It should be noted that we abstract from the economic impacts of the infrastructure expenditures. These are unlikely to have major repercussions on the long-term real income gains but could affect the timing of the gains depending on the source of the financing, i.e. domestic versus foreign. Foreign inflows could impact the short-term gains through their effect on the real exchange rate, unless there is strong leakage of the inflows in terms of imported goods and services. If investment was funded by higher government taxes, it would likely lower household consumption with impacts on private investment and relative prices. In addition, our modeling approach misses some of the channels that would be likely to increase the gains from the BRI such as additional foreign direct investment flows or new products or markets where countries might become competitive following implementation of BRI as in our approach intensive and extensive margins are determined by the existing trade flows. Furthermore, there is significant uncertainty regarding the projects to be implemented under BRI and their potential for trade cost reductions. Our analysis uses the best available assumptions, but the impacts of the BRI will ultimately depend on the specific investments and their effectiveness in reducing trade costs.

# **2. BRI-induced trade costs reductions**

This study employs the estimates of de Soyres et. al. (2018) to generate the BRI-induced trade costs reductions. The authors use network analysis to quantify the impact of the BRI on connectivity between countries before and after the infrastructure investments. The network model covers more than 1,000 cities and incorporates the current network of rail and maritime links to compute the shipment costs between all cities using a shortest path algorithm. The algorithm factors in the cost of a given transport path taking into consideration distance, travel time and vehicle operating costs. The analysis covers cities with population over 500,000 as well as the three most populous cities in the country. The network is generated by solving for each city pair the routing determined by the shortest time. The limitation of the methodology is that it fails to include road and air transport features in the current application. Other limitations are also discussed in the study by de Soyres et. al. (2018) such as lack of information on rail gauge, service frequency port facilities etc. Another key challenge was posed by the identification of BRI-related projects where timelines and specific locations were not always available. Nevertheless, the authors generate a consistent data set of BRI-related trade costs reductions in rail and maritime transport costs including switching across the two transport modes. These trade costs reductions are then applied to ad valorem equivalents of value of shipment day generated based on updated estimates of Hummels and Shaur (2013). The time in trade estimates are based on US imports data and variations in the premium paid for air shipping versus maritime shipping. The average delay of one day in shipping is estimated to be associated with ad valorem tariff of 4.9% in the baseline. However, the data is available at the HS2 digit level and aggregated to GTAP sectors and country pairs based on 2014 trade flows.

In the baseline, the trade among BRI countries air transport accounts for nearly 12% of total transport cost, land is around 31% and sea is around 58%. These shares vary dramatically across exporting countries—with high sea shares for island economies such as Indonesia and the Philippines. Therefore, our analysis covers a significant share of total transport services. In the baseline, the highest time in trade estimates are estimated in products of animal origin, cereals, fruits and nuts, pulp and paper; while products the least sensitive to time in trade covered special woven fabrics, silk, man-made fibers and filaments.

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