INTRA-INDUSTRY TRADE:PROGRESS AND CHALLENGES

Chris MilnerUniversity 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

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

France 0.03 0.27

Denmark 0.01 0.11

Belgium 0.02 0.11

Mexico 0.02 0.19

Netherlands 0.03 0.25

Table 1 Shares1 of Horizontal and Vertical2 IIT in USA’s Bilateral Trade in Manufactures

Source: Taken from Durkin and Krygier (1997)(1) Grubel-Lloyd index(2) Using +/- 15% unit value differential, though the study reports also results of a +/-25% differential

which are very similar to the above results.

Table 2 Relative Importance of Vertical and Horizontal IIT in UK’s bilateral Intra-Industry Trade (1988) (in Manufactured Goods)

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).

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%

With All Countries 32% 68%

Modelling IIT• 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

Chamberlinian-Heckscher-Ohlin (C-H-O) Model

• A model of simultaneous inter- and intra- industry 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

X1 X2 X3 R2

1970 -0.044 0.055 -0.014 0.266

(-3.141) (4.153) (-1.105)

1981 -0.006 0.027 -0.020 0.039

(-0.370) (1.686 (-1.283)

The t-values are in parentheses; n = 14 x 13/2 = 91.Source: Helpman (1987)

Table 3 Regressions for Intra-industry Trade from Helpman Study

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) (2)

Per-capita income differential 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 country-

specific 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)

2R

Cross Section / OLS Panel / Fixed Effects

(± 15%) (± 25%) (± 15%) (± 25%)

Per-capita income differential +* +** +*** +***

GDP of trading partner +*** +*** + +

GDP of USA - - -* -*

Distance -*** -***

Income distribution overlap +** +**

0.56 0.55 0.87 0.86

N 80 80 80 80

[***/**/* 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 inter-industry 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)