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 connec- Road Initiative would be largely beneficial. First, global tivity between China and more than 70 countries through income increases by 0.7 percent (in 2030 relative to the infrastructure investment and regional cooperation. The baseline). This translates into almost half a trillion dollars in initiative has the potential to accelerate significantly the 2014 prices and market exchange rates. The Belt and Road rate of economic integration and development in the Initiative area captures 82 percent of the gain, with the region, as trade costs decline. The goals of this paper are largest percent gains in East Asia. Second, globally, the Belt to (i) study the impacts of infrastructure improvements on and Road Initiative could contribute to lifting 7.6 million Belt and Road Initiative and non–Belt and Road Initiative people from extreme poverty and 32 million from mod- countries’ trade flows, growth, and poverty; and (ii) suggest erate poverty. Third, the initiative would lead to a modest policies that would help maximize gains from the Belt and increase in global carbon dioxide emissions, with a complex Road Initiative–induced trade cost declines. The analysis set of positive and negative outcomes at the national level captures the trade costs reductions as a result of infrastruc- for other types of emissions. ture improvements. The findings indicate that the Belt and 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 1 and Dominique van der Mensbrugghe 2 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. 2 The Center for Global Trade Analysis (GTAP), Department of Agricultural Economics, Purdue University, West Lafayette, IN 47906 (vandermd@Purdue.edu). Table of contents 1. INTRODUCTION .............................................................................................................................................. 3 2. BRI-INDUCED TRADE COSTS REDUCTIONS .......................................................................................... 4 3. MACRO RESULTS ........................................................................................................................................... 7 4. SOCIAL COSTS/BENEFITS OF THE BRI.................................................................................................... 9 4.1. FACTOR REWARDS, LABOR DISPLACEMENT AND POVERTY IMPLICATIONS ................................................... 9 4.2. EMISSIONS IMPLICATIONS ......................................................................................................................... 11 5. BRI IMPACTS ON SELECTED COUNTRIES ........................................................................................... 14 6. IMPACT OF COMPLEMENTARY POLICIES .......................................................................................... 16 7. SENSITIVITY ANALYSIS ............................................................................................................................. 18 8. CONCLUSIONS AND POLICY RECOMMENDATIONS ......................................................................... 19 TABLES ..................................................................................................................................................................... 22 ANNEX A: SUMMARY DESCRIPTION OF THE ENVISAGE MODEL AND THE MODEL DIMENSIONS ..................................................................................................................................................................................... 59 - ii - 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 BRI- induced 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. -3- 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. -4- 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 lower bound estimates BRIUBD BRI upper bound estimates BRIUBBD BRIUBBD and reduced border delays BRIUBBTD BRIUBBD and tariff reduction applied on a preferential basis among BRI countries BRIUBBTPD BRIUBBD and tariff reduction applied on a MFN basis by BRI countries 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. -5- 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 Kyrgyz Republic Thailand Tanzania Malaysia Ethiopia Cambodia Kenya Iran China Laos Pakistan Turkey USA Rest of East Asia Kazakhstan Vietnam Rest of South Asia Rest of Central Asia Indonesia India Philippines Rest of High-inc. Rest of E. Europe Rest of MENA Bangladesh Rest of W. Eur. Russia Sri Lanka Egypt Lat. Am. & Car. Nepal Rest of SSA EU ECA Poland Non BRI BRI World 0 2 4 6 8 10 12 BRI Non BRI 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 input- output coefficient is adjusted downwards by 5%. In the current configuration of the input database, -6- 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 3) 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. 4 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. 5 • 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. -7- • 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%). -8- • 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. 6 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. 7 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. -9- 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. 