10 FERNANDES-KLENOW-MELESHCHUK-PIEROLA-RODR ́ıGUEZ-CLARE

# **Correlation between intensive and extensive margin, and relation with distance**

We now move beyond the intensive margin elasticities and report additional stylized facts on the correlations between the intensive margin, the extensive margin, and distance. There is a positive and significant correlation between average exports per firm and the number of exporting firms (0.25, standard error 0.01) after taking out origin-year and destination-year effects. Table 6 shows how these margins vary with log distance with alternative sets of fixed effects. The elasticities are all negative and significant when controlling for origin-year and destination-year fixed effects: average exports per firm, the number of firms, average number of products exported per firm, and average exports per product per firm all decline with distance between trade partners.

# **Relation to previous empirical results**

We finish this section by relating our stylized facts to those of EKK, EKS, Bernard et al. (2007) and Bernard et al. (2009). EKK use firm-level export data for a single origin (France) and show that average exports per firm increase with market size of the destination (measured as manufacturing absorption) with an elasticity of 1/3. In Figure 4 we plot market size (horizontal axis) against our estimated destination fixed effects (vertical axis) from a regression of average exports per firm on origin, destination and year fixed effects based on the core sample and country pairs for which _Nij >_ 100. A regression line (not shown) through the points in the plot implies that average exports per firm increase with destination market size with an elasticity of 0.19, a bit lower than the result in EKK.<sup>15</sup> EKK also show that firms exporting to more destinations exhibit higher sales in the domestic (French) market. Our data does not include domestic sales, but we can instead look at sales in the most popular destination market for each origin. Let _xil|j_ denote average exports to destination _l_ computed across firms from _i_ that sell in markets _l_ and _j_ and let _l_<sup>_∗_</sup> ( _i_ ) _≡_ arg max _k Nik_ be the most popular destination market for each origin country _i_ (e.g., the United States (U.S.) for Mexico). In Figure 5 we plot log _xilx∗il_ ( _∗i_ )( _|il_ <u>)</u> _∗|j_ ( _i_ )<sup>(vertical axis) against log</sup> _NNil∗ij_ ( _i_ )<sup>(horizontal axis) for</sup> all _i_ and _j_ for the core sample.<sup>16</sup> It is very clear that the results derived by EKK for French firms remains valid for our data with many origin countries: firms that sell in more markets are more productive as proxied by their sales in their origin country’s most popular destination market.

> 15Similar findings are obtained in unreported plots where the destination fixed effects are based on the extended sample and all country pairs or based on the core sample and either country pairs for which _Nij >_ 100 or all country pairs.

> 16The EKK estimating sample includes only firms with sales in France. To implement an approach comparable to theirs, we drop all firms from country _i_ that do not sell to _l_<sup>_∗_</sup> ( _i_ ), so the sample includes only _Nil∗_ ( _i_ ) firms for country _i_ . This implies that all firms that make up _Nij_ are also selling to _l_<sup>_∗_</sup> ( _i_ ).