Thus, we would like to get a sense of how the magnitudes change as we vary these country
characteristics.
We do this in two ways. First, we calculate the averages of σ2 , ρ, h, and σA- for the
developed and developing country subsamples, and use them to calculate the impact of
trade on these two groups of countries.22 The subsample averages of σ2, ρ, h, and σA-
are summarized in Table T1. Developing countries are considerably more volatile, some-
what less diversified, and have lower average comovement of sectors. Table 9 presents the
comparison of the impact of trade on the developed and developing countries. In these
calculations, we keep the magnitude of the trade opening and the β,s the same for both.
The differences in the impact of trade between the two groups are pronounced. It turns
out that the same change in openness raises aggregate volatility by 0.0005 in the average
developed country, but by 0.0025, or five times as much, in the average developing country.
As a share of the average aggregate volatility in the two groups of countries, however, the
effect is stronger in developed ones: the increase corresponds to 40% of the average aggre-
gate volatility found in the developed subsample, compared to 28% in for the developing
subsample. The relative importance of the three individual effects does not differ greatly
between the two samples, as evident from Table 9. Perhaps surprisingly, the sector-level
volatility and comovement effects are relatively less important in the developing country
sample. The specialization effect, while still the largest quantitatively, is less important in
the developed country sample.
The developed and developing countries differ significantly along every variable that
goes into calculating our magnitudes. However, we might also like to know how changes in
an individual variable affect these magnitudes. To do this, we go back to the full sample
baseline calculation of the previous subsection, and vary σ2 , ρ, and h individually. Table 10
reports the results. In this table, rather than evaluating the three effects using the sample
means of σ2 , ρ, and h as we had done above, we evaluate them using each of these at the
25th and the 75th percentile of its distribution, one by one. Thus, this table allows us to see
how the sizes of the Sector Volatility Effect, the Comovement Effect, and the Specialization
Effect differ between countries at the 25th and the 75th percentile in the distribution of σ2 ,
for example.
It turns out that moving from the 25th to the 75th percentile in the distribution of
sector-level volatility more than quadruples the overall effect of trade opening. What is
interesting here is that the strongest effect of changing σ2 is not on the Sector Volatility
Effect itself, but on the Specialization Effect: while the magnitude of the former triples,
the latter increases by a factor of 4.4. The increase in σ2 also doubles the magnitude of
22Countries included in the developed subsample are denoted by a * in Appendix Table A1.
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