metadata: authors: 0: author: Maliszewska,Maryla
1: author: Van Der Mensbrugghe,Dominique
count: India
docna: 0: docna: The Belt and Road Initiative : Economic,
            Poverty and Environmental Impacts
docty: Policy Research Working Paper
subtopic: International Trade and Trade Rules,Inequality,Transport Services,Food Security,Construction Industry,Common Carriers Industry,Food & Beverage Industry,General Manufacturing,Pulp & Paper Industry,Textiles, Apparel & Leather Industry,Plastics & Rubber Industry,Business Cycles and Stabilization Policies
teratopic: International Economics and Trade,Poverty Reduction,Transport,Agriculture,Industry,Macroeconomics and Economic Growth
abstracts: cdata!: China's Belt and Road Initiative
            aims to improve connectivity between China and more than 70
            countries through infrastructure investment and regional
            cooperation. The initiative has the potential to accelerate
            significantly the rate of economic integration and
            development in the region, as trade costs decline. The goals
            of this paper are to (i) study the impacts of infrastructure
            improvements on Belt and Road Initiative and non–Belt and
            Road Initiative countries' trade flows, growth, and
            poverty; and (ii) suggest policies that would help maximize
            gains from the Belt and Road Initiative–induced trade cost
            declines. The analysis captures the trade costs reductions
            as a result of infrastructure improvements. The findings
            indicate that the Belt and Road Initiative would be largely
            beneficial. First, global income increases by 0.7 percent
            (in 2030 relative to the baseline). This translates into
            almost half a trillion dollars in 2014 prices and market
            exchange rates. The Belt and Road Initiative area captures
            82 percent of the gain, with the largest percent gains in
            East Asia. Second, globally, the Belt and Road Initiative
            could contribute to lifting 7.6 million people from extreme
            poverty and 32 million from moderate poverty. Third, the
            initiative would lead to a modest increase in global carbon
            dioxide emissions, with a complex set of positive and
            negative outcomes at the national level for other types of emissions.
geo_reg_key: 517198,517191,517212
repnme: repnme: The Belt and Road Initiative : Economic,
            Poverty and Environmental Impacts
display_title: The Belt and Road Initiative :
            Economic, Poverty and Environmental Impacts
listing_relative_url: /research/2019/04/30974802/belt-road-initiative-economic-poverty-environmental-impacts
topicv3: Agriculture and Food Security m1326205 435,Manufacturing Sectors m1326521 1281,Transport m1326661 135,Poverty m1326687 695,Trade m1326924 698
publishtoextweb_dt: 2019-04-10T00:00:00Z
historic_topic: International Economics and Trade,Poverty Reduction,Transport,Agriculture,Industry,Macroeconomics and Economic Growth
no_of_pages: 69
author_keys: 0: author_key: 545393
1: author_key: 428604
model_extractions: Policy Research Working Paper 8814

# The Belt and Road Initiative Economic, Poverty and Environmental Impacts

_Maryla Maliszewska Dominique van der Mensbrugghe_ Macroeconomics, Trade and Investment Global Practice April 2019
Policy Research Working Paper 8814

# **Abstract**

China’s Belt and Road Initiative aims to improve connectivity between China and more than 70 countries through infrastructure investment and regional cooperation. The initiative has the potential to accelerate significantly the rate of economic integration and development in the region, as trade costs decline. The goals of this paper are to (i) study the impacts of infrastructure improvements on Belt and Road Initiative and non–Belt and Road Initiative countries’ trade flows, growth, and poverty; and (ii) suggest policies that would help maximize gains from the Belt and Road Initiative–induced trade cost declines. The analysis captures the trade costs reductions as a result of infrastructure improvements. The findings indicate that the Belt and Road Initiative would be largely beneficial. First, global income increases by 0.7 percent (in 2030 relative to the baseline). This translates into almost half a trillion dollars in 2014 prices and market exchange rates. The Belt and Road Initiative area captures 82 percent of the gain, with the largest percent gains in East Asia. Second, globally, the Belt and Road Initiative could contribute to lifting 7.6 million people from extreme poverty and 32 million from moderate poverty. Third, the initiative would lead to a modest increase in global carbon dioxide emissions, with a complex set of positive and negative outcomes at the national level for other types of emissions.

This paper is a product of the Macroeconomics, Trade and Investment Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/research. The authors may be contacted at mmaliszewska@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **The Belt and Road Initiative: Economic, Poverty and Environmental Impacts**

Maryla Maliszewska<sup>1</sup> and Dominique van der Mensbrugghe<sup>2</sup> JEL: F14, F15, C68, Q56, I32, R41.

Keywords: Belt and Road Initiative, Computable General Equilibrium, Poverty, Environment and Trade.

> 1 Macroeconomics, Trade & Investment, The World Bank Group, 1818 H Street NW, Washington DC 20433 (mmaliszewska@worldbank.org). We are grateful to Michele Ruta and Gladys Lopez-Acevedo for comments and suggestions and to Maria Pereira for excellent research assistance. The poverty estimates under section 4.1 have been provided by Israel Osorio-Rodarte and Rakesh Ramasubbaiah.

> 2The Center for Global Trade Analysis (GTAP), Department of Agricultural Economics, Purdue University, West Lafayette, IN 47906 (vandermd@Purdue.edu).
# **Table of contents**

|**1.**<br>**INTRODUCTION .............................................................................................................................................. 3**|
|---|
|**2.**<br>**BRI-INDUCED TRADE COSTS REDUCTIONS .......................................................................................... 4**|
|**3.**<br>**MACRO RESULTS ........................................................................................................................................... 7**|
|**4.**<br>**SOCIAL COSTS/BENEFITS OF THE BRI .................................................................................................... 9**|
|4.1.<br>FACTOR REWARDS,LABOR DISPLACEMENT AND POVERTY IMPLICATIONS................................................... 9<br>4.2.<br>EMISSIONS IMPLICATIONS......................................................................................................................... 11|
|**5.**<br>**BRI IMPACTS ON SELECTED COUNTRIES ........................................................................................... 14**|
|**6.**<br>**IMPACT OF COMPLEMENTARY POLICIES .......................................................................................... 16**|
|**7.**<br>**SENSITIVITY ANALYSIS ............................................................................................................................. 18**|
|**8.**<br>**CONCLUSIONS AND POLICY RECOMMENDATIONS ......................................................................... 19**|
|**TABLES ..................................................................................................................................................................... 22**|
|**ANNEX A: SUMMARY DESCRIPTION OF THE ENVISAGE MODEL AND THE MODEL DIMENSIONS**<br>**..................................................................................................................................................................................... 59**|

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# **1. Introduction**

The Belt and Road Initiative (BRI) or One Belt One Road (OBOR) initiative was announced in the Fall of 2013 by President Xi Jinping of the People’s Republic of China (PRC). The President invoked the ancient Silk Road announcing the plans to bring Asia, Europe, Africa, and the Middle East closer together by constructing investment and trade networks and creating new institutional linkages. The BRI could promote trade, more efficient resource reallocation and strengthen economic growth across the region. It could also encourage countries to coordinate economic policy and improve regional collaboration. The goals of our analysis are to i) study the impacts of infrastructure improvements on BRI and non-BRI countries’ trade flows, growth and poverty; and ii) suggest policies that would help maximize gains from the BRI-induced trade cost declines.

To our best knowledge, there are only a few CGE-based studies on the impacts of the BRI. Fan Zhai (2017) uses estimates of elasticity of trade costs with respect to quality of infrastructure and per capita income to estimate the future reductions of trade costs due to BRI. He applies those estimates in a dynamic global CGE model and finds that BRI might bring important benefits to its members and beyond. With moderate assumptions on BRI investment, the simulation results indicate a global welfare gain of 1.3% of global GDP by 2030 with a boost to global trade by 5%. The vast majority of gains applies to BRI countries. Villafuerte, Corong, and Zhuang (2016) assume that BRI leads to a 25% reduction in road transport margins and 5% in sea transport margins, as well as a significant reduction in time to import by BRI countries due to the accompanying trade facilitation measures. The authors estimate that BRI GDP growth rates could increase by 0.1-0.7 percentage points, while total exports of BRI countries could increase by between $5 billion and $135 billion depending on the assumptions on trade costs reductions.

Our analysis adds value to the existing research by incorporating the impacts of BRI-related infrastructure improvements based on bilateral trade time reductions from de Soyres et. al. (2018). In addition, while the CGE analysis provides impacts on several economic variables (e.g. trade, employment, economic growth), we also study the impacts on poverty and greenhouse gas emissions. We also assess the role of trade policy reforms in maximizing the gains from BRIinduced infrastructure improvements.

We use the data on “value of time” from de Soyres et. al. (2018), which is based on Hummels and Schaur (2013) original estimates updated with trade flows from 2014. In our BRI simulations, the value of time in trade is adjusted based on the GIS estimates of the impacts of BRI projects on shipment time based on Baniya et. al. (2018). More details on these estimates are provided below.

The findings of this paper rely on the Envisage Model—a global, recursive dynamic computable general equilibrium model. The Envisage Model was initially developed at the World Bank, which continues to use it, though the core development team is now situated in the Center for Global Trade Analysis (GTAP) at Purdue University. More details on the model, the underlying database and the regional and sector dimensions, and the baseline assumptions for this study are provided in Annex A.

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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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The baseline scenario assumes the continuation of past trends with no decline in trade costs, the details are presented in Annex A along with the population and GDP data in Tables 1-3. In the counterfactual scenarios we study the impacts of the BRI-induced trade cost reductions. We apply the lower bound estimates of trade cost reductions due to BRI-related infrastructure improvements from de Soyres et. al. (2018) to generate the low case scenario (BRILBD). The upper bound estimates allow for switching across transport modes leading to deeper reduction of trade costs and form our high case scenario (BRIUBD). Further gains could be realized if in addition to improving the transport infrastructure, the trade facilitation reforms would lead to halving of border delays for BRI countries (BRIUBBD). Finally, we augment the last scenario with two variants of complementary policies where BRI countries implement a 50% reduction of tariffs in trade with each other (BRIUBBTD) or reduce their tariffs in trade with all trading partners (BRIUBBTPD). The scenarios are summarized below:

|**Code**|**Description**|
|---|---|
|`BRILBD`|BRI lowerbound estimates|
|`BRIUBD`|BRIupperbound estimates|
|`BRIUBBD`|BRIUBBD andreduced borderdelays|
|`BRIUBBTD`|BRIUBBDandtariff reductionapplied ona preferentialbasis amongBRIcountries|
|`BRIUBBTPD`|BRIUBBD andtariff reduction applied on a MFNbasis byBRIcountries|

Table 4 summarizes the shocks for the regions in the BRI area. The shock occurs in two time periods. One-half of the shock is assumed by 2025, and the remainder by 2030. The fourth and last simulation involves tariff reductions applied on MFN basis. Figure 1 displays the trade weighted aggregated across sectors bilateral trade costs reductions on exports originating from countries on the left-hand side of figure in our central scenario (BRIUBD). Most of BRI-induced bilateral trade costs reductions are below 10%, but several exporters experience higher trade costs reductions to most destinations. Those biggest cost reductions on trade costs of exporting are expected in Kyrgyz Republic, Kazakhstan, Ethiopia, the Lao People’s Democratic Republic and Cambodia. We would expect those countries to be the biggest beneficiaries of the BRI. The full bilateral data set of trade costs reductions is presented in Table 4.

When analyzing the bilateral trade costs reductions by using the example of imports by China, we note that the differences across sectors of economic activity are very small, but systematically vary by the source of exports. Again, South Asia experiences the biggest trade cost reductions, while countries that are not part of the BRI such as the United States or Latin American and Caribbean countries (LAC) register very small gains (less than 1%) from better maritime connectivity of China with other regions.

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12 Figure 1 Average import weighted trade cost reductions as a result of BRI investments under upper bound BRI related infrastructure investment scenario BRIUBD (percentages).

# Bilateral Trade Costs Reduction

<!-- Start of picture text --> Kyrgyz Republic<br>Thailand<br>Tanzania<br>Malaysia<br>Ethiopia<br>Cambodia<br>Kenya<br>Iran<br>China<br>Laos<br>Pakistan<br>Turkey<br>USA<br>Rest of East Asia<br>Kazakhstan<br>Vietnam<br>Rest of South Asia<br>Rest of Central Asia<br>Indonesia<br>India<br>Philippines<br>Rest of High-inc.<br>Rest of E. Europe<br>Rest of MENA<br>Bangladesh<br>Rest of W. Eur.<br>Russia<br>Sri Lanka<br>Egypt<br>Lat. Am. & Car.<br>Nepal<br>Rest of SSA<br>EU ECA<br>Poland<br>Non BRI<br>BRI<br>World<br>0 2 4 6 8 10<br>BRI Non BRI<br><!-- End of picture text --> _Source: de Soyres et. al. (2018)._ BRI-related infrastructure investments will naturally also reduce the costs of trading inside the countries. The estimated ad valorem equivalents of internal trade costs reductions from de Soyres et. al. (2018) are applied to input-output coefficients of trade services and all transport services. The domestic trade cost reductions range from Poland with a trade cost reduction of 0.9% for BRI countries and of 0.2% for non-BRI countries, to Kyrgyz Republic, the country that has the highest trade cost reductions, with reductions of 10.2% for BRI countries and 5.9% for non-BRI countries. To capture improvements in internal logistics and transportation, the diagonal element of the estimated improvements is assumed to apply to the domestic trade and transport services used to produce individual commodities. For example, if the domestic, i.e. diagonal, estimate of improvements in trade and transport is 5%, intermediate demand for the relevant trade and transport commodities in each sector is assumed to decline by 5% relative to output, i.e. the inputoutput coefficient is adjusted downwards by 5%. In the current configuration of the input database,

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the relevant services are trade services (TRD) and the three transport services—air, water and land (ATP, WTP, and OTP).

Under the upper bound infrastructure improvements scenario with the reduction of border delays (BRIUBBD) the global welfare gain increases from 0.7% to 1.1%, while the gain for the BRI area increases from 1.2% to 2%. The impact on the non-BRI region is somewhat negative, as it does not benefit from internal trade cost reductions but suffers from increased trade diversion as domestic inputs become relatively cheaper compared to imports.

# **3. Macro results**

The iceberg trade cost reductions benefit consumers of final (households) and intermediate goods (firms). Trade cost reductions brought about by infrastructure improvements lead to higher quantity of imports being available to importers. With lower trade costs, the price of a unit of imports is less expensive and increases the competitiveness of local production (using imported inputs) either sold on the domestic market or exported. As a result, production shifts to the most competitive sectors, leading to productivity gains and expansion of trade and faster economic growth in the BRI region. The trade cost reductions also apply to trade with non-BRI countries, leading to somewhat faster growth in non-BRI countries too.

Some of the key results are summarized in Table 5-13. Table 5 to 7 highlights the key macroeconomic indicators—real income (as measured by equivalent variation<sup>3</sup> ) and aggregate trade. Our discussion focuses on the upper bound infrastructure improvements scenario (BRIUBD). Summary results include:

- Global real income increases by 0.7 percent (in 2030 relative to the baseline), which in comparative terms is relatively sizeable as upper estimates of the real income impact of global free trade are around 1 percent.<sup>4</sup> This translates to almost 930 billion dollars in 2014 prices and market exchange rates.

- The BRI Area captures 70 percent of the gain, with China garnering around 20 percent of the total global gain. In percentage terms, the largest return accrues to Pakistan with an increase of 10.5 percent in overall real income and Kyrgyz Republic with 10.4 percent. East Asian economies also seeing sizable gains: Thailand (8.2%), Malaysia (7.7%) and Cambodia (5%), and significantly higher than the countries in South and West Asia. Ignoring the potential negative effects of financing BRI-related infrastructure, China would see an increase of 0.7 percent.<sup>5</sup>

- The non-BRI area sees some gains with an increase of 0.3 percent, most of which is captured by Ethiopia,  Europe and Rest of High-Income countries. These latter two regions, though not formally part of the BRI area, are integrated economies with the BRI area.

> 3 This is the expenditure to attain utility in year _t_ in any given simulation using base year prices. It is similar in magnitude to real private consumption.

> 4 The global average change in the value of time is 1.6 percentage points.

> 5 Real income is measured as the equivalent variation for households. We hold government expenditures fixed in real terms and thus there is no welfare impact from this channel. We could include the welfare linked to investment expenditures, but these would not substantially change the results in this scenario.

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- The volume of global exports increases by 1.7 percent (in 2030 relative to the baseline), translating to an increase of some $565 billion (in $2014).

- Most of the increase in exports occurs in the BRI area ($438 billion), which witnesses an increase in exports of some 2.8 percent. The largest increases in exports in percentage terms include Thailand (14.9%), Malaysia (12.4%), and Pakistan (9.8%). Not all BRI regions benefit in terms of trade growth, for example Rest of Eastern Europe sees a negligible increase, ECU (-0.7%), Poland (-0.4%), Nepal (-0.2%) and the Arab Republic of Egypt (-0.2%) see export declines.

- The non-BRI area shows a small increase in terms of exports (0.7%), with Latin America (-0.5%) and Rest of Western Europe with negative values. The highest percentage growth in exports in the Non-BRI Area is Ethiopia (3.9%).

- Import growth is higher than export growth, as the iceberg parameter directly benefits import and indirectly export growth through lower cost of imported inputs. At the global level, import growth is 3.4 percent (in 2030 relative to the baseline), evaluating to over $1,153 billion (in $2014 prices).

- Thailand (21.4%), Malaysia (18.5%) and Kyrgyz Republic (17.5%) witness the highest import growth. There are modest declines for ECU, but sizeable increases for Pakistan, Turkey and the Islamic Republic of Iran.

- The United States, and Rest of High-Income countries sees the bulk of the import increase for the non-BRI area, with negligible gains for Latin America.

Table 8a and 8b provide the detailed changes in export volumes in both percentage and level terms (relative to the baseline in 2030). The key findings include: Agricultural exports by the BRI area increase by 2 percent. China sees a large decrease in the exports of coal (-9.4%), but with gas increasing (3.5%), albeit from a relatively low base. The results for the other regions within the BRI area are variegated—depending on the source of the reduction in value of the time of trade and relative comparative advantage. Most of the large movements occur in manufacturing and extraction exports, though with some exceptional changes in agriculture in some cases. Lao PDR stands out as a country that would see a significant boom in a number of sectors—particularly in the extractive sectors and metal products. Another big beneficiary would be leather goods exports from the Kyrgyz Republic, increasing by over 150 percent.

- Export growth for the non-BRI regions has a negligible increase of 0.7%, with most of the dollar gains occurring in agriculture and wood products. The United States nonetheless sees a significant gain in electronics exports (14.9%).

As highlighted earlier, import changes in 2030 outstrip export changes. Table 9a and 9b show the corresponding figures for import changes (relative to the baseline in 2030):

- For the BRI area in aggregate, import growth is growing across all activities. Sectors with high import growth include electronics, construction, agriculture, and petroleum. Countries with high manufacturing import growth include Thailand and China. There are individual sectors experiencing big gains such as wood products imports by Pakistan (48.3%).

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- For the non-BRI area, the impact on import demand is also positive—overall of a growth of 2 percent, with most sectors expanding in terms of imports. Latin America and Rest of the Western Europe have the lowest growth rates.

Tables 10a and 10b unpack the macroeconomic results by looking at the detailed changes in value added—Table 10a in percentage terms relative to the baseline, and Table 10b in volume terms (at $2014 prices). A few summary findings:

- The BRI area sees an overall gain of $73 billion. Gains accrue to manufacturing (mostly textiles), followed by agriculture sectors, with a small gain in electricity and losses in extraction.<sup>6</sup> The largest increase in value added in level terms are in agriculture and processed foods.

- The largest percentage gains are in Malaysia and Thailand.

- The non-BRI area has imperceptible changes to value added in aggregate with negligible gains in agriculture (with notable gains in Ethiopia and the United States) and notable losses in electronics.

# **4. Social costs/benefits of the BRI**

## **_4.1. Factor rewards, labor displacement and poverty implications_**

BRI related investments are expected to lead to an increase of returns to factors with workers being relatively better off than capital and land owners. Table 11 provides some insights to the distributional impacts of the BRI initiative. It shows the change to aggregate real factor returns (deflated by the regional CPI) in 2030 relative to the baseline. For the BRI area in aggregate, the return to labor has a higher increase than the return to capital (including land and natural resources), 1.37% versus 0.87%. Unskilled workers would see a gain (1.36%) and skilled workers a slightly higher gain (1.38%). However, there are wide variations across regions. For example, Lao PDR and Thailand witness a fairly sizeable increase in skilled wages relative to unskilled. Pakistan and Kyrgyz Republic see the opposite. Likewise, the relative gains between labor and capital vary widely across regions. Land returns increase in all BRI regions, especially in Pakistan and Bangladesh and some regions see a decline in returns to natural resources. Kyrgyz Republic is again a significant outlier with returns to natural resources increasing by 13.2%. The changes to real factor returns tend to be smaller for the non-BRI area.

The impact of the BRI investments on labor displacement would be moderate. Table 12 reflects a measure of the potential net displacement of workers beyond what would be expected in the baseline in 2030 (in thousands). For the BRI area, total displacement is some 12 million workers, or 0.48 percent of the baseline labor force.<sup>7</sup> This is a relatively small amount, particularly as we assume that there is a transitional phase for the initiative. The EAP region is expected to lose

> 6 Aggregate definitions are: Agriculture (Agriculture), Services (Electricity, Construction, Trade services, Other, Water and Air transport, Hospitality services, Other business services and other services), Other (Minerals, oil, gas, and coal extraction). Manufacturing includes all other sectors.

> 7 Gross displacement is zero as the model assumes fixed employment. The displacement is measured as the sum across all sectors where employment increases. It is equal to the sum across all sectors where employment decreases.

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agricultural employment of about 0.8 million, while South Asia would gain over 4 million workers in the agricultural sector. Overall as a result of the BRI infrastructure investments the largest share of labor force of 0.9 percent is expected to switch jobs in EAP, followed by the SSA and MENA region where about 0.6 and 0.5 percent of labor force respectively would switch jobs. The BRI area could see a net loss of almost 0.8 million agricultural workers (in 2030 relative to the baseline). The majority of this would be in China, though many other regions would see agricultural employment losses as well such as Malaysia and Thailand. Bangladesh, Pakistan and India would see some significant increases in agricultural employment, as would Kenya and Tanzania. The displacement effect is significantly lower in the non BRI area.

While impacts would vary by countries, income gains under the BRI scenario would lift several million people from poverty relative to the baseline scenario.<sup>8</sup> There will be winners and losers in the short run, but if BRI investments materialize the poor in both BRI and non-BRI countries would likely experience welfare gains. To evaluate the effect on poverty<sup>9</sup> in countries that are likely to be the most affected, i.e. low and middle-income countries, the use of extreme and moderate international poverty lines at PPP$1.90 and PPP$3.20 a day are preferred.<sup>10</sup> Globally, BRI related investments could lift 7.6 million from extreme poverty and 32 million from moderate poverty. Developing countries in the BRI will benefit the most from the reductions in extreme poverty of 4.3 million and moderate poverty of 26.7 million.

In countries like Kenya and Tanzania, an additional 0.7 million poor people would be expected to be lifted from extreme poverty, at PPP$1.90 a day. This is approximately equivalent to an additional 1.0 and 0.9 percentage points reduction in the extreme poverty headcount rate. In South Asia, Pakistan would see some significant additional reductions in extreme poverty with 1.1 million people being lifted compared to the baseline. Bangladesh and India are expected to see a smaller number of people lifted out of poverty i.e. 0.2 million (0.11 percent of headcount) and 0.03 million (0.002 percent of headcount), respectively. In Nepal, the scenario with BRI infrastructure investment alone lifts an additional 60 thousand people out of extreme poverty compared to the baseline. In East Asia and Pacific, Philippines expects to see approximately 90 thousand people lifted out of extreme poverty compared to the baseline.<sup>11</sup>

> 8 In 2015, the World Bank estimated that 53.69 percent of the population in developing countries lived with less than PPP$5.50 a day – or 3,369 million. The baseline scenario, which contemplates a continuation of current demographic and economic trends, projects a reduction of 5.91 percentage points in the poverty headcount at PPP$5.50 a day by 2019 and an additional reduction of 12.64 percentage points by 2030.

> 9 Poverty estimates were obtained by linking results of a CGE model with a simple global microeconomic model. The initial global distribution of per capita consumption/income is based on PovcalNet data. Country-specific growth rates in domestic absorption per capita (real household consumption per capita) from the macro CGE are fully transmitted to household data assuming distribution-neutrality. To calculate the number of poor, the total population in each country is adjusted using United Nations population projections. This is based on the 158 countries in the BRI study that were mapped to the poverty estimates of the 163 countries found in the PovcalNet.

> 10 The World Bank now reports international poverty lines that are more closely related with national poverty standards. These poverty lines are set at $1.90, $3.20, $5.50, and $21.70 a day (in 2011 purchasing power parity (PPP)) for low-, lower-middle, upper-middle, and high-income countries, respectively.

> 11 Detailed country specific results are available from the authors upon request.

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# **_4.2. Emissions implications_**

Finally, the impact on emissions would be modest. Table 13 highlights the potential impact on emissions—both greenhouse gases and those more associated with local pollutants and concomitant health impacts. The Envisage model tracks the emissions of 14 gases.<sup>12</sup> Four are socalled greenhouse gases (GHGs),<sup>13</sup> that are most linked with radiative forcing and global warming. The remaining 10 are mostly local pollutants with potentially significant health effects—but can also interact with the GHGs and have an impact on climate change. For example, sulfur dioxide in the atmosphere lowers radiative forcing and thus acts to cool the atmosphere. In Envisage, carbon dioxide (CO2) emissions emanate exclusively from the combustion of fossil fuels—thus the model does not track changes from land-use changes (e.g. deforestation), or process emissions (e.g. from cement manufacturing). The remaining 13 gases are generated from three sources: 1) intermediate and final demand for goods and services; 2) factor use (e.g. land in rice production, or herds in livestock); and 3) output (such as methane emissions from landfills).

