**Table 5.  Identified irregularities and their characteristics**

|Panel A. Id|entified irregularities in|license N853 - food of ani|mal origin|Number of irreular|
|---|---|---|---|---|
|Product group|Origin countries|Irregularity, if reported|Border post|g<br>shipments sampled|
|2013 Milk and Milk products|Bosnia|Aflatoxin|Tabanovce|8|
|2013 Milk and Milk products|Croatia|Aflatoxin|Skopje|2|
|2013 Milk and Milk products|Morocco|-|Skopje|1|
|2013 Milk and Milk products|Serbia|-|Kavardarci|1|
|2013 Milk and Milk products|Serbia|Aflatoxin|Skopje|6|
|2013 Pork meat, fresh or frozen|Canada|-|Bogorodica|2|
|2013 Pork meat, fresh or frozen|Italy|-|Veles|1|
|2014 Meat products (not canned)|Bosnia|Listeria|Skopje|1|
|2014 Molluscs and Crustaceans|Greece|Listeria|Medzitlija|1|
|2014 Offal|Italy|Salmonella|Bogorodica|1|
|2014 Pork meat, fresh or frozen|Not reported|E Coli|Tabanovce|3|
|2014 Pork meat, fresh or frozen|Spain|Salmonella|Tabanovce|1|
|2014 Poultry meat, fresh or frozen|Brazil, Canada, Italy|Salmonella|Bogorodica|3|
|2014 Poultry meat, fresh or frozen|Croatia|Salmonella|Skopje|1|
|2014 Poultry meat, fresh or frozen|Germany|Salmonella|Tabanovce|1|
|2014 Poultry meat, fresh or frozen|Germany|E. Coli|Tabanovce|1|
|2014 Poultry meat, fresh or frozen|Greece|E. Coli|Bogorodica|2|
|2014 Poultry meat, fresh or frozen|Italy|Listeria|Bogorodica|1|
|2014 Poultry meat, fresh or frozen|Not reported|Salmonella|Tabanovce|3|
|2014 Prepared meat|Not reported|Salmonella|Tabanovce|1|
|2014 Prepared meat|Not reported|Listeria|Tabanovce|1|
|Panel|B. Identified irregulariti|es in license I047 - animal|feeds||
|Product group|Origin countries|Irregularity, if reported|Border post|Number of irregular<br>shipments sampled|
|2013 Concentrated feeds|Serbia, Slovenia|-|K. Palanka|11|
|2014 Concentrated feeds|Serbia|Clostridium|K. Palanka|1|

Notes: the table shows information calculated based on the FVA lab sample data set. “-“ indicates that the identified hazard was not reported in the FVA lab sample data set.

Table 6 presents the results from estimating by OLS Equation (2) in Panel A based on a sample covering pre-reform data only (ending on June 30, 2014) and Equation (3) in Panel B including data until December 2015 and in Panel C including data only until end of 2014, relying on data at the sampled shipment level where each shipment belongs to a given product group-country of origin-semester-year. Inference is based on Huber-White standard errors robust to heteroscedasticity, which we cluster by broad product group-country of origin because the specifications explain shipment level non-compliance with sampling rates at that more aggregate level (Moulton, 1990). In each of the panels the first half of the columns use as estimating sample all shipments sampled while t the second half of the columns exclude from the estimating sample shipments whose corresponding sampling rate at the product group-country of origin-semester-year is larger than 1.

The specifications in Panel A allow us to check, in principle, whether the likelihood of noncompliance is higher when the sampling rates are higher - before the reform. But given the extremely small number of sampled shipments that are non-compliant the regressions are unable to identify any significant link, even when we do not control for any type of fixed effects.

The specifications in Panels B and C show that once the post-reform semester-year data are included in the estimating sample there is generally a negative relationship between non-compliance rates and sampling rates per se, though with unstable significance across specifications. The coefficient on the post-reform indicator in columns (4) and (9) in both panels suggests that the FVA reform increased 30