**Table 1: Summary statistics**

||Average|Std. Deviation|Min|Max|
|---|---|---|---|---|
|Exports (million US$)|610738.8|5408312.0|10.0|3.68E+08|
|Number of product traded|116.2|162.6|1.0|744.0|
|Sectoral Avg export|2162452.0|1.05E+08|158.8|2.49E+10|
|Importer Internet penetration|29.5|27.5|0.0|96.5|
|Exporter Internet penetration|35.4|28.2|0.0|96.5|
|Importer GDP (current million US$)|435183.6|1494994.0|0.0|1.68E+07|
|Exporter GDP (current million US$)|558413.7|1665443.0|0.0|1.68E+07|

Finally we will also explore the effect of the Internet adoption on different types of goods. The Internet reduces the information and communication costs between exporters and importers and this effect is most relevant for goods that are differentiated and/or customized. We employ the classification from Rauch (1999) which allows us to classify the products into homogeneous and differentiated goods. In order to match trade date with the Rauch classification and to construct bilateral trade for each type of good, we use disaggregated data at the 4 digit SITC level from COMTRADE.

# **3. Results**

- (a) Bilateral Exports, Intensive and Extensive Margins

We examine the effects of the Internet adoption on bilateral export flows and the results are presented in Table 2. Column (1) contains the results of the OLS regression with year, importer and exporter fixed effects and while it is not the preferred specification, it affirms the relationship between the usual gravity variables and exports. The signs of the gravity variables are as expected in column (1): distance exerts a negative effect on exports similar to the results in the literature.<sup>4</sup> Other gravity variables, such as GDP, common language and contiguity, exerts a positive effect on exports. Column (2) contains the results from the preferred specification with year and country-pair fixed effects. As discussed above, the drawback of using country-pair fixed effects is that the non-time-varying bilateral variables such as distance are absorbed in the country-pair fixed effects. The estimation results show that by omitting factors specific to the country pairs in column (1), the effect of the exporter’s Internet adoption is biased downwards and the effects of the importer’s Internet adoption is biased upwards. Column (3) contains the results from the Pseudo-Poisson Maximum Likelihood (PPML) regression, which accounts for the zero trade flows (Santos-Silva and Tenreyro, 2006). The PPML regression is only performed with the year, importer and exporter fixed effects because including country-pair fixed effects was technically unfeasible. The results of the PPML regression are very similar to the OLS results.

The level of Internet adoption in the exporter has a larger effect on export flows than Internet adoption in the importer. The coefficients on the Internet adoption variable are the elasticities of exports with respect to Internet adoption. From column (2), a 10 percent increase in the exporter’s Internet adoption increases bilateral exports by 1.9 percent, while a 10 percent increase in the importer’s Internet adoption increases bilateral exports by 0.6 percent. The coefficients of Internet adoption in the exporting and

> 4 See Blum and Goldfarb (2006) who show that even online transactions are reduced by the effects of distance.

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