Explore real GDP growth projections dataset, including insights into the impact of COVID-19 on economic trends. This dataset covers countries such as Spain, Australia, France, Italy, Brazil, and more.

growth rate, Real, COVID-19, GDP

Spain, Australia, France, Italy, Brazil, Argentina, United Kingdom, United States, Canada, Russia, Turkiye, World, China, Mexico, Korea, India, Saudi Arabia, South Africa, Germany, Indonesia, JapanFollow data.kapsarc.org for timely data to advance energy economics research..Source: OECD Economic Outlook database.- India projections are based on fiscal years, starting in April. The European Union is a full member of the G20, but the G20 aggregate only includes countries that are also members in their own right. Spain is a permanent invitee to the G20. World and G20 aggregates use moving nominal GDP weights at purchasing power parities. Difference in percentage points, based on rounded figures.

This dataset provides an analysis of average monthly prices for four essential food items, namely Eggs, Milk, Bread, and Potatoes, in five different countries: Australia, Japan, Canada, South Africa, and Sweden. The dataset spans a five-year period, from 2018 to 2022, offering a comprehensive overview of how food prices have evolved over time in these nations.

The dataset includes information on the average monthly prices of each food item in the respective countries. This information can be valuable for studying and comparing the cost of living, assessing economic trends, and understanding variations in food price dynamics across different regions.

Use Cases:

Comparative Analysis: Researchers and analysts can compare food prices across the five countries over the five-year period to identify patterns, trends, and variations. This analysis can help understand differences in purchasing power and economic factors impacting food costs.

Cost of Living Studies: The dataset can be used to examine the cost of living in different countries, specifically focusing on the expenses related to basic food items. This information can be beneficial for individuals considering relocation or policymakers aiming to evaluate living standards.

Economic Studies: Economists and policymakers can utilize this dataset to analyze the impact of economic factors, such as inflation or currency fluctuations, on food prices in different countries. It can provide insights into the stability and volatility of food markets in each region.

Forecasting and Planning: Businesses in the food industry can leverage the dataset to forecast future food price trends and plan their operations accordingly. The historical data can serve as a foundation for predictive models and assist in optimizing pricing strategies and supply chain management.

Note: The dataset is based on average monthly prices and does not capture individual variations or specific regions within each country. Further analysis and interpretation should consider additional factors like seasonal influences, local market dynamics, and consumer preferences.

TThe ERS International Macroeconomic Data Set provides historical and projected data for 181 countries that account for more than 99 percent of the world economy. These data and projections are assembled explicitly to serve as underlying assumptions for the annual USDA agricultural supply and demand projections, which provide a 10-year outlook on U.S. and global agriculture. The macroeconomic projections describe the long-term, 10-year scenario that is used as a benchmark for analyzing the impacts of alternative scenarios and macroeconomic shocks.

Explore the International Macroeconomic Data Set 2015 for annual growth rates, consumer price indices, real GDP per capita, exchange rates, and more. Get detailed projections and forecasts for countries worldwide.

Annual growth rates, Consumer price indices (CPI), Real GDP per capita, Real exchange rates, Population, GDP deflator, Real gross domestic product (GDP), Real GDP shares, GDP, projections, Forecast, Real Estate, Per capita, Deflator, share, Exchange Rates, CPI

Afghanistan, Albania, Algeria, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan, Bolivia, Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burundi, Côte d'Ivoire, Cabo Verde, Cambodia, Cameroon, Canada, Central African Republic, Chad, Chile, China, Colombia, Congo, Costa Rica, Croatia, Cuba, Cyprus, Denmark, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Estonia, Eswatini, Ethiopia, Fiji, Finland, France, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Grenada, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hungary, Iceland, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kuwait, Kyrgyzstan, Laos, Latvia, Lebanon, Lesotho, Liberia, Libya, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Mauritania, Mauritius, Mexico, Moldova, Mongolia, Morocco, Mozambique, Myanmar, Namibia, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, Norway, Oman, Pakistan, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Samoa, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovakia, Slovenia, Solomon Islands, South Africa, Spain, Sri Lanka, Sudan, Suriname, Sweden, Switzerland, Syria, Tajikistan, Tanzania, Thailand, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Turkmenistan, Uganda, Ukraine, United Arab Emirates, United Kingdom, Uruguay, Uzbekistan, Vanuatu, Venezuela, Vietnam, Yemen, Zambia, Zimbabwe, WORLD Follow data.kapsarc.org for timely data to advance energy economics research. Notes:

Developed countries/1 Australia, New Zealand, Japan, Other Western Europe, European Union 27, North America

Developed countries less USA/2 Australia, New Zealand, Japan, Other Western Europe, European Union 27, Canada

Developing countries/3 Africa, Middle East, Other Oceania, Asia less Japan, Latin America;

Low-income developing countries/4 Haiti, Afghanistan, Nepal, Benin, Burkina Faso, Burundi, Central African Republic, Chad, Democratic Republic of Congo, Eritrea, Ethiopia, Gambia, Guinea, Guinea-Bissau, Liberia, Madagascar, Malawi, Mali, Mozambique, Niger, Rwanda, Senegal, Sierra Leone, Somalia, Tanzania, Togo, Uganda, Zimbabwe;

