THE INTRA-INDUSTRY TRADE IN HORTICULTURAL PRODUCTS BETWEEN
PORTUGAL AND THE EUROPEAN UNION (1988-2001)
Sousa Nunes, Fernando ([email protected])
Instituto Politécnico de Viana do Castelo - Escola Superior Agrária de Ponte de Lima
Área temática 3: Comercio e Integración
Abstract
The aim of this work is to analyse the horticulture Intra-Industry Trade (IIT) between Portugal and the
European Union, along the last thirteen years. Most significant countries for bilateral trade are studied,
being Spain by far the most important one. Grubel-Lloyd index and the methodology defined by the
Centre d’Etudes Prospectives et d’Informations Internacionales (CEPII) are used to calculate IIT.
Results obtained in period 1988-2001 emphasize the considerable low values for IIT in those products
between Portugal and its European commercial partners, mainly with Spain. The structural low trend
highlights the possibility of the Portuguese horticultural sector suffers structural adjustment costs, and
that can become worse if this situation still maintains. Since the CEPII approach presents a symmetric
evolution in time with the GL index, we can use both indicators indistinctly.
Keywords: Intra-Industry Trade; Horticulture sector; Grubel-Lloyd index and CEPII approach.
Resumen
El objetivo de este trabajo es analizar el Comercio Intraindustrial (CII) de los productos hortícolas
(frutas y legumbres), que se ha desarrollado entre Portugal y la Unión Europea en el período 1988-
2001. Se da una particular atención a los países comunitarios más significativos bajo el punto de vista
del comercio bilateral, como es el caso de España. Para el cálculo del CII son utilizadas dos
metodologías: el índice Grubel-Lloyd (GL) y la desarrollada por el Centre d’Etudes Prospectives et
d’Informations Internacionales (CEPII). Los resultados obtenidos a lo largo del período analizado
revelan un nivel de los valores del CII muy bajo para los productos hortícolas, entre Portugal y los
principales países europeos, sobre todo en lo que se refiere a España. Esta tendencia estructural a la
baja pone en evidencia la posibilidad de que el sector de frutas y legumbres portugués sufra
sustanciales costes de ajuste, que podrían agravarse todavía mas, aún, si la situación se mantiene. El
abordaje CEPII presenta una evolución temporal simétrica con la del índice Grubel-Lloyd,
legitimando de este modo una utilización indiferenciada de los dos métodos.
Palabras Clave: Comercio intraindustrial ; frutas y legumbres; índice Grubel-Lloyd y modelo CEPII.
2
THE INTRA-INDUSTRY TRADE IN HORTICULTURAL PRODUCTS BETWEEN
PORTUGAL AND THE EUROPEAN UNION (1988-2001)
Contents: 1. Introduction. 2. Agriculture and Intra-Industry Trade. 3. Static IIT – The Grubel-Lloyd
Index. 4. The CEPII Approach. 5. Dynamic IIT: The Brülhart Index. 6. Summary and Conclusions. 7. References. Annexes
1. Introduction
Portugal is a EU full member state since 1986 and we do expected a progressive and deep
economic integration process since then. The Single Market in 1993 established the real basis
for a true and effective commercial and economic liberalisation development between our
country and the rest of the EU member states. Degree and strength of economic integration
depends on whether trade is of inter (iIT) or intra-industry (IIT) category. According to Fertö
and Hubbard (2001), whereas the former is associated with a reallocation of resources
between industries, the latter suggests a reallocation within industries. A recent study of Mora
(2002) states that every European country increased its IIT in the period 1985-96, but the shift
is greatest in those economies which have joined the EU recently (Greece, Spain and
Portugal), bringing them closer to EU average. Thereby, this author concludes progress in
European integration has promoted an intra-industry specialization. A Smooth Adjustment
Hypothesis considered by Brülhart (2001) provides evidence that IIT expansion generally
entails lower adjustment costs than iIT. Therefore, is expected that as the Portuguese
economy becomes considerably more integrated into that of the EU, the sort of existent trade
will have important implications for internal economic adjustment costs.
Studding IIT differences among countries, Balassa (1986) found out that greater per capita
income, greater national income, greater openness, and the existence of a common border
with principal trading partners were positively correlated with the extent of IIT. Distance from
trading partners (a proxy for transportation costs) was negatively associated with intra-
industry trade. The existence of a preferential trading area, as a economic union, seems to be
positively correlated with a high level of IIT between two countries as well. Thus, considering
trade liaison between Portugal and some of its most important EU agriculture partners, it’s
3
expected to find out IIT significant levels, mostly with countries like Spain or France.
However, besides the growing economic importance of the so-called agri-business trade, we
must highlight the absence of an important theoretical body of literature on agriculture IIT
(Henderson et al., 1998).
The primary aim of the present work is to analyse the nature and intensity of Horticulture
products trade between Portugal and EU most important partners during the last thirteen
years. Predominantly, we’ll focus on the relationship with Spain since this neighbour country
is by far our most important partner on horticultural products trade. This paper is organized as
follows. Next section presents IIT theoretical concepts and it’s relevance on food and
agriculture context. In section 3 we pertain the conventional measure of IIT, the Grubel-Lloyd
index, to our data. In section 4 we apply for a diverse IIT approach developed by the “Centre
d’Etudes Prospectives et d’Informations Internationales” (CEPII). In section 5 we analyse and
submit to application the concept of marginal intra-industry trade, based on international trade
CN proposed on the version Gaspar. Last section summarises and concludes.
2. Agriculture and Intra-Industry Trade
As previously mentioned scientific literature on agriculture IIT it’s rather scarce. In a not
directly way, Faustino et al. (2001) when trying to establish clusters of products where
Portugal has competitive advantage in relation to Spain only found out one agriculture
product (the last one in a list of 19 product’s categories with a GL value greater than 0,5), that
is “milk and cream, not concentrate nor containing added sugar or other sweating matter”
(0401 CN code). The same authors also emphasised that the competitive position of Portugal
vis a vis Spain has deteriorated from 1996 and there is empirical evidence that our country
will suffer structural adjustment costs if the situation is not reversed. Studying the nature of
agro-food trade products between Hungary and the EU for the period 1992 to 1998, Fertö and
Hubbard (op. cit.) highlight the existence of a slight growth in IIT as measured by the GL
index. However, this increase is not uniform by country or product group, and probably
reflects different patterns of bilateral integration and progress in economic restructuring.
Specifically, a low level of IIT on “Fruits and Vegetables (f&v)”, the 05 CN code, was
registered in that period, even if located in the middle of a chart with 19 two digit level
product groups. Gregorova (2002), examining IIT in EU wine trade for the period 1996-99,
found a remarkable low value of GL index for Spain and Italy on this period. Thus, wine trade
4
presents inter-industry trade because of comparative advantage of wine production.