The change in the pattern of emissions generated by the BRI scenarios will reflect a complex constellation of factors—that can be broken into scale effects (e.g. change in GDP), technique effects (e.g. changes in input mix), and composition effects (e.g. changes in the structure of output within and across countries). Technique effects are likely to remain small as there are no explicit policies that are targeting emissions, i.e. the only changes in relative prices are coming from the trade policy changes including those linked to BRI. Moreover, most inputs are assumed to be consumed in fixed quantities. All else equal, the scale effects should line up with increases in GDP on a country basis. The composition effects are likely to be large as policies engendered by BRI lead to changing comparative advantage with significant changes in both the internal and external composition of output. These are not necessarily easy to trace in a modeled economy with many sectors and countries. If production moves to relatively ‘clean’ sectors and countries, the composition effects may counteract the scale effects, or vice versa.

Figure 2 provides an overall picture for the changes in emissions at the global level from the BRIUB scenario. GDP growth is some 0.12%, thus this scenario suggests that for most gases, the composition effect dominates the scale effect. There are some notable exceptions—F-gases, NMVB, and SO2. F-gases are linked in particular to electronics manufacturing, thus this suggests that re-allocation of electronics manufacturing would lead to somewhat cleaner production. SO2 is often related to coal-based electricity production. A decline in SO2 would bring some health benefits.

> 12 Emissions covered in Envisage include: Greenhouse gases: Carbon dioxide (CO2), Nitrous oxide (N2O), Methane (CH4), F-gases (HFCs, PFCs, SF6, NF3) and Other gases: Black carbon (BC), Carbon monoxide (CO), Ammonia (NH3), Non-methane volatile organic compounds short carbon cycle (NMVB), Non-methane volatile organic compounds long carbon cycle (NMVF), Nitrogen oxides (NOx), Organic Carbon (OC), Particulate matter 10 (PM10), Particulate matter 2.5 (PM2.5) and Sulfur dioxide (SO2). 13  Also referred to at times as the Kyoto gases as they were targeted in the Kyoto Protocol Agreement, signed in 1997.

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Figure 2. Change in global emissions under BRI investment scenario (BRIUBD) by 2030 (percentages).

<!-- Start of picture text --> BRI Infrastructure: change in global emissions in 2030 wrt to the<br>baseline (percent)<br>1.5<br>1.0<br>0.5<br>0.0<br>-0.5<br>-1.0<br>-1.5<br>-2.0<br>CO2 N2O CH4 F-GAS BC CO NH3 NMVB NMVF NOx OC PM 10 PM 2.5 SO2<br><!-- End of picture text --> Figure 3. Change in carbon emissions in 2030 with respect to Baseline under BRI related infrastructure investment scenario BRIUBD (percentages).

<!-- Start of picture text --> Percent change in carbon emissions in 2030 wrt to<br>Baseline<br>20.00<br>18.00<br>16.00<br>14.00<br>12.00<br>10.00<br>8.00<br>6.00<br>4.00<br>2.00<br>0.00<br>-2.00<br>NPL EGY CHN XSS IND LAC ECU POL KAZ USA E_U xbr IDN wld bri PHL EEU XHY XEA XCS RUS XMN ETH XSA VNM LKA KEN TUR TZA IRN THA MYS BGD KGZ PAK LAO KHM<br><!-- End of picture text --> The impact on CO2 emissions is negligible in aggregate with an increase of 0.5%. The BRI region itself sees an increase of 0.6%, but with China showing no change. There is considerable heterogeneity across countries and regions as highlighted in Figure 3. The reasons vary. In the case of Cambodia, there is a very large increase in output in all three transport sectors. On the other hand, Lao PDR sees a more modest increase in transport, around 5%, and relatively significant

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increases in the output of leather goods, chemicals, rubber and plastics, and fabricated metal products. Kyrgyz is more similar to Cambodia, with large increases in the transport sector. China, on the other end of the spectrum sees modest output declines in a number of sectors including air transport, chemicals, rubber and plastics, and pulp and paper.

Methane and nitrous oxide emissions also rise, respectively 0.7 and 0.9 percent—these are more closely identified with agriculture. There is a sizeable decline in the emissions of fluoridated gases, some 1.8 percent globally—perhaps linked to a re-allocation of electronics manufacturing towards less emitting regions such as ECU (-4.6%) and Thailand (-3.1%). The growth of global nongreenhouse gas emissions various across gases with some barely growing at all (NMVB) and others increasing by 1.2 percent (organic carbon). At the other end of the spectrum is sulfur dioxide (SO2) with a decrease of 0.3 percent. The results vary widely across regions, largely a reflection of the structural changes each region witnesses as a consequence of the BRI initiative. Just as an example, Lao PDR could see a large rise in some local pollutants such as NMVF (24.4%) and CO2 (7.7%), with potential deleterious effects on air quality and health.

Figure 4 highlights the sources of increase and decline in emissions for methane for the BRI region as a whole. Methane emissions rise by 0.6% for the region as a whole—more or less in line with GDP growth. The main source of methane emission growth is in intermediate use in transportation sectors (ATP, WTP), intermediate use in other manufacturing (XMN), processed foods (PFD), leather (LEA), and output growth in chemicals, rubber and plastics (CRP). Note that household demand is also a relatively large contributor. The large negative contributions are linked to fossil fuels—intermediate use in coal mining, oil extraction, electricity generation and coal production with other significant contributions in energy intensive manufacturing (KE5), pulp and paper (PPP) and petroleum and coal products (P_C). The other transport (OTP) is an interesting case as this is the only transport where output related emissions decline significantly. The reduction of internal trade costs driven by infrastructure improvements is improving productivity of this sector, resulting in smaller output of that sector.

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<!-- Start of picture text --> 10_COA xp_OTP<br>xp_COA 10. TRD<br>oeEL<br>= xp_KES<br>10_OIL 1O_KE5 1O_PPP a<br><!-- End of picture text --> <!-- Start of picture text -->
|IO_XMN |O_PFD 1O_ATP<br>lO_hhd | 10_AGR | 10_OME | fp_AGR<br>1O_LEA<br>xp_P_C | xplGAS | 10_ELE<br>Woe<br>xp_CRP<br>=<br>10 TRQ. | IOLONS<br>10_XSV<br>|O_WAP |O_WTP 1O5TEX | |O_OMN xp_AGR<br><!-- End of picture text -->
Lower costs of imported inputs and higher demand from abroad lead to expansion of exports of Pakistan in several sectors (Table 8b). The highest increases are recorded in chemicals, rubber and plastics, processed foods and other manufacturing, which consequently contributes to the highest rates of output growth in these sectors (Table 10b). On the other hand, the sectors that show the highest reductions in exports include agriculture and leather goods.

Kyrgyz Republic is the BRI country that has the second highest percentage welfare gains, with 10.4% by 2030 (relate to baseline), however it is one the lowest in absolute values, with only 1.3 billion dollars increase (in 2014 prices). Thanks to the gains obtained by the BRI projects that focus on transportation - mostly railway lines and roads, most sectors in the economy benefit from the high trade cost reductions. Kyrgyz Republic imports increase across all sectors, with machinery and equipment, textiles, leather goods and petroleum and coal products showing the highest increases. Agriculture records a sharp reduction in both exports and domestic products, creating a significant increase of agricultural imports. In terms of exports, Kyrgyz Republic sees an increase in the sectors of leather goods, coal, and machinery and equipment, as well as exports of trade services and other transport driving the expansion of output in those sectors. Gas and metal products show the highest reductions in output.

Lao PDR is expected to record a welfare gain amounting to 3.1% by 2030 (relative to the baseline). This is directly linked to the high level of trade cost reductions due to infrastructure improvements (see Table 4). These important gains will be associated with a faster access to the sea therefore benefiting trade with partner countries that can be reached through maritime connections. Among the projects that impact Lao PDR, the BRI related investments cover the new rail link from Vientiane to the Bangkok port in Thailand, but also the improvement of the Sihanoukville port in Cambodia while all the rail improvements in Vietnam also play a role. In addition, Kra canal in Thailand is particularly beneficial for all sea shipments going west – this will prevent ships from taking a long detour. The biggest decline of trade cost on imports is expected in sectors such as construction, trade services, paper products and, coal. These sectors also experience the increase of imports, but the biggest volume increases are recorded in machinery and equipment, chemicals, rubber and plastics and processed foods.

The largest increases in the volume of exports of Lao PDR are recorded in chemicals, rubber and plastics as well as in energy intensive manufacturing. On the other hand, the exports of agriculture, wearing apparel and processed foods show the highest decreases. Lower exports also drive output of these sectors to decline. Overall, Lao PDR output seems to be growing in most sectors, with trade services, other transport and hospitality services gaining the most value.

Ethiopia is not on our list of BRI countries, yet it is also expected to reap significant benefits from the reduction of trade costs and border cost delays among the BRI countries. The expected welfare gain amounts to 1.9% by 2030 (relative to the baseline). The biggest decline of trade costs on imports applies to Kyrgyz Republic, Kazakhstan, Cambodia and other countries in both East and South Asia and apply to coal, electricity and machinery and equipment. Faster increase of imports (relative to the baseline) applies mostly to metal products, and machinery and equipment and transport equipment.

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Ethiopia is expected to increase its exports of agricultural products, leather goods and energy intensive manufacturing. The business and hospitality services and metal products show a reduction in exports. The trade changes impact output generating significant expansion of output in agriculture, processed foods, leather goods and selected services sectors. Several other sectors exhibit a decrease of output, as resources are redirected to most profitable sectors. This applies to paper products, energy intensive manufacturing and metal products. The structure of the economy seems to move towards the primary sector – agriculture, with manufacturing growing only slightly and services experiencing a decline.

Finally, China also benefits significantly from the BRI-induced trade cost reductions. The welfare gain amounts to 0.7 % by 2030 (relative to the baseline). The sectors experiencing the largest trade cost reductions include petroleum and coal products, and water, air and other transport sectors. Imports of several products increase much more than in the baseline including electronics, chemicals, rubber and plastics, with agricultural goods experiencing the biggest increase in volume of imports.

On the other hand, China shows a much higher increase of exports of electronics, machinery and equipment and chemicals. Since there is a small reduction of output of agriculture and to accommodate its growth of exports, China will meet the increased external demand by increasing imports of this sector. Other sectors with high reductions of output are coal, oil, air transport and electronics. Sectors that show the highest increases in output are wearing apparel, metal products and machinery and equipment. The BRI induced trade cost reductions contribute to restructuring of Chinese output away from agriculture towards services with some positive impacts on manufacturing.

# **6. Impact of complementary policies**

In order to maximize the benefits from the BRI related infrastructure investments, countries can undertake additional trade policy and trade facilitation reforms. We analyze a couple of scenarios where in addition to the upper bound infrastructure investments, BRI countries implement trade facilitation measures that halve the border cost delays (BRIUBBD) and then in addition also halve tariffs on imports from BRI partners (BRIUBBTD) or on an MFN basis (BRIUBBTPD). The complementary reforms reduce the price of imports even further and improve market access for exporters. The reforms lower prices for final consumers resulting in welfare gains, as well as producers increasing their competitiveness, generating export growth and income gains.

The reduction of border delays brings about significant welfare gains (Table 5). At the global level the welfare gains reach 1.1 percent, while in the BRI area welfare gains increase to 2 percent as compared to 1.2 percent under infrastructure investment alone (as compared to the baseline in 2030). This translates into additional $400 billion for the BRI region as a whole. The additional gains are biggest for countries with significant border delays in the baseline. The welfare gains for Nepal, for Kazakhstan and Kyrgyz Republic are higher by over 10 percentage points. Significant benefits are also recorded by Cambodia, Lao PDR and rest of Central Asia. The non-BRI countries also do slightly better under this scenario with gains increasing from 0.3 to 0.4 percent for the region, while Ethiopia’s welfare gains almost triple to 6 percent relative to the baseline.

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The tariff reductions generate a further boost to trade and enhance welfare gains. However, with the tariffs at a low level already (average trade weighted tariff in BRI countries (vis-à-vis all trading partners) amounts to 3.1%, while for the non-BRI members it amounts to 1.4%), the additional gains are relatively small. Even though at the global level the gains are only slightly higher by $60 billion and $110 billion under preferential and multilateral tariff reductions, some countries experience significant benefits. With multilateral tariff liberalization the global gains are somewhat higher, driven by the higher gains recorded by the non-BRI countries. Under the preferential tariff reduction, the BRI welfare gains increase from 2.0 percent to 2.1 percent (or about $70 billion) by 2030, while the non-BRI countries suffer negligible welfare losses from trade diversion. Although overall gains are small, selected countries with initially relatively high tariffs benefit from own liberalization and better access to BRI countries including the Islamic Republic of Iran, Turkey, Tanzania, Malaysia and Thailand.

With the reduction of border cost delays (BRIUBBD) the structural change in the BRI area would be somewhat faster with overall net loss of agricultural employment of 0.9 million workers (in 2030 relative to the baseline) and agricultural employment gain of 5 million workers (Table 12). Overall, in the BRI area over 15 million would be changing their sector of employment, which amounts to a relatively low share of total labor force at 0.6 percent. Central Asia is the only region where labor displacement reaches relatively high share of total labor force at 2.6 percent. This is mostly driven by very high border delays in the baseline, reduction of which brings sizeable benefits to the region, but also stronger sectoral reallocation of workers. Some other countries also experience significant labor displacement, for example in Bangladesh over 5 percent of the labor force would be expected to switch sector of employment, while in Lao PDR, Malaysia and Pakistan this share reaches over 2 percent of the labor force. Compared to the scenario with infrastructure investment alone the additional labor displacement mostly affects Kazakhstan and Kyrgyz Republic with the additional impact of over 3 percent of the labor force, and to a smaller extent also Nepal and Lao PDR. The displacement of labor in the non-BRI area would affect about 2 million workers as compared to the labor displacement in the baseline in 2030.

The preferential reduction of tariffs within the BRI area brings about structural change in the regions where the initial tariffs are the highest i.e. MENA and SSA. An additional 0.14 and 0.33 percent of the labor force would switch sector of employment in 2030 compared to the scenario with infrastructure improvements and reduction of border cost delays. Overall in the BRI region over 17 million of workers or 0.7 percent of the labor force would switch the sector of employment, while about 3 million workers are expected to switch sector of employment in the non-BRI region. The net effect of tariff reductions on displacement is relatively small, therefore the countries that experienced the biggest displacement under the border cost reduction scenario remain the most affected when the preferential tariff reduction is implemented as well. The countries where tariff reduction makes a significant impact include Nepal, the Islamic Republic of Iran and Kenya with tariff reductions affecting an additional 0.5 percentage point of the labor force.

With the reduction of border cost delays (BRIUBBD) global poverty would be further reduced by an additional 6.5 million and 12.6 million people for the extreme and moderate poverty lines, respectively. Overall in the BRI area over 3.7 million would be lifted from extreme poverty under BRI with reduction in border cost delays, which amounts to a 0.7 percent of the total population by 2030. More than 7.6 million would be lifted from moderate poverty using the same

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assumptions. The preferential reduction of tariffs within the BRI area brings only marginal results in terms of poverty reduction. An additional 0.34 million and 1.7 million people would be lifted from extreme and moderate poverty by 2030 compared to the scenario with infrastructure improvements and reduction of border cost delay, mostly in the BRI area. The net effect of tariff reductions on displacement is relatively small, therefore the countries that experience the lowest poverty reductions under the border cost reduction scenario remain the least affected when the preferential tariff reduction is implemented as well.

# **7. Sensitivity analysis**

One of the key assumptions in our analysis is that the reduction of trade costs will impact domestic trade as much as cross-border trade. The estimates of de Soyres et. al. (2018) focus on maritime and rail transport routes, however in domestic transportation a larger proportion of trade takes place through road transportation. As a result, our assumptions of the internal trade cost reductions could be overestimated. We look at the impacts of the cross-border trade costs reductions alone to estimate the benefits of the BRI related infrastructure investments. Table 14 presents the results of this analysis. The key findings remain unchanged as the world and the BRI region experience welfare gains in the upper bound infrastructure scenario, but the gains are much smaller in line with a much more modest trade cost reduction. However, certain countries would see much smaller gains with no internal trade cost reductions. The most striking examples are Pakistan with gains declining from 10.5 to 0.8 percent, Bangladesh with gains declining from 6.9 to 0.7 percent as well as Malaysia and Thailand with gains declining from 7.7 to 4.6 percent and 8.2 to 5.4 percent respectively.

Further, we test the sensitivity of our findings to the elasticity of substitution between imported goods. The Armington assumption allows for product differentiation between countries of origin. We employ the elasticities typical for the structural model as in de Soyres, Mulabdic and Ruta<sup>14</sup> (2018) allowing for greater substitutability across products and making them more homogenous. Somewhat surprisingly, raising the Armington elasticity lowers the overall gains. In order to understand this better, we developed a model similar in spirit to the 1-2-3 model—a standard single country model with two produced goods (for domestic and export markets) and three prices.<sup>15</sup> We extended the model to include an import supply and an export demand schedules to better represent the endogenous terms of trade in the global model. The impacts of an improvement in the iceberg trade costs depend on five key parameters: the initial trade balance, the share of imports in domestic absorption, the export demand elasticity, the import supply elasticity and the Armington elasticity. Using this simple model, we look at the impacts of varying these key parameters individually and it is the case that raising the Armington elasticity reduces the impact on welfare from improving the iceberg parameter. We also undertook Monte Carlo simulations to assess a

> 14 In this model, the elasticity of trade with respect to trade costs is the dispersion of productivity and is not the elasticity of substitution as in Armington models. If producers of the intermediate good aggregate are restricted to purchase goods from the same source, regardless of the change in trade costs, then the trade elasticity will be given by the elasticity of substitution as in Armington models.

> 15  See Deverajan et al. 1990.

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broad range of (independent) draws<sup>16</sup> of these five key parameters and the results also show a negative relationship between the Armington elasticity and utility.<sup>17</sup> There are several reasons why the results might differ from (de Soyres, Mulabdic and Ruta, 2018). The results from the two models provide a range of the potential effects of the BRI. The results from the CGE model exercise abstract from some features that are known to have additional multiplier effects when lowering trade costs: (1) pro-productivity impacts from technology embodied in the imports of intermediate goods; and (2) potential employment effects from relaxing the assumption of a fixed labor supply. Both of these could be explored in future work to more fully scope the range of the potential effects. Beyond this, the two models also have specification differences that are likely to drive the results. Notably, the ‘structural’ model makes an assumption of Cobb-Douglas technology across intermediate goods (domestic and imported) and between intermediate goods and labor. With rare exceptions, most CGE models assume a Leontief specification. The former thus has strict complementarity across inputs with a technology shock (i.e. the BRI), but not the latter.

# **8. Conclusions and policy recommendations**

Our findings indicate that the BRI would be largely beneficial, but some countries outside the initiative could suffer from trade diversion. As a result of the BRI, global real income increases by 0.7 percent (in 2030 relative to the baseline), which in comparative terms is relatively sizeable as upper estimates of the real income impact of global free trade are around 1 percent. This translates to almost half a trillion dollars in 2014 prices and market exchange rates. The BRI Area captures 82 percent of the gain, with China garnering 36 percent of the total global gain. In percentage terms, the largest return accrues to the East Asia regional aggregate seeing an increase of 2.2 percent in overall real income. The non-BRI area sees some gains with an increase of 0.2 percent, most of which is captured by the European Union and the Rest of high-income region (which is dominated by the high-income economies of East Asia). These latter two regions, though not formally part of the BRI area, are the most integrated economies with the BRI area. There are minor losses for the regions in the Western Hemisphere.

BRI related investments can contribute to lifting 8.7 million people from extreme poverty and 34 million from moderate poverty at the global level. Under baseline conditions, the percentage of people living in extreme poverty, with less than PPP$1.90 a day, is projected to decline from 10.1 percent in 2015 to 5.2 percent by 2030. With infrastructure investments the BRI can additionally lift from extreme poverty up to 8.7 million people. These benefits extend to both BRI and nonBRI countries: 5.1 million from BRI area and 3.7 million from non-BRI countries.

Our estimates indicate that as a result of BRI related trade cost reductions changes in volume and structure of economic activity would have negligible impacts on CO2 emissions with an aggregate increase of 0.5% at a global level. The BRI region itself sees an increase of 0.6%, but with China showing no change. There is considerable heterogeneity across countries and regions.

> 16  Based on 20,000 draws.

> 17  A description of the extended 1-2-3 model and the results are available from the authors.

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Our study points to the importance of complementary policies such as the reduction of border delays and further tariff liberalization. Reducing the border delays within the BRI region by half brings about significant welfare gains. At the global level the welfare gains reach 1.1 percent, while in the BRI area the welfare gain increases to 2 percent as compared to 1.2 percent under infrastructure investment alone (as compared to the baseline in 2030). The tariff reductions generate a further boost to trade and enhance welfare gains. However, with the tariffs at a low level already, the additional gains are relatively small with an additional $60 billion and $110 billion under preferential and multilateral tariff reductions at a global level.

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. 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.

# **References**

Atamanov, Aziz; Castaneda Aguilar, Raul Andres; Corral Rodas, Paul Andres; Dewina, Reno; Diaz-Bonilla, Carolina; Jolliffe, Dean Mitchell; Lakner, Christoph; Lee, Kihoon; Montes, Jose; Moreno Herrera, Laura Liliana; Mungai, Rose; Newhouse, David Locke; Nguyen, Minh Cong; Prydz, Espen Beer; Sangraula, Prem; Yang, Judy. 2019. March 2019 PovcalNet Update: What's New (English). Global Poverty Monitoring Technical Note; no. 7. Washington, D.C.: World Bank Group.

de Soyres, F., Mulabdic, A., and Ruta, M. (2018). The Belt and Road Initiative: A Structural Analysis, Unpublished Working Paper, World Bank.

De Soyres, Francois Michel Marie Raphael; Mulabdic, Alen; Murray, Siobhan; Rocha Gaffurri, Nadia Patrizia; Ruta, Michele. 2018 _. How Much Will the Belt and Road Initiative Reduce Trade Costs?_ . Policy Research working paper; no. WPS 8614. Washington, D.C. : World Bank Group.

Devarajan, S., J.D. Lewis, and S. Robinson (1990), “Policy lessons from trade-focused, two-sector models,” _Journal of Policy Modeling_ , 12(4): 625-657. DOI:10.1016/0161-8938(90)90002-V.

Hummels, D. and Schaur, G. (2013), “Time as a Trade Barrier,” _American Economic Review_ , 103(7): 2945-59.

International Trade Centre (ITC). Market Access Map (MAcMap). 2015. “Tariff Rates for 2014– 2031 between TPP Member Countries absent the TPP Agreement.” Prepared for the Global Economic Partnership Agreement Research Consortium.

