This statistic shows the projected top ten largest national economies in 2050. By 2050, China is forecasted to have a gross domestic product of over ** trillion U.S. dollars.

The statistic depicts U.S. health expenditure as a percentage of the GDP from 2007 to 2009, and a forecast for 2050. In 2009, U.S. health expenditure accounted for 18 percent of the GDP.

This statistic shows the top ten countries projected to have the greatest average annual growth in gross domestic product from 2016 to 2050. From 2016 to 2050, Vietnam is projected to have an average annual GDP growth rate of 5 percent.

Roughly 12 percent of the annual GDP of lower income countries worldwide in 2050 could be at risk of loss due to exposure to climate hazards, in a slow transition scenario without adaptation measures. Extreme heat and water stress are forecast to have the biggest impact, at 4.7 and 3.2 percent, respectively. In contrast, in upper income countries, the same hazards would put less than one percent of the annual GDP at risk. Nevertheless, climate hazards would still put almost three percent of upper income countries' GDP at risk by 2050, in a no-adaptation scenario.

The impact of climate change has been forecasted to affect the economies of South-East Asian Nations (ASEAN) the hardest. The maximum projected loss incurred by the ASEAN in the event of a 3.2°C temperature rise is 37.4 percent. This is more than double the forecast loss of the Advanced Asia economies and 10 percent higher than the next largest forecast loss of the Middle East & Africa.

Ecuador EC: Population Projection: Mid Year: Growth data was reported at 0.330 % in 2050. This records a decrease from the previous number of 0.350 % for 2049. Ecuador EC: Population Projection: Mid Year: Growth data is updated yearly, averaging 1.120 % from Jun 1990 (Median) to 2050, with 61 observations. The data reached an all-time high of 2.490 % in 1993 and a record low of 0.330 % in 2050. Ecuador EC: Population Projection: Mid Year: Growth data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s Ecuador – Table EC.US Census Bureau: Demographic Projection.

Under current climate policies, Sudan would face a GDP loss of 32 percent by 2050 and a shrinkage of over 80 percent by 2100 due to climate change. According to the source's estimates, this would be the most significant loss among all assessed countries in Africa. Even in a scenario of limiting temperatures to 1.5 degrees Celsius, the damage to Sudan's economy would stand at a GDP reduction of 22 percent by 2050 and 51 percent by 2100. Eight out of 10 countries estimated to record the largest GDP reduction because of climate change globally were located in Africa. The estimates did not consider potential adaptation measures to alleviate the economic loss.

Morocco MA: Population Projection: Mid Year data was reported at 42,026,448.000 Person in 2050. This records an increase from the previous number of 41,880,296.000 Person for 2049. Morocco MA: Population Projection: Mid Year data is updated yearly, averaging 28,113,036.000 Person from Jun 1950 (Median) to 2050, with 101 observations. The data reached an all-time high of 42,026,448.000 Person in 2050 and a record low of 9,343,384.000 Person in 1950. Morocco MA: Population Projection: Mid Year data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s Morocco – Table MA.US Census Bureau: Demographic Projection.

Portugal PT: Population Projection: Mid Year: Growth data was reported at -0.630 % in 2050. This records a decrease from the previous number of -0.600 % for 2049. Portugal PT: Population Projection: Mid Year: Growth data is updated yearly, averaging -0.030 % from Jun 1991 (Median) to 2050, with 60 observations. The data reached an all-time high of 0.690 % in 1993 and a record low of -0.630 % in 2050. Portugal PT: Population Projection: Mid Year: Growth data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s Portugal – Table PT.US Census Bureau: Demographic Projection.

Jordan JO: Population Projection: Mid Year: Growth data was reported at 0.900 % in 2050. This records a decrease from the previous number of 0.920 % for 2049. Jordan JO: Population Projection: Mid Year: Growth data is updated yearly, averaging 2.025 % from Jun 1979 (Median) to 2050, with 72 observations. The data reached an all-time high of 18.740 % in 2013 and a record low of 0.770 % in 2024. Jordan JO: Population Projection: Mid Year: Growth data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s Jordan – Table JO.US Census Bureau: Demographic Projection.

Brazil Forecast: Infrastructure Investments to(GDP) Gross Domestic ProductRatio: Transformation data was reported at 1.805 % in 2050. This records a decrease from the previous number of 1.807 % for 2049. Brazil Forecast: Infrastructure Investments to(GDP) Gross Domestic ProductRatio: Transformation data is updated yearly, averaging 2.504 % from Dec 2021 (Median) to 2050, with 30 observations. The data reached an all-time high of 3.154 % in 2026 and a record low of 1.805 % in 2050. Brazil Forecast: Infrastructure Investments to(GDP) Gross Domestic ProductRatio: Transformation data remains active status in CEIC and is reported by Ministry of Development, Industry, Trade and Services. The data is categorized under Brazil Premium Database’s Investment – Table BR.OG003: Infrastructure Investments: Forecast.

