L4D Learning for Democracy

There are no official statistics on international online trade in goods so far. This paper uses a consumer survey to construct a unique matrix of online B2C domestic and cross-border trade in goods between the 27 EU Member States. We compare online and offline trade patterns for similar goods. We find that the standard gravity model performs well in explaining online cross-border trade flows. The model confirms the strong reduction in geographical distance-related trade costs, compared to offline trade. However, the trade costs associated with crossing language barriers increase when moving from offline to online trade. Institutional variables such as the quality of legal institutions, online payments facilities and costefficiency of parcel delivery systems might play a role in cross-border trade but they remain statistically insignificant in this dataset. In a linguistically segmented market like the EU, online home market bias remains high compared to bias in offline cross-border trade. We conclude that it is hard to predict at this stage whether regulators could boost online cross-border trade through improvements in legal and financial systems, and parcel delivery infrastructure.