Nonetheless, in what is concerned to Portugal, a traditional wine producer country, the
existence of extremely high values of IIT for 1998 and 1999 expresses the increasing imports
of wine during those two years (at the latest, imports and exports are almost equal).
Quasmi and Fausti (1999) emphasised the importance of NAFTA on bilateral agriculture and
agro-food IIT between US, Canada and Mexico for the period 1990-95. The authors consider
that this commercial agreement has significantly increased trade between the three countries
but there is evidence that trade involving US and Canada was of intra-industry nature, whilst
it was mostly of inter-industry nature among Mexico and the other two countries. This
assumption, however, is in contradiction with the conclusions of Ruffin and Anderson (1999)
who state that, contrary to popular belief, the top US imports from Mexico are not fruits and
vegetables, or clothing. These represent only 10 percent of U.S. imports1. In 1998, electrical
machinery and equipment ranks first, vehicles ranks second and nuclear reactors, boilers and
related items are third. The United States’ top three exports to Mexico are these same three
categories. Additionally, not only are Mexico’s exports to the U.S. quite similar to its imports
(IIT), but Mexico’s exports are more concentrated in those big items of intra-industry trade.
Perhaps, the most important point regarding U.S.- Mexico trade is the fact that of all imports
and exports between this two countries, about 80 percent represent IIT2.
Lovely and Nelson (2000), consider that the existence of substantial north-south IIT has led to
a sizeable literature on vertical IIT. An essential point is that vertical IIT may be endowment-
based and generate adjustment pressure more like that of inter-industry trade than intra-
industry trade. Fontagné and Freudenberg (2001) consider that whatever the methodology
implemented, a distinction between horizontal and vertical differentiation of products has to
be done, since determinants of both types are controversial. Thus, different countries will
engage in ITT in vertically differentiated products whereas similar ones will engage in ITT of
varieties within similar qualities. Their economic distance is therefore a determinant of ITT in
vertically differentiated products and empirical methods have to account for a distinction
between both types of ITT. Cristóbal (2001) also emphasizes the fact that until now literature 1 This apparent contradiction can be a consequence of inadequate empirical procedures. For instance, Nilsson (1997,1999) argues that the GL index may be not a good indicator to measure IIT when we face large differences in economic sizes between countries. 2 Veeramani (2002) states that another developing country as India presents significant levels of IIT on its international trade. In fact, accordingly the evidence from other countries, the liberalized policy environment biases trade expansion towards IIT.
5
on this issue often ignores the importance of the nature, vertical or horizontal, of the
differentiation of the traded varieties. Furthermore, this author states that, while the new
standard model of international trade (Helpman and Krugman, 1985) assumed horizontal
differentiation, recent empirical work on the nature of IIT has revealed that intra-industry
trade on vertically differentiated products is significant. Faustino et al. (op. cit.), focus the
importance of differentiated vertical and horizontal IIT on adjustment costs. Authors states
that it is generally accepted that the adjustment costs of a given specialization change or, in
response to integration processes, are lower if horizontal product differentiation is
predominant. The reason is that quality varieties are similar, so we have similar factor
intensity and lower costs of factor adjustment when the trade expands. Accordingly Fertö and
Hubbard (op. cit.), Henry de Frahan and Tharakan (1998) were the first to differentiate
between horizontal and vertical IIT in European food trade. In general their results confirm
the country- and industry-specific determinants of IIT anticipated by the theory. The analysis
of the agriculture trade outline between U.S. and ten European Central Countries made by
Van Berkum (1999), highlights the supremacy of vertical IIT, i.e. American exports are
higher quality type, while imports from Central Countries can be described as lower quality
products. According to Fertö and Hubbard (op. cit.), this fact suggests perhaps a
specialization within agriculture between two regions, with production becoming
complementary in nature.
In what concerns the relevance of Gross Domestic Product (GDP) to explain the existence and
intensity of IIT, authors are not totally coincident about this issue. In fact, while authors like
Hirschberg et. al. (1994), Appleyard and Field (1997), Lovely and Nelson (2000), inter alia,
assumed the importance of this indicator to justify ITT values, Hirschberg and Dayton (1996)
found out that GDP did not have a major effect on IIT for a majority of disaggregated food
processing sectors.
Positive effects of IIT are well known. Ruffin and Anderson (op. cit.) identify four of them:
(i) international trade did not caused the dislocations associated with iIT; (ii) IIT enhances the
gains from trade through better exploitation of economies of scale; (iii) specialization within
industrial categories may also stimulate innovation, and finally; (iv) IIT reduces the demands
for protection because in any industry there are both exports and imports, making it difficult
to achieve unanimity among those demanding protection. Along with the origins of IIT we
can enlighten the product differentiation, transport costs and geographical location, dynamic
6
economies of scale, degree of product aggregation and different income distributions in
countries, as some of the most important reason to justify IIT.
Trying to summarise, geographical proximity and degree of commercial openness seem to be
nowadays two major factors to explain IIT. Differences between IIT analysis and
quantification appear to be a result from the different interpretation of the traditional indexes
to measure IIT. Those dissimilarities can also be explained, as mentioned by Tizón and
Redondo (forthcoming), through a statistical illusion, that is the level of aggregation
considered on data analysis. Differences within IIT values interpretation give rise to the
importance of consider horizontal and vertical IIT approach. In section 4 we also apply for the
importance of marginal IIT, with horizontal or vertical nature as well.
3. Static IIT – The Grubel-Lloyd Index
Our work has a focal point on the analysis of trade flows between Portugal and the EU as
whole, and between our country and the most important common partners for a range of
Horticultural products. A separation between fresh (or chilled) and non fresh vegetables
products will be made as well as among fresh vegetables and fruits. We’ll use EUROSTAT
Combined Nomenclature (CN) data at four and six-digit level over the period 1988-01.
Accordingly, 14 CN product commodity were used for vegetable [0701-0714] and 8 CN
product commodity for fresh vegetable [0702-0709], when we develop Grubel-Lloyd index.
On the IIT CEPII approach 119 product commodity [070110-081290] will be employed on a
six-digit level basis.
Using XJ and MJ as the values of exports and imports of a certain commodity j, the Grubel-
Lloyd (GL) index of IIT in sector j is obtain as follow:
jj
jj
jj
jjjj
j
jj MX
MX
MX
MXMX
TTIIT
G+
−−=
+
−−+== 1 (1)
Gj gives IIT as a share of total trade in commodity j (TTj) and take values between 0 (no IIT,
that is exports or imports, but not both) and 1 (all trade is IIT – exports equal to imports in
each category).