Under current climate policies, Kenya would face a GDP loss of 14 percent by 2050 and a shrinkage of around 50 percent by 2100 due to climate change. According to the source's estimates, in a scenario of limiting temperatures to 1.5 degrees Celsius, the damage to Kenya's economy would stand at a GDP reduction of nine percent by 2050 and 24 percent by 2100. The estimates did not consider potential adaptation measures that could alleviate the economic loss.

The 2018 edition of Woods and Poole Complete U.S. Database provides annual historical data from 1970 (some variables begin in 1990) and annual projections to 2050 of population by race, sex, and age, employment by industry, earnings of employees by industry, personal income by source, households by income bracket and retail sales by kind of business. The Complete U.S. Database contains annual data for all economic and demographic variables for all geographic areas in the Woods & Poole database (the U.S. total, and all regions, states, counties, and CBSAs). The Complete U.S. Database has following components: Demographic & Economic Desktop Data Files: There are 122 files covering demographic and economic data. The first 31 files (WP001.csv – WP031.csv) cover demographic data. The remaining files (WP032.csv – WP122.csv) cover economic data. Demographic DDFs: Provide population data for the U.S., regions, states, Combined Statistical Areas (CSAs), Metropolitan Statistical Areas (MSAs), Micropolitan Statistical Areas (MICROs), Metropolitan Divisions (MDIVs), and counties. Each variable is in a separate .csv file. Variables: Total Population Population Age (breakdown: 0-4, 5-9, 10-15 etc. all the way to 85 & over) Median Age of Population White Population Population Native American Population Asian & Pacific Islander Population Hispanic Population, any Race Total Population Age (breakdown: 0-17, 15-17, 18-24, 65 & over) Male Population Female Population Economic DDFs: The other files (WP032.csv – WP122.csv) provide employment and income data on: Total Employment (by industry) Total Earnings of Employees (by industry) Total Personal Income (by source) Household income (by brackets) Total Retail & Food Services Sales ( by industry) Net Earnings Gross Regional Product Retail Sales per Household Economic & Demographic Flat File: A single file for total number of people by single year of age (from 0 to 85 and over), race, and gender. It covers all U.S., regions, states, CSAs, MSAs and counties. Years of coverage: 1990 - 2050 Single Year of Age by Race and Gender: Separate files for number of people by single year of age (from 0 years to 85 years and over), race (White, Black, Native American, Asian American & Pacific Islander and Hispanic) and gender. Years of coverage: 1990 through 2050. DATA AVAILABLE FOR 1970-2019; FORECASTS THROUGH 2050

