broad product group-country of origin-month-year, or at more aggregated levels. This allows to calculate the rate of non-compliant import shipments at those various levels of disaggregation.

The FVA lab sample data set suffers from two major weaknesses. The first weakness is that for two groups of products - food of non-animal origin and food contact materials - the data set records information _only_ on shipments from which laboratory test results were positive for some hazard. This means that the data lack information on the total number of samples taken for those products, which precludes the calculation of sampling rates and rates of non-compliance. Therefore, our analysis of sampling focuses exclusively on the remaining sets of FVA products: food of animal origin and animal feeds. The second weakness is that the products we could study were sampled much less frequently in 2015 than in previous years. The raw total number of FVA samples taken from imports of food of animal origin and animal feeds was 1,487 and 1,235, respectively in 2013 and 2014, but just 63 in 2015. The reason for this decline was the funding dispute with the public laboratories described in Section II.2 The third data set provided by the FVA is the import shipment data from the single window for import, export and transit of goods and tariff quota (EXIM) for the products covered by licenses I007, I047, and N853 over the period 2013-2015. The EXIM data set records each license application, which has a firm identifier (which was not made available to us due to confidentiality concerns), a tariff line variable, product descriptions, volume imported (and unit of measurement), date of application, and country of origin.<sup>28</sup> We use the EXIM data set to calculate the total number of FYR Macedonian import shipments by broad product group-country of origin-month-year, or at more aggregated levels. The numbers of import shipments are combined with the number of samples taken to the laboratory (discussed above) to calculate sampling rates of import shipments. After a few data problems described in Appendix A are addressed the cleaned EXIM data set imports of food of animal origin and animal feeds (requiring licenses I047 and N853) used in our analysis covers 40,212 shipments over the period 2013-2015.

The fourth data set containing comprehensive data on the universe of imports by FYR Macedonia (not only those imports that require a license from the FVA) was obtained from the State Statistical office (Makstat). The Makstat data set available for the period 2009-2015 includes import values (measured in US dollars) and volumes (measured in kilograms) by month, HS 10-digit code, and border post of entry.<sup>29</sup> Makstat provides highly credible measures of import flows, as Makstat simply processes the data provided by the Macedonian customs agency.<sup>30</sup> Hence, the Makstat data set is used to measure our key outcome

> 28 Note that applications for licenses are lodged at the border post when the goods have already been loaded and shipped to FYR Macedonia.  We therefore operate under the assumption that license applications from EXIM represent real shipments. 29 The ratio of FYR Macedonia’s total imports in the Makstat data set to FYR Macedonia’s total imports in the main international source of trade data, WITS, is very close to 100% in every year from 2009 to 2015.

> 30 We requested more detailed data from Macedonian customs, but they were not willing to share it.  Among other shortcomings, this means that our trade data lack firm-level information as well as information on the inspections undertaken by Macedonian customs. Separate inspections by the customs or other technical agencies would represent duplicative procedures of the kind that van der Meer and Ignacio (2011) describe as weaknesses common to developing country customs agencies.  From an econometric

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