i-D estimates help us understand whether the variety of imported FVA products grew faster than the variety of non-FVA products imported after the FVA reform. The results showed an insignificant effect of the FVA reform on the extensive margin of imports.

# **_V.4 Trade effects of heterogeneous treatment_**

As a supplement to the evidence from the D-i-D regressions, in this section we discuss the results from specifications that exploit heterogeneity in the degree of treatment by the FVA reform, which we capture by variation across product groups and origin countries over time in the level of sampling undertaken, to identify the link between the sampling rate and the level of imports. There are two caveats to keep in mind regarding these specifications. First, they are estimated on a sample including only food of animal origin and animal feeds, which are the FVA products for which we have the data necessary to construct sampling rates (as discussed in Section IV.2). Second, the product classification applied in these regressions is more aggregated than in the earlier D-i-D regressions using HS 4-digit products, due to the difficulties concording the FVA sampling data with the HS codes.<sup>55</sup> We estimate the impact of the sampling rate on log imports relying on the merged data set that combines FVA lab samples, EXIM and Makstat for import values and sampling rates measured at the level of the broad product group-country of origin-semester-year in the period 2013-2015.

Table 9 shows the results from estimating Equation (7) by OLS with standard errors robust to heteroscedasticity. All specifications control for the rich set of fixed effects specified in that equation to sweep out idiosyncratic shocks as well as trading partners’ world export supply shock and import demand shocks of FYR Macedonia’s immediate neighbors. The estimating samples used in columns (1)-(4) includes all observations while those used in columns (5)-(6) exclude observations with a sampling rate larger than 1, an anomaly discussed in Section VI.2. The evidence in Table 9 is generally weak and not consistent across specifications.

The coefficients on the sampling rate in columns (1), (4) and (5) capture not only the effect of reduced sampling activity due to the FVA reform but also of sharply reduced sampling activity due to the funding dispute with the public laboratories in 2015. We had hoped that in face of this unexpected and sharp decline the sampling rate we might be able to observe an effect of reduced sampling rates on imports.<sup>56</sup> However, the positive (though weak) estimates are of the opposite sign as would be expected if reduced

> 55 The much smaller numbers of observations in these regressions relate to the dropping of non-FVA products as a control group. But they also reflect aggregation across products associated with difficulties concording the trade classification with the verbal descriptions of product categories used in FVA sampling activity.

> 56 Because the funding dispute causes the sampling rate to fall nearly to zero, the change in the sampling rate in 2015 is virtually determined by the sampling rate prior to the reform.  If higher sampling activity was conducted on products whose imports were sensitive to sampling rates, the sudden elimination of sampling activity could help to identify the causal effect of reduced sampling activity.

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