Potential national income loss from climate risks can be computed using simple damage functions that estimate damages based on the temperature outcomes inferred from the emissions trajectories projected by the transition scenarios. Potential national income benefit from avoided climate damages can be computed by contrasting the damages estimates based on the temperature outcomes from the transition scenarios with the policy, or mitigation, costs from climate action needed to meet a particular temperature outcome.Sources: Network for Greening the Financial System (2023), Scenarios Portal; and International Institute for Applied Systems Analysis (2023), NGFS Phase 4 Scenario Explorer; IMF Staff Calculations.Category: Transition to a Low-Carbon EconomyMetadataThe framework of the Network of Central Banks and Supervisors for Greening the Financial System (NGFS) allows to simulate, in a forward-looking fashion, the dynamics within and between the energy, land-use, economy, and climate systems. Consistent with that framework, the NGFS explores a set of seven climate scenarios, which are characterized by their overall level of physical and transition risk. The scenarios in the current Phase IV (NGFS climate scenarios data set) are Low Demand, Net Zero 2050, Below 2°C, Delayed Transition, Nationally Determined Contributions (NDCs), Current Policies, and Fragmented World. Each NGFS scenario explores a different set of assumptions for how climate policy, emissions, and temperatures evolve. To reflect the uncertainty inherent to modeling climate-related macroeconomic and financial risks, the NGFS scenarios use different models, over and above the range of scenarios. These integrated assessment models (IAMs) are, by their acronyms: GCAM, MESSAGEix-GLOBIOM, and REMIND-MAgPIE. GDP losses and benefits are derived based on the National Institute Global Econometric Model (NiGEM). NiGEM consists of individual country models for the major economies, which are linked together through trade in goods and services and integrated capital markets. Country level data (or country aggregates, whenever country level disaggregation is not present) for GDP, population, primary energy consumption by fuel type, useful energy and carbon taxes from the IAM output is used as an input into the NiGEM scenarios. Climate scenarios within NiGEM can be broadly categorized into physical and transition events. While the effects of physical and transition shocks alongside policy decisions are contemporaneous, the scenarios in NiGEM can be run in a “stacked” manner, where each scenario uses the information provided by the previous scenario as its starting point. This allows for decomposition of shocks and their effects. Results are available for three scenarios: Net Zero 2050, Delayed Transition, and Current Policies. For details please see the NGFS climate scenarios presentation, the Climate scenarios technical documentation, and the User guide for data access.MethodologyThe NGFS climate scenarios database contains information on mitigation policy costs, business confidence losses, chronic climate damages, and acute climate damages. Mitigation policy costs reflect transition risk in a narrow sense and is measured against the Current Policies scenario (for which it is zero). Business confidence losses result from unanticipated policy changes, and only in the Delayed Transition scenario. GDP losses from chronic risks arise from an increase in global mean temperature. Estimates of the macroeconomic impact of acute risks are based on physical risk modelling covering different hazards. Acute risks are modeled independent of the input IAM. Results are available at the original sources for four hazards: droughts impacting on crop yields, tropical cyclones directly damaging assets, heatwaves affecting productivity and demand, and riverine floods directly damaging assets too. Apart from floods acute risks are the result of randomized stochastic output, yielding 60th to 99th percentile GDP impacts. In accordance with the presentation of the scenario results by the NGFS, the 90th percentile has been chosen as the representative confidence bound. That way, the results are focusing on tail risk. While the choice of the percentile will lead to marked differences for the GDP losses indicator, its influence on the GDP benefits indicator is muted due to comparing like-with-like. Further, the sum of the impacts from the four hazards is taken as the acute physical risk measure; see what follows for the methodology in deriving the net benefits. Net benefits can be calculated by comparing the impact of stronger climate action to the reference scenario, the Current Policies scenario: Net Benefit = 100 * (GDP[Policy scenario] / GDP[Current Policies] – 1). GDP in either scenario can be inferred from the hypothetical baseline with no transition nor physical risk and the percentage losses due to mitigation policy (MP), business confidence (BC), chronic climate (CC), and acute climate (AC): GDP = Baseline * (1 + (MP + BC + CC + AC) / 100). Plugging this into the above equation one finds after some algebra: Net Benefit = (MP[Policy scenario] – MP[Current Policies] + BC[Policy scenario] – BC[Current Policies] + CC[Policy scenario] – CC[Current Policies] + AC[Policy scenario] – AC[Current Policies]) / (1 + (MP + BC + CC + AC)[Current Policies] / 100). Obviously, MP[Current Policies] = BC[Current Policies] = BC[Net Zero 2050] = 0. In order to achieve consistency in aggregation of the four components to the total benefit, the denominator is kept fixed, while for the individual contributions only one component at a time, MP, BC, CC, or AC, is used in the numerator. Results are presented for the 49 countries, five geographic regions covering the remainder of countries, and a global and European total. The coverage of the five remainder regions refers to the country classification of emerging market and developing economies in the IMF’s World Economic Outlook.Data series: Potential National Income Loss From Climate RisksPotential National Income Benefit From Avoided Climate Damages

Kazakhstan KZ: Population Projection: Mid Year: Growth data was reported at 0.260 % in 2050. This records a decrease from the previous number of 0.290 % for 2049. Kazakhstan KZ: Population Projection: Mid Year: Growth data is updated yearly, averaging 0.505 % from Jun 1989 (Median) to 2050, with 62 observations. The data reached an all-time high of 1.320 % in 2009 and a record low of -2.170 % in 1994. Kazakhstan KZ: Population Projection: Mid Year: Growth data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s Kazakhstan – Table KZ.US Census Bureau: Demographic Projection.