7
To make possible contrast with other industries or countries, Grubel and Lloyd (1975) have
presented a GL index as a trade-weighted average (rather than simple arithmetic):
( ) ( )∑
∑
∑∑
∑=
=
=
=
=
+
−−=
⎟⎟⎟⎟⎟
⎠
⎞
⎜⎜⎜⎜⎜
⎝
⎛
+
+==
n
jn
jjj
n
jjjn
jn
jjj
jjjjj
MX
MX
MX
MXGLwGL
1
1
1
1
1
1 (2)
The aggregate GL index for vegetable products between Portugal and most significant
European countries on vegetable trade, is shown in Table 1, as follow:
Table 1: Grubel-Lloyd indices of Portuguese Vegetable trade
[0701-0714] with EU partners, 1988-01
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001
F 0,011 0,043 0,072 0,028 0,045 0,099 0,143 0,190 0,155 0,121 0,155 0,246 0,140 0,162
G 0,261 0,174 0,026 0,039 0,292 0,377 0,470 0,524 0,606 0,389 0,565 0,367 0,197 0,183
I 0,018 0,006 0,060 0,077 0,090 0,121 0,217 0,366 0,067 0,181 0,094 0,130 0,019 0,222
NL 0,020 0,066 0,045 0,055 0,091 0,069 0,033 0,187 0,214 0,178 0,072 0,206 0,086 0,072
Sp 0,044 0,060 0,084 0,085 0,070 0,081 0,352 0,252 0,089 0,049 0,115 0,140 0,241 0,118
UK 0,031 0,064 0,205 0,115 0,121 0,172 0,293 0,454 0,447 0,492 0,395 0,305 0,290 0,289
EU15 0,059 0,091 0,110 0,103 0,148 0,171 0,241 0,394 0,251 0,234 0,219 0,334 0,292 0,308
Source: Authors’ calculations based on NC data at the four-digit level, aggregated using trade share weights. (F – France; G – Germany; I – Italy; NL – The Netherlands; Sp – Spain; UK – United Kingdom; EU15 – European Union)
In first place we must highlight the low values for IIT between Portugal and our most
important partners, even if a slight increase can be recorded for IIT values in the period 1988-
01. Years 1994 and 1995 are exceptions on this context, which can be related with special
8
good production conditions in Portugal when compared with our neighbourhood countries3.
Somehow, this broaden relatively higher values of GL index among different countries
denote that geographical distance can probably be not a good explanatory factor.
A special focus should be made over Spanish values: even if erratic along the considered
period, GL index values evolution show a major propensity towards the maintenance of low
levels of IIT (GL<0,13, in average). This is of special meaning for Portugal since Spain is by
far our most important source of vegetable imports and our unique neighbour as well4.
Germany and UK relatively high GL indices contrast with low levels of absolute volume of
vegetables interchange between Portugal and those two countries. Like Fertö and Hubbard
(op. cit.), we also postulated that doesn’t seems to exist a direct relationship between the GL
index and the amount or level of IIT5. As the literature mentions, the GL index for the entire
EU tends to be higher than each one of the considered countries. This results are in
accordance with Tizón and Redondo analysis (op. cit.), who call attention to the polymorphic
character of IIT. This means that the total IIT it is always greater than the addition of the
parts.
For vegetable products, nature and intensity of trade are different if we considerer a fresh or
long term conservation approach. Empirical observation shows a lower volume of horticulture
trade between countries when level of conservation and geographical distance are restraint
variables. Thus, nearer countries with similar labour and capital allocations and comparable
ecological conditions should register significant (and perhaps, similar) levels of IIT on fresh
products. Looking at Table 2, we realise the insignificant value for GL index in fresh
vegetables trade between Portugal and Spain (being 2000 an exception with a GL index equal
to 0,257).
3 In this chapter quantities of products were used instead of prices. As proposed on the version Gaspar to analyse IIT (Tizón and Redondo, op. cit.), this procedure it is preferable by the following reasons: first, prices’ effect on measuring IIT is eliminated; second, quantities avoid the problem of the different evaluation to which flows of value are submitted, and finally; authors enlighten the importance of the change-tax over commercial flows measured by value. 4 However we must underlying recent conclusions from Martín-Montaner and Ríos (2002) who concludes that although Spanish IIT with the most OECD countries is of vertical low quality type, Spanish vertical high quality IIT with Portugal records the highest value among all countries: 48 percent. 5 Rajan (1996) distinguishes between degree of IIT (the GL index) and level of IIT (total trade minus iIT).
9
Table 2: Grubel-Lloyd indices of Portuguese Fresh Vegetable
Trade [0702-0709] with main EU Partners, 1988-01
Spain France The Netherlands EU
1988 0,004 0,032 0,016 0,088
1989 0,023 0,310 0,044 0,134
1990 0,042 0,149 0,027 0,177
1991 0,055 0,067 0,094 0,237
1992 0,098 0,051 0,160 0,272
1993 0,106 0,247 0,143 0,326
1994 0,128 0,160 0,210 0,315
1995 0,090 0,133 0,112 0,361
1996 0,045 0,069 0,250 0,216
1997 0,048 0,113 0,220 0,260
1998 0,112 0,184 0,369 0,267
1999 0,094 0,174 0,410 0,302
2000 0,257 0,090 0,422 0,346
2001 0,038 0,105 0,234 0,255
Source: Authors’ calculations based on CN data at the four-digit level, aggregated using trade share weights.
Being near to zero, values of GL index for fresh vegetables trade between Spain and Portugal
enlighten the importance of imports or exports (but not both) in each category, with inter-
industry trade as a major feature in this particular commercial relationship. Significantly
higher GL index values for EU and the Netherlands must be enlightened as well. Whilst the
former should be expected, the later is of great interest, mainly when we realise the distance
between the two countries and differences on ecological conditions. Once again GL index for
The Netherlands emphasizes the apparently weak capacity of the “geographical location”
variable as an explanatory issue for IIT. GL index values for horticulture are considerably low
when compared with those from other four-digit level categories, who presents, as Faustino et
al. (op. cit.) state, significant comparative advantages (GL>0,5) over Spain. That is the case
for iron and steel products, some wood products, clothes, electrical apparatus, shoes and other
manufactured products.