8 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 9 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. 10 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. 11 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. - 10 - 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. 12 Four are so- called greenhouse gases (GHGs), 13 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. - 11 - Figure 2. Change in global emissions under BRI investment scenario (BRIUBD) by 2030 (percentages). BRI Infrastructure: change in global emissions in 2030 wrt to the baseline (percent) 1.5 1.0 0.5 0.0 -0.5 -1.0 -1.5 -2.0 CO2 N2O CH4 F-GAS BC CO NH3 NMVB NMVF NOx OC PM 10 PM 2.5 SO2 Figure 3. Change in carbon emissions in 2030 with respect to Baseline under BRI related infrastructure investment scenario BRIUBD (percentages). Percent change in carbon emissions in 2030 wrt to Baseline 20.00 18.00 16.00 14.00 12.00 10.00 8.00 6.00 4.00 2.00 0.00 -2.00 IND E_U BGD USA bri TUR xbr IDN NPL VNM EGY CHN wld RUS LAC ECU POL PHL XMN ETH IRN THA MYS PAK LAO XSS KAZ EEU XHY XEA XCS XSA LKA KEN KGZ KHM TZA 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 - 12 - 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 non- greenhouse 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. - 13 - Figure 4: BRI Infrastructure: Decomposition of CH4 emission growth relative to baseline in 2030 (percent). Notes: IO are emissions linked to intermediate demand; XP are process emissions; HHD are final demand emissions linked to consumption and FP are emissions linked to production factors. 5. BRI impacts on selected countries Several countries will be particularly affected by the infrastructure improvements related to the BRI. We focus on the upper bound infrastructure improvements scenario (BRIUBD) to understand the specific impacts on those countries. Pakistan presents the highest welfare gain of the countries involved in the initiative, with a gain of 10.5% by 2030 (relative to the baseline), and an 8.6% share of the total gain of the BRI area (Table 5) These gains are the result of trade cost reductions originated by ventures such as the improvement of the Port of Gwadar connections, through highway, rail and pipeline infrastructure, as part of the China-Pakistan Economic Corridor Plan. Other projects include a Peshawar-Karachi Motorway, and an expansion and reconstruction of a railway between Karachi to Peshawar. The sector that shows the sharpest reductions in import trade costs is petroleum and coal products, but sectors such as construction, trade services and the transport sectors also exhibit high reductions. As a result of trade costs reductions, imports of several products increase (Table 9b). The biggest increases are recorded in agricultural goods, textiles and petroleum and coal products. Pakistan is importing less oil, chemical, rubber and plastic goods and less transport equipment than in the baseline. - 14 - 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. - 15 - 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. - 16 - 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 - 17 - 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 14 (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. 15 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. - 18 - broad range of (independent) draws 16 of these five key parameters and the results also show a negative relationship between the Armington elasticity and utility. 17 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 non- BRI 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. - 19 - 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 - 20 - 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 - 21 - Tables Table 1: Baseline population profile, million 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 - 22 - Table 2: Baseline GDP, $2014 billion 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 - 23 - Table 3: GDP per capita, $2014 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 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 - Table 4: Reductions in the value of the time of trade CHN bri xbr BRIL BRIU BRIU BRIUB BRIUB BRIL BRIU BRIU BRIUB BRIUB BRIL BRIU BRIU BRIUB BRIUB BD BD BBD BTD BTPD BD BD BBD BTD BTPD BD BD BBD BTD 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, 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 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 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 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. 