By applying Supply-demand Balance Analysis, the water resource supply and demand of the whole river basin and each county or district were calculated, based on which the vulnerability of the water resources system of the basin was evaluated. The IPAT equation was used to set a future water resource demand scenario, setting variables such as future population growth rate, economic growth rate, and unit GDP water consumption to establish the scenario. By taking 2005 as the base year and using assorted forecasting data of population size and economic scale, the future water demand scenarios of various counties and cities from 2010 to 2050 were forecast. By applying the basic structure of the HBV conceptual hydrological model of the Swedish Hydrometeorological Institute, a model of the variation tendency of the basin under climate change was designed. The glacial melting scenario was used as the model input to construct the runoff scenario under climate change. According to the national regulations of the water resources allocation of the basin, a water distribution plan was set up to calculate the water supply comprehensively. Considering of the supply and demand situation, the water resource system vulnerability was evaluated by the water shortage rate. By calculating the (grain production) land pressure index of the major counties and cities in the basin, the balance of supply and demand of land resources under the climate change, glacial melt and population growth scenarios was analyzed, and the vulnerability of the agricultural system was evaluated. The Miami formula and HANPP model were used to calculate the human appropriation of net primary biomass and primary biomass in the major counties and cities for the future, and the vulnerability of ecosystems from the perspective of supply and demand balance was assessed.

This map shows the annual average economic damage of floods due to intense precipitation in future climate (with climate projection 2050). The economic risk is calculated as a weighted combination of the 3 economic damage maps with high, medium and low probability, expressed in €/m2/year.

This map shows the economic damage of a flood from watercourses with a low probability, medium probability and high probability in future climate (with climate projection 2050). The flood damage is calculated in function of the water depth, season (worst possible scenario), flow rate and ascent rate, expressed in €/m2.

Under current climate policies, Morocco would face a GDP loss of 10 percent by 2050 and a shrinkage of 42 percent by 2100 due to climate change. According to the source's estimates, in a scenario of limiting temperatures to 1.5 degrees Celsius, the damage to Morocco's economy would stand at a GDP reduction of seven percent by 2050 and 18 percent by 2100. The estimates did not consider potential adaptation measures that could alleviate the economic loss.

This paper examines the co-benefits of a pathway to net zero emissions (NZE) in Ethiopia focusing on the economic, social and environmental impacts of climate change mitigation and adaption. Using a novel, participatory, systems dynamics modeling approach – the Ethiopia Green Economy Model (GEM) – the authors assess a NZE pathway against a business-as-usual (BAU) scenario to 2050. Assumptions, design of the model, and features of the pathways were gathered through a collaborative initiative, working with representatives of the government of Ethiopia and local experts. The assessment compares the costs of implementing BAU versus NZE development pathways to the co-benefits of climate action. A key policy question is: how will climate action impact growth and investment as well as poverty, income inequality, employment, and ecosystem services? This analysis shows that moving onto a NZE pathway could raise Ethiopia’s GDP growth to 8.1 percent compared to 6.7 percent per year under BAU from 2020 to 2050. Implementation of NZE is estimated to raise cumulative investment costs as well compared to BAU by 2050 but yields significantly more in co-benefits and avoided costs combined, with the latter mainly from energy savings. Economic performance under the NZE pathway will bring about economic structural change, with a decline in agricultural GDP offset by growth in industry and the service sector. Beyond economic growth, a NZE pathway is expected to create employment co-benefits, adding green jobs, while also bringing about faster reduction of extreme and moderate poverty and raising average disposable income. Overall, this broad economy-wide analysis shows a benefit to cost ratio (BCR) greater than 1 by 2030, with $1.04 of benefits generated for every dollar invested, rising to nearly triple this by 2050. Implementation challenges include the need for a dedicated financing strategy and complementary policies to ensure a just transition for unskilled workers; not examined in any detail here, these are topics ripe for future work. Investments in climate mitigation and adaptation in Ethiopia can synergize development along a 2050 NZE pathway, delivering net zero GHG emissions as well as tangible co-benefits across economic, social and environmental outcomes.Higher levels of investment in the NZE scenario leads to faster, more sustainable and inclusive growth compared to BAU in the longer term.Early introduction of NZE actions and policies in land use and forestry, and in energy and transport sectors, improve development outcomes but also present trade-offs, between skilled and unskilled workers for example, for a just transition that require complementary policy effort.Delay in shifting to a NZE pathway risks hindering economic progress and poverty reduction in a future increasing shaped by climate change. Investments in climate mitigation and adaptation in Ethiopia can synergize development along a 2050 NZE pathway, delivering net zero GHG emissions as well as tangible co-benefits across economic, social and environmental outcomes. Higher levels of investment in the NZE scenario leads to faster, more sustainable and inclusive growth compared to BAU in the longer term. Early introduction of NZE actions and policies in land use and forestry, and in energy and transport sectors, improve development outcomes but also present trade-offs, between skilled and unskilled workers for example, for a just transition that require complementary policy effort. Delay in shifting to a NZE pathway risks hindering economic progress and poverty reduction in a future increasing shaped by climate change.