Jolliffe, D., & Prydz, E. B. (2016). Estimating international poverty lines from comparable national thresholds. Journal of Economic Inequality. https://doi.org/10.1007/s10888-016-9327-5

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Ravallion, M., & Chen, S. (2011). Weakly Relative Poverty. The Review of Economics and Statistics, 93(4), 1251–1261. https://doi.org/10.1162/REST_a_00127 World Bank. 2018. Poverty and Shared Prosperity 2018: Piecing Together the Poverty Puzzle. World Bank, Washington, DC. License: Creative Commons Attribution CC BY 3.0 IGO World Bank. 2016. Poverty and Shared Prosperity 2016: Taking on Inequality. Washington, DC: World Bank. doi:10.1596/978-1-4648-0958-3. License: Creative Commons Attribution CC BY 3.0 IGO Zhai, F (2018), “China’s belt and road initiative: A preliminary quantitative assessment,” Journal of Asian Economics, in press. https://doi.org/10.1016/j.asieco.2017.12.006

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# **Tables**

# <u>Table 1: Baseline population profile, million</u>

||2014|2017|2020|2025|2030|
|---|---|---|---|---|---|
|World|7,248|7,497|7,739|8,120|8,477|
|BRI Area|4,731|4,878|5,015|5,218|5,393|
|Cambodia|15|16|17|18|19|
|China|1,364|1,383|1,398|1,410|1,410|
|Indonesia|254|264|272|285|295|
|Lao PDR|7|7|7|8|8|
|Malaysia|30|31|32|34|36|
|Philippines|99|104|108|116|124|
|Thailand|68|68|69|69|68|
|Vietnam|91|94|96|100|103|
|Rest of East Asia|100|103|105|110|113|
|Bangladesh|159|165|170|179|186|
|India|1,295|1,343|1,389|1,462|1,528|
|Nepal|28|29|30|32|33|
|Pakistan|185|197|208|227|245|
|Sri Lanka|21|21|21|22|22|
|Rest of South Asia|33|35|38|42|45|
|EU ECA|470|474|477|479|478|
|Russian Federation|144|144|143|142|139|
|Poland|38|38|38|37|37|
|Rest of Eastern Europe|61|61|60|58|57|
|Kazakhstan|17|18|19|19|20|
|Kyrgyz Republic|6|6|6|7|7|
|Rest of Central Asia|61|63|65|68|70|
|Iran,Islamic Rep.|78|81|83|86|89|
|Egypt,Arab Rep.|90|95|101|109|117|
|Turkey|78|80|82|85|88|
|Rest of MENA|248|262|277|301|324|
|Kenya|45|48|52|59|65|
|Tanzania|52|57|62|72|83|
|Non-BRI Area|2,517|2,619|2,724|2,902|3,084|
|Ethiopia|97|104|112|125|138|
|Rest of Sub-Saharan Africa|771|834|901|1,020|1,150|
|Latin America and Caribbean|626|646|665|694|720|
|United States|319|326|333|344|355|
|Rest of High-income|272|274|276|278|278|
|Rest of Western Europe|432|435|437|441|443|

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<u>Table 2: Baseline GDP, $2014 billion</u>

||2014|2017|2020|2025|2030|
|---|---|---|---|---|---|
|World|78,226|87,588|97,935|115,447|133,052|
|BRI Area|24,152|29,238|35,076|45,361|55,733|
|Cambodia|17|21|26|36|47|
|China|10,351|13,267|16,639|22,342|27,642|
|Indonesia|890|1,091|1,335|1,826|2,380|
|Lao PDR|12|15|19|26|34|
|Malaysia|338|389|444|548|662|
|Philippines|285|327|376|469|581|
|Thailand|404|463|533|663|802|
|Vietnam|186|229|282|374|477|
|Rest of East Asia|527|607|697|846|997|
|Bangladesh|173|212|261|355|463|
|India|2,042|2,477|3,015|4,064|5,274|
|Nepal|20|22|25|32|41|
|Pakistan|243|274|313|398|510|
|Sri Lanka|80|96|114|147|182|
|Rest of South Asia|25|29|34|43|55|
|EU ECA|4,971|5,575|6,208|7,292|8,383|
|Russian Federation|2,031|2,281|2,533|2,965|3,397|
|Poland|545|596|652|733|805|
|Rest of Eastern Europe|229|258|286|339|393|
|Kazakhstan|227|273|325|436|534|
|Kyrgyz Republic|7|9|10|14|18|
|Rest of Central Asia|219|257|304|388|482|
|Iran,Islamic Rep.|425|450|495|584|675|
|Egypt,Arab Rep.|301|355|432|578|760|
|Turkey|799|919|1,031|1,219|1,419|
|Rest of MENA|2,752|3,207|3,667|4,512|5,451|
|Kenya|61|73|88|119|162|
|Tanzania|48|59|73|108|156|
|Non-BRI Area|54,074|58,350|62,859|70,086|77,319|
|Ethiopia|56|68|84|115|158|
|Rest of Sub-Saharan Africa|1,579|1,877|2,248|2,993|3,947|
|Latin America and Caribbean|6,405|7,185|8,042|9,518|11,057|
|United States|17,348|18,928|20,544|22,934|25,084|
|Rest of High-income|10,268|10,982|11,681|12,808|13,870|
|Rest of Western Europe|18,418|19,310|20,260|21,718|23,203|

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<u>Table 3: GDP per capita, $2014</u>

||2014|2017|2020|2025|2030|
|---|---|---|---|---|---|
|World|10,792|11,683|12,655|14,217|15,695|
|BRI Area|5,014|5,883|6,859|8,512|10,105|
|Cambodia|1,095|1,314|1,570|2,013|2,498|
|China|7,587|9,593|11,906|15,851|19,601|
|Indonesia|3,500|4,140|4,911|6,417|8,056|
|Lao PDR|1,751|2,118|2,529|3,256|4,030|
|Malaysia|11,307|12,468|13,724|15,953|18,340|
|Philippines|2,873|3,149|3,464|4,038|4,700|
|Thailand|5,970|6,782|7,772|9,655|11,753|
|Vietnam|2,052|2,444|2,925|3,735|4,620|
|Rest of East Asia|5,290|5,918|6,609|7,711|8,784|
|Bangladesh|1,087|1,287|1,530|1,980|2,481|
|India|1,577|1,845|2,171|2,781|3,452|
|Nepal|702|758|835|1,008|1,232|
|Pakistan|1,315|1,391|1,502|1,754|2,084|
|Sri Lanka|3,853|4,573|5,369|6,830|8,393|
|Rest of South Asia|765|825|897|1,042|1,218|
|EU ECA|10,578|11,750|13,012|15,233|17,531|
|Russian Federation|14,122|15,863|17,675|20,939|24,436|
|Poland|14,337|15,694|17,246|19,630|21,989|
|Rest of Eastern Europe|3,739|4,247|4,784|5,810|6,953|
|Kazakhstan|13,155|15,169|17,559|22,561|26,714|
|Kyrgyz Republic|1,280|1,439|1,616|2,020|2,542|
|Rest of Central Asia|3,615|4,090|4,675|5,707|6,859|
|Iran,Islamic Rep.|5,443|5,563|5,940|6,750|7,628|
|Egypt,Arab Rep.|3,366|3,728|4,298|5,307|6,489|
|Turkey|10,304|11,431|12,536|14,363|16,179|
|Rest of MENA|11,099|12,228|13,243|14,981|16,837|
|Kenya|1,368|1,508|1,678|2,030|2,470|
|Tanzania|927|1,037|1,178|1,494|1,885|
|Non-BRI Area|22,321|23,171|24,029|25,192|26,190|
|Ethiopia|574|653|746|918|1,140|
|Rest of Sub-Saharan Africa|2,047|2,250|2,495|2,933|3,433|
|Latin America and<br>Caribbean|10,223|11,116|12,088|13,708|15,361|
|United States|54,399|58,074|61,696|66,572|70,627|
|Rest of High-income|37,792|40,086|42,366|46,153|49,852|
|Rest of Western Europe|42,661|44,436|46,328|49,267|52,340|

- 24 -
<u>Table 4: Reductions in the value of the time of trade</u>

||CHN|||||bri|||||xbr|||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
||BRIL<br>BD|BRIU<br>BD|BRIU<br>BBD|BRIUB<br>BTD|BRIUB<br>BTPD|BRIL<br>BD|BRIU<br>BD|BRIU<br>BBD|BRIUB<br>BTD|BRIUB<br>BTPD|BRIL<br>BD|BRIU<br>BD|BRIU<br>BBD|BRIUB<br>BTD|BRIUB<br>BTPD|
|World|1.0|1.9|2.9|3.0|3.0|1.0|2.2|3.7|3.7|3.7|0.4|1.3|1.5|1.5|1.6|
|BRI Area|1.8|3.0|5.3|5.4|5.4|1.4|2.7|4.8|4.8|4.8|0.7|1.8|2.4|2.4|2.4|
|Cambodia|2.7|2.9|3.9|3.9|3.9|4.3|4.6|8.8|8.8|8.8|3.0|4.1|4.2|4.2|4.2|
|China||||||2.1|3.5|5.6|5.6|5.6|0.7|2.0|2.2|2.2|2.2|
|Indonesia|0.1|1.1|1.4|1.4|1.4|0.4|2.1|2.3|2.1|2.1|0.1|1.5|2.0|2.0|2.0|
|Lao PDR|0.5|3.9|7.4|7.4|7.4|0.9|3.5|14.4|14.3|14.4|0.3|7.0|10.7|10.8|10.7|
|Malaysia|5.7|6.1|7.0|7.0|7.0|4.0|5.0|5.6|5.4|5.4|2.9|4.7|5.0|5.0|5.0|
|Philippines|0.0|0.4|0.5|0.5|0.5|0.7|2.0|2.1|2.1|2.1|0.6|1.8|1.8|1.8|1.8|
|Thailand|0.2|3.1|7.8|7.8|7.8|0.8|6.4|8.6|8.5|8.6|0.7|5.1|5.5|5.6|5.5|
|Vietnam|0.1|0.1|0.2|0.2|0.2|2.0|2.3|2.7|2.7|2.7|1.2|2.4|2.4|2.4|2.4|
|Rest of||||||||||||||||
|East Asia|1.2|2.0|5.8|5.7|5.7|0.6|2.6|4.1|4.1|4.1|0.3|1.3|1.4|1.4|1.4|
|Bangladesh|4.1|5.1|9.0|9.0|9.0|1.1|1.4|2.6|2.6|2.5|0.6|1.4|1.4|1.5|1.5|
|India|3.0|3.8|5.7|5.8|5.8|1.4|2.1|3.4|3.4|3.4|0.8|2.2|2.5|2.5|2.6|
|Nepal|3.5|4.3|20.4|20.5|20.5|0.5|0.9|21.9|21.9|21.9|0.4|1.5|10.0|10.3|10.3|
|Pakistan|3.3|3.3|3.3|3.3|3.3|1.8|3.1|5.3|5.0|5.0|1.0|2.4|4.7|4.7|4.7|
|Sri Lanka|2.3|2.9|3.9|3.8|3.8|0.8|1.2|2.6|2.6|2.6|0.6|2.3|2.4|2.5|2.5|
|Rest of S.||||||||||||||||
|Asia|2.7|2.9|8.2|8.3|8.3|1.8|2.3|11.2|11.2|11.2|1.6|2.9|10.1|10.3|10.3|
|EU ECA|2.3|2.3|2.3|2.2|2.2|0.6|0.9|2.1|2.1|2.1|0.1|0.2|0.3|0.4|0.3|
|Russian||||||||||||||||
|Federation|1.3|1.5|1.8|1.9|1.9|0.7|1.3|4.6|4.5|4.5|0.4|0.8|2.0|2.0|2.0|
|Poland|2.4|2.4|2.4|2.4|2.4|0.6|0.9|1.8|1.8|1.8|0.0|0.2|0.2|0.2|0.2|
|Rest of E.||||||||||||||||
|Europe|2.1|2.1|2.1|2.2|2.1|0.6|1.6|4.2|4.1|4.2|0.2|0.9|1.8|1.8|1.8|
|Kazakhstan|1.1|1.4|13.4|13.7|13.6|1.8|2.5|14.8|14.7|14.6|0.2|0.3|2.7|2.7|2.7|
|Kyrgyz||||||||||||||||
|Republic|25.5|25.9|38.3|36.9|37.0|8.4|10.2|26.4|26.4|26.4|5.1|6.0|17.3|17.3|17.3|

- 25 -
|Rest of C.||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|Asia|1.1|1.1|3.1|3.2|3.2|1.9|2.3|6.3|6.1|6.0|0.8|0.9|2.2|2.3|2.3|
|Iran,||||||||||||||||
|Islamic Rep.|1.4|6.0|11.4|11.8|11.8|1.0|4.1|8.2|8.5|8.5|0.4|0.8|2.3|2.3|2.3|
|Egypt,<br>Arab Rep.|2.0|2.0|2.0|2.0|2.0|0.4|1.0|2.2|2.2|2.2|0.3|0.5|0.6|0.6|0.7|
|Turkey|2.6|2.6|2.5|2.6|2.5|2.5|3.0|5.5|5.5|5.5|3.3|3.4|3.5|3.5|3.5|
|Rest of<br>MENA|0.9|2.7|4.6|4.9|4.8|0.5|1.5|2.9|3.0|3.0|0.3|1.0|3.1|3.1|3.1|
|Kenya|4.8|6.2|10.2|10.1|10.2|3.2|4.1|4.9|4.7|4.7|1.7|3.0|5.9|5.9|5.9|
|Tanzania|6.8|8.6|12.9|12.9|12.9|4.3|5.2|6.3|6.3|6.3|2.3|3.3|4.0|4.0|4.0|
|Non-BRI Area|0.5|1.4|1.6|1.6|1.6|0.6|1.6|2.5|2.4|2.5|0.2|0.8|0.9|0.9|0.9|
|Ethiopia|4.0|7.7|18.7|18.7|18.7|2.7|4.8|14.3|14.4|14.3|1.5|2.5|8.9|8.9|8.9|
|Rest of SSA|0.4|0.9|2.0|2.0|2.0|0.4|0.9|1.5|1.5|1.5|0.2|0.8|0.9|1.0|1.0|
|Lat. Am. &||||||||||||||||
|Car.|0.2|0.4|0.6|0.6|0.5|0.4|0.9|1.2|1.1|1.2|0.1|0.6|0.6|0.6|0.6|
|United<br>States|0.0|3.5|3.6|3.6|3.6|0.3|2.7|3.0|3.0|3.0|0.1|1.3|1.3|1.3|1.3|
|Rest of<br>High-inc.|0.0|0.7|0.8|0.8|0.8|0.6|1.9|2.6|2.5|2.6|0.4|1.8|1.8|1.8|1.8|
|Rest of W.<br>Eur.|2.2|2.2|2.2|2.2|2.2|0.9|1.3|2.7|2.6|2.6|0.2|0.4|0.4|0.4|0.4|

- 26 -
Table 5: Real income impacts of BRI (change relative to baseline in 2030)

||BR|ILBD|BR|IUBD|BR|IUBBD|BRI|UBBTD|BRI|UBBTPD|
|---|---|---|---|---|---|---|---|---|---|---|
||%|$bn|%|$bn|%|$bn|%|$bn|%|$bn|
|World|0.4|492.3|0.7|928.9|1.1|1405.0|1.1|1465.2|1.1|1515.6|
|BRI Area|0.8|419.6|1.2|651.2|2.0|1062.0|2.1|1135.9|2.1|1133.0|
|Cambodia|4.8|2.2|5.0|2.3|8.6|4.0|8.3|3.8|8.7|4.0|
|China|0.4|97.0|0.7|178.2|1.0|262.9|1.2|299.9|1.1|291.6|
|Indonesia|0.0|0.2|0.5|12.1|0.5|12.1|0.6|13.5|0.6|12.9|
|Lao PDR|0.7|0.2|3.1|1.1|9.2|3.2|9.1|3.2|9.3|3.2|
|Malaysia|6.8|40.6|7.7|46.0|8.1|48.5|8.5|51.0|8.3|50.0|
|Philippines|0.2|1.1|0.7|4.0|0.6|3.5|0.6|3.5|0.6|3.8|
|Thailand|3.0|23.9|8.2|64.6|9.7|76.0|9.9|77.7|9.7|76.6|
|Vietnam|1.1|5.5|1.6|7.6|1.6|7.7|1.7|8.4|1.6|7.7|
|Rest of East Asia|0.3|2.9|1.6|14.9|2.5|23.7|2.5|23.8|2.5|23.4|
|Bangladesh|6.7|31.3|6.9|32.5|7.2|34.0|7.3|34.2|7.4|34.6|
|India|0.2|12.1|0.4|23.4|0.6|30.5|0.8|44.4|1.0|51.3|
|Nepal|0.3|0.1|0.4|0.2|11.3|4.7|11.0|4.6|11.2|4.6|
|Pakistan|10.1|53.8|10.5|56.1|10.8|57.3|10.9|58.0|11.1|59.2|
|Sri Lanka|0.4|0.8|0.6|1.2|0.8|1.5|0.9|1.8|1.1|2.1|
|Rest of S. Asia|1.0|0.6|1.4|0.9|5.4|3.5|5.6|3.6|5.7|3.7|
|EU ECA|0.2|2.4|0.2|3.1|0.5|6.8|0.7|8.8|0.6|8.1|
|Russian Federation|1.1|35.0|1.2|39.2|1.9|59.6|1.9|61.8|1.9|61.7|
|Poland|0.2|1.3|0.2|1.8|0.3|2.3|0.4|2.8|0.4|3.0|
|Rest of E. Europe|0.3|1.2|0.8|3.1|1.6|5.9|1.6|5.9|1.4|5.2|
|Kazakhstan|0.3|1.4|0.5|2.1|15.4|71.5|15.4|71.6|15.5|71.9|
|Kyrgyz Republic|9.9|1.3|10.4|1.3|37.3|4.7|36.6|4.6|36.1|4.5|
|Rest of C. Asia|1.4|6.6|1.5|7.1|6.7|31.4|6.6|31.2|6.6|31.1|
|Iran,Islamic Rep.|2.0|13.4|3.0|20.5|4.3|28.8|4.9|33.3|4.9|33.2|
|Egypt,Arab Rep.|0.2|1.2|0.2|1.9|0.3|2.2|0.3|2.4|0.9|7.2|
|Turkey|3.6|53.2|3.6|53.7|3.9|57.5|4.1|61.2|4.2|61.7|
|Rest of MENA|0.5|24.5|1.3|65.7|4.1|209.4|4.1|211.5|4.1|207.0|
|Kenya|1.2|2.0|1.5|2.5|2.3|3.9|2.6|4.3|2.7|4.5|
|Tanzania|2.2|3.7|2.5|4.1|2.9|4.7|3.1|5.1|3.2|5.2|
|Non-BRI Area|0.1|72.7|0.3|277.7|0.4|343.0|0.4|329.3|0.5|382.6|
|Ethiopia|1.2|1.9|1.9|3.1|5.9|9.9|5.8|9.7|6.0|10.1|
|Rest of SSA|0.2|8.2|0.4|17.2|0.7|26.7|0.7|25.7|0.7|26.8|
|Lat. Am. & Car.|0.0|1.9|0.1|10.4|0.1|12.2|0.1|10.5|0.1|12.4|
|United States|0.0|1.7|0.4|107.2|0.4|110.9|0.4|109.0|0.5|122.5|
|Rest of High-inc.|0.1|14.5|0.5|69.1|0.5|76.9|0.5|71.9|0.6|87.0|
|Rest of W. Eur.|0.2|44.5|0.3|70.7|0.4|106.4|0.4|102.5|0.5|123.8|

- 27 -
Table 6: Export impacts of BRI (change relative to baseline in 2030)

||BRI|LBD|BRI|UBD|BRIU|BBD|BRI|UBBT|BRIU|BBTPD|
|---|---|---|---|---|---|---|---|---|---|---|
||%|$bn|%|$bn|%|$bn|%|$bn|%|$bn|
|World|0.7|233.1|1.7|564.8|2.4|776.6|2.9|970.1|3.6|1200.9|
|BRI Area|1.6|247.6|2.8|437.8|4.4|684.7|5.9|915.2|6.9|1070.1|
|Cambodia|6.0|2.7|5.6|2.5|10.9|4.9|10.9|4.9|12.0|5.3|
|China|1.5|84.1|2.7|147.8|3.7|206.6|4.6|253.5|6.3|348.2|
|Indonesia|-0.2|-1.3|1.4|7.5|1.4|7.5|2.2|12.0|2.5|13.7|
|Lao PDR|1.9|0.4|1.5|0.3|27.0|5.1|27.4|5.2|28.1|5.3|
|Malaysia|11.2|56.2|12.4|62.2|12.8|64.5|13.2|66.5|13.5|67.9|
|Philippines|0.6|1.1|2.5|4.9|1.8|3.7|2.4|4.8|3.0|5.9|
|Thailand|4.2|22.0|14.9|77.4|17.8|92.4|18.3|95.1|19.0|98.4|
|Vietnam|2.2|10.3|2.0|9.4|1.1|5.2|3.2|14.8|3.8|17.4|
|Rest of East Asia|-0.7|-5.1|1.1|7.8|0.8|5.4|0.9|6.0|0.7|4.7|
|Bangladesh|7.4|7.6|8.7|8.8|9.7|9.9|22.8|23.2|24.5|25.0|
|India|1.6|17.5|2.9|31.0|3.6|38.0|8.9|95.7|10.8|115.8|
|Nepal|-0.3|0.0|-0.2|0.0|30.2|3.4|43.1|4.8|43.4|4.8|
|Pakistan|8.6|6.7|9.8|7.7|12.7|9.9|20.7|16.2|22.5|17.6|
|Sri Lanka|0.4|0.2|1.0|0.5|1.1|0.5|4.5|2.0|6.1|2.8|
|Rest of S. Asia|2.4|0.3|3.2|0.4|19.3|2.2|26.9|3.0|27.4|3.1|
|EU ECA|-0.3|-2.9|-0.7|-5.6|-0.6|-5.1|0.2|1.7|0.0|0.3|
|Russian Federation|1.0|8.5|1.2|9.6|3.3|27.2|4.8|39.5|6.1|50.3|
|Poland|-0.2|-0.7|-0.4|-1.3|-0.7|-2.2|-0.1|-0.3|-0.1|-0.4|
|Rest of E. Europe|0.0|0.0|0.8|1.7|2.0|4.5|2.6|5.7|2.5|5.6|
|Kazakhstan|0.8|1.4|1.1|2.1|22.6|42.9|23.6|44.8|23.7|44.9|
|Kyrgyz Republic|5.4|0.9|5.4|0.9|36.8|5.8|37.4|5.9|36.9|5.8|
|Rest of C. Asia|2.4|3.3|2.6|3.5|8.9|11.9|10.3|13.8|10.5|14.1|
|Iran,Islamic Rep.|1.5|2.5|4.2|7.0|7.5|12.4|15.4|25.5|16.1|26.7|
|Egypt,Arab Rep.|-0.2|-0.3|-0.2|-0.4|-0.5|-0.8|1.8|3.0|2.7|4.5|
|Turkey|6.0|20.9|5.8|20.1|6.4|22.1|8.2|28.5|8.6|29.7|
|Rest of MENA|0.5|10.8|1.4|31.5|4.6|105.7|5.9|134.1|6.4|146.9|
|Kenya|0.3|0.1|0.2|0.1|1.9|0.7|8.0|3.0|9.0|3.3|
|Tanzania|2.4|0.7|2.5|0.7|2.6|0.7|8.4|2.3|9.5|2.6|
|Non-BRI Area|-0.1|-14.5|0.7|127.1|0.5|91.9|0.3|55.0|0.7|130.7|
|Ethiopia|2.4|0.4|3.9|0.7|12.2|2.1|11.9|2.1|12.2|2.1|
|Rest of SSA|0.3|2.9|0.8|8.4|1.0|11.3|0.9|10.0|1.1|12.6|
|Lat. Am. & Car.|-0.1|-2.5|-0.5|-10.5|-0.6|-14.0|-0.7|-15.9|-0.7|-14.5|
|United States|-0.6|-16.1|3.4|97.9|2.7|76.6|2.5|70.8|3.2|91.9|
|Rest of High-inc.|0.0|1.6|1.4|53.9|1.2|46.2|0.9|35.8|1.4|52.5|
|Rest of W. Eur.|0.0|-0.7|-0.3|-23.3|-0.4|-30.2|-0.6|-47.8|-0.2|-13.9|

- 28 -
Table 7: Import impacts of BRI (change relative to baseline in 2030)

||BRI|LBD|BRI|UBD|BRI|UBBD|BRIU|BBTD|BRIU|BBTPD|
|---|---|---|---|---|---|---|---|---|---|---|
||%|$bn|%|$bn|%|$bn|%|$bn|%|$bn|
|World|1.4|462.4|3.4|1152.7|4.8|1648.6|5.5|1862.8|6.2|2108.4|
|BRI Area|2.9|386.1|5.4|735.8|8.7|1179.9|10.6|1437.4|11.3|1530.9|
|Cambodia|9.8|4.3|9.5|4.1|18.5|8.0|18.2|7.9|19.1|8.2|
|China|3.1|128.4|5.6|229.9|8.0|329.2|9.7|397.8|11.1|457.6|
|Indonesia|-0.1|-0.3|3.4|16.7|3.5|17.0|5.2|25.5|5.1|25.1|
|Lao PDR|2.6|0.5|5.7|1.1|37.8|7.5|38.0|7.5|38.5|7.6|
|Malaysia|16.2|72.7|18.5|82.9|19.5|87.3|20.4|91.7|20.5|91.8|
|Philippines|1.1|2.3|4.0|8.4|3.4|7.1|3.8|8.0|4.2|8.8|
|Thailand|4.1|20.7|21.4|108.7|26.8|135.9|27.5|139.5|27.6|140.0|
|Vietnam|3.1|14.5|3.2|15.2|2.4|11.3|4.2|20.1|4.6|22.0|
|Rest of East Asia|-0.2|-1.1|3.2|23.0|4.0|28.7|4.3|30.4|4.1|29.1|
|Bangladesh|5.8|6.6|7.4|8.5|9.4|10.8|18.2|20.8|19.5|22.2|
|India|2.6|30.7|4.4|52.8|5.9|70.9|10.1|121.7|11.3|135.5|
|Nepal|0.7|0.1|1.2|0.1|47.4|5.8|55.3|6.7|55.2|6.7|
|Pakistan|5.8|5.8|9.3|9.3|12.7|12.7|18.8|18.8|19.7|19.6|
|Sri Lanka|1.7|0.9|3.0|1.5|3.8|1.9|6.8|3.4|7.8|3.9|
|Rest of S. Asia|3.5|0.7|4.5|0.9|21.1|4.4|25.0|5.2|25.3|5.3|
|EU ECA|0.1|0.5|-0.1|-1.2|0.5|3.9|1.6|13.6|1.5|12.2|
|Russian Federation|2.0|12.2|2.8|16.7|9.3|55.3|11.3|67.3|12.3|73.5|
|Poland|0.3|0.9|0.3|1.1|0.4|1.5|1.3|4.5|1.3|4.6|
|Rest of E. Europe|0.6|1.3|2.2|4.7|4.9|10.6|5.4|11.6|5.1|11.0|
|Kazakhstan|2.3|2.8|3.4|4.2|39.9|48.9|41.1|50.3|40.9|50.1|
|Kyrgyz Republic|16.7|1.9|17.5|2.0|72.5|8.1|72.6|8.1|72.0|8.0|
|Rest of C. Asia|5.2|6.7|6.1|7.9|18.2|23.7|19.4|25.3|19.5|25.4|
|Iran,Islamic Rep.|2.0|3.2|7.4|11.9|14.2|22.6|22.4|35.8|22.8|36.4|
|Egypt,Arab Rep.|0.6|1.1|1.0|1.8|1.1|1.9|3.0|5.3|3.2|5.8|
|Turkey|8.5|34.8|8.5|34.5|10.0|40.9|12.7|51.8|12.8|52.1|
|Rest of MENA|1.5|29.6|4.3|83.7|11.2|216.4|12.8|247.7|13.3|256.7|
|Kenya|4.7|2.1|5.7|2.5|9.7|4.3|14.3|6.3|14.8|6.6|
|Tanzania|6.4|2.4|7.4|2.7|9.0|3.3|12.7|4.7|13.1|4.8|
|Non-BRI Area|0.4|76.3|2.0|416.9|2.3|468.8|2.1|425.4|2.8|577.5|
|Ethiopia|4.0|1.2|6.7|1.9|22.6|6.6|22.2|6.4|22.9|6.7|
|Rest of SSA|0.8|8.3|2.0|20.3|3.1|31.6|2.9|29.8|3.4|34.4|
|Lat. Am. & Car.|0.1|1.5|0.1|3.1|0.1|3.0|-0.1|-1.4|0.3|6.4|
|United States|-0.3|-10.9|4.6|189.5|4.3|175.6|4.1|168.5|5.1|208.9|
|Rest of High-inc.|0.4|19.3|3.1|135.6|3.4|148.1|3.1|135.3|3.9|170.4|
|Rest of W. Eur.|0.6|56.9|0.8|66.5|1.2|103.8|1.0|86.7|1.7|150.6|