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) BRILBD BRIUBD BRIUBBD BRIUBBTD BRIUBBTPD % $ 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) BRILBD BRIUBD BRIUBBD BRIUBBT BRIUBBTPD % $ 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) BRILBD BRIUBD BRIUBBD BRIUBBTD BRIUBBTPD % $ 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 BRI Lao World Area Cambodia China Indonesia 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 Wearing apparel 1.2 1.4 1.8 0.8 0.9 -5.0 -11.7 -1.6 -8.6 0.4 Leather goods 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 Wood products 2.5 2.3 -12.2 11.7 -0.6 -4.2 -15.3 -3.8 -11.7 -3.7 Paper products, publishing 2.1 1.9 24.4 4.6 1.3 -7.8 -7.4 4.4 3.3 -0.2 Petroleum, coal products 2.0 4.6 1.7 -2.9 11.0 3.1 -0.9 26.2 -1.8 Chemical, rubber, plastic 1.4 2.8 -6.6 2.9 -0.9 17.5 -1.8 -0.2 -0.6 3.1 Energy intensive man. 0.8 1.0 18.8 1.0 5.0 9.1 1.1 -1.1 0.8 -1.0 Metal products 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 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 Hospitality services 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 Rest of East Sri South Russian Asia Bangladesh India Nepal Pakistan Lanka Asia EU ECA 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 Wearing apparel 3.2 7.8 -0.9 3.2 8.6 1.0 20.5 0.0 1.3 Leather goods -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 Wood products 3.6 -2.5 8.0 2.2 -40.9 2.5 13.1 0.1 4.1 Paper products, publishing -1.6 13.0 1.0 2.6 21.4 -1.4 20.7 0.3 3.1 Petroleum, coal products -2.6 55.4 3.8 17.9 2.7 9.0 0.2 1.9 Chemical, rubber, plastic -2.1 19.7 6.5 -8.0 72.9 4.0 29.1 -0.4 0.4 Energy intensive man. -0.7 45.1 2.5 -6.2 17.9 -3.1 2.5 -0.5 0.4 Metal products 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 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 Hospitality services -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. Rest of Rest of Iran, Egypt, Eastern Kyrgyz Central Islamic Arab Rest of Poland Europe Kazakhstan Republic Asia Rep. Rep. Turkey 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 Wearing apparel 0.0 0.5 1.8 34.9 6.1 14.7 -1.4 3.1 -2.6 Leather goods -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 Wood products -0.2 -0.4 7.9 32.1 14.1 16.7 4.5 8.9 -5.9 Paper products, publishing 0.3 0.3 1.0 6.9 8.7 15.9 0.5 0.0 -3.2 Petroleum, coal products -1.5 4.4 7.7 6.9 -0.4 14.0 1.3 21.8 8.6 Chemical, rubber, plastic 0.0 0.6 2.3 0.7 10.4 35.7 0.7 7.3 5.6 Energy intensive man. -0.5 -2.0 3.3 4.0 -1.8 8.1 -2.2 3.0 0.5 Metal products -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 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 Hospitality services 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. Rest of Latin Sub- America Rest of Rest of Non-BRI Saharan and United High- Western Kenya Tanzania Area Ethiopia Africa Caribbean States income 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 Wearing apparel -1.1 14.5 0.4 2.0 4.6 0.2 2.9 2.0 -0.1 Leather goods 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 Wood products -5.0 13.9 2.7 7.1 -0.4 2.7 9.0 5.7 0.0 Paper products, publishing -9.0 5.4 2.3 6.1 0.8 0.4 6.1 4.9 0.5 Petroleum, coal products 5.6 -0.8 -1.3 -0.8 0.5 -1.4 -1.4 Chemical, rubber, plastic -7.0 12.0 0.5 8.7 0.3 -0.5 2.7 1.9 -0.7 Energy intensive man. -4.6 6.6 0.6 5.4 -0.2 0.8 2.4 1.4 -0.1 Metal products 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 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 Hospitality services -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 3 Minerals n.e.s. -1714 -883 -5 -32 -105 64 -94 -122 -109 Coal 4565 3083 0 -381 1088 25 0 -23 0 -4 Oil -654 -8623 0 -28 -143 32 -3411 2 -170 -8 Gas 1343 1130 0 40 409 -7 -2428 0 -17 Textiles 10796 7677 16 5880 409 7 -92 -6 -1022 Wearing apparel 11832 11072 479 3484 229 -70 -304 -108 -573 1 Leather goods 6753 5328 463 2694 -105 38 -9 -12 823 15 Processed foods 43684 16011 -47 1558 3475 -21 -969 335 628 10 Wood products 4572 2250 -60 3222 -58 -69 -702 -101 -537 -1 Paper products, publishing 9690 2870 10 2769 192 -2 -238 31 122 Petroleum, coal products 28025 33466 0 1270 -120 21 310 -13 4632 Chemical, rubber, plastic 52343 41276 -40 13333 -629 148 -946 -11 -635 7 Energy intensive man. 16809 8975 41 3182 1300 199 227 -84 148 -1 Metal products 13670 11685 15 8673 129 13 210 56 777 6 Electronics 129909 172507 340 37360 -1032 41 73593 5319 49703 44 Machinery and equipment 85096 70106 229 47377 1317 44 4022 -4 16071 7 Transport equipment 54236 27102 482 6162 764 6 875 -136 11605 2 Manufactures, n.e.s. 20106 18160 65 4680 89 8 -2887 -61 967 10 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 1 Water transport 998 1635 84 164 -5 3 279 -10 137 1 Air transport 8963 8261 458 735 112 10 1307 66 1306 3 Hospitality services 762 -2730 -286 -113 -23 29 -991 -28 -754 Other business services 1348 -14438 -66 -707 -109 -26 -3888 -345 -3181 -4 Other services 45 -812 -13 -43 -6 -3 -176 -10 -250 Agriculture 32653 5983 -97 1734 180 -289 -751 52 -959 3 Manufacturing 487521 428485 1993 141644 5961 364 73092 5207 82710 102 Services 41124 8590 596 4832 121 100 -4197 -227 -4092 2 Other 3540 -5294 -5 -400 1250 114 -5933 -143 -295 -14 Total 564837 437765 2487 147809 7511 288 62211 4888 77364 94 - 34 - Table 8b: Change in the volume of exports in 2030, difference from baseline in $2014 million, ctd. Rest of Rest of East Sri South Russian Asia Bangladesh India Nepal Pakistan Lanka Asia EU ECA 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 Wearing apparel 226 6406 -436 21 940 144 5 -8 14 Leather goods -50 21 203 -2 -164 8 0 -168 -37 Processed foods -508 74 2389 -26 2447 -60 -6 417 1221 Wood products 12 -2 31 1 -71 7 2 16 664 Paper products, publishing -140 5 39 2 63 -9 3 55 265 Petroleum, coal products -2383 78 3789 0 131 5 26 65 2015 Chemical, rubber, plastic -1812 130 8418 -35 2731 146 41 -360 398 Energy intensive man. -89 250 1755 -33 645 -16 16 -288 289 Metal products 77 23 992 21 198 3 5 -197 47 Electronics 8771 