We examine the determinants of FDI flows using the gravity-type empirical specification that has been widely used in previous studies such as the seminal work by Markusen et al. (2001) and Yeaple (2003). The specification is as follows: where subscripts i and j index host and parent countries, respectively, and the subscript t indexes year, BilateralFDI is the bilateral FDI flow from country i to country j, MktSize a vector of GDP of the host and source countries, HCdiff measures the host and source countries’ difference in human capital, Transport is a vector of transportation cost measures between country i and country j including air distance, sea distance, driving distance and driving time, Infrastructure is a vector of indices that measure the quality of trade-related logistic infrastructure including railway, airway, and port quality, PTAdepth measures the depth of the trade agreement between the host and source countries using the WTO RTA data, X is a vector of other country characteristics including a dummy variable for sharing border, a dummy for using same language, a dummy for sharing colonial ties, and a measure of business environment using the number of days required to start a business, D� and D� are vectors of country dummies used to control for all time-invariant country characteristics, and D� ia a vector of year dummies.

Figure A.3 shows positive and statistically significant correlations between FDI inflows and host countries’ GDP per capita, school enrollment, logistics performance, and port infrastructure quality. Countries with a higher income, higher levels of human capital, and better logistic and port infrastructure quality are shown to receive greater FDI inflows.

To examine empirically the effects of host-country economic characteristics, we estimate equation (1) first for a pooled sample of countries and then separating BRI and non-BRI countries to investigate how the determinants of investment flows might vary between BRI and the rest of the world.

Table 9 shows that most of the empirical regularities established in previous studies hold in our broad cross-country data. Most of the factors that have been considered in the literature exert significant and expected effects. As in earlier studies, transportation costs between source and host countries are found in general to reduce FDI, but the effect varies significantly by the mode of transportation. A 1-percent increase in air distance is associated with 0.7-1 percent decrease in the volume of FDI. Land transportation cost, measured by either driving distance or driving time, is also found to exert a significant and negative effect: a 1-percent increase in driving time, for instance, leads to a close to 1-percent decrease in FDI. In contrast, the effect of sea distance is weaker (insignificant in some specifications): a 1-percent increase in sea distance is related to around 0.1percent decrease in FDI flows.

Infrastructure quality is found to matter: the results show a significant and positive relationship between each of the three infrastructure quality measures, namely, railway, airway and port qualities, and FDI inflows. Countries with higher railway and airway indices and better ports tend to attract a greater volume of FDI. For example, improving the level of railway index from BRI countries (11.8) to the level of high-income countries (18.5) is associated with 4.3 percent increase in FDI flows.

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