Chris Milner
University of Nottingham
Presentation to INTECO Workshop at the
University of Valencia, Dec 1 st -2 nd , 2005

• 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?

• Progress
– On measurement
– On modelling
• theoretical
• empirical
• Overall Evaluation
– Challenges

• 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)

• 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

• GL index measures share of IIT in gross trade (GT) ie IIT/GT where:
– IIT = 2 min (X j
, M j
)
– GT = (X j
+ M j
) = IIT j
+ NT j
(NT j
= 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

• 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 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 Shares 1 of Horizontal and Vertical 2 IIT in USA’s Bilateral Trade in Manufactures
Country
Canada
Germany
Switzerland
UK
Norway
Luxembourg
Austria
Sweden
New Zealand
Australia
Spain
0.02
0.00
0.00
0.01
Finland
Ireland
Mexico
0.01
0.01
Italy 0.02
Japan 0.03
Source: Taken from Durkin and Krygier (1997)
(1)
France
Grubel-Lloyd index
0.03
(2) 0.01
0.02
0.02
0.03
0.01
0.02
0.00
Horizontal IIT
0.15
0.03
0.03
0.07
0.13
0.19
0.09
0.14
0.03
0.04
0.07
0.27
0.11
0.11
0.19
0.25
0.04
0.04
0.08
Vertical IIT
0.20
0.22
0.18

Table 2
Relative Importance of Vertical and Horizontal IIT in UK’s bilateral Intra-Industry
Trade (1988) (in Manufactured Goods)
With EU Countries
With OECD Countries
With Developing/ Industrialising Countries including
Singapore
Korea, Rep.
China
Malaysia
Thailand
Share (%) in Total IIT
Horizontal
33%
Vertical
67%
33%
9%
67%
91%
10%
9%
7%
6%
9%
90%
91%
93%
94%
91%
With All Countries 32% 68%
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).

• Comprehensive explanations usually based on
‘large’ numbers (competitive market structures) rather than ‘small’ numbers
(oligopolistic) models
• Variety of monopolistic competition/neo-
Chamberlinian 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

• 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’

• 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 :
– B jk
= a + b(percapdiff jk
) + cV jk
+ e jk (1)
– where Bjk = G-L index of IIT
– percapdiff = absolute per capita income differential between countries j, k
– and V = vector of control variables

• 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)

X
1
X
2
= log | (GDP i
/POP
= min (log(GDP i i
) – (GDP
), log(GDP j j
/POP
)) j
) |
X
3
= max (log(GDP i
), log(GDP j
))
The results for the extreme years are given in table 4.6
Table 3 Regressions for Intra-industry Trade from Helpman Study
X
1
X
2
X
3
1970 -0.044
(-3.141)
0.055
(4.153)
-0.014
(-1.105)
R 2
0.266
1981 -0.006
(-0.370)
0.027
(1.686
-0.020
(-1.283)
0.039
The tvalues are in parentheses; n = 14 x 13/2 = 91.
Source: Helpman (1987)

• 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

• 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)
Per-capita income differential
Capital-labour differential
Min. GDP
Max. GDP
R 2 (with country dummies)
Fixed Effects Estimates
(1) (2)
0.038
(3.609)
1.315
(18.483)
-0.005
(-0.079)
0.524
(0.965)
0.029
(3.235)
1.327
(18.666)
-0.013
(-0.197)
0.523
(0.966)
[t ratios in brackets]
Source: Hummels and Levinsohn (1995), Table V.

• 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)

• 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)

• 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

• 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)
Per-capita income differential
GDP of trading partner
GDP of USA
Distance
Income distribution overlap
R
2
N
Cross Section / OLS
(± 15%) (± 25%)
+*
+***
-
-***
+**
+***
-
-***
+**
0.56
80
+**
0.55
80
Panel / Fixed Effects
(± 15%)
+***
+
-*
0.87
80
(± 25%)
+***
+
-*
0.86
80
[***/**/* denotes 1%/5%/10% level of significance respectively]
Source: Taken from Durkin and Krygier, 1997.

• 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
INTER-Industry Trade
INTRA-Industry trade
Horizontal Intra-Industry
Trade
Vertical IIT Type I – High
Quality (VTX/VTM>1.15)
Vertical IIT Type II – Low
Quality (VTX/VTM<0.85)
High
Skilled
56.1
43.9
3.7
Medium
Skilled
Clerical Production Average
49.1
50.9
-3.4
71.1
28.9
-3.3
70.5
29.5
2.0
61.7
38.3
-0.3
27.6
12.7
37.0
17.4
24.8
7.4
19.5
7.0
27.2
11.3

• 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)

• 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

• 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)