savings at the region wide level. Between each pair of cells, we take a mean of the reduction in costs of exports and imports as a simple measure of the extent to which a cell is directly affected by the change in transport costs.

- (2) Armington supply response:  Consumers and producers adjust behavior, but the number of varieties (firms) in each sector and cell is held constant.

- (3) Monopolistic competition in manufacturing and non‐tradable services sectors:  Firms enter and exit in response to profit opportunities, so that equilibrium profits are zero.  As usual in a Dixit‐Stiglitz setting, this means that equilibrium firm size is constant.

- (4) Labor mobility:  While the total population of each country remains constant, households move between cells in response to changes in relative real per capita income across cells.  We compare zero mobility with a high (but not ‘perfect’) level of mobility.  Population movement has a significant effect on urban land rents, so we also allow land to convert from rural to urban in response to changes in relative urban‐rural rents.

- (5) Localization economies:   Calibration gives sector‐cell specific productivity parameters z�� _._ These are split into two multiplicative elements, the initial calibrated productivity parameter, and a part depending on the ratio of the number of firms in the cell to the base population in the cell. An increase in this ratio raises productivity.  Further details of this and other relationships are given in appendix 2.

# 3. **Data**

The Belt and Road Initiative (BRI) aims to better connect China to the rest of Asia, Europe and Africa through the development of six major transport corridors. Our focus is on the impact of potential rail investments and of reductions in the time taken to cross borders in an area of Central Asia that spans the seven countries indicated in Figure 1. Each of these countries except Turkmenistan contains multiple cells, and these are listed in appendix 1. The model is calibrated to data on employment, population, land area, national accounts and trade. It also uses a network of current transport times and their projected changes. We discuss each of these sources of data in turn.

**_Employment:_** Employment data were gathered on a country by country level. For China, the data for the three Western cells, Gansu, Xinjiang, and Qinghai, come from the National Bureau of Statistics in China, http://www.stats.gov.cn.  For Kazakhstan, the data come from the Agency of Statistics of the Republic of Kazakhstan http://stat.gov.kz, reported at the sector and province level. In Kyrgyzstan, employment data at the region and sector level are from the National Statistical Committee of the Kyrgyz Republic http://www.stat.kg/en/. In Uzbekistan, the sector and region employment data are from the State Committee of the Republic of Uzbekistan on Statistics, https://www.stat.uz/en/. For all these countries, we select data from 2016. In Tajikistan, regional data are calculated from the Labor Force Survey 2016, Statistics Agency of Tajikistan. In Pakistan, cell and sector data are from the Labor Force Survey 2014‐2015 available from the Pakistan Bureau of Statistics http://www.pbs.gov.pk. In Turkmenistan, data are only available at the national level, broken into sectoral employment http://www.stat.gov.tm/. We therefore only have one location within the country in our analysis.

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