709 1312 0 72 43 12 -4579 -658 Machinery and 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 Hospitality services -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. Rest of Iran, Egypt, Eastern Kyrgyz Rest of Islamic Arab Rest of Poland Europe Kazakhstan Republic Central Asia Rep. Rep. Turkey 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 Wearing apparel 3 20 2 139 57 6 -97 898 -632 Leather goods -6 -52 3 136 24 14 17 131 -292 Processed foods 643 911 759 -39 790 87 277 419 272 Wood products -13 -12 1 5 7 1 19 118 -81 Paper products, publishing 36 8 1 6 10 8 10 -1 -318 Petroleum, coal products -99 1058 620 3 -31 2875 96 1352 17775 Chemical, rubber, plastic 12 122 280 7 398 5424 103 1918 11519 Energy intensive man. -113 -755 631 121 -129 237 -209 1107 415 Metal products -73 -41 28 15 17 15 -61 615 -472 Electronics -1456 -288 -438 34 14 19 -1140 655 -361 Machinery and 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 Hospitality services 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. Rest of Latin Sub- America Rest of Rest of Non-BRI Saharan and United High- Western Kenya Tanzania Area Ethiopia Africa Caribbean States income 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 Wearing apparel -15 55 760 3 336 85 222 274 -160 Leather goods 28 67 1425 41 104 870 460 253 -303 Processed foods -74 -5 27673 13 1525 10600 6296 2583 6656 Wood products -10 23 2321 1 -36 317 1263 791 -14 Paper products, publishing -60 7 6821 0 53 134 3729 2089 814 Petroleum, coal products 20 0 -5441 0 -173 -710 1009 -1951 -3615 Chemical, rubber, plastic -196 55 11068 3 111 -613 10313 9716 -8463 Energy intensive man. -61 366 7834 26 -291 1228 3190 3966 -285 Metal products 11 -17 1985 0 50 -422 1093 2709 -1445 Electronics 9 19 -42599 -1 -498 -18536 23964 -24505 -23022 Machinery and 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 Hospitality services -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 BRI Lao World Area Cambodia China Indonesia 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 Wearing apparel 2.4 4.4 10.8 5.6 0.7 14.1 17.6 2.0 30.9 1.5 Leather goods 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 Wood products 4.1 6.1 26.2 8.3 7.0 8.4 24.5 4.2 13.2 2.2 Paper products, publishing 3.7 5.6 4.1 10.3 2.8 6.7 14.3 2.8 14.2 2.7 Petroleum, coal products 5.1 7.8 17.7 12.1 2.6 9.8 12.4 5.6 36.9 5.6 Chemical, rubber, plastic 3.0 5.0 4.1 6.7 3.6 7.7 12.8 2.1 13.4 2.7 Energy intensive man. 2.4 4.0 6.4 5.9 1.5 4.4 9.7 0.0 19.5 2.4 Metal products 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 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 Hospitality services 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 Rest of East Sri South Russian Asia Bangladesh India Nepal Pakistan Lanka Asia EU ECA 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 Wearing apparel 3.7 10.1 5.4 1.6 19.4 3.6 2.2 0.5 2.3 Leather goods 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 Wood products 9.3 18.9 9.3 4.1 48.3 3.2 -1.0 0.1 3.2 Paper products, publishing 1.6 0.0 8.4 1.5 0.2 0.9 2.1 0.0 1.8 Petroleum, coal products 1.8 10.2 7.9 0.5 16.1 3.6 3.8 1.3 4.4 Chemical, rubber, plastic 2.5 3.4 5.9 -1.7 -8.6 3.3 5.8 -0.2 1.7 Energy intensive man. 2.2 -4.3 2.9 -0.6 1.9 1.3 3.0 -0.7 1.0 Metal products 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 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 Hospitality services 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. Rest of Rest of Iran, Egypt, Eastern Kyrgyz Central Islamic Arab Rest of Poland Europe Kazakhstan Republic Asia Rep. Rep. Turkey 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 Wearing apparel 0.8 2.2 1.3 10.4 2.9 3.8 0.4 14.9 4.5 Leather goods 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 Wood products 0.3 3.2 3.3 4.7 1.0 1.6 0.3 10.4 6.5 Paper products, publishing 0.2 2.1 3.3 13.5 3.4 4.5 0.4 10.0 2.6 Petroleum, coal products 1.4 10.7 5.8 14.4 10.4 32.3 3.5 13.6 4.3 Chemical, rubber, plastic 0.2 0.8 2.8 9.9 2.9 9.9 0.6 7.6 4.4 Energy intensive man. -0.5 -0.4 2.4 16.9 4.5 2.9 0.2 4.7 1.7 Metal products 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 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 Hospitality services -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. Rest of Latin Sub- America Rest of Rest of Non-BRI Saharan and United High- Western Kenya Tanzania Area Ethiopia Africa Caribbean States income 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 Wearing apparel 9.0 7.6 1.6 7.1 1.0 -0.3 2.8 2.3 1.0 Leather goods 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 Wood products 21.6 13.2 2.8 13.8 3.0 0.5 7.9 3.4 1.0 Paper products, publishing 10.1 3.1 2.6 3.9 2.0 0.5 6.1 4.8 1.5 Petroleum, coal products 6.3 4.7 3.4 1.3 2.1 1.6 4.8 8.9 1.3 Chemical, rubber, plastic 6.6 3.6 1.8 3.9 1.7 0.4 5.5 3.0 0.3 Energy intensive man. 0.9 4.5 0.9 4.1 0.9 -0.8 2.4 2.9 -0.2 Metal products 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 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 Hospitality services 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 BRI Lao World Area Cambodia China Indonesia PDR Malaysia Philippines Thailand Vietnam Agriculture 59436 48561 118 14690 1852 38 2909 254 3730 1677 Minerals n.e.s. 2151 2400 3 2000 12 10 -45 -13 