Emerging markets/5 Mexico, Brazil, Chile, Czech Republic, Hungary, Poland, Slovakia, Russia, China, India, Korea, Taiwan, Indonesia, Malaysia, Philippines, Thailand, Vietnam, Singapore

BRIICs/5 Brazil, Russia, India, Indonesia, China; Former Centrally Planned Economies

Former centrally planned economies/7 Cyprus, Malta, Recently acceded countries, Other Central Europe, Former Soviet Union

USMCA/8 Canada, Mexico, United States

Europe and Central Asia/9 Europe, Former Soviet Union

Middle East and North Africa/10 Middle East and North Africa

Other Southeast Asia outlook/11 Malaysia, Philippines, Thailand, Vietnam

Other South America outlook/12 Chile, Colombia, Peru, Bolivia, Paraguay, Uruguay

Indicator Source

Real gross domestic product (GDP) World Bank World Development Indicators, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service all converted to a 2015 base year.

Real GDP per capita U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, GDP table and Population table.

GDP deflator World Bank World Development Indicators, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service, all converted to a 2015 base year.

Real GDP shares U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, GDP table.

Real exchange rates U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, CPI table, and Nominal XR and Trade Weights tables developed by the Economic Research Service.

Consumer price indices (CPI) International Financial Statistics International Monetary Fund, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service, all converted to a 2015 base year.

Population Department of Commerce, Bureau of the Census, U.S. Department of Agriculture, Economic Research Service, International Data Base.

Canada CA: Foreign Direct Investment Financial Flows: Inward: USD: Total: Australia data was reported at 1.226 USD bn in 2023. This records a decrease from the previous number of 3.961 USD bn for 2022. Canada CA: Foreign Direct Investment Financial Flows: Inward: USD: Total: Australia data is updated yearly, averaging 965.335 USD mn from Dec 2016 (Median) to 2023, with 8 observations. The data reached an all-time high of 5.490 USD bn in 2019 and a record low of -1.148 USD bn in 2020. Canada CA: Foreign Direct Investment Financial Flows: Inward: USD: Total: Australia data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Canada – Table CA.OECD.FDI: Foreign Direct Investment Financial Flows: USD: by Region and Country: OECD Member: Annual. Reverse investment:Reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) cannot be identified but is believed to be extremely rare. Netting of reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. In the case of Canada, any extension of loans by the DIE to its parent is netted out from inward and outward transactions and positions, regardless of the DIE's equity ownership in its parent. Treatment of debt transactions and positions between fellow enterprises: asset/liability basis. FDI transactions and positions by partner country and by industry include resident Special Purpose Entities (SPEs), which cannot yet be reported separately. Valuation method used for listed inward and outward equity positions: Own funds at book values. Valuation method used for unlisted inward and outward equity positions: Own funds at book values. Valuation method used for inward and outward debt positions: Book value .; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. Direct investment relationships are identified according to the criteria of the Framework for Direct Investment Relationships (FDIR) method. Debt between fellow enterprises are completely covered except in outward FDI positions. Collective investment institutions are covered as direct investment enterprises. Non-profit institutions serving households are covered as direct investors. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the resident direct investor. Outward FDI positions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.

This dataset contains monthly exchange rate data for four major global currencies: United States Dollar (USD), British Pound (GBP), Canadian Dollar (CAD), and Australian Dollar (AUD). The data spans multiple years, starting from January 1999, and is recorded on a monthly basis. It is structured in CSV format with five columns: Date, USD_Price, GBP_Price, CAD_Price, and AUD_Price. The Date column represents the timestamp of the recorded exchange rate in the YYYY-MM-DD format, while the remaining columns represent the exchange rates for their respective currencies.

This dataset can be used for various financial and economic analyses, including identifying long-term trends, studying fluctuations in exchange rates, and understanding periods of stability and volatility. It is particularly useful for researchers and analysts looking to examine historical currency trends and assess the factors influencing foreign exchange markets.

Financial professionals can leverage this data to build predictive models and apply machine learning techniques to estimate future exchange rates. By analyzing past trends, it is possible to gain insights into potential market movements and develop strategies for risk management and investment decision-making.

Economists can use the dataset to examine the impact of global economic events on currency values and study correlations between exchange rates and macroeconomic indicators such as inflation, interest rates, and trade balances. This can provide a deeper understanding of how economic policies and external shocks affect currency markets over time.

Additionally, the dataset is valuable for comparing currency movements with stock markets, commodity prices, and international trade patterns. It enables researchers to analyze how different currencies react to financial crises, policy changes, and economic shifts. By offering a comprehensive view of historical exchange rate fluctuations, this dataset serves as a foundation for financial forecasting, economic research, and market correlation studies.