10
The desegregation of GL index by category can also give us important information as shown
on Tables 3 and 4. In what is concerning to vegetable trade between Portugal and Spain, data
doesn’t exhibit a comprehensible outline. For fresh or chilled products [0701-0709] GL index
are extremely low and present a strong propensity to decrease along the period. Relatively
high IIT values for tomatoes in 2000 (GL=0,653), cabbages and cauliflowers in 1992
(GL=0,538), or even lettuce in 1999 and 2000 (0,380 and 0,461), emphasises the erratic
evolution of the Portuguese position vis a vis the Spain and the non-structural nature of our
commercial production and exportation with that country. In frozen and dried vegetables the
erratic evolution of GL index still maintains even. Nevertheless, significant levels of IIT can
be observed in certain types of commodity products like dried vegetables (GL=0,465, in
average), or dried leguminous vegetables (GL=0,375). However, all this unfavourable picture
should be contextualise in time and we must focus on the general (even if slightly) increase on
GL index evolution. As a matter of fact, at the first years a considerable number of products
have GL index equal to 0, which means, in this particular case, imports but no exports to
Spain. This scenario it is in opposition with last years’ values, where only one 0 value can be
recorded among 14 commodity products in a three years period (1999-01).
Values of GL index for disaggregated commodity groups of vegetables products between
Portugal and EU15 are shown on Table 4. As expected, higher GL index values are recorded
for the large majority of commodity products between this two commercial partners, when
compared with Spain only. However some focus should be made in products like tomatoes,
cabbages & cauliflowers, lettuce, and frozen vegetables where the GL index presents in
average values between 0,48 and 0,83. We can also state that vegetables trade between
Portugal and UE as a whole for the period 1988-01 reveals an almost total absence of
products where IIT can’t be found (three 0 values for cucumbers and manioc are the
exceptions). Finally, in fresh vegetable products only cabbages and lettuce presents IIT
consistent values along the period which means the presence of a strengthen two-way trade
movement between Portugal and some EU countries6.
A comparison between fruits and vegetables GL index for trade with Spain and the EU as a
whole, for two particular years is shown on Table 5.
6 In 2001, values of lettuce exportations from Portugal to Spain, France and UK, were, respectively, 188, 935, and 740 Tons.
11
Table 5: Grubel-Lloyd indices of Portuguese Vegetable [0702-0709] and Fruit [0804-0810] Trade with Spain and EU as a whole, in 1993 and 2001
Spain EU
Vegetables Fruits Vegetables Fruits
1993 0,081 0,086 0,171 0,213
2001 0,118 0,144 0,308 0,280
Source: Authors’ calculations based on CN data at the four-digit level, aggregated using trade share weights.
Results enlighten the slightly increase on GL values for vegetables and fruits for trade with
Spain between those two years. Results also make clear that there are no significant
differences between GL index for fruits and vegetables (more evident in the case of Spain) in
each one of the years. This means both sectors have no different characteristics in trade flows
nature. Trade with EU reveals a positional change between both periods, with vegetables
registering the highest GL index value in 2001 (0,308). Although increasing from an year to
another, IIT increment on fruits it is not so significant as happened with vegetables. Despite
the increase on IIT from 1993 till 2001 in all categories, one must emphasise the rise on
vegetables IIT with the EU. This probably means Portugal is developing stronger commercial
relationships in vegetable products with other EU partners instead of Spain, in a notorious
comparative advantage basis. In section 4 we’ll apply for the marginal concept of IIT which
states suitable information about dynamic IIT among different periods.
4. The CEPII approach
The CEPII approach is based on the principle that it’s preferred a methodology in which total
trade can be divided in several types, calculated on a strict bilateral basis at the most detailed
level of sectoral breakdown (Fontagné and Freudenberg, op. cit.). In fact, according to the
same authors, as soon as overall trade is imbalanced, trade can never be completely of an
intra-industry nature, since exports cannot match imports in every industry. Thus, a three
categories division on international trade is proposed: (i) IIT (balanced by definition); (ii) iIT,
which becomes balanced at the aggregate level as soon as we separate it from the; (iii) trade
12
imbalance. The CEPII approach tries to solve some of the inconsistencies of the solutions
proposed by Grubel & Lloyd, Michaely & Aquino and Bela Balassa methods.
An adjusted version of the GL index basically considers the share of overlap trade in
balanced trade (instead of total trade) and it’s presented as follow:
∑ ∑
∑∑
−−+
−−+=
j jjkjkjkjk
jjkjkjk
jjk
adjustedk
MXMX
MXMXGL
)()(
)( (3)
Aquino (1978) criticises the GLadjusted index, mostly because of the high trade aggregation
level. Thus, he suggests a new indicator based on hypothetical exports and imports at the most
elementary level, each sector considered.
∑∑ +
=
jjk
jjkjk
jkejk X
MXXX
)(21
; ∑
∑ +=
jjk
jjkjk
jkejk M
MXMM
)(21
After adapted this indicator to the unadjusted GL index, Aquino defined a new indicator,
equal to the one defined by Michaely, 15 years before (1962).
Michaely & Aquino k = ∑ ∑∑−−
jj
jk
jk
jjk
jk
MM
XX
211 =
21 1
21∑=
−−
N
iPP
(4)
The autonomy of the MAk index vis-à-vis trade structure is one of the reasons explaining the
preference for other kind of indicators like the GL nonadjusted indicator. In this case trade
imbalance is a part of inter-industry trade flows and trade flows can be divided in only two
types: IIT and iIT.
According to Fontagné and Freudenberg (op. cit.), “another conceptual problem is that the
Balassa indicator (1966) - of which the GL and related indicators are derived - is used in the
literature both as an indicator of IIT and of revealed comparative advantages”.
13
For a particular industry, the Balassa indicator assumes the analytic form:
jj
jjj MX
MXB
+
−= =
1
1
+
−
i
i
i
i
mxmx
Where 11 +≤≤− jB (5)
Using this indicator, 1− means total imports on sector j, 1+ total exports on sector j, and 0
indicates IIT imports and exports with the same extent7. For N number of trade sectors the
Balassa index takes the following analytic form:
∑= +
−=
N
j jj
jjN mx
mxN
B1 )(
)(1 where 11 +≤≤− NB (6)
This average value do not considers trade share weights and thus underestimates important
flows and overestimate negligible flows. Among others, this is one of the reasons why the
Balassa indicator has been under criticism and replaced by other (or acutely readapted)8.
The CEPII approach, proposed by Fontagné and Freudenberg, tries to clarify or minimise the
following constraints usually founded in the indicators previously analysed: (i) minimises the
bias arising from sectoral aggregation by using far more disaggregated classifications; (ii)
minimises the bias of geographic aggregation by only considering bilateral flows; (iii)
considers, depending on the degree in overlap, both exports and imports as being part of
either two-way trade or one way-trade, and; (iv) distinguishes between vertical and horizontal
differentiation by incorporating price differences9. Thus, as seen bellow, in the indicator
7 The GL index it is in fact an adaptation of the Bela Balassa index: jj BGL −= 1 8 In a recent work, Hinloopen and Marrewijk (2001), argues that the Balassa index differs considerably across countries, make comparisons of the index between countries problematic. 9 Recently, the seminal works of Fontagné and Freudenberg done for the European Commission (1997) were under strong criticism by Nielsen and Lüthje (2002). Authors argue that behind the apparent stability of the aggregate distribution over time of the three types of trade (iIT, IIT in vertically differentiated products and IIT in horizontally differentiated products), big changes can be observed in relation to which products belong to the different categories. By the contrary, Mora (2002) found out similarity between their IIT results and those of Fontagné and Freudenberg in a panel of data for the European Countries.
