both products: EX_ADJUST_POS for NC sawnwood and IM_ADJUST_NEG for C sawnwood. Discrepancies were significantly larger for bilateral flows where EFI made these adjustments to the original volume data in QORIG.

In results that are shown in Appendix 8 but not here, we also found that our variables for the misrecording of species group, C_DELTA and NC_DELTA, had statistically significant coefficients when we added them to the regression models for NC and C sawnwood, respectively. To our surprise, the coefficients were positive instead of negative. The magnitudes of the coefficients were small, however, and the addition of these variables had a negligible impact on the signs, magnitudes, and statistical significance of the coefficients on the other explanatory variables. For this reason, we conclude that misclassification of species group, whether unintentional or otherwise, is not an important explanation for observed discrepancies between import and export statistics.

Because the fixed effects are defined for pairs of countries, the CONTIGUITY variable drops out of the model. The coefficient on the remaining variable related to discrepancies in actual trade flows, SWITCH_SIGN, is highly significant, negative, and not statistically different for the two products. As expected, its absolute magnitude is less than 1: 60-70 percent of a negative discrepancy (reported exports exceeding reported imports) shows up as a positive discrepancy in the following year. This suggests that shipment lags play a role in explaining negative discrepancies.

The remaining variables pertain to the intentional unreporting of imports and exports. Results for the two products are similar for several of the variables. In particular, and as expected, the coefficients on IM_UVAL and EX_UVAL are negative and positive, respectively. Both are highly statistically significant, and their magnitudes are comparable for the two products. Also as expected, the coefficient on IM_DUTY×UVAL is negative for both products, though it is significant at the 5-percent level only for C sawnwood. The coefficient on the other interaction term, IM_DUTY×GOV, has a positive sign for both products, but it too is significant only for C sawnwood.

Results for the other variables match our expectations less well. The coefficient on IMDUTY is significant for both products but negative only for C sawnwood. The coefficient on EX_GOV is significant for both products but has the wrong sign, positive, for both. The coefficient on IM_GOV is not significant for either product and is incorrectly signed for NC sawnwood.

Regarding the coefficient estimates, the results are therefore stronger for C sawnwood than for NC sawnwood. The best results among the variables related to unreported imports and exports are for the sawnwood price variables, IM_UVAL and EX_UVAL. One sense in which the results are stronger for NC sawnwood than for C sawnwood, however, is in terms of goodness-of-fit. The _R_<sup>2</sup> statistic is twice as large for NC sawnwood as for C sawnwood. Even the former is very small, however: the value of 0.131 indicates that the regression model explains only 13.1 percent of the variation in the discrepancies within and between pairs of trading countries. Most of the variation remains unexplained and in the error term, η _ijt_ . Despite this low explanatory power, the large _F_ statistics—118.28 for NC, 68.26 for C—indicate that the overall regression models for the two products are statistically significant.

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