- 29 -
Table 8a: Change in the volume of exports in 2030, percent change from baseline

||World|BRI<br>Area|Cambodia|China|Indonesia|Lao<br>PDR|Malaysia|Philippines|Thailand|Vietnam|
|---|---|---|---|---|---|---|---|---|---|---|
|Agriculture|2.8|2.0|-13.5|7.2|4.7|-4.9|-12.6|0.5|-5.5|1.6|
|Minerals n.e.s.|-0.3|-0.7|-2.4|-0.5|-1.3|4.6|-3.8|-1.4|-8.4|-1.7|
|Coal|2.4|2.6||-9.4|1.5|132.9|9.9|-6.6|32.7|-12.1|
|Oil|0.0|-0.5||-2.8|-0.7|8.1|-31.6|1.0|-41.2|-6.0|
|Gas|0.3|0.4||3.5|1.5|-0.8|-16.3||-16.6|9.0|
|Textiles|1.7|1.8|3.1|2.6|2.1|17.5|-2.2|-0.6|-8.6|0.4|
|Wearingapparel|1.2|1.4|1.8|0.8|0.9|-5.0|-11.7|-1.6|-8.6|0.4|
|Leathergoods|1.5|1.7|13.3|1.4|-0.6|22.6|-1.6|-1.0|13.8|3.5|
|Processed foods|2.2|2.3|-4.1|1.8|3.4|-2.5|-1.8|2.5|1.0|3.0|
|Woodproducts|2.5|2.3|-12.2|11.7|-0.6|-4.2|-15.3|-3.8|-11.7|-3.7|
|Paper products,<br>publishing|2.1|1.9|24.4|4.6|1.3|-7.8|-7.4|4.4|3.3|-0.2|
|Petroleum, coal<br>products|2.0|4.6||1.7|-2.9|11.0|3.1|-0.9|26.2|-1.8|
|Chemical, rubber,<br>plastic|1.4|2.8|-6.6|2.9|-0.9|17.5|-1.8|-0.2|-0.6|3.1|
|Energyintensive man.|0.8|1.0|18.8|1.0|5.0|9.1|1.1|-1.1|0.8|-1.0|
|Metalproducts|2.3|3.7|29.6|4.3|3.7|47.7|5.2|5.1|12.1|8.5|
|Electronics|3.7|7.4|26.1|2.4|-4.5|6.7|39.9|8.9|76.9|3.3|
|Machinery and<br>equipment|2.7|4.4|31.5|4.5|4.4|36.3|8.7|0.0|30.5|2.2|
|Transport equipment|1.9|3.8|40.5|2.5|3.1|31.9|8.4|-2.4|19.4|2.5|
|Manufactures,n.e.s.|2.2|3.1|21.0|1.6|0.7|8.6|-22.1|-1.9|6.5|4.6|
|Electricity|0.3|0.4||0.6||9.0|-1.3||-3.3|-0.8|
|Construction|2.8|3.4|9.7|6.0|1.3|20.4|-6.2|1.3|4.8|6.0|
|Trade services|2.0|2.3|-2.3|3.6|1.6|6.2|-3.1|1.2|-13.8|2.7|
|Other transport|1.8|3.2|30.8|4.3|1.1|7.9|-6.8|1.1|0.0|11.3|
|Water transport|0.5|2.7|33.7|5.7|-0.3|10.1|8.6|-0.9|2.1|13.5|
|Air transport|1.7|5.7|32.0|6.0|1.7|14.2|10.2|1.7|13.3|12.4|
|Hospitalityservices|0.3|-2.9|-15.6|-0.7|-0.7|7.5|-22.8|-1.6|-12.0|-4.1|
|Other business services|0.1|-1.7|-12.3|-0.8|-1.0|-7.0|-21.7|-2.3|-23.4|-4.8|
|Other services|0.0|-0.9|-4.9|-0.3|-0.2|-1.9|-6.8|-0.8|-9.4|-1.6|
|**Agriculture**|2.8|2.0|-13.5|7.2|4.7|-4.9|-12.6|0.5|-5.5|1.6|
|**Manufacturing**|2.1|3.9|5.4|2.7|1.6|4.5|17.7|3.5|19.1|2.6|
|**Services**|0.8|0.5|8.9|1.9|0.3|4.7|-7.5|-0.7|-6.1|1.1|
|**Other**|0.1|-0.2|-2.4|-3.0|1.0|4.2|-21.1|-1.6|-16.4|-6.8|
|**Total**|1.7|2.8|5.6|2.7|1.4|1.5|12.4|2.5|14.9|2.0|

- 30 -
Table 8a: Change in the volume of exports in 2030, percent change from baseline, ctd.

||Rest of<br>East<br>Asia|Bangladesh|India|Nepal|Pakistan|Sri<br>Lanka|Rest of<br>South<br>Asia|EU ECA|Russian<br>Federation|
|---|---|---|---|---|---|---|---|---|---|
|Agriculture|4.4|-10.2|7.8|0.5|-31.7|-0.8|3.6|2.0|5.9|
|Minerals n.e.s.|-0.6|11.5|0.1|-2.5|-6.4|-1.9|6.0|0.1|-0.3|
|Coal|19.5||0.4||11.9||12.8|-5.3|6.3|
|Oil|-2.3||-4.6||38.8||-5.9|2.8|0.8|
|Gas|2.7|-20.2|11.8||51.3||6.9|1.1|1.5|
|Textiles|-0.7|13.1|2.6|2.8|0.3|-2.0|22.6|0.4|1.6|
|Wearingapparel|3.2|7.8|-0.9|3.2|8.6|1.0|20.5|0.0|1.3|
|Leathergoods|-2.3|1.6|2.2|-0.7|-11.5|1.4|2.8|-1.3|-1.4|
|Processed foods|-3.0|4.9|6.5|-2.2|17.7|-1.6|-1.1|0.9|4.4|
|Woodproducts|3.6|-2.5|8.0|2.2|-40.9|2.5|13.1|0.1|4.1|
|Paper products,<br>publishing|-1.6|13.0|1.0|2.6|21.4|-1.4|20.7|0.3|3.1|
|Petroleum, coal<br>products|-2.6|55.4|3.8||17.9|2.7|9.0|0.2|1.9|
|Chemical, rubber,<br>plastic|-2.1|19.7|6.5|-8.0|72.9|4.0|29.1|-0.4|0.4|
|Energyintensive man.|-0.7|45.1|2.5|-6.2|17.9|-3.1|2.5|-0.5|0.4|
|Metalproducts|1.8|71.4|5.4|9.9|34.7|2.0|16.1|-0.8|0.8|
|Electronics|9.5|203.3|7.6|1.1|34.9|9.2|35.7|-6.5|-8.0|
|Machinery and<br>equipment|1.1|197.6|6.3|5.5|15.7|7.9|25.1|-1.7|-3.5|
|Transport equipment|1.3|51.8|-1.3|2.8|48.6|-0.6|26.1|-0.7|-1.2|
|Manufactures,n.e.s.|22.7|126.0|8.9|11.4|56.9|7.4|20.1|-1.6|1.7|
|Electricity|0.1||0.4||||1.1|0.5|0.7|
|Construction|-1.7|-9.9|3.7|0.7|7.4|0.4|2.7|1.7|0.4|
|Trade services|-0.9|-17.0|10.6|2.0|-6.8|2.2|1.6|2.2|1.1|
|Other transport|-0.6|-5.1|6.7|1.7|-7.0|2.5|5.4|0.2|0.3|
|Water transport|-2.5|-7.5|5.5|-0.7|-19.9|1.1|1.9|-1.0|1.3|
|Air transport|-1.5|-6.5|3.9|1.4|-10.4|3.2|9.6|0.3|-0.3|
|Hospitalityservices|-2.3|19.5|0.4|-1.8|41.2|-2.8|-0.3|3.3|4.2|
|Other business services|-2.1|-3.0|-0.9|-2.4|2.0|-3.4|-2.7|2.7|-0.6|
|Other services|-0.7|-4.2|-0.2|-0.5|0.9|-0.8|-1.6|0.8|0.0|
|**Agriculture**|4.4|-10.2|7.8|0.5|-31.7|-0.8|3.6|2.0|5.9|
|**Manufacturing**|2.5|10.1|4.2|0.2|14.2|1.9|7.7|-1.2|0.9|
|**Services**|-1.6|-3.4|0.4|-1.0|-1.6|-0.8|1.1|1.6|0.1|
|**Other**|2.9|-3.5|0.1|-2.5|-5.8|-1.9|5.4|-1.5|1.3|
|**Total**|1.1|8.7|2.9|-0.2|9.8|1.0|3.2|-0.7|1.2|

- 31 -
Table 8a: Change in the volume of exports in 2030, percent change from baseline, ctd.

||Poland|Rest of<br>Eastern<br>Europe|Kazakhstan|Kyrgyz<br>Republic|Rest of<br>Central<br>Asia|Iran,<br>Islamic<br>Rep.|Egypt,<br>Arab<br>Rep.|Turkey|Rest of<br>MENA|
|---|---|---|---|---|---|---|---|---|---|
|Agriculture|1.8|3.3|22.6|-13.1|9.4|4.6|4.7|1.4|0.8|
|Minerals n.e.s.|0.5|-0.3|-0.3|-5.6|1.4|2.7|0.2|-2.8|-0.9|
|Coal|-4.7|11.8|1.9|146.6|46.5|76.5|||11.1|
|Oil||-1.9|-1.4|-32.8|-1.1|-6.3|0.6|-16.6|0.2|
|Gas|3.2|-0.5|-2.5||3.2|0.6|1.5|4.6|0.9|
|Textiles|0.8|0.2|1.5|22.6|4.1|13.5|-0.4|1.9|-0.4|
|Wearingapparel|0.0|0.5|1.8|34.9|6.1|14.7|-1.4|3.1|-2.6|
|Leathergoods|-0.2|-2.5|1.7|158.8|14.8|13.2|1.6|4.8|-3.8|
|Processed foods|1.6|2.9|16.9|-6.0|22.4|7.1|2.4|1.3|0.5|
|Woodproducts|-0.2|-0.4|7.9|32.1|14.1|16.7|4.5|8.9|-5.9|
|Paper products,<br>publishing|0.3|0.3|1.0|6.9|8.7|15.9|0.5|0.0|-3.2|
|Petroleum, coal<br>products|-1.5|4.4|7.7|6.9|-0.4|14.0|1.3|21.8|8.6|
|Chemical, rubber,<br>plastic|0.0|0.6|2.3|0.7|10.4|35.7|0.7|7.3|5.6|
|Energyintensive man.|-0.5|-2.0|3.3|4.0|-1.8|8.1|-2.2|3.0|0.5|
|Metalproducts|-0.7|-1.4|11.0|29.0|23.5|18.7|-5.1|7.3|-3.7|
|Electronics|-7.7|-11.3|-15.4|26.2|4.3|37.6|-30.4|14.8|-0.8|
|Machinery and<br>equipment|-1.5|-0.3|2.5|51.8|67.1|13.3|-6.5|4.6|-8.2|
|Transport equipment|-0.2|-1.4|53.1|5.1|52.7|20.1|0.8|21.7|-2.1|
|Manufactures,n.e.s.|-1.7|-2.3|6.6|24.0|9.0|13.9|0.3|13.0|-0.9|
|Electricity|0.4|-0.2|1.0|-2.2|0.7|1.0|0.9|-1.3|0.9|
|Construction|1.4|1.1|3.0|29.4|15.0|15.1|2.1|11.7|6.3|
|Trade services|1.4|0.1|3.9|14.7|13.6|10.2|0.6|1.5|7.3|
|Other transport|-0.3|0.5|1.9|17.8|7.0|13.1|-0.4|12.3|3.5|
|Water transport|-0.7|3.8|0.8|20.4|7.1|7.8|-1.2|8.3|5.4|
|Air transport|-0.9|2.2|3.2|23.1|6.1|42.4|-0.5|12.8|3.0|
|Hospitalityservices|3.1|-0.6|0.1|-7.6|0.0|-2.3|1.3|-8.9|1.2|
|Other business services|2.7|-1.2|0.2|-15.0|-0.4|-2.3|0.6|-12.9|0.4|
|Other services|0.8|-0.2|0.0|-1.5|-0.2|-1.0|0.4|-3.3|0.1|
|**Agriculture**|1.8|3.3|22.6|-13.1|9.4|4.6|4.7|1.4|0.8|
|**Manufacturing**|-0.7|0.5|5.1|11.6|9.5|21.4|-1.8|7.1|3.1|
|**Services**|1.5|0.3|1.1|8.4|3.5|9.2|0.2|3.1|2.1|
|**Other**|-3.2|0.7|-1.3|-1.6|-0.3|-5.4|0.6|-2.8|0.2|
|**Total**|-0.4|0.8|1.1|5.4|2.6|4.2|-0.2|5.8|1.4|

- 32 -
Table 8a: Change in the volume of exports in 2030, percent change from baseline, ctd.

||Kenya|Tanzania|Non-BRI<br>Area|Ethiopia|Rest of<br>Sub-<br>Saharan<br>Africa|Latin<br>America<br>and<br>Caribbean|United<br>States|Rest of<br>High-<br>income|Rest of<br>Western<br>Europe|
|---|---|---|---|---|---|---|---|---|---|
|Agriculture|3.2|1.7|3.1|5.5|2.3|2.6|5.4|4.8|1.2|
|Minerals n.e.s.|-0.3|-1.8|-0.2|-1.2|-0.2|0.2|-0.3|-0.7|0.1|
|Coal||13.3|2.1||5.5|7.0|3.7|-1.0|-5.5|
|Oil|||1.1||0.3|2.8|-0.5|-0.4|1.2|
|Gas|||0.2||0.9|0.7|1.5|-0.9|0.0|
|Textiles|3.1|0.2|1.5|4.6|1.2|0.2|3.1|2.7|0.0|
|Wearingapparel|-1.1|14.5|0.4|2.0|4.6|0.2|2.9|2.0|-0.1|
|Leathergoods|3.4|26.1|1.1|12.3|2.7|3.8|6.9|2.3|-0.3|
|Processed foods|-2.0|-0.1|2.1|2.7|2.4|3.4|3.8|1.5|1.1|
|Woodproducts|-5.0|13.9|2.7|7.1|-0.4|2.7|9.0|5.7|0.0|
|Paper products,<br>publishing|-9.0|5.4|2.3|6.1|0.8|0.4|6.1|4.9|0.5|
|Petroleum, coal<br>products|5.6||-0.8||-1.3|-0.8|0.5|-1.4|-1.4|
|Chemical, rubber,<br>plastic|-7.0|12.0|0.5|8.7|0.3|-0.5|2.7|1.9|-0.7|
|Energyintensive man.|-4.6|6.6|0.6|5.4|-0.2|0.8|2.4|1.4|-0.1|
|Metalproducts|5.3|-8.0|0.7|-2.6|0.9|-2.5|2.2|4.7|-1.0|
|Electronics|2.6|20.8|-3.6|-1.2|-8.8|-18.0|14.9|-3.9|-8.2|
|Machinery and<br>equipment|10.4|10.3|0.9|-0.8|-0.9|-6.4|3.9|4.4|-0.6|
|Transport equipment|23.6|15.9|1.3|3.1|0.4|-4.2|3.0|5.7|-0.6|
|Manufactures,n.e.s.|-7.2|8.5|0.6|13.2|9.7|-5.1|5.2|0.9|-1.3|
|Electricity|1.2||0.3|-0.8|-0.1|0.8|0.5|0.4|0.2|
|Construction|0.0|2.7|2.4|4.0|2.1|-0.6|3.6|4.3|1.3|
|Trade services|-2.0|-2.2|1.9|6.7|3.0|2.4|4.2|1.6|1.7|
|Other transport|2.6|15.5|0.5|1.0|1.5|0.6|4.0|0.5|-0.9|
|Water transport|8.2|21.3|-0.4|0.5|-1.6|-0.1|-0.3|2.7|-1.2|
|Air transport|4.9|21.4|0.2|1.7|2.6|0.9|1.9|2.9|-1.0|
|Hospitalityservices|-17.2|-7.9|1.8|-3.8|0.6|2.7|1.8|0.4|2.0|
|Other business services|-12.0|-13.8|1.1|-3.8|0.6|2.5|0.0|-0.3|1.6|
|Other services|-3.0|-3.6|0.3|-1.5|0.2|0.8|0.1|0.1|0.5|
|**Agriculture**|3.2|1.7|3.1|5.5|2.3|2.6|5.4|4.8|1.2|
|**Manufacturing**|-1.5|4.8|0.5|5.4|0.7|-2.1|4.0|1.5|-0.8|
|**Services**|-2.1|-2.4|1.0|0.1|1.0|1.6|1.0|1.0|0.8|
|**Other**|-0.3|-1.7|0.7|-1.2|0.4|1.9|1.5|-0.7|0.4|
|**Total**|0.2|2.5|0.7|3.9|0.8|-0.5|3.4|1.4|-0.3|

- 33 -
Table 8b: Change in the volume of exports in 2030, difference from baseline in $2014 million

||World|BRI Area|Cambodia|China|Indonesia|Lao PDR|Malaysia|Philippines|Thailand|Vietn|
|---|---|---|---|---|---|---|---|---|---|---|
|Agriculture|32653|5983|-97|1734|180|-289|-751|52|-959||
|Minerals n.e.s.|-1714|-883|-5|-32|-105|64|-94|-122|-109||
|Coal|4565|3083|0|-381|1088|25|0|-23|0|-|
|Oil|-654|-8623|0|-28|-143|32|-3411|2|-170|-|
|Gas|1343|1130|0|40|409|-7|-2428|0|-17||
|Textiles|10796|7677|16|5880|409|7|-92|-6|-1022||
|Wearingapparel|11832|11072|479|3484|229|-70|-304|-108|-573||
|Leathergoods|6753|5328|463|2694|-105|38|-9|-12|823|1|
|Processed foods|43684|16011|-47|1558|3475|-21|-969|335|628|1|
|Woodproducts|4572|2250|-60|3222|-58|-69|-702|-101|-537|-|
|Paperproducts, publishing|9690|2870|10|2769|192|-2|-238|31|122||
|Petroleum,coalproducts|28025|33466|0|1270|-120|21|310|-13|4632||
|Chemical,rubber, plastic|52343|41276|-40|13333|-629|148|-946|-11|-635||
|Energyintensive man.|16809|8975|41|3182|1300|199|227|-84|148|-|
|Metalproducts|13670|11685|15|8673|129|13|210|56|777||
|Electronics|129909|172507|340|37360|-1032|41|73593|5319|49703|4|
|Machineryand equipment|85096|70106|229|47377|1317|44|4022|-4|16071||
|Transport equipment|54236|27102|482|6162|764|6|875|-136|11605||
|Manufactures,n.e.s.|20106|18160|65|4680|89|8|-2887|-61|967|1|
|Electricity|272|130|0|16|0|8|0|0|-7||
|Construction|4224|1949|3|836|25|1|-278|5|60||
|Trade services|13226|4982|-21|2396|55|6|-213|27|-1396||
|Other transport|11287|9614|436|1549|72|72|-236|68|-7||
|Water transport|998|1635|84|164|-5|3|279|-10|137||
|Air transport|8963|8261|458|735|112|10|1307|66|1306||
|Hospitalityservices|762|-2730|-286|-113|-23|29|-991|-28|-754||
|Other business services|1348|-14438|-66|-707|-109|-26|-3888|-345|-3181|-|
|Other services|45|-812|-13|-43|-6|-3|-176|-10|-250||
|**Agriculture**|32653|5983|-97|1734|180|-289|-751|52|-959||
|**Manufacturing**|487521|428485|1993|141644|5961|364|73092|5207|82710|10|
|**Services**|41124|8590|596|4832|121|100|-4197|-227|-4092||
|**Other**|3540|-5294|-5|-400|1250|114|-5933|-143|-295|-1|
|**Total**|564837|437765|2487|147809|7511|288|62211|4888|77364|9|

- 34 -
Table 8b: Change in the volume of exports in 2030, difference from baseline in $2014 million, ctd.

||Rest of<br>East<br>Asia|Bangladesh|India|Nepal|Pakistan|Sri<br>Lanka|Rest of<br>South<br>Asia|EU ECA|Russian<br>Federation|
|---|---|---|---|---|---|---|---|---|---|
|Agriculture|444|-125|519|11|-905|-22|33|562|1619|
|Minerals n.e.s.|-77|4|5|-1|-45|-2|7|3|-42|
|Coal|1113|0|1|0|0|0|2|-59|1647|
|Oil|-198|0|0|0|2|0|-15|1|1689|
|Gas|498|-6|1|0|1|0|126|2|917|
|Textiles|-18|467|1183|21|67|-23|11|49|27|
|Wearingapparel|226|6406|-436|21|940|144|5|-8|14|
|Leathergoods|-50|21|203|-2|-164|8|0|-168|-37|
|Processed foods|-508|74|2389|-26|2447|-60|-6|417|1221|
|Woodproducts|12|-2|31|1|-71|7|2|16|664|
|Paper products,<br>publishing|-140|5|39|2|63|-9|3|55|265|
|Petroleum, coal<br>products|-2383|78|3789|0|131|5|26|65|2015|
|Chemical, rubber,<br>plastic|-1812|130|8418|-35|2731|146|41|-360|398|
|Energyintensive man.|-89|250|1755|-33|645|-16|16|-288|289|
|Metalproducts|77|23|992|21|198|3|5|-197|47|
|Electronics|8771|709|1312|0|72|43|12|-4579|-658|
|Machinery and<br>equipment|340|480|3924|1|109|131|8|-2035|-624|
|Transport equipment|196|166|-1068|0|179|-2|12|-944|-151|
|Manufactures,n.e.s.|5273|453|6335|37|1476|197|7|-335|195|
|Electricity|1|0|0|0|0|0|2|73|17|
|Construction|-35|-10|118|2|19|1|3|61|30|
|Trade services|-382|-13|1363|5|-20|9|9|355|37|
|Other transport|-216|-16|2209|7|-41|29|67|43|39|
|Water transport|-241|-33|273|0|-83|45|3|-39|56|
|Air transport|-300|-5|146|2|-238|4|51|33|-29|
|Hospitalityservices|-252|41|16|-12|46|-9|-3|397|101|
|Other business services|-2361|-136|-2540|-44|71|-172|-56|1242|-187|
|Other services|-54|-136|-13|-3|45|-1|-5|45|0|
|**Agriculture**|444|-125|519|11|-905|-22|33|562|1619|
|**Manufacturing**|9895|9262|28868|7|8821|573|141|-8310|3664|
|**Services**|-3842|-308|1573|-42|-202|-94|71|2211|63|
|**Other**|1337|-2|7|-1|-42|-2|120|-54|4210|
|**Total**|7834|8827|30967|-25|7673|456|364|-5591|9556|

- 35 -
Table 8b: Change in the volume of exports in 2030, difference from baseline in $2014 million, ctd.

||Poland|Rest of<br>Eastern<br>Europe|Kazakhstan|Kyrgyz<br>Republic|Rest of<br>Central Asia|Iran,<br>Islamic<br>Rep.|<br>Egypt,<br>Arab<br>Rep.|Turkey|Rest of<br>MENA|
|---|---|---|---|---|---|---|---|---|---|
|Agriculture|161|762|1010|-395|278|181|512|362|181|
|Minerals n.e.s.|2|-28|-16|-9|33|140|3|-173|-242|
|Coal|-56|108|64|18|4|15|0|0|3|
|Oil|0|-11|-1648|-13|-702|-5064|218|-1|1727|
|Gas|0|0|-32|0|423|29|41|1|1127|
|Textiles|37|6|1|26|51|63|-27|482|-28|
|Wearingapparel|3|20|2|139|57|6|-97|898|-632|
|Leathergoods|-6|-52|3|136|24|14|17|131|-292|
|Processed foods|643|911|759|-39|790|87|277|419|272|
|Woodproducts|-13|-12|1|5|7|1|19|118|-81|
|Paperproducts, publishing|36|8|1|6|10|8|10|-1|-318|
|Petroleum,coalproducts|-99|1058|620|3|-31|2875|96|1352|17775|
|Chemical,rubber, plastic|12|122|280|7|398|5424|103|1918|11519|
|Energyintensive man.|-113|-755|631|121|-129|237|-209|1107|415|
|Metalproducts|-73|-41|28|15|17|15|-61|615|-472|
|Electronics|-1456|-288|-438|34|14|19|-1140|655|-361|
|Machineryand equipment|-604|-29|65|246|367|17|-265|1287|-3169|
|Transport equipment|-84|-125|645|10|1090|68|5|7534|-535|
|Manufactures,n.e.s.|-304|-46|16|18|33|19|3|1292|-394|
|Electricity|8|-3|3|-13|13|9|2|-8|13|
|Construction|46|6|3|41|106|122|53|226|438|
|Trade services|53|3|16|359|322|325|13|49|1571|
|Other transport|-27|47|19|189|182|761|-85|2666|1477|
|Water transport|-4|96|1|6|63|130|-6|202|312|
|Air transport|-21|74|22|102|126|1790|-15|1452|611|
|Hospitalityservices|79|-8|0|-45|0|-16|43|-953|86|
|Other business services|479|-98|3|-108|-37|-271|62|-1484|457|
|Other services|15|-6|0|-4|-4|-20|9|-79|11|
|**Agriculture**|161|762|1010|-395|278|181|512|362|181|
|**Manufacturing**|-2019|779|2615|725|2699|8854|-1267|17807|23700|
|**Services**|628|112|67|526|771|2831|76|2072|4977|
|**Other**|-54|69|-1631|-3|-241|-4881|262|-174|2615|
|**Total**|-1283|1721|2060|853|3506|6985|-418|20068|31473|

- 36 -
Table 8b: Change in the volume of exports in 2030, difference from baseline in $2014 million, ctd.