14
proposed by those authors we have “two-way” trade when the value of the minority trade
flow represents at least 10% of the opposite majority trade flow10:
%10);();(≥=
ii
iij mxMax
mxMinCEPII (7)
Below this level, the minority flow cannot be considered significant as it does not represent a
structural element of trade. IIT also allows division between different qualities among
identical products. In this case imports’ unitary values (Pmj) and exports’ unitary values (Pxj)
are important features in the analyse. The CEPII approach suggests three quality levels, as
follows:
• High levels (L1): 15,1/ fjj PmPx jjj xofWeightxofValuePx /=
• Low levels (L2): 85,0/ pjj PmPx
• Middle levels (L3): 15,1/85,0 ≤≤ jj PmPx jjj mofWeightmofValuePm /=
If exports average prices for a certain product are not higher then 15 percent of imports
average prices in the same product we have middle level trade, that is genuine/pure IIT or
horizontal IIT (same product, identical qualities). At the other two situations (vertical IIT) we
do have low level or high level IIT. Finally, we can state that each traded product must be
considered as a part of one only of the different four types of trade, that is, three quality levels
for IIT (overlap >10%) and iIT (overlap < 10%)11.
Thus, Fruits and Vegetables trade flows between Portugal and Spain for the period 1988-2001
were analysed under the CEPII approach. In this case, to avoid the categorical aggregation
problem we used CN at six-digit level [070110-081290] in a total of 119 products. Intra and
inter industry trade values are shown at Table 6 and Figures 1 and 2.
10 Nevertheless, there is a connection between the CEPII index and most traditional indexes of international trade. Tizón and Redondo (op. cit.) states that trade flows respecting CEPII conditions are under following gaps: (i) to the Balassa index, in percent values is -81,82≤Bj≤+81,82; (ii) to the GL index, also in percent values we have GLi ≤18,18, and the export-import ratio (in percent values) it is stated between 10,0 and 1000,0. 11 In our work we also consider export and import modules on inter industry trade.
15
Table 6: Decomposition of f&v trade flows between Portugal and Spain
under CEPII approach (1988-2001)
Intra Industry Trade (IIT) Inter Industry Trade (iIT)
Year Low
level
Middle
level
High
level
total Imports
module
Exports
module
total TOTAL
1988 5,49 0 0,35 5,84 91,4 2,76 94,16 100
1989 2,45 0,01 3,02 5,48 85,09 9,43 94,52 100
1990 4,63 0,86 2,09 7,58 80,71 11,71 92,42 100
1991 8,01 2,04 0,05 10,1 76,44 13,46 89,9 100
1992 5,64 1,97 9,11 16,72 66,97 16,31 83,28 100
1993 15,57 5,87 1,11 22,55 72,95 4,5 77,45 100
1994 11,6 5,08 16 32,65 64,46 2,89 67,35 100
1995 20,19 8,1 9,65 37,94 59,99 2,07 62,06 100
1996 17,24 2,25 1,5 20,99 76,37 2,64 79,01 100
1997 13,96 1,83 1,62 17,41 79,49 3,1 82,59 100
1998 15,15 3,58 2,16 20,89 75,88 3,23 79,11 100
1999 16,1 1,61 1,41 19,12 77,73 3,15 80,88 100
2000 18,3 7,01 2,59 27,9 69,38 2,72 72,1 100
2001 10,3 1,95 5,7 17,95 79,47 2,58 82,05 100
Source: Authors’ calculations based on CN data at the six-digit level, aggregated using trade share weights.
IIT indicators under CEPII approach expose the relevance and higher dimension of iIT when
compared with IIT values. In fact, besides a slight increase on IIT values along the period, for
the majority of the year’s indexes are under 30 percent, being 1994 and 1995 the exceptions.
But, the great advantage of CEPII approach lies on the partition of all trade flows, especially
those related with IIT, as shown on Figure 1 (all figures were made by the author, based on
CN data).
As we can see, the increase on IIT values is mainly due to “low level” IIT products. The
linear trend analysis highlights the fact that the gap between those “low level” products and
the two other categories (high and middle level) increase along the period 1988-01. This
means that when Portugal increases trade (exports and imports) within the F&V sector, lower
quality type products are predominant and vertical IIT prevail.
16
As Mora (2002) states, a high share of low quality VIIT means that a country is specializing
into relatively low-price export goods in the vertically differentiated sectors. By opposition, a
high share of high quality VIIT implies that VIIT takes the form of high-valued exports. The
trade situation mentioned above is not a positive feature for Portugal since as seen previously
(Faustino et. al., op. cit.) adjustment costs are higher if vertical product differentiation is
predominant. The distribution of all five types of trade is presented on Figure 2.
Fig. 2: Decomposition of trade flows for Fruits and Vegetables - CEPII version. Portugal vs Spain
0%
20%
40%
60%
80%
100%
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
(Years)
(%)
iIT Exp.Module
iIT Imp.Module
IIT high level
IIT midlle level
IIT low level
Besides the dominance of vertical IIT along all period, this figure emphasises the fact that
higher IIT “high level” index were stated at 1994 and 1995. At those two years amount of
total IIT between Portugal and Spain was maximal and exportations of F&V to our
neighbours reached the highest values. However, the pattern of results it’s not clear enough to
assume that higher IIT values goes along with higher middle or high level of IIT values.
Figure 1: Scatter diagram of CEPII Intra Industry Trade index (1988-01)(Portugal vs Spain: Fruit and Vegetable)
y = 1,2912x + 9,1102
y = 0,9787x + 4,4193
y = 0,0678x + 3,5147y = 0,2447x + 1,1762
0
5
10
15
20
25
30
35
40
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001
(Year)
(%)
Low level Middle level High level total IITLinear (total IIT) Linear (Low level) Linear (High level) Linear (Middle level)
17
Figure 2 also gives us a more clear idea about the relevance of the imports module on inter-
industry trade, amongst all F&V trade with Spain. As a mater of fact, in relative terms, along
the latest 13 years Portugal has been acutely dependent on F&V coming from our neighbour
country, and our exports to Spain were also negligible on that period12. According to the
literature, inter-industry trade is motivated by differences in factor endowments as a source of
comparative advantage and it will be higher when differences between countries increase.