Canada CA: Foreign Direct Investment Financial Flows: Outward: USD: Total: Australia data was reported at 3.107 USD bn in 2023. This records a decrease from the previous number of 4.254 USD bn for 2022. Canada CA: Foreign Direct Investment Financial Flows: Outward: USD: Total: Australia data is updated yearly, averaging 1.832 USD bn from Dec 2016 (Median) to 2023, with 8 observations. The data reached an all-time high of 5.441 USD bn in 2021 and a record low of -755.593 USD mn in 2019. Canada CA: Foreign Direct Investment Financial Flows: Outward: USD: Total: Australia data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Canada – Table CA.OECD.FDI: Foreign Direct Investment Financial Flows: USD: by Region and Country: OECD Member: Annual. Reverse investment:Reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) cannot be identified but is believed to be extremely rare. Netting of reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. In the case of Canada, any extension of loans by the DIE to its parent is netted out from inward and outward transactions and positions, regardless of the DIE's equity ownership in its parent. Treatment of debt transactions and positions between fellow enterprises: asset/liability basis. FDI transactions and positions by partner country and by industry include resident Special Purpose Entities (SPEs), which cannot yet be reported separately. Valuation method used for listed inward and outward equity positions: Own funds at book values. Valuation method used for unlisted inward and outward equity positions: Own funds at book values. Valuation method used for inward and outward debt positions: Book value .; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. Direct investment relationships are identified according to the criteria of the Framework for Direct Investment Relationships (FDIR) method. Debt between fellow enterprises are completely covered except in outward FDI positions. Collective investment institutions are covered as direct investment enterprises. Non-profit institutions serving households are covered as direct investors. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the resident direct investor. Outward FDI positions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.

Canada CA: Foreign Direct Investment Position: Outward: Total: Australia data was reported at 58,285.398 CAD mn in 2023. This records an increase from the previous number of 55,115.531 CAD mn for 2022. Canada CA: Foreign Direct Investment Position: Outward: Total: Australia data is updated yearly, averaging 35,611.926 CAD mn from Dec 2011 (Median) to 2023, with 13 observations. The data reached an all-time high of 58,285.398 CAD mn in 2023 and a record low of 19,627.000 CAD mn in 2013. Canada CA: Foreign Direct Investment Position: Outward: Total: Australia data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Canada – Table CA.OECD.FDI: Foreign Direct Investment Position: by Region and Country: OECD Member: Annual. Reverse investment:Reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) cannot be identified but is believed to be extremely rare. Netting of reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. In the case of Canada, any extension of loans by the DIE to its parent is netted out from inward and outward transactions and positions, regardless of the DIE's equity ownership in its parent. Treatment of debt transactions and positions between fellow enterprises: asset/liability basis. FDI transactions and positions by partner country and by industry include resident Special Purpose Entities (SPEs), which cannot yet be reported separately. Valuation method used for listed inward and outward equity positions: Own funds at book values. Valuation method used for unlisted inward and outward equity positions: Own funds at book values. Valuation method used for inward and outward debt positions: Book value .; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. Direct investment relationships are identified according to the criteria of the Framework for Direct Investment Relationships (FDIR) method. Debt between fellow enterprises are completely covered except in outward FDI positions. Collective investment institutions are covered as direct investment enterprises. Non-profit institutions serving households are covered as direct investors. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the resident direct investor. Outward FDI positions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.

Canada CA: Foreign Direct Investment Position: Outward: % of Total (FDI) Foreign Direct Investment: Total: Australia data was reported at 2.684 % in 2023. This records a decrease from the previous number of 2.712 % for 2022. Canada CA: Foreign Direct Investment Position: Outward: % of Total (FDI) Foreign Direct Investment: Total: Australia data is updated yearly, averaging 2.847 % from Dec 2011 (Median) to 2023, with 13 observations. The data reached an all-time high of 4.064 % in 2012 and a record low of 2.473 % in 2015. Canada CA: Foreign Direct Investment Position: Outward: % of Total (FDI) Foreign Direct Investment: Total: Australia data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Canada – Table CA.OECD.FDI: Foreign Direct Investment: % of Total FDI: by Region and Country: OECD Member: Annual. Reverse investment:Reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) cannot be identified but is believed to be extremely rare. Netting of reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. In the case of Canada, any extension of loans by the DIE to its parent is netted out from inward and outward transactions and positions, regardless of the DIE's equity ownership in its parent. Treatment of debt transactions and positions between fellow enterprises: asset/liability basis. FDI transactions and positions by partner country and by industry include resident Special Purpose Entities (SPEs), which cannot yet be reported separately. Valuation method used for listed inward and outward equity positions: Own funds at book values. Valuation method used for unlisted inward and outward equity positions: Own funds at book values. Valuation method used for inward and outward debt positions: Book value .; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. Direct investment relationships are identified according to the criteria of the Framework for Direct Investment Relationships (FDIR) method. Debt between fellow enterprises are completely covered except in outward FDI positions. Collective investment institutions are covered as direct investment enterprises. Non-profit institutions serving households are covered as direct investors. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the resident direct investor. Outward FDI positions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.