fth of the within-country dispersion of export shares. While not a rst order determinant of export composition, the mechanism is quantitatively meaningful. Furthermore, as discussed above, measurement error in the use of annual correlations and variances to proxy for their within-year counterparts, as well as the evidence from BLS price data that the within-year measures have less dispersion than their annual counterparts, suggest that the true coecient for the correlation in equation (7) may be larger than the ones reported in Table 3. Therefore, it is likely that these quantitative impacts are a conservative estimate of the true economic relevance of this mechanism.

Bilateral regressions show similar results. The coecient is also signicantly negative across specications. In this case, an increase in the volatility of a country's exchange rate against the US dollar from the 10th to the 90th percentile (75 percentage points increase) raises by 20 percent the ratio of the export share of a good at the 10th percentile level of correlation (-0.65) relative to a good at the 90th percentile (0.29) (measured at the average level of price volatility). This corresponds to 11 percent of the average within country-pair standard deviation of log export shares. Comparing hypothetical commodities with correlations of -0.7 and 0.7 yields a 30 percent increase in the relative export share of the former, corresponding to 16 percent of the within countrypair variation of relative shares. This smaller explanatory power is not surprising since the term included in the regression is only part of the actual covariance between bilateral exchange rates and importer's prices, the other term being the covariance between the importer and exporter exchange rates against the dollar, which is absorbed non-parametrically.

Overall, the results for the baseline specication indicate that dierences in natural hedge across commodities have a small but non-negligible impact of natural hedge on trade patterns. This is encouraging considering the typically poor t of Heckscher-Ohlin regressions.

The results presented in columns (2), (3), (5), and (6) show that the measures of revealed factor intensities matter for trade patterns. Column (2) introduces the interaction of the baseline measures of factor intensity with a country's measure of factor abundance. The regression in Column (3) replaces these interactions by the interaction of the measure of the overall factor intensity of a commodity and a country's relative output per worker, which is a measure of a country's overall factor abundance (see Romalis (2004)). This measure is also the _PRODY_ measure introduced by Hausmann et al. (2007) and controls in a general way for the possibility that richer countries tend to export similar products, beyond what can be explained by relative factor endowments. The results of these two columns show that, in fact, countries tend to concentrate a relatively larger fraction of their exports in goods that are intensive in their more abundant factors. All estimated coecients are positive and statistically signicant, except for the one for capital intensity in Column (2), but the sign and signicance of the main coecient remain unaected. There is, however, a decline in the magnitude of the main coecient in the regressions for global trade shares, which is about half the size of the baseline when controlling for overall factor intensity in column (3). Part of this decline is due to the smaller sample of countries for which there are data on the factor endowments.

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