This can probably be the case for horticulture (or even agriculture as a whole) between
Portugal and Spain due to the low level of capital endowment employed in the Portuguese
agricultural production. Finally, the comparison between values of IIT under the Grubel-
Lloyd index and the CEPII approach can be graphically seen on Figure 3.
Figure 3: IIT of F&V between Portugal and Spain: CEPII vs GL(1988 - 2001)
05
10152025303540
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
(Years)
(%)
CEPII IITGL IIT*100
12 France, the other Spanish neighbour, is also largely dependent on Spain for F&V: in 1995, IIT and iIT values were, respectively, 17,93 and 82,07 per cent, being 76,21 the “Import Module”. Spain, in fact, assumes a leadership position in the F&V Single Market. Results for IIT and iIT between Spain and EU in 1994 and 1995 are shown below:
Intra Industry Trade (IIT) Inter Industry Trade (iIT)
Year Low level
Middle level
High level total Imports
module Exports module total TOTAL
1994 3,55 5,89 12,31 21,75 2,02 76,23 78,25 100 1995 1,11 9,53 7,62 18,26 1,91 79,83 81,74 100
Source: Author’ calculations based on CN data at the six-digit level, aggregated using trade share weights.
18
Figure 3 emphasises the fact that the distribution of values for both indicators along the
period is almost symmetric. This phenomena sustains the idea of CEPII approach as an
important and solid connection between the French and Anglo-Saxony “ways of thinking” on
ITT. The existence of permanent higher values for the CEPII approach with reference to GL
index is in harmony with literature on this issue. So far we have been using traditional static
indexes to measure IIT. Nowadays, however, marginal IIT is considered as a useful index for
adjustment costs and trade liberalisation analysis. Those analyses will be done in the next
section.
5. Dynamic IIT: the Brülhart Index
As Fertö and Hubbard (2001) noticed, “…an assumption sometimes implicit in the literature
on trade liberalisation has been that GL index, as a measure of IIT, is negatively correlated
with factor market adjustment costs. But adjustment costs are dynamic phenomena, and the
static GL index is not a suitable measure in this instance”. Greenaway and Milner (1986) were
the first authors to state that Grubel-Lloyd index was a poor indicator to identify IIT dynamics
in a context of adjustment costs induce by trade13. Thus, marginal IIT is now a broaden index
to measure changes in trade14. By far, the most accepted in recent literature (Lovely and
Nelson, 2000; Faustino et al., 2001; Cristóbal, 2001) is the index proposed by Brülhart (1994,
2001):
( ) ( )nttntt
nttntt
MMXXMMXX
AMIIT−−
−−
−+−
−−−−== 1 (8)
or
MXMX
A∆+∆
∆−∆−= 1 (9)
13 On this subject see also works from Greenaway et al. (1994). 14 At Azhar et. al., 1998 and Brülhard, 2001, a good explanation about several indexes to measure marginal intra-industry trade can be found.
19
Like the traditional GL index, BA varies between 0 and 1, where 0 indicates marginal trade
being of totally inter-industry nature, and 1, marginal trade of a completely intra-industry
nature. According to Brülhard (2001), A can be summed, like the GL index, across industries
of the same level of statistical desegregation by applying the following formula for a weighted
average:
∑=
=k
jjjw AwA
1
where ( )∑
=
∆+∆
∆+∆= k
jjj
jjj
MX
MXw
1
(10)
and where Aw is the weighted average of MIIT over all industries of the economy or over all
the sub-industries of an industry, denoted by j…k. Although overrides the restrictions of
previous indexes, Brülhard indicator was evolved under some criticism. For instance, Oliveras
and Terra (1997), declare that “there is no general relationship between the A index of a
certain period and the corresponding index of its constituent sub-periods. Second, there is no
general relationship between the A index of a certain industry and the correspondent indices
of its sub-industries”. Thus, the same authors state that choice of level of aggregation and
selection of period to be analysed are fundamental to obtain constructive conclusions.
Another definitive assumption about marginal intra-industry trade concerns is horizontal or
vertical nature15. Aturupane, Djankov and Hoekman (1999), consider the existence of
horizontal intra-industry trade (HIIT) when there is two-way trade in products of similar
quality, but different characteristics or attributes. Thus, they suggest that the more alike
countries are in terms of their income, the greater the HIIT is. HIIT is also associated with
economies of scale and a high degree of product differentiation. Vertical intra-industry trade
(VIIT) concerns both exports and imports of a similar product of varying qualities and is more
a reflection of endowment or technology-based factors.
Thom and McDowell (1999) pointed out that traditional marginal indicators (as Brüllard’s) do
not make a distinction between HIIT and VIIT and merely identify IIT with horizontal IIT.
These authors proposed the application of a new method to calculate MIIT based on the join
15 Recent analyses on new approaches to measure horizontal IIT can be found in Gullstrand (2002).
20
application of the traditional Brülhart’s index and the aggregate index (10). The first
measures the extents of HIIT and the second Total IIT (TIIT). Vertical IIT is the difference
between these two indices and inter industry-trade (iIT) is 1-TIIT. Working with CN at four-
digit level we analysed changes in vegetables trade flows between Portugal and five European
countries and the EU as a whole. The results for two periods16 are presented on Table 7.
Table7: Decomposition of the Change in Portuguese Vegetable Trade Flows
with the EU and five European countries (2001-88; 2001-95)
TMIIT HMIIT VMIIT MiIT
(Aj) (Aw) (Aj-Aw) (1-Aj)
01/88 01/95 01/88 01/95 01/88 01/95 01/88 01/95
France 0,279 0,144 0,198 0,134 0,081 0,010 0,721 0,856
Germany 0,309 0,250 0,195 0,051 0,114 0,200 0,690 0,750
Netherlands 0,181 0,167 0,017 0,010 0,164 0,157 0,819 0,833
Spain 0,147 0,110 0,132 0,074 0,016 0,036 0,853 0,890
UK 0,188 0,539 0,008 0,155 0,180 0,383 0,812 0,462
EU 15
0,560
0,377
0,456
0,263
0,104
0,114
0,440
0,623
Source: Authors’ calculations based on NC data at four-digit level, aggregated using trade share weights. Note: TMIIT is total marginal intra-industry trade, HMIIT is horizontal marginal intra-industry trade, VMIIT is vertical marginal intra-industry trade, and MiIT is marginal inter-industry trade.