||Kenya|Tanzania|Non-BRI<br>Area|Ethiopia|Rest of<br>Sub-<br>Saharan<br>Africa|Latin<br>America<br>and<br>Caribbean|United<br>States|Rest of<br>High-<br>income|Rest of<br>Western<br>Europe|
|---|---|---|---|---|---|---|---|---|---|
|Agriculture|454|170|26671|567|3142|6746|8068|5891|2256|
|Minerals n.e.s.|-1|-16|-831|0|-162|203|-47|-854|30|
|Coal|0|1|1483|0|740|619|484|-349|-12|
|Oil|0|0|7969|0|1276|6319|-2|-215|592|
|Gas|0|0|213|0|188|83|176|-245|12|
|Textiles|6|1|3118|5|43|32|921|2152|-35|
|Wearingapparel|-15|55|760|3|336|85|222|274|-160|
|Leathergoods|28|67|1425|41|104|870|460|253|-303|
|Processed foods|-74|-5|27673|13|1525|10600|6296|2583|6656|
|Woodproducts|-10|23|2321|1|-36|317|1263|791|-14|
|Paper products,<br>publishing|-60|7|6821|0|53|134|3729|2089|814|
|Petroleum, coal<br>products|20|0|-5441|0|-173|-710|1009|-1951|-3615|
|Chemical, rubber,<br>plastic|-196|55|11068|3|111|-613|10313|9716|-8463|
|Energyintensive man.|-61|366|7834|26|-291|1228|3190|3966|-285|
|Metalproducts|11|-17|1985|0|50|-422|1093|2709|-1445|
|Electronics|9|19|-42599|-1|-498|-18536|23964|-24505|-23022|
|Machinery and<br>equipment|72|27|14989|-1|-210|-9426|13032|16137|-4542|
|Transport equipment|92|28|27134|2|135|-9639|12539|29851|-5755|
|Manufactures,n.e.s.|-30|14|1946|9|1249|-2339|4830|332|-2135|
|Electricity|0|0|142|0|-4|44|7|22|73|
|Construction|0|1|2275|3|29|-17|389|1199|672|
|Trade services|-1|-18|8245|17|188|521|1315|2207|3996|
|Other transport|14|112|1673|2|214|253|2432|172|-1400|
|Water transport|50|9|-637|0|-53|-19|-10|548|-1102|
|Air transport|118|30|702|40|259|160|1075|1560|-2392|
|Hospitalityservices|-3|-23|3492|-5|50|453|1046|95|1854|
|Other business services|-280|-194|15786|-39|140|2394|11|-559|13838|
|Other services|-79|-9|857|-13|24|166|67|46|567|
|**Agriculture**|454|170|26671|567|3142|6746|8068|5891|2256|
|**Manufacturing**|-210|639|59036|103|2398|-28419|82861|44397|-42304|
|**Services**|-182|-91|32534|5|846|3955|6331|5290|16107|
|**Other**|-1|-16|8833|0|2042|7223|611|-1663|621|
|**Total**|61|702|127074|675|8428|-10494|97871|53914|-23320|

- 37 -
Table 9a: Change in the volume of imports in 2030, percent change from baseline

||World|BRI<br>Area|Cambodia|China|Indonesia|Lao<br>PDR|Malaysia|Philippines|Thailand|Vietnam|
|---|---|---|---|---|---|---|---|---|---|---|
|Agriculture|4.6|6.2|17.3|4.4|3.8|7.4|19.1|7.3|24.0|6.2|
|Minerals n.e.s.|0.4|0.6|4.9|0.7|0.5|7.8|-1.8|-0.4|4.4|0.7|
|Coal|4.8|7.8|8.2|9.7|2.5|24.2|9.0|-0.4|22.7|9.0|
|Oil|0.0|1.0|-9.5|0.2|-0.6|1.6|19.0|-1.1|10.2|2.9|
|Gas|0.5|1.8|-16.0|0.0|-0.1|22.2|8.2|6.1|6.9||
|Textiles|2.8|3.9|3.2|4.0|1.7|2.3|7.5|1.0|12.1|1.6|
|Wearingapparel|2.4|4.4|10.8|5.6|0.7|14.1|17.6|2.0|30.9|1.5|
|Leathergoods|3.1|5.7|16.4|5.5|4.6|13.6|15.6|-0.2|21.7|5.2|
|Processed foods|3.5|5.6|17.9|5.4|5.5|10.2|18.5|4.7|19.1|6.5|
|Woodproducts|4.1|6.1|26.2|8.3|7.0|8.4|24.5|4.2|13.2|2.2|
|Paper products,<br>publishing|3.7|5.6|4.1|10.3|2.8|6.7|14.3|2.8|14.2|2.7|
|Petroleum, coal<br>products|5.1|7.8|17.7|12.1|2.6|9.8|12.4|5.6|36.9|5.6|
|Chemical, rubber,<br>plastic|3.0|5.0|4.1|6.7|3.6|7.7|12.8|2.1|13.4|2.7|
|Energyintensive man.|2.4|4.0|6.4|5.9|1.5|4.4|9.7|0.0|19.5|2.4|
|Metalproducts|4.0|5.5|6.2|6.7|5.0|3.4|15.8|1.2|13.9|1.8|
|Electronics|6.9|10.5|18.0|7.6|4.1|5.0|34.5|8.5|45.6|2.9|
|Machinery and<br>equipment|4.8|6.7|7.8|7.7|2.9|4.8|18.2|3.2|18.8|1.1|
|Transport equipment|3.8|6.1|13.0|7.7|10.3|3.0|15.6|5.9|20.5|4.0|
|Manufactures,n.e.s.|3.9|6.2|8.3|14.5|1.5|9.9|9.3|1.9|16.0|6.7|
|Electricity|0.3|1.1|-2.2|0.8||2.5|8.0||8.3|1.7|
|Construction|5.9|8.3|18.3|9.1|5.6|19.8|21.3|8.0|20.2|5.1|
|Trade services|4.6|7.2|25.8|5.9|5.6|13.8|30.1|5.9|38.5|9.9|
|Other transport|4.7|7.5|15.5|10.2|6.0|18.4|6.7|7.7|29.3|8.3|
|Water transport|2.9|4.3|14.7|13.2|6.7|14.7|3.6|10.2|2.0|6.6|
|Air transport|4.2|6.9|13.4|9.0|6.6|15.7|8.9|8.0|24.7|8.0|
|Hospitalityservices|0.3|1.8|10.6|0.6|0.7|0.3|14.9|1.0|18.5|1.9|
|Other business services|0.1|1.4|8.6|0.6|0.4|0.6|11.0|1.2|17.8|2.7|
|Other services|0.1|0.7|6.7|0.7|0.5|1.3|10.4|1.1|16.6|2.4|
|**Agriculture**|4.6|6.2|17.3|4.4|3.8|7.4|19.1|7.3|24.0|6.2|
|**Manufacturing**|4.1|6.4|9.2|7.4|3.6|5.4|19.5|4.4|23.4|3.0|
|**Services**|1.9|3.9|12.9|4.5|2.9|7.7|12.8|3.9|22.3|4.4|
|**Other**|0.4|1.4|5.0|0.9|-0.5|7.6|12.2|-0.9|10.0|1.6|
|**Total**|3.4|5.4|9.5|5.6|3.4|5.7|18.5|4.0|21.4|3.2|

- 38 -
Table 9a: Change in the volume of imports in 2030, percent change from baseline, ctd.

||Rest of<br>East<br>Asia|Bangladesh|India|Nepal|Pakistan|Sri<br>Lanka|Rest of<br>South<br>Asia|EU ECA|Russian<br>Federation|
|---|---|---|---|---|---|---|---|---|---|
|Agriculture|6.4|30.6|4.9|6.3|52.4|7.0|-2.4|0.7|5.2|
|Minerals n.e.s.|0.9|1.8|0.2|0.1|12.1|-1.6|1.2|-0.4|0.0|
|Coal|10.2|17.7|5.6|-1.7|4.4|0.3|8.1|2.7|1.9|
|Oil|-2.3|12.7|1.2|1.7|-9.5|-1.5|2.8|-0.6|-0.3|
|Gas|1.0||0.8|3.7|||8.4|0.1|1.3|
|Textiles|5.7|6.4|5.2|1.2|20.0|1.9|1.7|0.2|1.9|
|Wearingapparel|3.7|10.1|5.4|1.6|19.4|3.6|2.2|0.5|2.3|
|Leathergoods|5.0|12.5|6.6|3.7|30.9|2.4|7.9|0.3|3.2|
|Processed foods|5.7|12.4|3.1|2.9|19.1|5.4|7.4|0.4|2.9|
|Woodproducts|9.3|18.9|9.3|4.1|48.3|3.2|-1.0|0.1|3.2|
|Paper products,<br>publishing|1.6|0.0|8.4|1.5|0.2|0.9|2.1|0.0|1.8|
|Petroleum, coal<br>products|1.8|10.2|7.9|0.5|16.1|3.6|3.8|1.3|4.4|
|Chemical, rubber,<br>plastic|2.5|3.4|5.9|-1.7|-8.6|3.3|5.8|-0.2|1.7|
|Energyintensive man.|2.2|-4.3|2.9|-0.6|1.9|1.3|3.0|-0.7|1.0|
|Metalproducts|5.2|-6.0|10.0|2.5|-2.3|3.3|8.0|-0.1|2.5|
|Electronics|7.4|3.4|10.4|6.9|6.3|8.7|5.2|-2.0|2.7|
|Machinery and<br>equipment|3.2|-0.4|12.9|0.4|4.8|5.3|3.0|0.1|4.7|
|Transport equipment|4.2|-6.6|10.3|0.6|-5.5|0.6|3.8|0.0|2.3|
|Manufactures,n.e.s.|5.3|-21.2|7.0|2.3|-3.0|4.0|4.9|0.7|3.5|
|Electricity|1.2||0.7|-3.6|5.6||1.5|0.0|0.7|
|Construction|5.2|16.6|10.8|6.4|15.4|10.1|12.8|1.5|6.2|
|Trade services|3.6|-7.3|10.9|7.6|4.1|12.3|9.9|0.7|4.2|
|Other transport|3.7|1.7|9.0|6.5|9.5|9.5|8.0|2.1|6.5|
|Water transport|3.1|3.4|3.5|5.5|14.0|7.7|7.0|1.6|3.7|
|Air transport|4.3|10.0|5.2|6.8|11.6|11.6|10.1|1.0|4.9|
|Hospitalityservices|0.9|-0.7|0.6|1.2|4.1|1.5|2.2|-0.5|-0.1|
|Other business services|0.9|4.2|0.2|0.8|8.3|2.1|1.4|-1.1|0.9|
|Other services|0.9|-2.3|0.7|0.6|-0.4|1.6|1.9|-0.8|0.4|
|**Agriculture**|6.4|30.6|4.9|6.3|52.4|7.0|-2.4|0.7|5.2|
|**Manufacturing**|4.5|3.7|6.7|0.8|6.7|2.9|5.2|-0.2|2.7|
|**Services**|2.1|3.9|2.7|3.5|7.7|5.8|4.7|0.0|2.9|
|**Other**|-1.8|11.5|1.3|-1.2|-7.4|-1.5|1.5|-0.3|0.9|
|**Total**|3.2|7.4|4.4|1.2|9.3|3.0|4.5|-0.1|2.8|

- 39 -
Table 9a: Change in the volume of imports in 2030, percent change from baseline, ctd.

||Poland|Rest of<br>Eastern<br>Europe|Kazakhstan|Kyrgyz<br>Republic|Rest of<br>Central<br>Asia|Iran,<br>Islamic<br>Rep.|Egypt,<br>Arab<br>Rep.|Turkey|Rest of<br>MENA|
|---|---|---|---|---|---|---|---|---|---|
|Agriculture|1.3|4.9|11.2|35.1|18.5|7.6|2.9|13.4|2.7|
|Minerals n.e.s.|-0.5|-1.0|1.7|4.2|2.0|2.7|-0.2|1.9|0.3|
|Coal|2.8|5.1|4.7|15.0|76.5|57.2|0.1|11.7|1.6|
|Oil|-0.6|0.4|3.1|28.0|-0.1|7.3|-0.4|2.4|3.6|
|Gas|0.4|0.1|-0.6|7.9|2.4|8.1|2.4|2.2|1.1|
|Textiles|0.2|1.2|1.9|18.6|3.9|4.6|1.7|9.1|2.5|
|Wearingapparel|0.8|2.2|1.3|10.4|2.9|3.8|0.4|14.9|4.5|
|Leathergoods|0.5|1.5|1.4|30.8|3.7|4.7|0.7|13.5|7.5|
|Processed foods|0.9|3.9|4.3|34.0|11.1|6.5|1.8|14.0|3.2|
|Woodproducts|0.3|3.2|3.3|4.7|1.0|1.6|0.3|10.4|6.5|
|Paper products,<br>publishing|0.2|2.1|3.3|13.5|3.4|4.5|0.4|10.0|2.6|
|Petroleum, coal<br>products|1.4|10.7|5.8|14.4|10.4|32.3|3.5|13.6|4.3|
|Chemical, rubber,<br>plastic|0.2|0.8|2.8|9.9|2.9|9.9|0.6|7.6|4.4|
|Energyintensive man.|-0.5|-0.4|2.4|16.9|4.5|2.9|0.2|4.7|1.7|
|Metalproducts|0.8|0.1|2.1|14.8|3.4|7.3|1.2|11.0|7.0|
|Electronics|-0.3|4.2|5.5|52.1|6.6|10.5|1.5|10.9|14.3|
|Machinery and<br>equipment|0.4|2.1|2.7|39.2|5.0|9.5|-0.2|9.8|6.9|
|Transport equipment|1.0|3.4|7.0|18.0|11.2|7.3|0.2|10.4|4.8|
|Manufactures,n.e.s.|1.5|2.7|2.0|18.6|2.3|3.2|0.1|8.1|1.8|
|Electricity|-0.2|0.5|-0.4|7.3|1.4|4.3|-2.2|3.2|1.0|
|Construction|0.8|4.2|7.1|44.1|3.2|9.5|2.7|16.5|8.1|
|Trade services|0.6|3.8|7.0|58.8|10.9|0.7|2.3|12.9|6.7|
|Other transport|2.2|3.8|9.1|18.9|7.4|5.3|2.0|-1.4|6.7|
|Water transport|2.4|2.7|10.2|25.5|4.9|-2.2|2.5|-6.0|3.9|
|Air transport|1.1|2.7|7.8|8.6|5.3|6.4|0.6|7.0|5.5|
|Hospitalityservices|-1.2|0.7|0.3|2.0|0.8|3.1|-0.2|6.5|-0.2|
|Other business services|-1.1|0.4|-0.1|6.8|0.6|2.9|-0.9|8.0|-0.4|
|Other services|-0.9|0.5|0.1|1.9|0.4|1.9|-0.8|3.5|-0.2|
|**Agriculture**|1.3|4.9|11.2|35.1|18.5|7.6|2.9|13.4|2.7|
|**Manufacturing**|0.4|2.9|3.2|17.9|6.1|8.8|1.0|9.2|5.0|
|**Services**|0.0|1.7|3.7|12.9|2.9|3.3|0.0|6.2|2.3|
|**Other**|-0.2|0.4|1.6|11.9|3.0|7.8|-0.3|3.2|1.8|
|**Total**|0.3|2.2|3.4|17.5|6.1|7.4|1.0|8.5|4.3|

- 40 -
Table 9a: Change in the volume of imports in 2030, percent change from baseline, ctd.

||Kenya|Tanzania|Non-BRI<br>Area|Ethiopia|Rest of<br>Sub-<br>Saharan<br>Africa|Latin<br>America<br>and<br>Caribbean|United<br>States|Rest of<br>High-<br>income|Rest of<br>Western<br>Europe|
|---|---|---|---|---|---|---|---|---|---|
|Agriculture|10.6|18.2|2.1|10.6|3.1|1.3|3.4|4.0|1.0|
|Minerals n.e.s.|2.2|2.0|-0.1|1.5|0.1|-0.4|0.2|-0.2|-0.2|
|Coal|-3.6|30.0|1.6|8.4|11.8|2.7|13.4|1.2|1.1|
|Oil|-4.0|-3.3|-0.7|-5.8|-0.9|-1.2|0.0|-1.1|-1.1|
|Gas|||-0.2|-5.9|-0.4|-0.4|0.3|-0.4|-0.1|
|Textiles|5.3|6.1|1.4|6.9|1.0|-0.1|4.0|1.9|0.8|
|Wearingapparel|9.0|7.6|1.6|7.1|1.0|-0.3|2.8|2.3|1.0|
|Leathergoods|9.8|8.3|1.8|11.1|1.6|0.4|3.0|2.3|1.1|
|Processed foods|12.3|15.8|2.1|10.3|2.1|0.9|4.3|3.4|1.1|
|Woodproducts|21.6|13.2|2.8|13.8|3.0|0.5|7.9|3.4|1.0|
|Paper products,<br>publishing|10.1|3.1|2.6|3.9|2.0|0.5|6.1|4.8|1.5|
|Petroleum, coal<br>products|6.3|4.7|3.4|1.3|2.1|1.6|4.8|8.9|1.3|
|Chemical, rubber,<br>plastic|6.6|3.6|1.8|3.9|1.7|0.4|5.5|3.0|0.3|
|Energyintensive man.|0.9|4.5|0.9|4.1|0.9|-0.8|2.4|2.9|-0.2|
|Metalproducts|5.5|6.0|3.1|13.6|2.2|-0.4|8.2|4.4|1.8|
|Electronics|18.0|11.2|4.0|5.3|4.7|-0.9|9.8|3.5|1.7|
|Machinery and<br>equipment|3.7|8.2|3.6|12.9|3.4|0.1|9.3|4.3|1.9|
|Transport equipment|2.5|8.7|2.8|10.7|2.3|0.2|5.3|5.6|1.1|
|Manufactures,n.e.s.|14.4|3.6|3.1|9.0|2.0|-0.5|5.0|4.0|2.1|
|Electricity|-0.3|1.2|0.0||-0.2|-0.3|0.3|0.2|0.0|
|Construction|18.0|17.3|4.0|10.8|3.3|3.1|7.2|7.3|2.7|
|Trade services|14.3|19.6|2.8|4.2|3.7|1.5|6.3|5.3|1.2|
|Other transport|17.1|6.0|3.4|8.8|3.7|2.4|3.5|7.0|2.1|
|Water transport|15.0|4.3|2.4|4.3|2.8|1.3|3.5|3.9|1.9|
|Air transport|15.9|2.5|3.3|2.8|3.1|2.9|4.3|5.2|2.0|
|Hospitalityservices|3.6|0.9|-0.4|2.7|0.0|-1.0|-0.4|0.3|-0.7|
|Other business services|5.3|5.8|-0.5|1.1|-0.1|-1.1|-0.1|0.2|-0.7|
|Other services|-1.0|0.9|-0.3|-0.2|-0.1|-0.8|0.1|0.0|-0.7|
|**Agriculture**|10.6|18.2|2.1|10.6|3.1|1.3|3.4|4.0|1.0|
|**Manufacturing**|6.1|7.2|2.6|7.2|2.3|0.1|6.2|4.0|1.1|
|**Services**|6.5|6.4|1.0|4.5|1.2|0.4|1.4|2.7|0.3|
|**Other**|-3.8|2.2|-0.5|2.3|-0.4|-0.7|0.0|-0.7|-0.7|
|**Total**|5.7|7.4|2.0|6.7|2.0|0.1|4.6|3.1|0.8|

- 41 -
Table 9b: Change in the volume of imports in 2030, difference from baseline in $2014 million

||World|BRI<br>Area|Cambodia|China|Indonesia|Lao<br>PDR|Malaysia|Philippines|Thailand|<br>Vietnam|
|---|---|---|---|---|---|---|---|---|---|---|
|Agriculture|59436|48561|118|14690|1852|38|2909|254|3730|<br>1677|
|Minerals n.e.s.|2151|2400|3|2000|12|10|-45|-13|78|<br>9|
|Coal|9944|8369|0|4574|1|2|418|-6|685|<br>15|
|Oil|-672|10296|0|920|-107|0|1689|-109|5640|<br>0|
|Gas|2025|2464|0|0|0|0|253|1|828|<br>0|
|Textiles|18597|14349|353|2631|364|8|446|71|988|<br>671|
|Wearingapparel|23700|11718|70|1323|40|4|2183|49|830|<br>314|
|Leathergoods|14371|9125|112|1639|184|3|964|-4|1025|<br>444|
|Processed foods|74849|49017|1091|9450|1704|139|5753|762|4871|<br>2599|
|Woodproducts|8073|4630|10|2134|63|1|338|52|155|<br>82|
|Paper products,<br>publishing|18073|10610|33|5630|241|22|676|86|714|<br>172|
|Petroleum, coal<br>products|75615|45501|676|11603|1923|64|2684|487|4835|<br>1350|
|Chemical, rubber,<br>plastic|117188|76027|168|32992|2238|156|7054|488|7751|<br>1531|
|Energyintensive man.|53377|42422|325|14030|511|103|4247|2|10788|<br>946|
|Metalproducts|24375|12372|36|1922|554|43|1386|69|2130|<br>273|
|Electronics|244198|164697|193|54046|1382|82|32245|3840|30691|<br>2665|
|Machinery and<br>equipment|159200|86344|241|24256|1829|202|9318|911|13344|<br>610|
|Transport equipment|111953|57289|418|19032|2617|82|3700|1058|6429|<br>513|
|Manufactures,n.e.s.|38042|16519|44|8764|88|12|973|43|1323|<br>433|
|Electricity|272|284|-5|11|0|2|5|0|133|<br>13|
|Construction|9087|5713|33|772|100|109|854|10|366|<br>67|
|Trade services|29891|18840|88|8167|344|19|878|63|3451|<br>173|
|Other transport|28428|14304|16|5227|284|7|278|93|1584|<br>131|
|Water transport|5832|2217|2|541|81|2|62|19|49|<br>51|
|Air transport|22381|9801|41|2533|344|7|413|141|1567|<br>132|
|Hospitalityservices|762|1586|6|131|15|0|884|6|336|<br>22|
|Other business services|1348|9230|26|751|67|6|2052|48|3999|<br>262|
|Other services|209|1073|11|181|13|1|250|10|400|<br>36|
|**Agriculture**|59436|48561|118|14690|1852|38|2909|254|3730|<br>1677|
|**Manufacturing**|981611|600618|3771|189451|13738|923|71967|7913|85874|<br>12604|
|**Services**|98210|63048|218|18313|1249|151|5677|391|11884|<br>888|
|**Other**|13448|23530|4|7495|-94|13|2315|-127|7232|<br>24|
|**Total**|1152703|735758|4110|229950|16745|1125|82868|8431|108720|<br>15192|

- 42 -
Table 9b: Change in the volume of imports in 2030, difference from baseline in $2014 million, ctd.

||Rest of<br>East<br>Asia|Bangladesh|India|Nepal|Pakistan|Sri<br>Lanka|Rest of<br>South<br>Asia|EU ECA|Russian<br>Federation|
|---|---|---|---|---|---|---|---|---|---|
|Agriculture|879|4604|3447|24|4184|129|-27|168|1501|
|Minerals n.e.s.|37|6|155|0|31|-5|12|-28|0|
|Coal|8|30|1567|-2|37|0|1|73|65|
|Oil|-1589|248|2950|0|-682|-42|2|-273|0|
|Gas|69|0|129|0|0|0|0|6|30|
|Textiles|626|1475|796|5|1588|130|13|42|282|
|Wearingapparel|527|110|237|39|100|22|10|111|1010|
|Leathergoods|505|154|415|13|262|5|10|46|492|
|Processed foods|3031|1593|2182|13|1153|176|464|286|1595|
|Woodproducts|170|9|247|0|149|5|-4|5|74|
|Paper products,<br>publishing|149|0|868|2|4|9|4|0|176|
|Petroleum, coal<br>products|890|736|2103|6|2460|304|61|326|531|
|Chemical, rubber,<br>plastic|1256|433|6988|-27|-1266|153|85|-197|1075|
|Energyintensive man.|467|-398|3929|-12|135|49|42|-423|275|
|Metalproducts|374|-93|1160|5|-33|29|32|-19|326|
|Electronics|7122|141|8879|36|303|126|47|-1428|1140|
|Machinery and<br>equipment|1781|-53|8732|3|433|131|39|62|2771|
|Transport equipment|2332|-299|2355|4|-230|45|44|-15|1499|
|Manufactures,n.e.s.|1014|-345|1161|3|-26|34|10|118|380|
|Electricity|8|0|7|-4|2|0|2|2|2|
|Construction|85|4|274|0|17|2|14|51|610|
|Trade services|890|-24|1677|9|18|29|19|56|445|
|Other transport|690|3|1046|8|75|25|19|271|1293|
|Water transport|290|1|349|3|16|99|5|25|107|
|Air transport|576|123|840|10|94|8|23|66|574|
|Hospitalityservices|67|0|30|0|10|2|2|-30|-13|
|Other business services|643|48|199|1|420|24|12|-453|444|
|Other services|89|-15|49|0|-3|3|3|-30|32|
|**Agriculture**|879|4604|3447|24|4184|129|-27|168|1501|
|**Manufacturing**|20243|3465|40052|91|5032|1217|858|-1086|11626|
|**Services**|3338|140|4471|28|650|193|99|-40|3495|
|**Other**|-1475|284|4801|-2|-614|-46|16|-222|95|
|**Total**|22984|8493|52770|140|9252|1493|946|-1181|16717|

- 43 -
Table 9b: Change in the volume of imports in 2030, difference from baseline in $2014 million, ctd.

