relative gains in export value, with an average of quadrupling the export value between
the two periods. Nevertheless, these gains take place at a very low level which is
depicted in absolute terms of “difference”. Strongest gains in export value were
experienced by French Polynesia.
Cluster 4 (small exporters, winners): A large group of 24 small to medium exporters
(average below 100,000 13, including e.g. Bolivia and Madagascar) is found that in average
experienced gains in exports above the benchmark ratio of 1.4. All countries increased
their exports in this time span.
Cluster 1 (small and medium exporters, losers): The second large group of 18 countries
is a rather heterogeneous group both, in terms of the average of exports and in terms of
the difference. It is small to medium exporters that all faced losses of their exports
compared to the benchmark ratio of 1.4. All countries except Guyana and Mauritius have
a ratio below 0. This implies not only relative losses of the market share of these
countries but even a decrease of exports in total values. Medium exporters in this group
(average between 200,000 and 410,000) with considerable losses of export values (ratio
between 0.82 and 0.89) are Iran, Indonesia and Panama. Smaller exporters (average
below 50,000) with losses in this group are Venezuela, Malaysia and Gambia.
Cluster 5 (medium exporters, winners): A small group of six mainly African countries is
medium- sized exporters (average 100,000 to 400,000) that faced strong gains in their
export performance. Strongest gains are experienced by Ghana which more than tripled
its exports; other examples are Kenya and Egypt.
Cluster 10 (large exporter, very strong winner): Peru clearly stands apart from the rest of
the countries with strong gains in exports (almost tripled) yet being the smallest
exporter (average of around 550,000) of the group of large exporters.
Cluster 20 (large exporters, winners): Cluster 20 is the largest cluster of the group of
large exporters. Its average gains in exports are above the developing countries’ average
of 1.4. Most successful in terms of “ratio” in this group are Guatemala, Argentina and
Costa Rica. At the lower end (in terms of ratio slightly below 1.4)) are Morocco, Brazil,
and the Philippines.
Cluster 30 (very large exporters, strong winners): This cluster includes the small group
of the largest and, at the same time, in total values the most expanding exporters. It
consists of the three countries China, Mexico, and Chile. These countries almost doubled
their exports on a very high level.
Cluster 100 (large exporter, loser): Thailand, is the only large exporter showing strong
losses on a very high level. Since it is the only large country showing this tendency it was
found as an outliner and requires a specific analysis.
Overall, from the cluster analysis of developing countries according to the development
of fruit/ vegetable exports, it became evident that very different patterns can be
observed. Some general trends are (1) all large countries are winners, except for
Thailand. (2) Within the group of small and medium exporters we find a larger group of
winners (37 countries) than of losers (22 countries). We find the same diverse structure
within the group of the LDCs. From the total group of 15 LDCs which were included in
the analysis of the fruit/ vegetable sector 5 LDC are in groups of losers, while 10 of them
are found in groups of winners whereof three even belong to a group of very strong
winners. (3) We find rather stable exports in the second time span especially when
comparing the coefficient of variation to that we will observe in the meat market.
Principally it can be stated, that even though the market of fruits and vegetables is
highly dominated by some major players, various small countries tend to increase their
market share within the last decade. This implies that at least, SPS measures in the
sector did not have a negative effect in terms of strengthening the competitiveness of
large producers and impeding the competitiveness of small ones.
The cluster analysis for meat was performed slightly different. Again, the group was
split into large exporters and small exporters although the sample is smaller for meat
exports (n=46) since a large proportion of developing countries does not export meat to
the OECD at all, or only in single years. Including the “coefficient of variation” in the
cluster analysis led to rather heterogeneous clusters regarding the “ratio”. In general, the
coefficient of variation in meat exports is much higher than for fruit/ vegetable exports
indicating to a higher instability in this market. To find a clearer pattern of winners and
losers, this variable was dropped and only the “difference” and the “ratio” were used for
clustering. This was a rather pragmatic decision. In the group of 40 small exporters, we
chose a 5- cluster- solution, the group of only six large exporters was described by three
13 Except for Korea (285,000) and Honduras (340,000).
11