78 9 Coal 9944 8369 0 4574 1 2 418 -6 685 15 Oil -672 10296 0 920 -107 0 1689 -109 5640 0 Gas 2025 2464 0 0 0 0 253 1 828 0 Textiles 18597 14349 353 2631 364 8 446 71 988 671 Wearing apparel 23700 11718 70 1323 40 4 2183 49 830 314 Leather goods 14371 9125 112 1639 184 3 964 -4 1025 444 Processed foods 74849 49017 1091 9450 1704 139 5753 762 4871 2599 Wood products 8073 4630 10 2134 63 1 338 52 155 82 Paper products, publishing 18073 10610 33 5630 241 22 676 86 714 172 Petroleum, coal products 75615 45501 676 11603 1923 64 2684 487 4835 1350 Chemical, rubber, plastic 117188 76027 168 32992 2238 156 7054 488 7751 1531 Energy intensive man. 53377 42422 325 14030 511 103 4247 2 10788 946 Metal products 24375 12372 36 1922 554 43 1386 69 2130 273 Electronics 244198 164697 193 54046 1382 82 32245 3840 30691 2665 Machinery and equipment 159200 86344 241 24256 1829 202 9318 911 13344 610 Transport equipment 111953 57289 418 19032 2617 82 3700 1058 6429 513 Manufactures, n.e.s. 38042 16519 44 8764 88 12 973 43 1323 433 Electricity 272 284 -5 11 0 2 5 0 133 13 Construction 9087 5713 33 772 100 109 854 10 366 67 Trade services 29891 18840 88 8167 344 19 878 63 3451 173 Other transport 28428 14304 16 5227 284 7 278 93 1584 131 Water transport 5832 2217 2 541 81 2 62 19 49 51 Air transport 22381 9801 41 2533 344 7 413 141 1567 132 Hospitality services 762 1586 6 131 15 0 884 6 336 22 Other business services 1348 9230 26 751 67 6 2052 48 3999 262 Other services 209 1073 11 181 13 1 250 10 400 36 Agriculture 59436 48561 118 14690 1852 38 2909 254 3730 1677 Manufacturing 981611 600618 3771 189451 13738 923 71967 7913 85874 12604 Services 98210 63048 218 18313 1249 151 5677 391 11884 888 Other 13448 23530 4 7495 -94 13 2315 -127 7232 24 Total 1152703 735758 4110 229950 16745 1125 82868 8431 108720 15192 - 42 - Table 9b: Change in the volume of imports in 2030, difference from baseline in $2014 million, ctd. Rest of Rest of East Sri South Russian Asia Bangladesh India Nepal Pakistan Lanka Asia EU ECA 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 Wearing apparel 527 110 237 39 100 22 10 111 1010 Leather goods 505 154 415 13 262 5 10 46 492 Processed foods 3031 1593 2182 13 1153 176 464 286 1595 Wood products 170 9 247 0 149 5 -4 5 74 Paper products, publishing 149 0 868 2 4 9 4 0 176 Petroleum, coal products 890 736 2103 6 2460 304 61 326 531 Chemical, rubber, plastic 1256 433 6988 -27 -1266 153 85 -197 1075 Energy intensive man. 467 -398 3929 -12 135 49 42 -423 275 Metal products 374 -93 1160 5 -33 29 32 -19 326 Electronics 7122 141 8879 36 303 126 47 -1428 1140 Machinery and 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 Hospitality services 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. Rest of Rest of Iran, Egypt, Eastern Kyrgyz Central Islamic Arab Rest of Poland Europe Kazakhstan Republic Asia Rep. Rep. Turkey 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 Wearing apparel 106 80 162 187 182 91 14 1164 2524 Leather goods 29 35 148 142 90 165 9 561 1523 Processed foods 228 516 344 106 1945 1002 288 1604 5363 Wood products 7 34 33 12 34 17 11 205 733 Paper products, publishing 20 91 57 26 64 147 14 663 617 Petroleum, coal products 96 1722 153 170 537 2504 542 3604 4625 Chemical, rubber, plastic 85 264 350 127 359 1464 154 4763 7086 Energy intensive man. -134 -51 181 150 508 309 38 2620 3592 Metal products 86 3 78 55 130 369 41 798 2477 Electronics -91 305 328 104 232 730 110 3044 17929 Machinery and 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 Hospitality services -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. Rest of Latin Sub- America Rest of Rest of Non-BRI Saharan and United High- Western Kenya Tanzania Area Ethiopia Africa Caribbean States income 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 Wearing apparel 121 106 11982 100 208 -135 5248 3275 3286 Leather goods 62 92 5246 28 214 78 2217 1205 1503 Processed foods 299 462 25832 113 1852 1124 7282 9220 6241 Wood products 21 32 3444 6 108 35 1743 991 561 Paper products, publishing 109 18 7462 10 257 191 2289 2459 2256 Petroleum, coal products 319 190 30114 59 1454 2582 6492 14887 4639 Chemical, rubber, plastic 340 156 41161 108 1712 1489 22117 12462 3274 Energy intensive man. 42 153 10955 95 569 -950 4429 7656 -843 Metal products 85 55 12003 170 658 -252 5468 3060 2898 Electronics 312 183 79502 74 2591 -2451 49265 20560 9463 Machinery and 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 Hospitality services 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 BRI Cambo Lao Philipp World Area dia China Indonesia PDR Malaysia 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 Wearing apparel 1.6 1.9 2.3 0.6 0.6 -3.5 -10.7 -0.6 5.7 0.4 Leather goods 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 Wood products -1.3 -1.8 -6.1 0.1 -0.4 -4.5 -11.3 -2.7 -3.6 -4.4 Paper products, publishing -0.7 -1.0 -1.4 -0.4 -0.3 -15.1 -5.2 -1.1 -1.6 -1.0 Petroleum, coal products 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 Energy intensive manu. -0.7 -0.7 0.0 -0.1 0.3 8.7 -4.5 -1.7 -2.3 -1.6 Metal products -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 Machinery and 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 Hospitality services 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 