||Poland|Rest of<br>Eastern<br>Europe|Kazakhstan|Kyrgyz<br>Republic|Rest of<br>Central<br>Asia|Iran,<br>Islamic<br>Rep.|Egypt,<br>Arab<br>Rep.|Turkey|Rest of<br>MENA|
|---|---|---|---|---|---|---|---|---|---|
|Agriculture|127|306|365|44|1268|853|484|1979|2590|
|Minerals n.e.s.|-12|-20|33|1|13|8|-4|47|67|
|Coal|64|132|1|13|20|3|0|602|69|
|Oil|-139|107|32|4|0|9|-8|577|1161|
|Gas|15|28|-5|4|46|362|0|466|231|
|Textiles|20|62|60|215|190|262|135|1560|1078|
|Wearingapparel|106|80|162|187|182|91|14|1164|2524|
|Leathergoods|29|35|148|142|90|165|9|561|1523|
|Processed foods|228|516|344|106|1945|1002|288|1604|5363|
|Woodproducts|7|34|33|12|34|17|11|205|733|
|Paper products,<br>publishing|20|91|57|26|64|147|14|663|617|
|Petroleum, coal<br>products|96|1722|153|170|537|2504|542|3604|4625|
|Chemical, rubber,<br>plastic|85|264|350|127|359|1464|154|4763|7086|
|Energyintensive man.|-134|-51|181|150|508|309|38|2620|3592|
|Metalproducts|86|3|78|55|130|369|41|798|2477|
|Electronics|-91|305|328|104|232|730|110|3044|17929|
|Machinery and<br>equipment|156|398|430|280|717|1679|-32|4506|12918|
|Transport equipment|287|245|744|119|898|480|32|3911|10600|
|Manufactures,n.e.s.|94|62|38|48|65|181|2|524|1347|
|Electricity|-2|8|-2|1|26|22|-1|17|35|
|Construction|10|17|469|8|106|90|15|43|1541|
|Trade services|22|80|30|18|156|23|21|172|1939|
|Other transport|129|158|81|79|147|212|36|-32|2372|
|Water transport|18|18|9|2|24|-25|4|-13|468|
|Air transport|32|54|69|19|118|258|11|313|1389|
|Hospitalityservices|-26|13|1|2|7|72|-2|74|-30|
|Other business services|-158|34|-8|18|57|512|-69|586|-404|
|Other services|-17|13|1|1|6|57|-22|100|-98|
|**Agriculture**|127|306|365|44|1268|853|484|1979|2590|
|**Manufacturing**|991|3767|3103|1740|5950|9400|1357|29528|72411|
|**Services**|7|395|650|148|647|1222|-7|1260|7211|
|**Other**|-73|247|62|23|78|383|-11|1692|1528|
|**Total**|1052|4715|4181|1955|7943|11858|1822|34458|83741|

- 44 -
Table 9b: Change in the volume of imports in 2030, difference from baseline in $2014 million, ctd.

||Kenya|Tanzania|Non-BRI<br>Area|Ethiopia|Rest of<br>Sub-<br>Saharan<br>Africa|Latin<br>America<br>and<br>Caribbean|United<br>States|Rest of<br>High-<br>income|Rest of<br>Western<br>Europe|
|---|---|---|---|---|---|---|---|---|---|
|Agriculture|205|165|10875|54|675|769|2720|4232|2425|
|Minerals n.e.s.|2|2|-250|3|25|-57|17|-104|-133|
|Coal|-3|0|1574|2|92|190|212|774|305|
|Oil|-97|0|-10969|0|-296|-814|-120|-4474|-5264|
|Gas|0|0|-439|0|-9|-65|119|-408|-75|
|Textiles|140|137|4248|51|294|-53|2144|962|849|
|Wearingapparel|121|106|11982|100|208|-135|5248|3275|3286|
|Leathergoods|62|92|5246|28|214|78|2217|1205|1503|
|Processed foods|299|462|25832|113|1852|1124|7282|9220|6241|
|Woodproducts|21|32|3444|6|108|35|1743|991|561|
|Paper products,<br>publishing|109|18|7462|10|257|191|2289|2459|2256|
|Petroleum, coal<br>products|319|190|30114|59|1454|2582|6492|14887|4639|
|Chemical, rubber,<br>plastic|340|156|41161|108|1712|1489|22117|12462|3274|
|Energyintensive man.|42|153|10955|95|569|-950|4429|7656|-843|
|Metalproducts|85|55|12003|170|658|-252|5468|3060|2898|
|Electronics|312|183|79502|74|2591|-2451|49265|20560|9463|
|Machinery and<br>equipment|226|457|72856|597|4701|170|36067|17034|14287|
|Transport equipment|110|281|54665|205|2616|541|24295|18002|9005|
|Manufactures,n.e.s.|101|28|21523|24|373|-247|9223|5912|6238|
|Electricity|0|0|-12|0|-16|-17|15|5|0|
|Construction|2|44|3374|112|572|71|278|1181|1160|
|Trade services|16|62|11051|8|585|394|2700|4703|2660|
|Other transport|33|38|14125|21|525|671|2723|5374|4811|
|Water transport|9|2|3615|34|97|247|167|1421|1648|
|Air transport|38|6|12580|58|522|1166|2603|4686|3545|
|Hospitalityservices|3|3|-825|2|2|-182|-82|157|-721|
|Other business services|55|58|-7882|11|-75|-1168|-211|396|-6835|
|Other services|-6|5|-864|0|-26|-212|41|-20|-648|
|**Agriculture**|205|165|10875|54|675|769|2720|4232|2425|
|**Manufacturing**|2285|2349|380992|1641|17606|2121|178281|117686|63657|
|**Services**|151|218|35161|245|2187|970|8234|17904|5620|
|**Other**|-98|2|-10083|4|-188|-747|228|-4212|-5168|
|**Total**|2543|2735|416945|1945|20281|3112|189463|135610|66534|

- 45 -
|Table 10a: Change in real value added in 2030, percent change from baseline|
|---|

||<br>World|<br>BRI<br>Area|<br>Cambo<br>dia|<br>China|<br>Indonesia|<br>Lao<br>PDR|<br>Malaysia|<br>Philipp<br>ines|Thailand|Vietnam|
|---|---|---|---|---|---|---|---|---|---|---|
|Agriculture|0.5|0.5|-0.5|-0.2|-0.1|-0.6|-7.9|-0.1|-2.1|-1.0|
|Minerals n.e.s.|-0.5|-0.5|-0.3|-0.4|-0.1|4.2|-3.8|-1.4|-0.8|-1.6|
|Coal|-0.5|-0.7||-1.0|1.4|68.2|-32.0|-3.5|-33.7|-5.6|
|Oil|-0.2|-0.3||-0.8|-1.1|7.8|-12.2|-2.0|-15.7|-4.1|
|Gas|1.1|1.4||0.5|0.4|-0.5|-7.4|-0.4|-7.4|0.1|
|Textiles|2.3|2.6|-1.4|0.5|0.4|-0.9|-5.6|-0.8|-4.1|0.2|
|Wearingapparel|1.6|1.9|2.3|0.6|0.6|-3.5|-10.7|-0.6|5.7|0.4|
|Leathergoods|0.2|0.1|11.7|0.5|-0.6|17.5|-5.5|-0.5|11.5|2.9|
|Processed foods|0.9|1.1|0.1|0.2|0.8|3.0|-2.9|0.5|1.8|0.4|
|Woodproducts|-1.3|-1.8|-6.1|0.1|-0.4|-4.5|-11.3|-2.7|-3.6|-4.4|
|Paperproducts, publishing|-0.7|-1.0|-1.4|-0.4|-0.3|-15.1|-5.2|-1.1|-1.6|-1.0|
|Petroleum,coalproducts|0.8|1.3|-15.3|-0.2|-1.1|5.3|2.5|-1.2|5.6|-0.5|
|Chemical,rubber, plastic|-0.6|-0.5|-10.7|-0.9|-1.8|15.0|-6.3|-2.4|-5.6|-0.5|
|Energyintensive manu.|-0.7|-0.7|0.0|-0.1|0.3|8.7|-4.5|-1.7|-2.3|-1.6|
|Metalproducts|-0.4|-0.1|2.1|0.6|-0.4|12.5|1.2|-1.5|3.0|7.4|
|Electronics|0.0|2.0|13.9|-0.9|-4.9|5.2|28.7|6.6|42.9|2.6|
|Machineryand equipment|-0.7|-0.4|16.6|0.6|0.3|17.6|3.2|-1.6|20.4|1.5|
|Transport equipment|-0.6|-0.5|19.0|-0.5|-1.5|6.8|2.6|-5.5|10.7|-0.7|
|Manufactures,n.e.s.|0.7|1.4|2.7|-0.8|-0.1|1.8|-22.5|-1.3|3.5|2.2|
|Electricity|0.1|0.2|8.3|0.2|0.2|7.2|5.8|-0.3|6.4|0.1|
|Construction|0.2|0.4|0.5|0.4|0.1|1.9|1.7|-0.3|4.1|0.0|
|Trade services|-1.0|-1.8|0.7|-0.1|0.1|2.8|0.2|0.0|-1.4|0.9|
|Other transport|-0.9|-1.2|9.4|-0.4|-0.4|3.7|-8.0|0.3|-3.7|0.1|
|Water transport|-2.5|-3.4|6.4|-0.1|-0.9|2.1|-3.6|-0.2|0.8|2.2|
|Air transport|-0.9|-1.0|11.6|-1.2|-0.1|3.1|-3.8|0.2|-2.3|1.8|
|Hospitalityservices|0.4|0.5|-3.6|0.4|0.0|4.8|-8.2|0.2|3.1|-0.5|
|Other business services|-0.1|-0.3|-0.3|0.1|-0.2|-1.2|-4.1|-0.1|-2.3|-0.9|
|Other services|0.0|0.0|0.7|0.2|0.1|-0.4|-0.3|0.1|-0.1|0.3|
|**Agriculture**|0.5|0.5|-0.5|-0.2|-0.1|-0.6|-7.9|-0.1|-2.1|-1.0|
|**Manufacturing**|0.3|0.6|1.5|0.0|0.0|2.8|6.4|0.3|4.7|0.7|
|**Services**|-0.3|-0.5|-0.2|0.1|0.0|0.5|-0.9|0.0|-0.2|-0.1|
|**Other**|-0.1|-0.1|-0.3|-0.7|0.2|-0.2|-8.8|-1.5|-7.7|-2.2|
|**Total**|0.00|0.00|0.00|0.00|0.00|0.00|0.04|0.00|0.02|0.00|

- 46 -
|Table 10|a: Change in|real value added|in 2030, perc|ent chan|ge from b|aseline, ct|d.<br>|||
|---|---|---|---|---|---|---|---|---|---|
||||||||Rest of||Russia|
||Rest of<br>East Asia|Bangladesh|India|Nepal|Pakista<br>n|Sri Lanka|South<br>Asia|EU ECA|Feder<br>ation|
|Agriculture|0.4|9.1|0.2|0.1|1.9|0.0|0.4|1.0|1.5|
|Minerals n.e.s.|-1.1|6.1|-1.3|-1.4|-0.6|-0.3|0.4|-0.3|-0.5|
|Coal|13.0|13.6|-2.0|3.9|-1.3||2.6|-1.8|3.9|
|Oil|-2.8||-0.5||0.9|-2.2|-4.2|1.1|0.7|
|Gas|2.1|3.0|-0.2||11.6||6.2|0.2|1.3|
|Textiles|-1.8|11.0|0.3|1.3|-0.2|-2.2|3.0|0.1|0.3|
|Wearingapparel|1.3|8.9|-0.4|-0.8|9.5|1.3|0.4|-0.2|0.5|
|Leathergoods|-2.1|3.3|-0.3|-2.8|6.7|0.8|-3.3|-1.4|-0.5|
|Processed foods|-1.2|11.1|0.5|-0.7|6.5|0.4|-2.4|0.5|1.5|
|Woodproducts|8.4|1.1|-1.1|-1.0|-12.2|0.1|3.3|-0.2|1.6|
|Paperproducts, publishing|-1.6|2.5|-1.7|-1.4|-5.5|-0.7|-1.2|0.1|0.2|
|Petroleum,coalproducts|-2.4|12.7|0.9|1.8|-6.6|-1.4|1.1|-0.3|0.7|
|Chemical,rubber, plastic|-3.8|1.6|-0.4|-7.6|5.7|0.1|2.1|-0.6|-0.7|
|Energyintensive manu.|-0.9|10.6|-1.7|-3.1|-8.1|-1.6|-1.7|-0.7|-0.4|
|Metalproducts|-1.0|11.7|-0.8|0.5|-3.6|-0.9|-3.2|-1.2|-0.3|
|Electronics|7.5|84.5|-8.3|-10.7|-4.4|-1.8|-0.7|-7.4|-7.8|
|Machineryand equipment|-1.2|43.0|-1.7|0.3|-7.3|1.7|2.4|-1.9|-1.1|
|Transport equipment|-2.6|17.4|-1.6|-0.6|-2.7|-0.6|-0.4|-0.9|-1.0|
|Manufactures,n.e.s.|18.8|9.0|2.6|6.0|12.2|5.8|-1.6|-1.3|0.0|
|Electricity|1.1|3.9|0.0|0.4|13.2|0.4|0.8|0.2|1.3|
|Construction|0.1|2.3|-0.2|-0.6|-2.5|-0.3|-0.7|0.0|0.7|
|Trade services|-0.3|-26.5|0.0|-0.7|-13.6|0.1|-2.6|0.0|-0.5|
|Other transport|-1.0|-11.4|0.0|-0.1|-17.1|0.3|-1.9|0.0|-1.1|
|Water transport|-0.4|-11.2|2.0|-0.8|-19.7|0.4|-1.5|0.5|-1.1|
|Air transport|-1.3|-13.3|-1.6|-0.4|-16.0|-0.1|1.9|0.1|-1.7|
|Hospitalityservices|-0.3|10.2|0.1|-0.4|20.0|0.4|0.4|1.0|1.9|
|Other business services|-0.8|-1.4|-0.4|-0.7|7.2|-0.7|-1.1|0.5|0.1|
|Other services|0.0|-0.8|0.0|0.0|-1.4|0.2|-0.6|0.0|0.0|
|**Agriculture**|0.4|9.1|0.2|0.1|1.9|0.0|0.4|1.0|1.5|
|**Manufacturing**|-0.4|10.3|-0.3|-0.3|2.4|0.5|-1.4|-1.0|0.0|
|**Services**|-0.3|-12.0|-0.1|-0.2|-3.6|-0.1|-0.6|0.1|0.0|
|**Other**|4.9|3.2|-1.3|-1.3|2.6|-0.3|5.5|-0.4|1.2|
|**Total**|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.01|

- 47 -
|Table 10|a: Chang|e in real val<br>|ue added in 2|030, perce|nt change<br>|from bas<br>|eline, ct<br>|d||
|---|---|---|---|---|---|---|---|---|---|
|||Rest of|||Rest of|Iran,|Egypt,|||
||Poland|Eastern<br>Europe|Kazakhstan|Kyrgyz<br>Republic|Central<br>Asia|<br>Islamic<br>Rep.|<br>Arab<br>Rep.|Turkey|Rest of<br>MENA|
|Agriculture|0.6|1.8|2.9|-9.8|0.8|1.2|0.2|1.3|0.4|
|Minerals n.e.s.|-0.3|-0.8|0.2|-3.1|0.1|1.1|-0.3|-1.7|-0.4|
|Coal|-0.8|-0.2|1.0|15.3|-0.7|10.1||-7.8|-5.0|
|Oil|1.0|-1.0|-0.8|5.1|-0.9|-0.6|0.1|-6.9|0.8|
|Gas|0.0|0.2|-0.7|-3.8|2.2|4.1|0.1|2.1|1.4|
|Textiles|0.3|-0.4|-0.5|3.8|0.7|3.9|-0.2|3.3|-2.3|
|Wearingapparel|-0.1|0.3|-0.5|32.7|3.2|2.6|0.2|4.9|-2.3|
|Leathergoods|-0.3|-2.3|-0.3|156.8|3.9|4.0|0.2|3.6|-4.7|
|Processed foods|0.8|1.5|1.0|-5.0|1.8|1.7|0.3|4.5|0.6|
|Woodproducts|-0.5|-1.2|-0.9|1.4|0.7|0.1|-0.5|-0.1|-3.1|
|Paperproducts, publishing|0.2|-0.6|-0.2|-8.2|-0.7|-1.7|0.0|-1.5|-2.2|
|Petroleum,coalproducts|-0.5|0.2|2.5|12.6|-0.5|4.4|-0.5|1.5|3.8|
|Chemical,rubber, plastic|-0.3|-0.6|0.2|-9.3|1.6|14.0|-0.5|-0.9|1.6|
|Energyintensive manu.|-0.6|-2.3|0.6|-0.2|-1.5|0.4|-1.1|-1.8|-1.6|
|Metalproducts|-1.0|-1.7|-1.2|-16.2|-1.5|-0.2|-1.2|0.8|-3.2|
|Electronics|-7.5|-6.0|-7.3|-10.3|-3.6|-3.8|-8.8|-4.1|-10.5|
|Machineryand equipment|-1.7|-2.2|-2.0|2.8|1.5|-6.6|-5.3|-2.9|-7.8|
|Transport equipment|-0.5|-1.5|4.3|-3.5|13.0|1.2|0.2|10.0|-5.3|
|Manufactures,n.e.s.|-1.2|-1.4|-0.5|-9.6|-0.2|-1.8|-0.4|6.1|-1.7|
|Electricity|0.2|-0.1|0.6|6.8|1.2|3.4|-0.3|1.5|1.1|
|Construction|0.1|-0.3|-0.5|9.1|1.0|2.0|0.0|-0.9|0.8|
|Trade services|0.0|0.2|0.2|8.5|0.4|-2.5|-0.1|-5.2|0.3|
|Other transport|0.0|-0.3|0.0|7.4|-2.0|-3.0|-0.2|-1.1|0.4|
|Water transport|1.3|1.0|-0.1|3.4|-0.8|-0.5|0.6|-8.8|1.9|
|Air transport|-0.7|0.1|-0.1|11.1|-0.6|15.8|-0.5|1.6|0.2|
|Hospitalityservices|0.5|0.1|0.1|-5.1|0.4|-0.3|0.3|1.2|0.4|
|Other business services|0.4|-0.1|-0.3|-5.4|0.1|-0.3|0.0|0.3|0.1|
|Other services|0.1|0.1|0.1|0.9|0.1|-0.1|0.0|0.0|-0.2|
|**Agriculture**|0.6|1.8|2.9|-9.8|0.8|1.2|0.2|1.3|0.4|
|**Manufacturing**|-0.6|-1.0|0.2|-0.7|1.7|1.5|-0.5|2.4|-2.1|
|**Services**|0.0|0.0|0.0|0.2|-0.1|-0.8|0.0|-0.6|0.2|
|**Other**|-0.5|-0.4|-0.1|2.4|0.3|2.1|0.1|-2.4|0.8|
|**Total**|0.00|0.0|0.000|0.01|0.00|0.01|0.00|0.00|0.01|

- 48 -
|Table 10|a: Chan|ge in real v|alue add|ed in 203|0, percent ch<br>Rest of|ange from b<br>Latin|aseline,|ctd.||
|---|---|---|---|---|---|---|---|---|---|
||Kenya|Tanzania|Non-<br>BRI<br>Area|Ethiopia|Sub-<br>Saharan<br>Africa|America<br>and<br>Caribbean|United<br>States|Rest of<br>High-<br>income|Rest of<br>Western<br>Europe|
|Agriculture|1.3|0.7|0.5|2.5|0.3|1.2|1.9|0.8|0.4|
|Minerals n.e.s.|-2.7|-2.0|-0.5|-0.2|-0.7|-0.1|-0.5|-0.8|-0.3|
|Coal||-0.5|0.6|-26.6|1.3|3.2|0.3|-2.7|-2.4|
|Oil|-9.1||0.3||0.2|1.2|-0.8|-0.7|0.5|
|Gas|-4.0|-0.5|0.2||0.4|0.0|0.0|-0.3|0.0|
|Textiles|-3.3|-3.9|0.0|-0.3|-0.3|0.2|-0.4|1.2|-0.4|
|Wearingapparel|-1.5|0.9|0.2|1.1|0.5|0.2|-0.5|-0.2|-0.3|
|Leathergoods|-2.2|6.8|0.6|2.4|0.0|1.0|-0.2|0.3|-0.7|
|Processed foods|-1.3|0.5|0.5|2.2|0.3|0.8|0.6|0.0|0.4|
|Woodproducts|-2.7|-2.8|-0.4|-2.2|-0.5|0.0|-0.2|-0.5|-0.7|
|Paperproducts, publishing|-7.3|-5.8|-0.2|-3.5|-0.7|-0.1|0.2|-0.1|-0.2|
|Petroleum,coalproducts|-4.2|-6.1|-0.8|-5.7|-0.9|-0.5|-0.4|-1.2|-1.0|
|Chemical,rubber, plastic|-11.0|-2.1|-0.8|-5.2|-1.6|-0.6|-0.6|-0.6|-1.0|
|Energyintensive manu.|-7.9|0.3|-0.8|-2.6|-1.0|-0.6|-0.8|-0.7|-0.6|
|Metalproducts|-6.7|-16.9|-1.0|-4.4|-1.5|-0.9|-1.1|0.0|-1.3|
|Electronics|-13.1|-11.4|-6.5|-19.4|-6.3|-8.3|-2.1|-5.1|-8.6|
|Machineryand equipment|-10.0|-11.0|-1.6|-9.5|-2.7|-3.2|-1.2|0.7|-1.4|
|Transport equipment|-3.6|-5.7|-0.7|-6.9|-1.7|-2.4|-0.2|2.6|-0.9|
|Manufactures,n.e.s.|-6.8|-3.3|-1.1|-2.4|1.0|-1.4|0.3|-1.7|-1.3|
|Electricity|-1.9|-0.4|-0.2|-2.1|-0.3|0.0|0.0|0.1|0.0|
|Construction|-1.2|-0.1|-0.1|0.4|-0.2|-0.1|-0.3|0.0|0.0|
|Trade services|-1.4|-4.9|-0.1|-0.8|-0.5|-0.2|-0.3|0.1|0.1|
|Other transport|-2.2|-3.4|-0.3|-1.5|-0.5|-0.2|-0.7|-0.3|-0.2|
|Water transport|0.1|-2.9|0.2|-4.8|-1.0|0.0|-0.6|1.1|0.8|
|Air transport|-0.8|-2.8|-0.6|-2.2|-0.7|-0.4|-0.8|0.1|-0.6|
|Hospitalityservices|-2.1|-1.5|0.2|0.5|0.0|0.1|0.6|0.2|0.4|
|Other business services|-3.1|-2.7|0.0|-1.0|-0.1|0.1|0.0|0.0|0.2|
|Other services|-0.5|-0.3|0.0|0.1|-0.1|0.0|0.1|0.1|0.1|
|**Agriculture**|1.3|0.7|0.5|2.5|0.3|1.2|1.9|0.8|0.4|
|**Manufacturing**|-2.6|-0.6|-0.5|0.3|-0.1|-0.7|-0.5|-0.5|-1.0|
|**Services**|-1.6|-1.5|0.0|-0.1|-0.2|0.0|0.0|0.1|0.1|
|**Other**|-2.9|-0.8|0.0|-0.2|0.0|0.3|-0.4|-0.8|-0.2|
|**Total**|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|

- 49 -
# Table 10b: Change in real value added in 2030, <u>difference from baseline in $2014 million</u>

||World|BRI<br>Area|Cambodia|China|Indonesia|Lao<br>PDR|Malaysia|Philippines|Thailand|Vi|
|---|---|---|---|---|---|---|---|---|---|---|
|Agriculture|5336600|4261940|-22738|-438260|-27350|-15807|-114563|-19699|-161517|-|
|Minerals n.e.s.|-68350|-45287|-34|-15026|-530|81|-202|-3353|-2900||
|Coal|-42018|-46444|0|-26715|4234|22|-155|-443|-5636|-|
|Oil|-26475|-38379|0|-5768|-2371|28|-6267|-53|-40739|-|
|Gas|85804|83570|0|71|2317|-273|-8143|-38|-6369||
|Textiles|703034|704060|-747|28061|5314|-80|-2014|-2291|-10711||
|Wearingapparel|356126|346488|21339|29011|2347|-1294|-3018|-2450|10575||
|Leathergoods|14766|4415|5665|7986|-3554|812|-410|-259|5556||
|Processed foods|1445410|1211010|729|101973|82732|7790|-15448|24403|28079||
|Woodproducts|-120216|-108842|-225|1066|-2548|-75|-8483|-3821|-5464||
|Paper products,<br>publishing|-116718|-98496|-15|-13520|-1680|-35|-6404|-1008|-2435||
|Petroleum, coal<br>products|29750|36390|-68|-1315|-1400|26|477|-182|5560||
|Chemical, rubber,<br>plastic|-264379|-166558|-2813|-98870|-57410|259|-28652|-12295|-69724||
|Energy intensive<br>manu.|-261311|-186681|0|-18089|4073|1757|-12373|-3251|-10240|-|
|Metalproducts|-74931|-12743|14|21665|-4412|57|1648|-873|2451||
|Electronics|10430|328477|2303|-81636|-5790|63|338248|46793|167096||
|Machinery and<br>equipment|-294955|-106782|1558|85964|2303|219|11762|-13166|83555||
|Transport equipment|-162823|-99342|1467|-30661|-19428|16|6347|-5720|64433||
|Manufactures,n.e.s.|114004|157892|149|-16185|-171|94|-44604|-2372|10184||
|Electricity|96112|120012|46|10814|202|330|1052|-466|26881||
|Construction|562300|661260|1455|392532|3855|622|28727|-6469|73394||
|Trade services|-5786060|-5331250|7493|-79317|14157|2941|7354|1368|-67771||
|Other transport|-1046410|-935660|3644|-152201|-15001|2434|-28801|634|-22354||
|Water transport|-279466|-286213|251|-3749|-4655|52|-1818|-23|1540||
|Air transport|-87631|-65766|2635|-23043|-223|143|-10258|42|-3552||
|Hospitalityservices|418890|327457|-25936|112280|4142|3899|-37331|1864|29112||
|Other business<br>services|-537410|-565200|-1087|38163|-16281|-783|-50661|-5339|-85404|-|
|Other services|81080|-76150|5056|198540|38960|-3239|-9978|8817|-6323||
|Agriculture|5336600|4261940|-22738|-438260|-27350|-15807|-114563|-19699|-161517|-|
|Manufacturing|1378190|2009280|29353|15450|375|9611|237077|23508|278916||
|Services|-6578600|-6151500|-6443|494020|25155|6399|-101714|428|-54477|-|
|Other|-51038|-46540|-34|-47437|3650|-141|-14766|-3888|-55645|-|
|Total|85200|73200|138|23770|1830|62|6034|349|7276||

