To test more directly for the presence of shipment lags, we also included a variable, SWITCH_SIGN, that equaled the lagged discrepancy ∆ _ijt-1_ when a positive discrepancy (imports exceed exports) was preceded by a negative discrepancy (imports exceed exports)—i.e., when ∆ _ijt_ > 0 and ∆ _ijt-1_ < 0—and 0 otherwise. We expect the coefficient on this variable to be negative, with an absolute value less than one: the coefficient shows the proportion of the negative discrepancy that arrives in the following year.

# **5.1.4 Explanatory variables related to unreported flows: IM_DUTY** **_it_ , IM_UVAL** **_ijt_ , EX_UVAL** **_ijt_ , IM_GOV** **_it_ , EX_GOV** **_jt_**

We were able to compile cross-country data for all the variables in the theoretical model except the level of fines and other punishments that companies faced if they were caught underreporting imports or exports. IM_DUTY is the sawnwood import tariff. We pieced together data for this variable from tariff schedules in various GATT and WTO documents. We did not include a corresponding variable for export taxes, because such taxes equaled zero in every country for which we had data. We expect the coefficient on this variable to be negative: higher tariffs create an incentive for greater underreporting of imports—hence, larger negative discrepancies as we have defined them, imports minus exports.

IM_UVAL and EX_UVAL, the import and export unit values, are our proxies for sawnwood import and export prices. We constructed them by dividing reported import and export values by the corresponding quantities (the QUANTITY series). We expressed them in constant (inflation-adjusted) US dollars per cubic meter. One reason we limited the sample to reported flows of 100 cubic meters was to reduce the error in constructing these variables. For example, if a country imports or exports only 1-9 cubic meters in a year (and there were some such observations in the EFI database), then we can only have confidence in our estimate of the unit value to an order of magnitude (i.e., 10 times). To the extent that the regulations companies seek to evade are more costly for sawnwood that is more valuable, which would be true not only for ad valorem import tariffs but also nontariff trade barriers like export quotas, we expect the coefficient on IM_UVAL to be negative (higher import prices create an incentive for greater underreporting of imports, hence a more negative discrepancy) and the coefficient on EX_UVAL to be positive (higher export prices create an incentive for greater underreporting of exports, hence a more positive discrepancy).

IM_GOV and EX_GOV are the indicators of quality of governance for importing and exporting countries, respectively. We constructed these variables using economywide indicators of institutional quality developed by Political Risk Services (PRS). PRS rates countries according to 24 measures of economic, social, and political risks in its monthly _International Country Risk Guide_ . Knack and Keefer (1995) selected five of these measures and compiled annual time series for a large set of countries. The three most relevant to the risk of illegal trade activities are:<sup>10</sup>

> 10 The other two variables are expropriation risk (the risk of confiscation and nationalization) and government repudiation of contracts (an indicator of contract enforcement between the government and private parties).

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