declarations randomized by GasyNet.

When we extend the sample by including withheld declarations, excess interaction is again associated with significantly accelerated clearance, significantly reduced fraud, lower value and tax adjustments and significantly higher tax revenue losses, as is shown in panel C. However this preferential treatment is driven by the declarations withheld from delegated randomization since we did not observe these correlations in the sample of declarations randomized by GasyNet analyzed in panel B.

In panel D we consider the entire sample of declarations and include the excess interaction share, a dummy for being withheld from delegated randomization, and the interaction between these two measures. The coefficients on the interaction term are consistently highly statistically significant. Preferential treatment is most pronounced for declarations that are withheld from delegated randomization and handled by inspectors who interact excessively frequently with a given broker. Such declarations are especially rapidly cleared, especially less likely to be deemed fraudulent, are subject to significantly lower value and tax adjustments, and, as a result, exhibit higher tax revenue losses.

The preferential treatment by inspectors of declarations characterized by excess interaction was thus enabled by manipulation of the IT system. Our placebo tests show clearly that when declarations are truly randomly assigned, there is hardly any excess interaction. Whatever accidental excess interaction nonetheless arises is not correlated with customs outcomes. By contrast, declarations withheld from delegated randomization are associated with excess interaction and an increased risk of tax evasion. They receive privileged treatment from inspectors, especially when such inspectors are handling a significantly larger share of a given broker’s declarations than would be expected had the assignment of declarations followed official rules. All in all, these results corroborate our methodology to detect corruption and also attest to the difficulties associated with dislodging systemic corruption.

An event study of the impact of the delegated randomization on tax yield per declaration, shown in Appendix Figure A6, is consistent with this interpretation. Tax revenues increased significantly in the first few months of delegated randomization, but these gains were not sustained.<sup>54</sup> Appendix Table A24 (panel B) presents estimates of the costs of corruption during the delegated randomization period, following a similar approach to that described in Section 7.<sup>55</sup> According to our preferred estimates which calculate hypothetical tax yield using prices reported by exporters, declarations that were likely the object of corruption - notably those withheld from randomization cleared by an inspector who interacted excessively frequently with the broker registering them - would have yielded an _additional_

> 54For the event study we use a sample including 6 months before and after the start of the delegated randomization and estimate an OLS regression of log 1 plus tax yield per declaration on dummies that define the position of the month relative to November 2017 as well as inspector, broker, source country, HS2-product, and calendar month fixed effects.

> 55We use estimates from regressions of hypothetical tax revenue losses on the excess interaction share, a dummy for declarations being withheld and their interaction shown in Appendix Table A23. Tax revenue in the absence of corruption is now calculated as _T_<sup>_NC_</sup> = _T ∗ exp_ ( _β_<sup>�</sup> _E ∗ ES_ + _β_<sup>�</sup> _P ∗ WFR_ + _β_<sup>�</sup> _EP ∗ ES ∗ WFR_ ), where _WFR_ is a dummy for declarations whithheld from randomization. The details on this calculation are shown in Appendix C.

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