Those analyses suggest that trade change between Portugal and those five European countries
was roughly entirely inter-industry trade. In fact, values of MiIT (1-Aj) for horticultural
products with those five countries, in both periods, range between 69 percent and 89 percent,
being the UK the exception in period 2001/88, with 44 percent. If we focus on values of
horizontal and vertical intra-industry trade among the two periods, no clear pattern can be
identified for countries. Thus it is not possible to state that HMIIT (the pure intra-industry
trade) overcomes to VIIT. Results once again emphasise the extremely low values of IIT with
Spain, with marginal values (horizontal and vertical) lower than 8% at the period 2001/95.
This situation its even more accurate if we analyse just fresh vegetable products, as seen in
Table 8.
16 The first stage concerns all period, and second one analyses the most significant seven years in terms export/import of horticultural products with Spain and the rest of the EU.
21
Table 8: Decomposition of the Change in Portuguese Total [0701-0714] and Fresh
[0702-0709] Vegetable Trade Flows with the main EU partners, 2001/95 Member state TMIIT HMIIT VMIIT MiIT
(Aj) (Aw) (Aj-Aw) (1-Aj)
Total Fresh Total Fresh Total Fresh Total Fresh
France 0,144 0,070 0,134 0,061 0,010 0,010 0,856 0,930
Netherlands 0,167 0,771 0,010 0,028 0,157 0,743 0,833 0,229
Spain 0,110 0,030 0,074 0,030 0,036 0,000 0,890 0,970
EU 15 0,377 0,458 0,263 0,148 0,114 0,309 0,623 0,542
Source: Authors’ calculations based on CN data at four-digit level, aggregated using trade share eights.
Choosing data for our most significant partners at the horticultural trade, results highlight the
lower levels of fresh horticultural HIIT with Spain, France and the European Union (being
The Netherlands the exception) when compared with total values (CN 0701-0714). In our
case the split between horizontal and vertical MIIT its only significant in two cases: The
Netherlands and the EU, both for fresh products. Detailed results by vegetable product groups
under Brülhard index are in Table 9.
Table 9: Marginal Intra-Industry Trade between Portugal and Spain, by commodity group and period
NC product commodity – 4 digit level 2001/88 2001/95
0701 Potatoes, fresh or chilled 0,076 0,000
0702 Tomatoes, fresh or chilled 0,013 0,000
0703 Onions, Shallots, Garlic, … 0,014 0,010
0704 Cabbages, Cauliflowers, … 0,084 0,054
0705 Lettuce and Chicory, … 0,231 0,269
0706 Carrots, Turnips, Salsify, ... 0,004 0,006
0707 Cucumbers and Gherkins ... 0,091 0,245
0708 Leguminous vegetables, … 0,056 0,097
0709 Other vegetables, … 0,194 0,232
0710 Vegetab.uncooked or cooked, frozen 0,190 0,129
0711 Vegetables provisioally preserved 0,231 0,054
0712 Dried vegetables 0,674 0,236
0713 Dried leguminous vegetables 0,896 0,715
0714 Manioc, and other roots or tubers… 0,988 0,993
Source: Authors’ calculations based on CN data at the four-digit level.
22
Among such small values of MIIT for fresh products, one must emphasise the product
categories 0705 and 0709: Lettuce & Chicory; and Other Vegetables. Oliveras and Terra (op.
cit.) considered highly recommended to measure MIIT for different levels of aggregation to
evade the risk of incorrectly interpolating the characterization of one sector’s adjustment
process to all its sub-industries. Table 10 presents the results of MIIT for horticultural
products between Portugal and Spain at six (6D) and four-digit (4D) level.
Table 10: Decomposition of the Change in Portuguese Vegetable Trade Flows with Spain (4 versus 6 digits)
Period TMIIT HMIIT VMIIT MiIT
(Aj) (Aw) (Aj-Aw) (1-Aj)
4D 6D 4D 6D 4D 6D 4D 6D
2001 - 1988 0,147 0,224 0,132 0,084 0,016 0,140 0,853 0,776
2001 - 1995 0,110 0,292 0,074 0,082 0,036 0,210 0,890 0,708
Source: Authors’ calculations based on CN data at four and six-digit level, aggregated using trade share weights.
For both periods results reveal that in a six-digit analysis values of TMIIT are higher then a
four-digit analysis. By opposition, marginal inter-industry trade is lower when we use a six-
digit level, which is in accordance with literature on this issue. In relative terms, vertical MIIT
values are considerably higher then four-digit values. This results show the importance to
differentiate levels of aggregation to analyse MIIT. In our case differences were mainly
noticed for vertical IIT whilst pure MIIT (horizontal) registered no significant differences, at
least in the period 2001-95.
6. Summary and conclusions
The present work analyses intra-industry trade between Portugal and the European Union for
a range of horticultural products (vegetables and fruits). Portugal adherence to the EEC in
1986 and, most of all the integration at the Single Market in 1993 gives rise to the phenomena
of economic integration and liberalisation. Accordingly to literature, factors like a “common
border” and a “open market”, inter alia, promotes intra-industry trade and its positive effects
on economy and society are well known. Intra-industry trade with the EU as a whole for
23
vegetable products along the period 1988-2001 shows a slight increasing trend. However,
results differ significantly among countries being the Germany and UK those with the higher
average IIT values along the period 1988-2001. By opposition, Spain, reveals one of the
lowest IIT values (GL=0,12, in average), which is even lower if we consider results of fresh
(or chilled) vegetables only (GL=0,09). When horticultural IIT is split into fruits and
vegetables, results doesn’t show significant differences in each one IIT values. Somehow,
those results go against common belief which judges vegetables IIT as higher than fruits IIT
in trade with Spain.
Among the range of vegetable products one must enlighten IIT values for tomatoes, and
lettuce in 2000 (GL=0,653 and 0,461, respectively). Thus, disaggregated IIT values for
vegetables reflect the absence of a clear trade pattern among those products during the period
1988-2001. Results of two-way trade with EU show a much more consistent trend along the
period (particularly when compared with Spain) registering higher IIT values (GL=0,21 in
average). This is the result of both higher levels of IIT in other countries besides Spain and
the statistic illusion which makes the total value higher than the sum of parts. Also, results
concerning almost all countries (Spain included) present a pick on IIT values for 1994 and
1995, followed by a slight decrease till 2001. Characteristics of IIT with Spain are of special
interest for Portugal since that country is by far our most important source of vegetables
imports. Thus, if this situation doesn’t change Portuguese horticultural production will suffer
structural adjustment costs. Additionally, results pointed out the apparent debility of the
“geographical proximity” and the “free market” factors as positive determinants on the
definition of eminent levels of IIT definition and performance.
