scenario where the transportation mode can change. Then we proceed to estimate the effects of the BRI on shipping times under these two scenarios.<sup>12</sup>

# **a. The lower bound scenario**

Recognizing that choices of transportation mode do not only take into account shipment time but also shipment costs and other considerations, we build our main estimates of reduction in shipment time by avoiding large changes in transport mode before and after the BRI. These are conservative estimates as the new BRI infrastructure might actually induce some firms to substitute maritime link in favor of rail links which might be more expensive but also significantly faster. By not considering these changes, the estimates should be interpreted as the minimum gains in terms of shipping time that can be achieved by taking advantage of all new and upgraded transport links but without any change in the transportation mode.

In the previous section, we showed that the network analysis results in the pre‐BRI scenario are in line with other data sources both in terms of city‐pair shipping times and in terms of aggregate modal shares. Taking those results as a starting point, we build a first post‐BRI scenario where the shares of maritime and rail transportation modes would not exhibit significant change for each city‐pair. To do so, we use a two‐steps procedure. We provide here an intuitive description of our method and give a more detailed explanation in the annex.

We proceed in two steps. First, we run a network analysis with all BRI transport projects taken into account and find the optimal shipping route between all city‐pairs, keeping our maritime preference as in the pre‐ BRI computation. Second, for each origin‐destination, we compute the share of maritime and rail in the optimal path and compare them to the modal shares from the pre‐BRI scenario. If the optimal route after the BRI features a change in the modal share lower than 5%, we keep the result as is since there is no major shift in transportation mode. If, instead, the optimal route features a modal switch above 5%, we run additional scenarios and change the preference for maritime links until we find a shipping route post‐ BRI that keeps the transportation mode unchanged.

The procedure described above allows us to obtain results at the city‐pair level where before and after BRI travel time can be compared in a sensible manner. It should be emphasized that this lower bound scenario indeed corresponds to a conservative estimate since exporters benefit from an improved network but they cannot take advantage of those improvements to change their transportation mode. Figures 1 and 2 below show two examples of routes before and after the BRI where there is no significant mode switch – and which therefore are part of the lower bound analysis. In Figure 1, we can see that the shipping route between Beijing and Dushanbe goes through rail links both before and after the

> 12 One difficulty of such a network analysis is the association of each city with an “entry point” in the transportation network – usually referred to as “snapping”. Because cities are never exactly located on the network, we need to specify a snapping tolerance when performing this step. Since we compare two scenarios

> ( _before_ and _after_ the BRI), we also need to make sure each city is associated with the same snapping unless there is a new network element in their surroundings. To ensure we do not have inconsistencies between scenarios, we compare the snapping and manually exclude all cities featuring difference between scenarios. The number of cities quoted in the paper (1,000 in the global database and 1,964 in the regional database) reflects the cities selected through this procedure and which are actually used in our analysis.

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