10a: Change in real value added in 2030, percent change from baseline, ctd. Rest of Russia Rest of Pakista South Feder East Asia Bangladesh India Nepal n Sri Lanka Asia EU ECA 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 Wearing apparel 1.3 8.9 -0.4 -0.8 9.5 1.3 0.4 -0.2 0.5 Leather goods -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 Wood products 8.4 1.1 -1.1 -1.0 -12.2 0.1 3.3 -0.2 1.6 Paper products, publishing -1.6 2.5 -1.7 -1.4 -5.5 -0.7 -1.2 0.1 0.2 Petroleum, coal products -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 Energy intensive manu. -0.9 10.6 -1.7 -3.1 -8.1 -1.6 -1.7 -0.7 -0.4 Metal products -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 Machinery and 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 Hospitality services -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 10a: Change in real value added in 2030, percent change from baseline, ctd Rest of Rest of Iran, Egypt, Eastern Kyrgyz Central Islamic Arab Rest of Poland Europe Kazakhstan Republic Asia Rep. Rep. Turkey 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 Wearing apparel -0.1 0.3 -0.5 32.7 3.2 2.6 0.2 4.9 -2.3 Leather goods -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 Wood products -0.5 -1.2 -0.9 1.4 0.7 0.1 -0.5 -0.1 -3.1 Paper products, publishing 0.2 -0.6 -0.2 -8.2 -0.7 -1.7 0.0 -1.5 -2.2 Petroleum, coal products -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 Energy intensive manu. -0.6 -2.3 0.6 -0.2 -1.5 0.4 -1.1 -1.8 -1.6 Metal products -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 Machinery and 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 Hospitality services 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 10a: Change in real value added in 2030, percent change from baseline, ctd. Rest of Latin Non- Sub- America Rest of Rest of BRI Saharan and United High- Western Kenya Tanzania Area Ethiopia Africa Caribbean States income 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 Wearing apparel -1.5 0.9 0.2 1.1 0.5 0.2 -0.5 -0.2 -0.3 Leather goods -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 Wood products -2.7 -2.8 -0.4 -2.2 -0.5 0.0 -0.2 -0.5 -0.7 Paper products, publishing -7.3 -5.8 -0.2 -3.5 -0.7 -0.1 0.2 -0.1 -0.2 Petroleum, coal products -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 Energy intensive manu. -7.9 0.3 -0.8 -2.6 -1.0 -0.6 -0.8 -0.7 -0.6 Metal products -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 Machinery and 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 Hospitality services -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, difference from baseline in $2014 million BRI Lao World Area Cambodia China Indonesia PDR Malaysia Philippines Thailand Vie Agriculture 5336600 4261940 -22738 -438260 -27350 -15807 -114563 -19699 -161517 -1 Minerals n.e.s. -68350 -45287 -34 -15026 -530 81 -202 -3353 -2900 Coal -42018 -46444 0 -26715 4234 22 -155 -443 -5636 -1 Oil -26475 -38379 0 -5768 -2371 28 -6267 -53 -40739 -2 Gas 85804 83570 0 71 2317 -273 -8143 -38 -6369 Textiles 703034 704060 -747 28061 5314 -80 -2014 -2291 -10711 Wearing apparel 356126 346488 21339 29011 2347 -1294 -3018 -2450 10575 Leather goods 14766 4415 5665 7986 -3554 812 -410 -259 5556 2 Processed foods 1445410 1211010 729 101973 82732 7790 -15448 24403 28079 Wood products -120216 -108842 -225 1066 -2548 -75 -8483 -3821 -5464 Paper products, publishing -116718 -98496 -15 -13520 -1680 -35 -6404 -1008 -2435 Petroleum, coal products 29750 36390 -68 -1315 -1400 26 477 -182 5560 Chemical, rubber, plastic -264379 -166558 -2813 -98870 -57410 259 -28652 -12295 -69724 Energy intensive manu. -261311 -186681 0 -18089 4073 1757 -12373 -3251 -10240 -1 Metal products -74931 -12743 14 21665 -4412 57 1648 -873 2451 1 Electronics 10430 328477 2303 -81636 -5790 63 338248 46793 167096 4 Machinery and equipment -294955 -106782 1558 85964 2303 219 11762 -13166 83555 1 Transport equipment -162823 -99342 1467 -30661 -19428 16 6347 -5720 64433 Manufactures, n.e.s. 114004 157892 149 -16185 -171 94 -44604 -2372 10184 1 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 1 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 Hospitality services 418890 327457 -25936 112280 4142 3899 -37331 1864 29112 Other business services -537410 -565200 -1087 38163 -16281 -783 -50661 -5339 -85404 -8 Other services 81080 -76150 5056 198540 38960 -3239 -9978 8817 -6323 3 Agriculture 5336600 4261940 -22738 -438260 -27350 -15807 -114563 -19699 -161517 -1 Manufacturing 1378190 2009280 29353 15450 375 9611 237077 23508 278916 8 Services -6578600 -6151500 -6443 494020 25155 6399 -101714 428 -54477 -2 Other -51038 -46540 -34 -47437 3650 -141 -14766 -3888 -55645 -3 Total 85200 73200 138 23770 1830 62 6034 349 7276 - 50 - Table 10b: Change in real value added in 2030, difference from baseline in $2014 million, ctd. Russia Rest of n Rest of South Federa East Asia Bangladesh India Nepal Pakistan Sri Lanka Asia EU ECA 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 Wearing apparel 4172 224065 -16139 -2539 67871 6792 273 -204 766 Leather goods -1544 895 -3926 -2707 3875 349 -709 -762 -921 Processed foods -35940 354037 127143 -5735 384639 1606 -7460 1419 30459 Wood products 3944 7232 -11525 -187 -67805 44 207 -107 3287 Paper products, publishing -4306 6792 -33116 -1176 -16238 -972 -394 130 280 Petroleum, coal products -819 764 5156 3 -1196 -50 53 -53 1012 Chemical, rubber, plastic -10683 3299 -25168 -443 91082 210 183 -1339 -1718 Energy intensive manu. -1395 26186 -88865 -4037 -8213 -1016 -1556 -1150 -4789 Metal products -1698 46280 -34960 819 -13776 -323 -1636 -1628 -948 Electronics 14080 23970 -75019 -219 -7032 -310 -25 -5020 -7375 Machinery and 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 Hospitality services -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, difference from baseline in $2014 million, ctd. Rest of Rest of Iran, Egypt, Eastern Kazakhst Kyrgyz Central Islamic Arab Rest of Poland Europe an Republic Asia Rep. Rep. Turkey 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 Wearing apparel -19 437 -11 192 189 2854 912 19705 -20869 Leather goods -19 -1511 -2 160 77 2266 155 2763 -34182 Processed foods 1250 12617 582 -160 8941 20970 4510 73601 18090 Wood products -89 -1338 -12 0 14 17 -358 -27 -15730 Paper products, publishing 87 -1306 -10 -173 -148 -1229 -53 -3371 -8029 Petroleum, coal products -20 284 42 29 -70 12604 -67 145 16509 Chemical, rubber, plastic -256 -1610 24 -57 820 46251 -1291 -3784 23006 Energy intensive manu. -408 -8389 136 -43 -1143 4036 -4585 -7215 -24673 Metal products -548 -1867 -32 -242 -239 -866 -1742 1201 -22754 Electronics -1416 -15372 -616 -197 -1477 -9059 -14055 -7147 -71609 Machinery and 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 Hospitality services 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, difference from baseline in $2014 million, ctd. Rest of Latin Sub- America Rest of Rest Tanzani Non-BRI Saharan and United High- West Kenya a Area Ethiopia Africa Caribbean States income Euro Agriculture 197910 193693 1074710 64179 543870 372990 61701 19643 1 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 Wearing apparel -765 855 9639 1201 6493 4847 -1045 -633 Leather goods -119 1933 10351 1242 57 10429 -66 232 Processed foods -24830 6675 234401 51308 61282 97402 8437 1211 1 Wood products -1973 -553 -11374 -1299 -5406 18 -1469 -1147 Paper products, publishing -6538 -774 -18222 -6912 -7459 -2948 2957 -1276 Petroleum, coal products -90 -23 -6640 -1 -1102 -1912 -183 -2299 Chemical, rubber, plastic -7315 -621 -97822 -3154 -15856 -30845 -10410 -12030 -2 Energy intensive manu. -6363 870 -74630 -9096 -18367 -20840 -7359 -10552 Metal products -1598 -13417 -62188 -7156 -10819 -14721 -8893 -322 -2 Electronics -4422 -592 -318047 -246 -12456 -123579 -5966 -110425 -6 Machinery and equipment -3410 -2864 -188173 -1376 -25148 -102501 -29555 14005 -4 Transport equipment -451 -815 -63482 -6511 -18480 -71830 -2720 53106 -1 Manufactures, n.e.s. -3660 -104 -43886 -3264 4407 -22241 835 -10492 -1 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 9 Other transport -3825 -907 -110754 -2811 -30728 -17312 -23706 -14589 -2 Water transport 19 -21 6747 -426 -3296 53 -2241 6526 Air transport -420 -55 -21865 -861 -4496 -3748 -6451 354 Hospitality services -37329 -7202 91432 3381 2343 25426 48601 7292 Other business services -49863 -96676 27780 -39437 -32820 19519 8868 1189 7 Other services -11710 -10285 157230 53669 -38778 21837 71254 18883 3 Agriculture 197910 193693 1074710 64179 543870 372990 61701 19643 1 Manufacturing -63167 -11269 -631100 12191 -45582 -275829 -56739 -75986 -18 Services -134304 -181384 -427100 -75328 -496070 -102700 -100 66310 18 Other -460 -659 -4498 -670 952 7749 -3485 -7625 Total -21 380 12000 371 3170 2200 1370 2340 - 53 - Table 11: Real factor returns, percent change in 2030 relative to baseline Total Un-skilled Skilled labor Capital Land 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 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 - Table 12: Labor displacement, change in 2030 relative to baseline BRIUBD Percent of labor Agriculture Total 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 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 - Table 13: Percent change in emissions in 2030 relative to the baseline CO2 CH4 N2O FGAS BC 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 - Table 13: Percent change in emissions in 2030 relative to the baseline, ctd. NMVB NMVF Nox OC PM10 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 (% deviations from the baseline in 2030) 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. 18 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 non- linear Engel curves in the LES framework. 19 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. - 59 - 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. 20 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. 21 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. 22 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. - 60 - 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 23 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. 24 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. - 61 - Table A1: Regional dimension 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) - 62 - The model’s reference year is 2014 and the model is initialized and calibrated to the GTAP Data Base, Version 10 pre-release 2. 25 The 141 regions in the database have been aggregated to 34 regions, see Table A-1. 