Individual values of the CEPII approach to determine IIT in fruits and vegetables are in
general higher then those of the traditional GL index but the shape of both curves is quite
similar. Must of all, CEPII approach allowed us to identify “low quality” predominant nature
of the slight increase on fruits and vegetables IIT between Portugal and Spain over the period
1988-2001. Therefore, this Portuguese “specialization” in low quality F&V products may
increase the adjustment costs process since vertical product differentiation is predominant in
this case. Results under CEPII approach also emphasise the strong inter-industry nature of
horticultural trade between Portugal and Spain, being imports the prevailing element.
24
Marginal intra-industry trade as an indicator to measure dynamic IIT reveals that change in
f&v trade between Portugal and the EU was mainly inter-industry or intra-industry of a
horizontal nature, both periods considered (2001-88; 2001-95). This trend can also be found
in other countries like Spain (specifically with fresh products), where marginal inter-industry
assumes a much higher dimension than the EU as a whole (this is not the case for Germany,
Netherlands and UK). That major trend reinforce the previous conclusion (and apprehension)
of higher adjustment costs as a consequence of prevailed vertical product differentiation in a
trade change process. Furthermore, literature also postulates higher levels of inter-industry
trade when economic and social differences between countries increase, and that can be the
case between Portugal and Spain.
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26
ANNEX 1
Table 3: Grubel-Lloyd indices of Portuguese Vegetable Trade with Spain by commodity group, 1988-2001
CN product commodity
Four-digit level 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001
0701 Potatoes, fresh or chilled 0,006 0,009 0,015 0,042 0,023 0,002 0,477 0,326 0,086 0,015 0,029 0,049 0,076 0,047
0702 Tomatoes, fresh or chilled 0,000 0,165 0,084 0,056 0,008 0,017 0,147 0,201 0,035 0,005 0,121 0,144 0,653 0,013
0703 Onions, Shallots, Garlic, … 0,000 0,000 0,045 0,000 0,015 0,000 0,003 0,004 0,001 0,004 0,166 0,002 0,051 0,009
0704 Cabbages, Cauliflowers, … 0,000 0,148 0,000 0,365 0,538 0,225 0,202 0,219 0,116 0,039 0,044 0,091 0,300 0,084
0705 Lettuce and Chicory, … 0,000 0,000 0,556 - 0,516 0,329 0,000 0,053 0,003 0,019 0,038 0,380 0,461 0,229
0706 Carrots, Turnips, Salsify, ... 0,000 0,000 0,000 0,001 0,013 0,002 0,000 0,000 0,000 0,000 0,045 0,002 0,002 0,004
0707 Cucumbers and Gherkins ... - 0,000 0,000 0,967 0,000 0,120 0,038 0,000 0,023 0,000 0,000 0,152 0,072 0,091
0708 Leguminous vegetables, … 0,930 0,724 0,326 0,989 0,780 0,279 0,120 0,007 0,004 0,004 0,017 0,037 0,039 0,064
0709 Other vegetables, … 0,020 0,295 0,164 0,193 0,186 0,311 0,450 0,147 0,196 0,284 0,152 0,305 0,311 0,183
0710
Vegetables uncooked or
cooked, frozen 0,698 0,915 0,985 0,922 0,575 0,635 0,483 0,473 0,210 0,226 0,227 0,186 0,302 0,239
0711
Vegetables provisioally
preserved 0,264 0,158 0,094 0,038 0,110 0,205 0,007 0,812 0,009 0,011 0,000 0,000 0,187 0,241
0712 Dried vegetables 0,041 0,000 0,517 0,386 0,598 0,000 0,842 0,000 0,508 0,851 0,633 0,666 0,741 0,727
0713
Dried leguminous vegetables 0,054 0,069 0,000 0,002 0,480 0,351 0,640 0,222 0,115 0,133 0,418 0,831 0,977 0,957
0714
Manioc, and other roots or
tubers, … 0,000 0,000 0,143 - 0,000 0,001 0,644 0,000 0,663 0,192 0,235 0,604 0,866 0,988
Source: Authors’ calculations based on CN data at the four-digit level, aggregated using trade share weights.
27
ANNEX 2
Table 4: Grubel-Lloyd indices of Portuguese Vegetable Trade with the EU by commodity group, 1988-2001
CN product commodity
Four-digit level 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001
0701 Potatoes, fresh or chilled 0,020 0,047 0,054 0,048 0,051 0,049 0,153 0,316 0,212 0,1284 0,103 0,195 0,113 0,096
0702 Tomatoes, fresh or chilled 0,020 0,621 0,484 0,939 0,877 0,451 0,512 0,692 0,371 0,3109 0,378 0,245 0,700 0,092
0703 Onions, Shallots, Garlic, … 0,002 0,015 0,052 0,070 0,078 0,029 0,020 0,046 0,028 0,0269 0,100 0,015 0,061 0,029
0704 Cabbages, Cauliflowers, … 0,367 0,389 0,236 0,483 0,503 0,775 0,965 0,812 0,775 0,9846 0,623 0,989 0,862 0,485
0705 Lettuce and Chicory, … 0,071 0,164 0,897 0,436 0,233 0,448 0,907 0,869 0,401 0,7089 0,920 0,996 0,997 0,712
0706 Carrots, Turnips, Salsify, ... 0,544 0,258 0,097 0,084 0,094 0,125 0,083 0,170 0,107 0,1117 0,175 0,176 0,133 0,229
0707 Cucumbers and Gherkins ... 0,000 0,106 0,702 0,829 0,080 0,377 0,049 0,028 0,040 0,0073 0,000 0,157 0,068 0,093
0708 Leguminous vegetables, … 0,134 0,325 0,956 0,619 0,620 0,443 0,258 0,225 0,119 0,1359 0,121 0,060 0,047 0,089
0709 Other vegetables, … 0,854 0,987 0,768 0,866 0,502 0,644 0,662 0,375 0,439 0,5368 0,316 0,515 0,509 0,554
0710
Vegetables uncooked or
cooked, frozen 0,994 0,893 0,858 0,979 0,893 0,83 0,787 0,847 0,594 0,7977 0,706 0,866 0,848 0,706
0711
Vegetables provisioally
preserved 0,712 0,480 0,449 0,532 0,520 0,424 0,073 0,736 0,093 0,0255 0,001 0,012 0,251 0,240
0712 Dried vegetables 0,693 0,732 0,804 0,599 0,523 0,157 0,192 0,037 0,324 0,4749 0,626 0,527 0,531 0,363
0713
Dried leguminous vegetables 0,138 0,102 0,021 0,030 0,554 0,043 0,215 0,159 0,118 0,0885 0,359 0,548 0,589 0,755
0714
Manioc, and other roots or
tubers, … 0,000 0,205 0,424 0,001 0,094 0,189 0,529 0,948 0,891 0,5982 0,231 0,666 0,286 0,873
Source: Authors’ calculations based on NC data at the four-digit level, aggregated using trade share weights.