declarations, the following specification is estimated by OLS: where _Yd_ is one of the declaration-level customs outcomes described in Section 3 (clearance time, fraud records, value and tax adjustments, hypothetical tax revenue losses). The main regressor of interest is the excess interaction share _ESibt_ defined in Section 4. The vector of declaration characteristics _Xd_ includes the tax rate, the risk score, a dummy for the red channel, a dummy for being a mixed shipment, the share of differentiated products, and a dummy for GasyNet’s valuation advice. Inspector fixed effects _μi_ , broker fixed effects _νb_ , HS 2-digit product fixed effects _πp_ , source country fixed effects _κc_ , and month-year fixed effects _τm_ are also controlled for. The independent and identically distributed (i.i.d) error is _ε_ .

The inclusion of inspector fixed effects accounts for heterogeneity across inspectors in their average productivity, ability, work ethic, and other time-invariant characteristics that may impact their performance. Broker fixed effects account for heterogeneity in their import patterns, efficacy, record-keeping, and other characteristics that may impact customs clearance. Since average differences in inspector and broker characteristics are accounted for, the specification is stringent in that identification of the coefficient on the excess interaction share is based on the interaction between the inspector and broker relative to other pairings of inspectors and brokers. Standard errors are clustered two-way by inspector and by broker.<sup>38</sup>

# **6.1 Main Findings**

The results from estimating Equation (5) are shown in Table 3. Inspectors assess declarations registered by brokers with whom they interact excessively frequently significantly faster than other declarations. Column (1) implies that a 10 percent increase in the excess interaction share is associated with a 20 percent (or approximately a 4-hour) reduction in clearance times. Declarations characterized by excess interaction are also less likely to be deemed fraudulent: column (2) shows that a 10 percent increase in the excess interaction share is associated with a 2.8 percent reduction in the likelihood of fraud being recorded. This is a large effect given that the unconditional probability of fraud being recorded is 8 percent (see Appendix Table A3).

In the same vein, columns (3) and (4) show that value and tax adjustments are significantly lower for declarations characterized by excess interaction. A 10 percent increase in the excess interaction share is linked to a 0.8 percent lower increase in value and a 0.9 percent lower increase in tax yield. These are again sizeable effects given that the unconditional averages of value and tax adjustment are 2 percent.

> 38Due to the inclusion of a large set of fixed effects, our estimates are obtained using the reghdfe Stata command drawing on Guimaraes and Portugal (2010). The current version of the command eliminates from the number of observations singletons and adjusts standard errors for their exclusion. A singleton is an observation unique in the sample in having a given fixed effect equal to one: e.g., a declaration with imports from source country A if no other declaration reports importing from country A.

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