for estimating this gravity model. The results from this estimator produce several interesting conclusions regarding trade in services.
First, GDP per capita rather than the population of the country (i.e., wealth of the country rather than size) determines the importer’s demand for service commodities. A 1 percent increase in GDP per head increases imports of services by 1.3%. Intuitively, this would be expected as individuals and countries tend to consume more services as they become richer. A similar effect appears to hold in the exporting country: a richer country (rather than a larger country) will be able to produce more service commodities and will export more services.
Second, a common language is the only other explanatory variable that is significant. A shared language will increase trade between two countries. As discussed in section 4.1, it is reasonable to expect a common language to have a positive impact on trade services (perhaps even more so than in goods trade). Many service transactions rely on the movement of physical persons and person to person communication, both of which will be greatly facilitated by a common language.
Distance has no significant influence on trade flows using the HTM. Similar to adjacency, this may reflect the fact that physical distances have little or no relevance for the movement of service commodities. The lack of a statistically significant coefficient on the distance variable is particularly interesting because it confirms an earlier finding of Egger (2002) in relation to the application of the HTM gravity model to goods trade. 22
Finally, the insignificance of both countries being members of the EU is likely due to the fact that service trade is not fully liberalised within the EU. This finding differs from the majority of research on goods trade that finds free trade areas and customs unions to be positively related to trade in those commodities. Perhaps surprisingly, adjacency has no impact on trade levels. This may reflect the fact that physical borders have little relevance to trade in services.
The effects of distance and borders are likely to vary for different types of services. In the following sections, the results for the four disaggregated services sectors (travel, transport, government and commercial services) are examined. A description of the composition of each of these sectors and the data sources for additional variables are contained in the appendix.
The results of the standard gravity model estimated for imports of travel services are shown in panel I of table 4. As noted in section 4.2, the Hausman and Hausman-Taylor over-identification tests indicate that the HTM is most appropriate in this case. Imports of travel services are found to be positively influenced by a common language, GDP per capita and population in the importing country, but the population of the exporting country is also statistically significant and exerts a strong negative effect on trade.23 The
22 McPherson and Trumbell (2003) also find evidence in support of this argument. However, others have found distance to be statistically significant in trade in goods using a Hausman-Taylor estimator (e.g., De Santis and Vicarelli, 2006 and Boudier-Bensebaa and Lamotte, 2006).
23 In the case of travel, care must be taken in the interpretation of the variables. For travel services, the importing country is the “home” of traveller. The country visited, where the service is purchased, is the exporter.