- 50 -
# Table 10b: Change in real value added in 2030, <u>difference from baseline in $2014 million, ctd.</u>

||Rest of<br>East Asia|Bangladesh|India|Nepal|Pakistan|Sri Lanka|Rest of<br>South<br>Asia|EU ECA|Russia<br>n<br>Federa<br>tion|
|---|---|---|---|---|---|---|---|---|---|
|Agriculture|70636|3092936|510920|18586|763932|-212|27553|5772|17221|
|Minerals n.e.s.|-2364|892|-8198|-385|-1476|-173|121|-218|-415|
|Coal|45088|5|-49352|11|-1|0|148|-1609|4687|
|Oil|-1162|0|-6332|0|25|-1|-138|777|4143|
|Gas|9107|6377|-1565|0|10417|0|18614|34|6780|
|Textiles|-1447|647435|20709|4115|-5749|-2358|1783|39|467|
|Wearingapparel|4172|224065|-16139|-2539|67871|6792|273|-204|766|
|Leathergoods|-1544|895|-3926|-2707|3875|349|-709|-762|-921|
|Processed foods|-35940|354037|127143|-5735|384639|1606|-7460|1419|30459|
|Woodproducts|3944|7232|-11525|-187|-67805|44|207|-107|3287|
|Paper products,<br>publishing|-4306|6792|-33116|-1176|-16238|-972|-394|130|280|
|Petroleum, coal<br>products|-819|764|5156|3|-1196|-50|53|-53|1012|
|Chemical,rubber, plastic|-10683|3299|-25168|-443|91082|210|183|-1339|-1718|
|Energyintensive manu.|-1395|26186|-88865|-4037|-8213|-1016|-1556|-1150|-4789|
|Metalproducts|-1698|46280|-34960|819|-13776|-323|-1636|-1628|-948|
|Electronics|14080|23970|-75019|-219|-7032|-310|-25|-5020|-7375|
|Machinery and<br>equipment|-2449|51359|-130289|3|-75670|1544|112|-7588|-18110|
|Transport equipment|-7762|23710|-75487|-42|-16876|-151|-64|-1873|-3210|
|Manufactures,n.e.s.|25593|18512|137517|5079|13850|3829|-207|-1155|-275|
|Electricity|4484|2296|8948|128|41401|179|66|294|1457|
|Construction|1527|85713|-19707|-776|-48454|-922|-703|-299|19991|
|Trade services|-28608|-3928879|-25538|-5770|-900406|1064|-4767|-161|-39597|
|Other transport|-24841|-457151|2377|-176|-157213|1193|-572|-159|-30714|
|Water transport|-728|-271669|8371|-68|-1775|358|-56|202|-3279|
|Air transport|-5201|-21084|-2648|-38|-11205|-44|57|29|-8098|
|Hospitalityservices|-7967|159850|1422|-2392|105515|2060|4180|2834|20966|
|Other business services|-39944|-26948|-254138|-1588|120947|-15782|-14272|10389|9486|
|Other services|2441|-75175|41290|-482|-267467|3066|-20689|1607|4123|
|Agriculture|70636|3092936|510920|18586|763932|-212|27553|5772|17221|
|Manufacturing|-20255|1434538|-203969|-7065|348760|9193|-9441|-19292|-1075|
|Services|-98837|-4533047|-239620|-11164|-1118657|-8827|-36757|14735|-25664|
|Other|50669|7274|-65447|-374|8965|-173|18745|-1015|15196|
|Total|2213|1700|1880|-16|3000|-19|99|200|5678|

- 51 -
# Table 10b: Change in real value added in 2030, <u>difference from baseline in $2014 million, ctd.</u>

||Poland|Rest of<br>Eastern<br>Europe|Kazakhst<br>an|Kyrgyz<br>Republic|Rest of<br>Central<br>Asia|Iran,<br>Islamic<br>Rep.|Egypt,<br>Arab<br>Rep.|Turkey|Rest of<br>MENA|
|---|---|---|---|---|---|---|---|---|---|
|Agriculture|137|35324|1512|-4045|2426|69296|18714|28089|29126|
|Minerals n.e.s.|-100|-1858|98|-121|55|548|-16|-2034|-3402|
|Coal|-393|-1122|236|185|-20|390|0|-825|-46|
|Oil|29|-322|-477|135|-7183|-1665|64|-577|49911|
|Gas|-1|132|-11|-10|11247|16354|14|56|17871|
|Textiles|47|-442|-17|20|46|12754|-716|20577|-8440|
|Wearingapparel|-19|437|-11|192|189|2854|912|19705|-20869|
|Leathergoods|-19|-1511|-2|160|77|2266|155|2763|-34182|
|Processed foods|1250|12617|582|-160|8941|20970|4510|73601|18090|
|Woodproducts|-89|-1338|-12|0|14|17|-358|-27|-15730|
|Paper products,<br>publishing|87|-1306|-10|-173|-148|-1229|-53|-3371|-8029|
|Petroleum, coal<br>products|-20|284|42|29|-70|12604|-67|145|16509|
|Chemical, rubber,<br>plastic|-256|-1610|24|-57|820|46251|-1291|-3784|23006|
|Energyintensive manu.|-408|-8389|136|-43|-1143|4036|-4585|-7215|-24673|
|Metalproducts|-548|-1867|-32|-242|-239|-866|-1742|1201|-22754|
|Electronics|-1416|-15372|-616|-197|-1477|-9059|-14055|-7147|-71609|
|Machinery and<br>equipment|-1682|-8472|-124|265|261|-20164|-324|-11231|-62926|
|Transport equipment|-317|-9767|246|-95|6769|6602|39|24723|-54044|
|Manufactures,n.e.s.|-626|-1840|-4|-23|-10|-1253|-50|5531|-6819|
|Electricity|98|-2159|804|2943|7393|2992|-1923|3172|5890|
|Construction|224|-4970|-667|7521|13854|42659|-1446|-13772|113967|
|Trade services|-277|8043|115|17698|3164|-190505|-2543|-132753|63372|
|Other transport|65|-3613|-78|3006|-67707|-11763|-732|-7858|36641|
|Water transport|229|1388|-117|38|-1990|-127|120|-21637|12894|
|Air transport|-199|85|-207|1086|-1864|14203|-180|691|3538|
|Hospitalityservices|512|442|968|-16709|2663|-899|147|9323|6741|
|Other business services|2545|-1877|-7265|-26161|6837|-5119|198|19836|5602|
|Other services|1203|9046|4874|14997|17836|-8125|5144|3079|-56127|
|**Agriculture**|137|35324|1512|-4045|2426|69296|18714|28089|29126|
|**Manufacturing**|-4015|-38577|203|-323|14029|75783|-17624|115471|-272471|
|**Services**|4400|6385|-1575|4418|-19813|-156683|-1214|-139919|192518|
|**Other**|-465|-3171|-154|189|4100|15626|62|-3380|64334|
|**Total**|58|-38|-13|238|741|4021|-63|261|13510|

- 52 -
# Table 10b: Change in real value added in 2030, <u>difference from baseline in $2014 million, ctd.</u>

||Kenya|Tanzani<br>a|Non-BRI<br>Area|Ethiopia|Rest of<br>Sub-<br>Saharan<br>Africa|Latin<br>America<br>and<br>Caribbean|United<br>States|Rest of<br>High-<br>income|Rest<br>Wes<br>Euro|
|---|---|---|---|---|---|---|---|---|---|
|Agriculture|197910|193693|1074710|64179|543870|372990|61701|19643||
|Minerals n.e.s.|-426|-336|-23063|-670|-15079|-1305|-1034|-4008||
|Coal|0|0|4426|0|6330|911|423|-1709||
|Oil|-27|0|11904|0|7527|7888|-2949|-1633||
|Gas|-8|-323|2235|0|2174|255|75|-275||
|Textiles|-1632|-1840|-1026|-2548|-2729|2889|-1301|4636||
|Wearingapparel|-765|855|9639|1201|6493|4847|-1045|-633||
|Leathergoods|-119|1933|10351|1242|57|10429|-66|232||
|Processed foods|-24830|6675|234401|51308|61282|97402|8437|1211||
|Woodproducts|-1973|-553|-11374|-1299|-5406|18|-1469|-1147||
|Paperproducts, publishing|-6538|-774|-18222|-6912|-7459|-2948|2957|-1276||
|Petroleum,coalproducts|-90|-23|-6640|-1|-1102|-1912|-183|-2299||
|Chemical,rubber, plastic|-7315|-621|-97822|-3154|-15856|-30845|-10410|-12030|-|
|Energyintensive manu.|-6363|870|-74630|-9096|-18367|-20840|-7359|-10552||
|Metalproducts|-1598|-13417|-62188|-7156|-10819|-14721|-8893|-322|-|
|Electronics|-4422|-592|-318047|-246|-12456|-123579|-5966|-110425|-|
|Machineryand equipment|-3410|-2864|-188173|-1376|-25148|-102501|-29555|14005|-|
|Transport equipment|-451|-815|-63482|-6511|-18480|-71830|-2720|53106|-|
|Manufactures,n.e.s.|-3660|-104|-43886|-3264|4407|-22241|835|-10492|-|
|Electricity|-3360|-406|-23902|-2775|-21722|-686|288|792||
|Construction|-22434|-3977|-98961|11858|-62209|-22954|-23774|-1996||
|Trade services|-5382|-61855|-454800|-97928|-304362|-124841|-72940|47855||
|Other transport|-3825|-907|-110754|-2811|-30728|-17312|-23706|-14589|-|
|Water transport|19|-21|6747|-426|-3296|53|-2241|6526||
|Air transport|-420|-55|-21865|-861|-4496|-3748|-6451|354||
|Hospitalityservices|-37329|-7202|91432|3381|2343|25426|48601|7292||
|Other business services|-49863|-96676|27780|-39437|-32820|19519|8868|1189||
|Other services|-11710|-10285|157230|53669|-38778|21837|71254|18883||
|**Agriculture**|197910|193693|1074710|64179|543870|372990|61701|19643||
|**Manufacturing**|-63167|-11269|-631100|12191|-45582|-275829|-56739|-75986|-1|
|**Services**|-134304|-181384|-427100|-75328|-496070|-102700|-100|66310|1|
|**Other**|-460|-659|-4498|-670|952|7749|-3485|-7625||
|**Total**|-21|380|12000|371|3170|2200|1370|2340||

- 53 -
<u>Table 11: Real factor returns, percent change in 2030 relative to baseline</u>

||<br>Un-skilled|<br>Skilled|<br>Total<br>labor|<br>Capital|<br>Land|<br>Natl. res.|Non-labor|Total|
|---|---|---|---|---|---|---|---|---|
|World|0.88|0.7|0.79|0.5|1.97|0.36|0.57|0.66|
|BRI Area|1.36|1.38|1.37|0.84|1.76|0.12|0.87|1.02|
|Cambodia|4.7|3.99|4.54|5.6|4.05|4.18|5.07|4.88|
|China|0.59|0.91|0.70|0.22|0.32|-0.09|0.19|0.41|
|Indonesia|0.56|0.66|0.59|0.25|0.37|0.24|0.25|0.36|
|Lao PDR|1.09|3.34|1.47|3.24|1.19|5.03|2.22|1.97|
|Malaysia|10.78|10.52|10.67|4.32|0.57|-1.59|3.59|6.28|
|Philippines|0.62|0.74|0.68|0.46|0.49|-0.1|0.45|0.52|
|Thailand|7.45|9.15|8.16|6.75|3.63|-1.93|6.32|6.82|
|Vietnam|2.31|1.85|2.16|1.94|1.24|-0.1|1.67|1.91|
|Rest of East Asia|2.81|1.79|2.19|0.69|2.16|1.75|0.81|1.3|
|Bangladesh|8.48|8.7|7.83|10.55|21.23|4.62|12.71|9.79|
|India|0.82|0.14|0.53|0|0.9|-0.08|0.21|0.34|
|Nepal|1.25|0.36|1.02|0.52|1.22|0.42|0.71|0.83|
|Pakistan|27.89|5.19|15.44|7.76|24.12|3.56|9.56|10.81|
|Sri Lanka|0.77|0.01|0.50|0.82|0.67|0.46|0.79|0.68|
|Rest of S. Asia|3.13|1.67|2.48|0.66|3.04|2.44|1.36|1.75|
|EU ECA|0.24|0.23|0.23|-0.01|1.75|0.45|0.06|0.11|
|Russian|||||||||
|Federation|1.2|1.57|1.40|0.67|2.83|0.63|0.7|0.89|
|Poland|0.08|0.1|0.09|0.13|1.29|0.02|0.16|0.14|
|Rest of E.|||||||||
|Europe|1.02|0.75|0.88|0.91|3.28|0.52|1.13|1|
|Kazakhstan|1.16|0.42|0.85|0.2|4.31|0.28|0.31|0.53|
|Kyrgyz Republic|26.07|7.95|20.42|11.71|6.55|13.19|10.16|13.08|
|Rest of C. Asia|1.98|1.34|1.76|0.74|2.61|0.5|0.93|1.22|
|Iran, Islamic<br>Rep.|4.8|4.41|4.58|1.16|5.92|0.27|1.14|1.57|
|Egypt,Arab Rep.|0.52|0.28|0.38|0.23|0.77|0.3|0.26|0.31|
|Turkey|4.72|4.52|4.65|4.13|4.14|-1.35|4.12|4.26|
|Rest of MENA|1.42|1.45|1.43|0.73|1.85|1.14|0.8|0.96|
|Kenya|4.48|1.7|3.76|0.87|4.38|1.3|1.13|2.22|
|Tanzania|4.65|2.35|4.02|0.67|3.97|1.04|1.2|2.61|
|Non-BRI Area|0.36|0.48|0.43|0.19|1.77|0.31|0.22|0.33|
|Ethiopia|0.69|1.1|0.78|0.58|2.75|0.52|0.87|0.92|
|Rest of SSA|0.94|0.21|0.62|-0.23|0.8|0.28|-0.11|0.23|
|Lat. Am. & Car.|0.37|0.01|0.20|-0.04|1.3|0.43|0.03|0.09|
|United States|0.09|0.55|0.38|0.45|3.52|0.11|0.5|0.42|
|Rest of High-inc.|0.66|0.66|0.66|0.34|1.81|0.04|0.35|0.5|
|Rest of W. Eur.|0.26|0.28|0.28|0.18|0.95|0.24|0.19|0.22|

- 54 -
<u>Table 12: Labor displacement, change in 2030 relative to baseline</u>

||||<br>BRIUB|<br>D||
|---|---|---|---|---|---|
||Agriculture||Total||Percent of labor<br>force|
||displ-|displ+|displ-|displ+||
|World Total|-821.8|6141.9|-14000.2|14000.2|0.37|
|BRI regions|-821.8|5074.8|-11966.2|11966.2|0.48|
|Cambodia|-22.7|0.0|-53.5|53.5|0.58|
|China|-438.6|0.0|-998.5|998.5|0.13|
|Indonesia|-27.4|0.0|-160.8|160.8|0.11|
|Lao PDR|-15.7|0.0|-22.6|22.6|0.54|
|Malaysia|-114.0|0.0|-382.6|382.6|2.36|
|Philippines|-19.7|0.0|-83.0|83.0|0.15|
|Thailand|-161.5|0.0|-516.9|516.9|1.32|
|Vietnam|-17.6|0.0|-180.4|180.4|0.39|
|Rest of East Asia|0.0|70.3|-190.0|190.0|0.32|
|Bangladesh|0.0|3090.8|-4775.3|4775.3|5.59|
|India|0.0|509.3|-972.0|972.0|0.15|
|Nepal|0.0|18.6|-31.3|31.3|0.15|
|Pakistan|0.0|761.8|-1885.0|1885.0|2.18|
|Sri Lanka|-0.6|0.4|-23.2|23.2|0.24|
|Rest of South Asia|0.0|27.5|-53.2|53.2|0.37|
|EU ECA|0.0|5.6|-21.9|21.9|0.08|
|Russian Federation|0.0|16.9|-118.3|118.3|0.17|
|Poland|0.0|0.1|-5.9|5.9|0.04|
|Rest of Eastern Europe|0.0|35.2|-67.6|67.6|0.26|
|Kazakhstan|0.0|1.4|-9.4|9.4|0.09|
|Kyrgyz Republic|-4.0|0.0|-48.9|48.9|1.70|
|Rest of Central Asia|0.0|2.3|-82.4|82.4|0.29|
|Turkey|0.0|27.5|-205.9|205.9|0.71|
|Egypt,Arab Rep.|0.0|18.6|-31.0|31.0|0.09|
|Iran,Islamic Rep.|0.0|68.8|-250.8|250.8|0.82|
|Rest of MENA|0.0|28.6|-380.5|380.5|0.34|
|Kenya|0.0|197.7|-201.2|201.2|0.78|
|Tanzania|0.0|193.3|-214.1|214.1|0.53|
|Non-BRI regions|0.0|1067.1|-2034.0|2034.0|0.15|
|Ethiopia|0.0|63.7|-186.2|186.2|0.27|
|Rest of Sub-Saharan Africa|0.0|542.4|-676.8|676.8|0.16|
|Latin America and<br>Caribbean|0.0|370.1|-588.0|588.0|0.18|
|United States|0.0|59.9|-194.6|194.6|0.11|
|Rest of High-income|0.0|19.1|-165.7|165.7|0.13|
|Rest of Western Europe|0.0|11.9|-222.8|222.8|0.11|

- 55 -
<u>Table 13: Percent change in emissions in 2030 relative to the baseline</u>

||<br>CO2|<br>CH4|<br>N2O|<br>FGAS|<br>BC|<br>CO|NH3|
|---|---|---|---|---|---|---|---|
|World|0.5|0.7|0.9|-1.8|0.6|0.8|0.5|
|BRI Area|0.6|0.6|0.9|-0.7|0.6|0.9|0.4|
|Cambodia|17.7|2.8|1.5||8.6|5.5|3.2|
|China|0.0|-0.1|0.1|-0.6|0.0|0.1|0.1|
|Indonesia|0.3|0.3|0.1|0.0|0.6|0.5|0.1|
|Lao PDR|7.7|3.1|-0.8||3.4|0.5|-0.6|
|Malaysia|5.1|-2.8|-2.8|16.0|-1.0|3.6|-4.3|
|Philippines|0.7|0.0|0.3|-2.3|0.1|0.3|-0.1|
|Thailand|4.1|-0.8|3.3|-3.1|-8.6|0.1|-2.4|
|Vietnam|1.8|-0.8|0.6|-0.1|2.3|1.4|0.1|
|Rest of East Asia|0.8|2.0|1.2|2.6|1.8|1.5|1.3|
|Bangladesh|5.8|3.8|6.4|0.0|18.2|15.2|5.8|
|India|0.1|0.4|0.2|0.0|0.0|0.2|-0.3|
|Nepal|-0.3|0.5|0.5||0.6|0.4|0.4|
|Pakistan|7.3|7.3|10.9|16.8|11.0|11.2|8.8|
|Sri Lanka|1.8|0.6|0.6|0.0|3.2|2.6|1.0|
|Rest of S. Asia|1.6|1.4|1.6||1.7|0.9|1.0|
|EU ECA|0.1|0.3|0.4|-4.6|0.1|0.2|0.7|
|Russian Federation|1.1|1.0|0.8|-1.0|0.8|1.1|1.4|
|Poland|0.1|-0.1|0.3|-4.7|0.1|0.2|0.5|
|Rest of E. Europe|0.7|0.7|0.8|-3.9|0.7|0.5|1.6|
|Kazakhstan|0.2|0.7|2.1|-5.6|0.5|0.7|2.4|
|Kyrgyz Republic|6.8|-0.8|-2.9|-5.1|7.0|1.5|-3.4|
|Rest of C. Asia|1.0|0.6|1.3|-1.6|0.6|0.7|0.9|
|Iran,Islamic Rep.|3.9|1.8|3.9|1.9|2.1|3.0|2.1|
|Egypt,Arab Rep.|-0.1|0.1|0.1|-1.8|0.2|-0.1|0.2|
|Turkey|2.7|1.2|2.3|-2.1|-0.8|2.4|2.3|
|Rest of MENA|1.1|1.2|0.8|-5.3|1.1|1.2|0.6|
|Kenya|2.1|3.0|3.5|-8.3|1.7|2.5|0.9|
|Tanzania|3.5|2.9|3.1||4.4|4.4|2.8|
|Non-BRI Area|0.3|0.8|0.9|-3.2|0.6|0.6|0.8|
|Ethiopia|1.3|2.2|2.5|-14.5|1.8|1.7|1.2|
|Rest of SSA|0.0|0.7|0.8|-3.0|0.8|0.9|0.7|
|Lat. Am. & Car.|0.1|0.9|1.1|-1.8|0.3|0.5|0.9|
|United States|0.2|0.8|0.9|-1.4|0.1|0.3|1.4|
|Rest of High-inc.|0.7|0.2|0.6|-2.6|0.9|0.8|0.7|
|Rest of W. Eur.|0.2|0.2|0.2|-6.4|0.1|0.2|0.3|

- 56 -
<u>Table 13: Percent change in emissions in 2030 relative to the baseline, ctd.</u>

||<br>NMVB|<br>NMVF|<br>Nox|<br>OC|<br>PM10|<br>PM2_5|SO2|
|---|---|---|---|---|---|---|---|
|World|0.0|0.4|0.4|1.2|0.7|0.7|-0.3|
|BRI Area|-0.2|0.5|0.5|1.2|0.7|0.7|-0.3|
|Cambodia|6.5|15.9|5.1|5.6|5.2|4.2|7.7|
|China|0.0|-0.3|-0.1|0.3|0.1|0.1|-0.7|
|Indonesia|0.7|0.5|0.2|0.5|0.5|0.4|0.1|
|Lao PDr|2.3|24.4|2.8|1.2|1.1|0.7|5.8|
|Malaysia|-22.5|2.7|1.1|3.5|-3.9|0.5|-2.3|
|Philippines|-1.9|0.9|0.4|0.5|-0.1|0.2|-0.6|
|Thailand|-23.7|2.8|0.3|3.4|-6.6|-1.1|-14.5|
|Vietnam|-0.6|-0.3|2.4|1.8|1.3|1.3|1.5|
|Rest of East Asia|3.1|1.9|1.4|1.4|1.6|1.3|1.2|
|Bangladesh|18.5|4.9|5.5|18.1|16.7|16.0|8.0|
|India|0.1|-0.1|-0.4|0.4|0.2|0.1|-1.3|
|Nepal|0.5|0.4|0.5|0.5|0.5|0.5|0.6|
|Pakistan|12.0|3.5|7.9|14.5|13.3|12.7|10.3|
|Sri Lanka|3.0|1.9|1.7|2.9|2.8|2.9|1.0|
|Rest of S. Asia|1.4|1.5|1.2|1.8|1.7|1.7|0.3|
|EU ECA|0.2|-0.1|-0.1|0.4|0.2|0.2|-0.6|
|Russian Federation|1.4|1.1|0.9|1.3|1.1|1.0|0.8|
|Poland|0.4|-0.1|-0.1|0.3|0.2|0.2|0.0|
|Rest of E. Europe|1.1|0.9|0.2|1.7|0.6|0.7|-1.1|
|Kazakhstan|1.7|0.0|0.3|1.1|0.8|0.9|0.2|
|Kyrgyz Republic|-6.1|3.9|4.4|1.1|0.5|0.6|-6.8|
|Rest of C. Asia|1.2|0.4|0.8|0.9|0.8|0.8|0.2|
|Iran,Islamic Rep.|4.6|2.6|3.0|2.3|2.8|2.6|3.8|
|Egypt,Arab Rep.|0.2|-0.1|0.1|0.2|0.0|0.1|0.0|
|Turkey|1.3|0.8|1.1|1.1|0.7|0.9|-4.7|
|Rest of MENA|-1.7|1.4|1.2|1.2|0.7|1.0|1.0|
|Kenya|2.0|2.2|1.1|4.4|1.6|3.2|0.3|
|Tanzania|1.9|3.6|3.3|5.8|4.7|5.1|1.5|
|Non-BRI Area|0.5|0.2|0.2|1.0|0.8|0.8|-0.5|
|Ethiopia|-6.9|1.3|1.9|3.5|1.6|2.9|1.5|
|Rest of SSA|1.1|0.4|0.1|0.9|1.0|0.9|-0.3|
|Lat. Am. & Car.|1.3|0.1|0.0|0.7|0.6|0.6|-1.0|
|United States|0.6|0.1|0.0|0.7|0.6|0.4|0.0|
|Rest of High-inc.|0.9|0.2|0.7|0.9|0.4|0.6|-0.8|
|Rest of W. Eur.|0.2|-0.1|0.2|0.4|0.2|0.3|-0.4|

- 57 -
Table 14: Sensitivity Analysis: welfare gains with and without internal trade cost reductions (% <u>deviations from the baseline in 2030)</u>

||BRIUB|BRIUBD|BRIUBB|BRIUBBD|BRIUBBTP|BRIUBBTPD|
|---|---|---|---|---|---|---|
|World|0.5|0.7|0.7|1.1|0.8|1.1|
|BRI Area|0.8|1.2|1.2|2.0|1.4|2.1|
|Cambodia|5.0|5.0|8.6|8.6|8.6|8.7|
|China|0.6|0.7|0.8|1.0|0.9|1.1|
|Indonesia|0.5|0.5|0.5|0.5|0.5|0.6|
|Lao PDr|3.0|3.1|9.0|9.2|9.1|9.3|
|Malaysia|4.6|7.7|5.0|8.1|5.2|8.3|
|Philippines|0.7|0.7|0.6|0.6|0.6|0.6|
|Thailand|5.4|8.2|6.8|9.7|6.8|9.7|
|Vietnam|1.5|1.6|1.5|1.6|1.5|1.6|
|Rest of East Asia|1.5|1.6|2.4|2.5|2.4|2.5|
|Bangladesh|0.7|6.9|1.1|7.2|1.2|7.4|
|India|0.5|0.4|0.6|0.6|1.0|1.0|
|Nepal|0.4|0.4|8.2|11.3|8.0|11.2|
|Pakistan|0.8|10.5|1.0|10.8|1.4|11.1|
|Sri Lanka|0.6|0.6|0.8|0.8|1.1|1.1|
|Rest of S. Asia|0.9|1.4|3.9|5.4|4.1|5.7|
|EU ECA|0.2|0.2|0.4|0.5|0.6|0.6|
|Russian|||||||
|Federation|0.4|1.2|1.0|1.9|1.1|1.9|
|Poland|0.2|0.2|0.2|0.3|0.3|0.4|
|Rest of E. Europe|0.7|0.8|1.4|1.6|1.2|1.4|
|Kazakhstan|0.4|0.5|4.0|15.4|4.1|15.5|
|Kyrgyz Republic|10.2|10.4|35.8|37.3|34.7|36.1|
|Rest of C. Asia|0.8|1.5|2.2|6.7|2.1|6.6|
|Iran,Islamic Rep.|1.5|3.0|2.6|4.3|3.3|4.9|
|Egypt,Arab Rep.|0.2|0.2|0.3|0.3|0.9|0.9|
|Turkey|1.4|3.6|1.6|3.9|1.9|4.2|
|Rest of MENA|1.2|1.3|2.8|4.1|2.8|4.1|
|Kenya|1.4|1.5|2.3|2.3|2.6|2.7|
|Tanzania|1.5|2.5|1.9|2.9|2.2|3.2|
|Non-BRI Area|0.3|0.3|0.3|0.4|0.4|0.5|
|Ethiopia|1.8|1.9|5.7|5.9|5.8|6.0|
|Rest of SSA|0.4|0.4|0.6|0.7|0.7|0.7|
|Lat. Am. & Car.|0.1|0.1|0.1|0.1|0.1|0.1|
|United States|0.3|0.4|0.3|0.4|0.3|0.5|
|Rest of High-inc.|0.5|0.5|0.5|0.5|0.6|0.6|
|Rest of W. Eur.|0.3|0.3|0.4|0.4|0.4|0.5|

- 58 -
# **Annex A: Summary description of the Envisage model and the model dimensions**

The description of the Envisage Model follows the circular flow of an economy paradigm. Firms purchase input factors (for example labor and capital) to produce goods and services. Households receive factor income and in turn demand goods and services produced by firms. And, equality of supply and demand determine equilibrium prices for factors, goods and services. The model is solved as a sequence of comparative static equilibria where the factors of production are exogenous for each time period and linked between time periods with accumulation expressions.