26 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. 27 Table A-2: Sector dimension 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 Wood products (LUM) 8 Paper products, publishing (PPP) 9 Textiles (TEX) 10 Wearing apparel (WAP) 11 Leather goods (LEA) 12 Energy intensive manufacturing (KE5) 13 Petroleum, coal products (P_C) 14 Chemical, rubber, plastic products (CRP) 15 Transport equipment (TRQ) 16 Electronics (ELE) 17 Metal products (FMP) 18 Machinery and 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 Hospitality services (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 The GTAP concordance is available in Table A-3. 27 The GTAP concordance is available in Table A-4. - 63 - 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. 28 The near-term GDP projections, through 2020, use the latest World Bank Global Economic Prospects (GEP) forecast. 29 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. 30 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. 31 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)Kt-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. - 64 - 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. 32 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 Sub- Saharan 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. Table A-3: GTAP regional concordance Region name 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 East Asia (XEA), Brunei Darussalam (BRN), 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 (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. - 65 - (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 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), 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 (KWT), Oman (OMN), Qatar (QAT), Saudi Arabia (SAU), United Arab Emirates (ARE), Rest of Western Asia (XWS), Morocco (MAR), Tunisia (TUN), Rest of North Africa (XNF) 27 Ethiopia (ETH) Ethiopia (ETH) 28 Kenya (KEN) Kenya (KEN) 29 Tanzania (TZA) Tanzania (TZA) 30 Rest of Sub-Saharan Africa (XSS) Benin (BEN), Burkina Faso (BFA), Cameroon (CMR), Côte d'Ivoire (CIV), Ghana (GHA), Guinea (GIN), Nigeria (NGA), Senegal (SEN), Togo (TGO), Rest of Western Africa (XWF), Central Africa (XCF), South- Central Africa (XAC), Madagascar (MDG), Malawi (MWI), Mauritius (MUS), Mozambique (MOZ), Rwanda (RWA), Uganda (UGA), Zambia (ZMB), Zimbabwe (ZWE), Rest of Eastern Africa (XEC), Botswana (BWA), Namibia (NAM), South Africa (ZAF), Rest of South African Customs Union (XSC) 31 Latin America and Caribbean (LAC) Mexico (MEX), Rest of North America (XNA), Argentina (ARG), Bolivia (BOL), Brazil (BRA), Chile (CHL), Colombia (COL), Ecuador (ECU), Paraguay (PRY), Peru (PER), Uruguay (URY), Venezuela, RB (VEN), Rest of South America (XSM), Costa Rica (CRI), Guatemala (GTM), Honduras (HND), Nicaragua (NIC), Panama (PAN), El Salvador (SLV), Rest of Central America (XCA), Dominican Republic (DOM), Jamaica (JAM), Puerto Rico (PRI), Trinidad 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 SAR, China (HKG), Japan (JPN), Korea, Rep. (KOR), Taiwan, China (TWN), Canada (CAN), Rest of the World (XTW) 34 Rest of Western Europe (E_U) Austria (AUT), Belgium (BEL), Cyprus (CYP), Denmark (DNK), Finland (FIN), France (FRA), Germany (DEU), Greece (GRC), Ireland (IRL), Italy (ITA), Luxembourg (LUX), Malta (MLT), Netherlands (NLD), Portugal (PRT), Spain (ESP), Sweden (SWE), United Kingdom (GBR), Switzerland (CHE), Norway (NOR), Rest of EFTA (XEF), Rest of Europe (XER) - 66 - Table A-4: GTAP sector concordance Sector name GTAP concordance 1 Agriculture (AGR) Paddy rice (PDR), Wheat (WHT), Cereal grains, n.e.s. (GRO), Vegetables and fruits (V_F), Oil seeds (OSD), Sugar cane and sugar beet (C_B), Plant- based fibers (PFB), Crops, n.e.s. (OCR), Bovine cattle, sheep and goats, horses (CTL), Animal products n.e.s. (OAP), Raw milk (RMK), Wool, silk- worm cocoons (WOL), Forestry (FRS) 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), Meat products n.e.s. (OMT), Vegetable oils and fats (VOL), Dairy products (MIL), Processed rice (PCR), Sugar (SGR), Food products n.e.s. (OFD), Beverages and tobacco products (B_T) 7 Wood products (LUM) Wood products (LUM) 8 Paper products, Paper products, publishing (PPP) publishing (PPP) 9 Textiles (TEX) Textiles (TEX) 10 Wearing apparel (WAP) Wearing apparel (WAP) 11 Leather goods (LEA) Leather products (LEA) 12 Energy intensive Mineral products n.e.s. (NMM), Ferrous metals (I_S), Metals n.e.s. (NFM) manufacturing (KE5) 13 Petroleum, coal products Petroleum, coal products (P_C) (P_C) 14 Chemical, rubber, plastic Chemical, rubber, plastic products (CRP) products (CRP) 15 Transport equipment Motor vehicles and parts (MVH), Transport equipment n.e.s. (OTN) (TRQ) 16 Electronics (ELE) Electronic equipment (ELE) 17 Metal products (FMP) Metal products (FMP) 18 Machinery and Machinery and equipment n.e.s. (OME) equipment (OME) 19 Manufactures, n.e.s. Manufactures n.e.s. (OMF) (XMN) 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 Recreation and other services (ROS) (ROS) 27 Other business services Insurance (ISR), Communication (CMN), Financial services n.e.s. (OFI), (XBS) Business services n.e.s. (OBS) 28 Other services (XSV) Water (WTR), Public administration and defense, education, health services (OSG), Dwellings (DWE) - 67 -