We have presented two empirical examples that illustrate the relevance for policy
makers of using value-added trade data compared to traditional trade data. We
specified a new CGE model based on additional information derived from the USITC
work on value-added trade data and the implied global linkages between countries.
Using this new model we find substantial and important quantitative differences for
the size of macro, sectoral and geographic impacts along supply chains compared
with a more traditional gross trade based model. We also developed a practical tool
for estimating the effect of fluctuations in nominal exchange rates on the value of US
imports of manufactured goods using a structural model of trade and a value-added
decomposition of gross trade flows. We find that estimates of pass through rates that
do not incorporate value-added trade data can be systematically understated, while
estimates of trade elasticities that do not incorporate value-added trade data can be
systematically overstated.