Production is implemented as a series of nested constant-elasticity-of-substitution (CES) functions the aim of which is to capture the substitutability across all inputs. Three production archetypes are implemented. The first is for crops that reflects intensification of inputs versus land extensification. The second is for livestock that reflects range-fed versus ranch-fed production. The final, also referred to as the default, revolves largely around capital/labor substitutability. Some production activities highlight specific inputs (for example agricultural chemicals in crops and feed in livestock) and all activities include energy and its components as part of the cost minimization paradigm. Production is also identified by vintage—divided into _Old_ and _New_ — with typically lower substitution possibilities associated with _Old_ capital.

Each production activity is allowed to produce more than one commodity—for example the ethanol sector can produce ethanol and distiller’s dried grains with solubles (DDGS). And commodities can be formed by the output of one or more activities (for example electricity). ENVISAGE therefore uses a different classification of activities and commodities.<sup>18</sup> One of the features of the model is that it integrates the new GTAP power data base that disaggregates GTAP’s electricity sector (‘ely’) into 11 different power sources plus electricity transmission and distribution. Though the database has both the supply and demand side for all 11 power sources, the aggregation facility permits the aggregation of electricity demand into a single commodity and the ‘make’ matrix specification combines the output from the different power activities into a single electricity commodity.

Income accrues from payments to factors of production and is allocated to households (after taxes). The government sector accrues all net tax payments and purchases goods and services. The model incorporates multiple utility functions for determining household demand. There is a set of three household demand functions linked to the ubiquitous linear expenditure system (LES): the standard LES, the extended LES (ELES) that incorporates household saving into the utility function, and ‘an implicitly directly additive demand system’ (AIDADS), that allows for nonlinear Engel curves in the LES framework.<sup>19</sup> The fourth option uses the constant differences in elasticity (CDE) utility function that is used in the core GTAP model (Hertel 1997 and Corong et al. 2017). The ELES incorporates the decision to save in a top-level utility function. The other demand systems assume savings is an exogenous proportion of disposable income in the default closure. The consumer utility function determines consumer demand bundles that are subsequently

> 18 Production activities are indexed with _a_ and commodities are indexed with _i_ . 19  Users can also specify implementing a Cobb-Douglas (CD) utility function, which can be considered part of the LES framework.

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converted to produced goods using a consumer demand ‘make’ or transition matrix. Investment is savings driven and equal to domestic saving adjusted by net capital flows.

Trade is modeled using the so-called Armington specification that posits that demand for goods is differentiated by region of origin. The model allows for domestic/import sourcing at the aggregate level (after aggregating domestic absorption across all agents), or at the agent-level. In the standard specification, a second Armington nest allocates aggregate import demand across all exporting regions using a representative agent specification. Note that a newer, though minimally tested version, allows for sourcing imports by agent—also known as the MRIO specification. Exports are modeled in an analogous fashion using a nested constant-elasticity-of-transformation (CET) specification. The domestic supply of each commodity is supplied to the domestic market and an aggregate export bundle using a top-level CET function. The latter is allocated across regions of destination using a second-level CET function.<sup>20</sup> Each bilateral trade node is associated with four prices: 1) the producer price; 2) the export border price, also referred to as the free-on-board (FOB) price; 3) the import border price, also referred to as the cost, insurance and freight (CIF) price; and 4) the end-user price that includes all applicable trade taxes. The wedge between the producer price and the FOB price is represented by the export tax (or subsidy if negative) and the wedge between the CIF and end-user prices represents the import tariff (and perhaps other import related distortions). The wedge between the CIF and FOB prices represents the international trade and transport margin. These margins represent the use of real resources that are supplied by each region. The global international trade and transport sector purchases these services from each region so as to minimize the aggregate cost.

The model has two fundamental markets for goods and services. Domestically produced goods sold on the domestic market, and domestically produced goods sold by region of destination. All other goods and services are composite bundles of these goods. Two market equilibrium conditions are needed to clear these two markets.<sup>21</sup> The model incorporates five types of production factors: 1) labor (of which there can be up to 5 types); 2) capital; 3) land; 4) a sector specific natural resource (such as fossil fuel energy reserves); and 5) water. The labor market is allowed to be segmented (though not required). The model allows for regime switching between full and partial wage flexibility. Capital is allocated across sectors so as to equalize rates of returns. If all sectors are expanding, _Old_ capital is assumed to receive the economy-wide rate of return. In contracting sectors, _Old_ capital is sold on secondary markets using an upward sloping supply curve. This implies that capital is only partially mobile across sectors. Aggregate land and water supply are specified using supply curves. Though there are several options, the preferred supply curve is a logistic function that has an upper bound. Water demand also includes exogenous components for environmental uses and groundwater recharge. Land and water are allocated across activities using a nested CET specification.<sup>22</sup> Natural resources are

> 20  The model allows for perfect transformation, which is the standard specification in the GTAP model.

> 21  If there are _N_ commodities and _R_ regions, there will be _R_ × _N_ market clearing conditions for domestic goods and _R_ × _N_ × _R_ market clearing conditions for bilateral trade.

> 22

> Land is only implemented for agricultural activities. Water demand by activity is only present in irrigated crop sectors. Other water demand is based on aggregate demand functions with market clearing, but is not part of the cost structure.

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supplied to each sector using an iso-elastic supply function with the possibility differentiated elasticities depending on market conditions.

ENVISAGE incorporates the main greenhouse gases—carbon, methane, nitrous oxides and fluorinated gases, as well as 10 additional non-greenhouse gases<sup>23</sup> that may have impacts on the atmosphere and climate change, but often have significant local impacts, particularly on health. Emissions are generated by consumption of commodities (such as fuels), factor use (for example land in rice production and herds in livestock production) and there are also processed base emissions such as methane from landfills.<sup>24</sup> A number of carbon control regimes are available in the model. Carbon taxes can be imposed exogenously—potentially differentiated across regions. The incidence of the carbon tax allows for partial or full exemption by commodity and end-user. For example, households can be exempted from the carbon tax on natural gas consumption. The model allows for emission caps in a flexible manner—where regions can be segmented into coalitions on a multi-regional or global basis. In addition to the standard cap system, a cap and trade system can be defined where each region within a coalition is assigned an initial emission quota.

Dynamics involves three elements. Labor supply (by skill level) grows at an exogenously determined rate. The aggregate capital supply evolves according to the standard stock/flow motion equation, i.e. the capital stock at the beginning of each period is equal to the previous period’s capital stock, less depreciation, plus the previous period's level of investment. The third element is technological change. The standard version of the model assumes labor augmenting technical change—calibrated to given assumptions about GDP growth and inter-sectoral productivity differences. In policy simulations, technology is typically assumed to be fixed at the calibrated levels.

For this particular study, key model specifications include:

- Agent-based Armington specification for import demand, with an aggregate agent allocation of total import demand by source region

- The value of time in trade is captured by an iceberg parameter—specified for each commodity and bilateral trade node. The iceberg parameter is assumed to be fixed over time in the baseline.

- Diagonal make matrix, i.e. one-to-one correspondence between activities and commodities

- Constant-differences-in-elasticity (CDE) utility function

- Logistic aggregate land supply function

- The capital account is fixed within each time period. Net capital flows decline to zero by 2050, with an interim target in 2030 of 5% of GDP for countries whose capital account is greater than 5% in the base year.

> 23  Black carbon (BC), carbon monoxide (CO), ammonia (NH3), volatile organic compounds (NMVB and NMVF), nitrogen oxides (NOx), organic carbon (OC), particulate matter (PM10 and PM2.5) and sulfur dioxide (SO2). 24  The current version of the model does not include carbon emissions from deforestation—an important source of global carbon emissions.

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# <u>Table A1: Regional dimension</u>

||<br>**Region name (code in parenthesis)**|
|---|---|
|1|Cambodia(KHM)|
|2|China(CHN)|
|3|Indonesia(IDN)|
|4|Lao PDR(LAO)|
|5|Malaysia(MYS)|
|6|Philippines(PHL)|
|7|Thailand(THA)|
|8|Vietnam(VNM)|
|9|Rest of East Asia(XEA)|
|10|Bangladesh(BGD)|
|11|India(IND)|
|12|Nepal(NPL)|
|13|Pakistan(PAK)|
|14|Sri Lanka(LKA)|
|15|Rest of South Asia(XSA)|
|16|EU ECA(ECU)|
|17|Russian Federation(RUS)|
|18|Poland(POL)|
|19|Rest of Eastern Europe(EEU)|
|20|Kazakhstan(KAZ)|
|21|Kyrgyz Republic(KGZ)|
|22|Rest of Central Asia(XCS)|
|23|Turkey (TUR)|
|24|Egypt,Arab Rep.(EGY)|
|25|Iran, Islamic Rep.(IRN)|
|26|Rest of MENA(XMN)|
|27|Ethiopia(ETH)|
|28|Kenya(KEN)|
|29|Tanzania(TZA)|
|30|Rest of Sub-Saharan Africa(XSS)|
|31|Latin America and Caribbean(LAC)|
|32|United States(USA)|
|33|Rest of High-income(XHY)|
|34|Rest of Western Europe(E_U)|

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The model’s reference year is 2014 and the model is initialized and calibrated to the GTAP Data Base, Version 10 pre-release 2.<sup>25</sup> The 141 regions in the database have been aggregated to 34 regions, see Table A-1.<sup>26</sup> Similarly, the database’s 57 sectors have been aggregated to 28, see Table A-2, with an emphasis on the more traded manufacturing sectors, and the trade and transport services.<sup>27</sup> <u>Table A-2: Sector dimension</u>

||**Sector name (code in parenthesis)**|
|---|---|
|1|Agriculture(AGR)|
|2|Coal(COA)|
|3|Oil(OIL)|
|4|Gas(GAS)|
|5|Minerals n.e.s.(OMN)|
|6|Processed foods(PFD)|
|7|Woodproducts(LUM)|
|8|Paperproducts, publishing (PPP)|
|9|Textiles(TEX)|
|10|Wearingapparel(WAP)|
|11|Leathergoods(LEA)|
|12|Energyintensive manufacturing (KE5)|
|13|Petroleum, coalproducts(P_C)|
|14|Chemical,rubber, plasticproducts(CRP)|
|15|Transport equipment(TRQ)|
|16|Electronics(ELE)|
|17|Metalproducts(FMP)|
|18|Machineryand equipment(OME)|
|19|Manufactures, n.e.s.(XMN)|
|20|Electricity (ELY)|
|21|Construction(CNS)|
|22|Trade services(TRD)|
|23|Air transport(ATP)|
|24|Water transport(WTP)|
|25|Other transport(OTP)|
|26|Hospitalityservices(ROS)|
|27|Other business services(XBS)|
|28|Other services(XSV)|

> 25  Pre-releases are only made available to GTAP Board members. The public version of Version 10 is expected to be available in the summer of 2019.

> 26

> 27

> The GTAP concordance is available in Table A-3.

> The GTAP concordance is available in Table A-4.

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The key macro-economic drivers of the baseline are based on a number of existing baselines. Population and labor growth are calibrated to the United Nation’s Population Division 2015 projection, the medium variant.<sup>28</sup> The near-term GDP projections, through 2020, use the latest World Bank Global Economic Prospects (GEP) forecast.<sup>29</sup> Beyond 2020, the baseline is calibrated to the so-called Shared Socio-Economic Pathway (SSP) 2, or SSP2. The SSPs, of which there are 5, have been developed by the Integrated Assessment Modeling (IAM) Community to provide a macroeconomic framework for quantitative analysis of the economics of climate change.<sup>30</sup> Three economic modeling groups have quantified global GDP projections: the Organisation for Economic Co-operation and Development (OECD), the International Institute for Applied Systems Analysis (IIASA), and the Potsdam Institute for Climate Impact Research (PIK). All three teams harmonized to the same demographic projections provided by IIASA’s demographic unit. For our purposes, we are using the OECD-based SSP2 projection. SSP2, also referred to as the ‘middle of the road’ scenario, is being treated by many modeling groups as a business as usual scenario.

Labor force growth is equated with the growth rate of the population cohort ages 15-64, sometimes referred to as the working-age population. The GEP forecast is used to project real GDP growth from 2014-2020. The SSP2 projection is used to project real per-capita GDP growth, complemented by the UN population projection.<sup>31</sup> We target real GDP growth by calibrating labor productivity in the baseline. We allow for sector differences in labor productivity growth, with a (fixed) higher rate in agriculture and manufacturing, relative to services. Other factors that impact calibrated labor productivity include an exogenous improvement in energy efficiency, agricultural yields, and international trade and transport margins.

The baseline also incorporates the following list of exogenous assumptions:

- Bilateral tariff rates are modified over time according to a schedule of tariff rates prepared by the ITC (2015). This schedule is based on existing trade agreements. More details are available from the authors.

- The income parameter of the CDE is adjusted between periods based on an estimated economic relation between the income parameter and aggregate per capita consumption. The parametrization of the relationship is based on a least-squares estimate using the base year GTAP database. One key purpose is to reduce the share of food expenditures as incomes rise.

- Capital accumulation is based on the standard capital motion equation: _Kt_ =(1- δ ) _K_ t-1+ _It_ -1, thus the capital stock trends depend on investment/savings decisions. In the baseline, household savings are adjusted in order to target future trends in the investment to GDP ratio—with the basic idea that these trends should more or less line up with steady state

> 28  http://www.un.org/en/development/desa/publications/world-population-prospects-2015-revision.html

> 29 _Global Economic Prospects, January 2018: Broad-Based Upturn, but for How Long?_ Advance edition. Washington, DC: World Bank. License: Creative Commons Attribution CC BY 3.0 IGO (https://openknowledge.worldbank.org/bitstream/handle/10986/28932/9781464811630.pdf).

> 30  A Special Issue of _Global Environmental Change_ provides significant background material on the SSPs and their development. See in particular Dellink et al. 2017 for a discussion of the OECD-based macroeconomic drivers.

> 31  In other words, we overlay SSP2’s population projection with the UN’s, but assume the same growth rate of GDP in per capita terms.

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returns to capital. Baseline net capital flows are assumed to decline to zero by 2050— however, regions with an initial level above 5 percent of GDP (in absolute terms), are assumed to linearly drive this down to 5 percent of GDP by 2030.<sup>32</sup> The focus of the paper is on the BRI initiative, though we will briefly outline the contours of the baseline:

- World population is expected to rise from 7.3 billion in 2014 to 8.5 billion in 2030, an increase of around 1.2 billion, and about 1 percent per annum on average (see Table 1).

- The BRI region accounts for around one-half of the increase, mostly South Asia, with SubSaharan Africa accounting for the major contribution in the non-BRI area, with an increase of almost 400 million. There is a small decline in BRI’s share of global population, from 65 to 63 percent.

- Global GDP will rise from $78 $2014 billion in 2014 to $133 $2014 billion in 2030—an average annual increase of 3.4 percent.

- BRI’s share of global output climbs relatively sharply from 31 percent to 42 percent (at 2014 prices and market exchange rates). In terms of average annual growth rates, BRI’s increases at a rapid clip of 5.4 percent per annum, whereas the non-BRI region would see an increase of 2.3 percent per annum (see Table 2).

- Average global income in per capita terms rises by 45 percent—over 100 percent for the BRI area and only 16 percent for non-BRI (see Table 3).

- Despite the relatively high growth in per capita incomes in many developing countries, convergence in incomes (at market exchange rates and 2014 prices) is slight, for example the BRI region on average only sees its per capita income rise from 9.5 percent of the U.S. average to 10.5 percent.

<u>Table A-3: GTAP regional concordance</u>

||<br>**Region name**|<br>**GTAP concordance**|
|---|---|---|
|1|Cambodia (KHM)|Cambodia(KHM)|
|2|China (CHN)|China(CHN)|
|3|Indonesia (IDN)|Indonesia(IDN)|
|4|Lao PDR (LAO)|Lao PDR(LAO)|
|5|Malaysia (MYS)|Malaysia(MYS)|
|6|Philippines (PHL)|Philippines(PHL)|
|7|Thailand (THA)|Thailand(THA)|
|8|Vietnam (VNM)|Vietnam(VNM)|
|9|Rest of East Asia (XEA)|Rest of Oceania (XOC), Mongolia (MNG), Rest of<br>East Asia (XEA), Brunei Darussalam (BRN),<br>Singapore (SGP), Rest of Southeast Asia (XSE)|
|10|Bangladesh (BGD)|Bangladesh(BGD)|
|11|India (IND)|India(IND)|
|12|Nepal (NPL)|Nepal(NPL)|
|13|Pakistan (PAK)|Pakistan(PAK)|
|14|Sri Lanka (LKA)|Sri Lanka(LKA)|
|15|Rest of South Asia (XSA)|Rest of South Asia (XSA)|
|16|EU ECA (ECU)|Czech Republic (CZE), Estonia (EST), Hungary<br>(HUN), Latvia (LVA), Lithuania (LTU), Slovak Rep.|

> 32  We make an exception for the Kyrgyz Republic, which has an initial trade deficit of over 100 percent of GDP.

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(SVK), Slovenia (SVN), Bulgaria (BGR), Croatia (HRV), Romania (ROU)

|17|Russian Federation (RUS)|Russian Federation(RUS)|
|---|---|---|
|18|Poland (POL)|Poland(POL)|
|19|Rest of Eastern Europe (EEU)|Albania (ALB), Belarus (BLR), Ukraine (UKR), Rest<br>of Eastern Europe(XEE)|
|20|Kazakhstan (KAZ)|Kazakhstan(KAZ)|
|21|Kyrgyz Rep. (KGZ)|Kyrgyz Republic(KGZ)|
|22|Rest of Central Asia (XCS)|Tajikistan (TJK), Rest of Former Soviet Union (XSU),<br>Armenia (ARM), Azerbaijan (AZE), Georgia (GEO)|
|23|Turkey (TUR)|Turkey (TUR)|
|24|Egypt, Arab Rep. (EGY)|Egypt,Arab Rep.(EGY)|
|25|Iran, Islamic Rep. (IRN)|Iran,Islamic Rep.(IRN)|
|26|Rest of MENA (XMN)|Bahrain (BHR), Israel (ISR), Jordan (JOR), Kuwait<br>(KWT), Oman (OMN), Qatar (QAT), Saudi Arabia<br>(SAU), United Arab Emirates (ARE), Rest of Western<br>Asia (XWS), Morocco (MAR), Tunisia (TUN), Rest of<br>North Africa (XNF)|
|27|Ethiopia (ETH)|Ethiopia(ETH)|
|28|<br>Kenya (KEN)|Kenya(KEN)|
|29|<br>Tanzania (TZA)|Tanzania(TZA)|
|30|<br>Rest of Sub-Saharan Africa (XSS)|Benin (BEN), Burkina Faso (BFA), Cameroon (CMR),<br>Côte d'Ivoire (CIV), Ghana (GHA), Guinea (GIN),<br>Nigeria (NGA), Senegal (SEN), Togo (TGO), Rest of<br>Western Africa (XWF), Central Africa (XCF), South-<br>Central Africa (XAC), Madagascar (MDG), Malawi<br>(MWI), Mauritius (MUS), Mozambique (MOZ),<br>Rwanda (RWA), Uganda (UGA), Zambia (ZMB),<br>Zimbabwe (ZWE), Rest of Eastern Africa (XEC),<br>Botswana (BWA), Namibia (NAM), South Africa<br>(ZAF), Rest of South African Customs Union (XSC)|
|31|Latin America and Caribbean (LAC)|<br>Mexico (MEX), Rest of North America (XNA),<br>Argentina (ARG), Bolivia (BOL), Brazil (BRA), Chile<br>(CHL), Colombia (COL), Ecuador (ECU), Paraguay<br>(PRY), Peru (PER), Uruguay (URY), Venezuela, RB<br>(VEN), Rest of South America (XSM), Costa Rica<br>(CRI), Guatemala (GTM), Honduras (HND),<br>Nicaragua (NIC), Panama (PAN), El Salvador (SLV),<br>Rest of Central America (XCA), Dominican Republic<br>(DOM), Jamaica (JAM), Puerto Rico (PRI), Trinidad<br>and Tobago (TTO), Rest of Caribbean (XCB)|
|32|United States (USA)|United States of America(USA)|
|33|Rest of High-income (XHY)|Australia (AUS), New Zealand (NZL), Hong Kong<br>SAR, China (HKG), Japan (JPN), Korea, Rep. (KOR),<br>Taiwan, China (TWN), Canada (CAN), Rest of the<br>World (XTW)|
|34|Rest of Western Europe (E_U)|<br>Austria (AUT), Belgium (BEL), Cyprus (CYP),<br>Denmark (DNK), Finland (FIN), France (FRA),<br>Germany (DEU), Greece (GRC), Ireland (IRL), Italy<br>(ITA), Luxembourg (LUX), Malta (MLT), Netherlands<br>(NLD), Portugal (PRT), Spain (ESP), Sweden (SWE),<br>United Kingdom (GBR), Switzerland (CHE), Norway<br>(NOR), Rest of EFTA (XEF), Rest of Europe (XER)|

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||Tabl|e A-4: GTAP sector concordance|
|---|---|---|
||**Sector name**|**GTAP concordance**|
|1<br>|Agriculture (AGR)<br>|Paddy rice (PDR), Wheat (WHT), Cereal grains, n.e.s. (GRO), Vegetables<br>and fruits (V_F), Oil seeds (OSD), Sugar cane and sugar beet (C_B), Plant-<br>based fibers (PFB), Crops, n.e.s. (OCR), Bovine cattle, sheep and goats,<br>horses (CTL), Animal products n.e.s. (OAP), Raw milk (RMK), Wool, silk-<br>worm cocoons (WOL), Forestry (FRS)<br>|
|2|Coal (COA)|Coal (COA)|
|3|Oil (OIL)|Oil (OIL)|
|4|Gas (GAS)|Gas (GAS), Gas manufacture, distribution (GDT)|
|5|Minerals n.e.s. (OMN)|Minerals n.e.s. (OMN)|
|6|Processed foods (PFD)|Fishing (FSH), Bovine cattle, sheep and goat, horse meat products (CMT),<br>Meat products n.e.s. (OMT), Vegetable oils and fats (VOL), Dairy products<br>(MIL), Processed rice (PCR), Sugar (SGR), Food products n.e.s. (OFD),<br>Beverages and tobacco products (B_T)|
|7|Wood products (LUM)|Wood products (LUM)|
|8|Paper products,<br>publishing (PPP)|Paper products, publishing (PPP)|
|9|<br>Textiles (TEX)|Textiles (TEX)|
|10|Wearing apparel (WAP)|Wearing apparel (WAP)|
|11|Leather goods (LEA)|Leather products (LEA)|
|12|Energy intensive<br>manufacturing (KE5)|Mineral products n.e.s. (NMM), Ferrous metals (I_S), Metals n.e.s. (NFM)|
|13|Petroleum, coal products<br>(P_C)|Petroleum, coal products (P_C)|
|14|Chemical, rubber, plastic<br>products (CRP)|Chemical, rubber, plastic products (CRP)|
|15|Transport equipment<br>(TRQ)|Motor vehicles and parts (MVH), Transport equipment n.e.s. (OTN)|
|16|Electronics (ELE)|Electronic equipment (ELE)|
|17|Metal products (FMP)|Metal products (FMP)|
|18|Machinery and<br>equipment (OME)|Machinery and equipment n.e.s. (OME)|
|19|<br>Manufactures, n.e.s.<br>(XMN)|Manufactures n.e.s. (OMF)|
|20|Electricity (ELY)|Electricity (ELY)|
|21|Construction (CNS)|Construction (CNS)|
|22|Trade services (TRD)|Trade (TRD)|
|23|Air transport (ATP)|Air transport (ATP)|
|24|Water transport (WTP)|Sea transport (WTP)|
|25|Other transport (OTP)|Transport n.e.s. (OTP)|
|26|Hospitality services<br>(ROS)|Recreation and other services (ROS)|
|27|<br>Other business services<br>(XBS)|Insurance (ISR), Communication (CMN), Financial services n.e.s. (OFI),<br>Business services n.e.s. (OBS)|
|28|Other services (XSV)|Water (WTR), Public administration and defense, education, health services<br>(OSG), Dwellings (DWE)|

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