sawnwood from Germany. Discrepancies were also significant for exports of nonconiferous sawnwood to Sweden and the United Kingdom; imports reported by these two trading partners were smaller than the exports reported by Romania.

To answer the second question, we analyzed data on bilateral trade statistics discrepancies pooled across European countries. Our analysis was guided by a theoretical model that distinguished three potential, and not mutually exclusive, causes of discrepancies in reported trade flows: measurement error, discrepancies in actual flows (e.g., shipments leave an exporting country in one year but do not arrive in the importing country until the following year), and intentional underreporting of imports or exports to evade government regulations. We found statistical support for each of these causes, including intentional underreporting. But even in combination, the three causes explained very little of the variation in the discrepancies across countries and over time. Discrepancies between European countries’ trade statistics and those of their trading partners are evidently mostly due to factors not explained by the econometric model. Moreover, some of the variables that we included in the econometric model to represent these factors had impacts opposite of what theory predicts.

One of the purposes of this study was to evaluate the practical usefulness of econometric methods for detecting illegal trade practices in the forest sector. For several reasons, our experience with the analysis presented in this report leaves us skeptical about the usefulness of such methods. The first is the simple fact that any econometric approach that is based on observed statistical discrepancies is necessarily blind to underreporting that occurs simultaneously at both the point of export and the point of import. An example is smuggling that is not detected by the customs authorities of either the exporting country or the importing country. Even when underreporting occurs more in one country than in the other, thus leading to an observable discrepancy, the explanatory variables in a model might not do a good job of completely capturing the factors that determine the degree of underreporting. Illegal activities could remain undetected in the portion of the variation in the discrepancies that the model fails to explain—which in our case was most of the variation. A third reason relates to the basis for measuring trade statistics discrepancies. We focused on discrepancies defined in terms of physical trade volumes, to avoid the obvious problems associated with discrepancies defined in terms of trade values (e.g., transport costs and exchange rate fluctuations). But it is possible that volumes could be reported accurately but values could be intentionally underreported. Our analysis misses this type of underreporting. Finally, and most generally, an econometric study that focuses on international trade has no bearing on illegal activities that occur purely in a domestic context, such as illegal felling of timber that is processed and consumed locally or collusion in timber auction markets. Such illegal activities could well be much more important than the ones in the trade sector that were the focus of the econometric analysis in this study.

Although improved data might overcome some of the shortcomings of econometric methods for detecting illegal trade activities in the forest sector, for an individual country like Romania we suspect that simpler statistical techniques like the ones used in section 3 of this report are more useful. Simple statistics like mean values that identify trading partners with whom Romania has persistent and large discrepancies could be used by customs authorities and NGOs as a guide for determining which shipments to check more carefully. Even this approach is not necessarily easy to implement, however, as it requires not just access to Romanian trade 22