%)
(± 25%)
+*
+**
+***
+***
+***
+***
+
+
-
-
-*
-*
Distance
-***
-***
Income distribution overlap
+**
+**
R2
0.56
0.55
0.87
0.86
N
80
80
80
80
Per-capita income differential
GDP of trading partner
GDP of USA
[***/**/* denotes 1%/5%/10% level of significance respectively]
Source: Taken from Durkin and Krygier, 1997.
Factor Content Evidence on IIT
• Traditional factor content studies assume an H-O world with
homogenous goods within industries and common technologies
across countries
– use a single technology matrix to measure factors embodied
in exports and imports
– measure factor content of net trade
• Following a suggestion of Davis and Weinstein (2001) that if
drop above assumptions there may net exchanges of factors
embodied in IIT as well as net trade, Cabral, Falvey & Milner
(2005) extend this approach to:
– distinguish also between skill content of vertical and
horizontal IIT
Table 8 Skill Content of Intra-Industry Trade as a Share of Total Skill Content of
UK Trade with Some Middle Income Countries (alternative estimates)
(%)
With productivity
adjustment
High
Skilled
Medium
Skilled
Clerical Production Average
INTER-Industry Trade
56.1
49.1
71.1
70.5
61.7
INTRA-Industry trade
43.9
50.9
28.9
29.5
38.3
Horizontal Intra-Industry
Trade
3.7
-3.4
-3.3
2.0
-0.3
Vertical IIT Type I – High
Quality (VTX/VTM>1.15)
27.6
37.0
24.8
19.5
27.2
Vertical IIT Type II – Low
Quality (VTX/VTM<0.85)
12.7
17.4
7.4
7.0
11.3
Evaluation of Progress
• Scepticism about empirical significance of IIT
has waned, but renewed interest in
measurement issues (decomposition, dynamic
measures, extending measure to include
international production)
• Now a large theoretical literature explaining
alternative types of IIT and in alternative
contexts (market structures, economy-types)
• Attraction of integrating intra- and interindustry trade in a general equilibrium setting
(eg C-H-O model)
Progress (cont)
• Strong initial support for C-H-O model
– not direct testing
– not using horizontal IIT as dependent variable
– reliance on cross section estimation
• More recent evidence shows that results
sensitive to
– use of refined measures of IIT, RHS variables
– use of panel estimation
• Vertical IIT apparently more important than
horizontal IIT in both N-N and N-S trade
– empirical evidence suggests that vertical IIT
driven by factor endowment differences
Challenges
• Theoretical modelling of possibility of
simultaneous vertical IIT, horizontal IIT and net
trade
• Decomposition of IIT
• Econometric testing of more general models
• Defining industries in the presence of
heterogeneous firms
• A range of policy issues (e.g. adjustment costs of
trade expansion)