The statistic shows gross domestic product (GDP) per capita in the ASEAN countries from 2020 to 2024, with projections up until 2030. In 2024, GDP per capita in Singapore was almost ****** U.S. dollars: more than five times the average of all ASEAN countries, and more than 80 times larger than that of Myanmar.

In 2024, the total gross domestic product (GDP) of all ASEAN states amounted to approximately 3.95 trillion U.S. dollars, a significant increase from the previous years. In fact, the GDP of the ASEAN region has been skyrocketing for a few years now, reflecting the region’s thriving economy. Power in the EastThe Association of Southeast Asian Nations (ASEAN) comprises Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, the Philippines, Singapore, Thailand, and Vietnam. It was established in 1967 among five of these countries (Indonesia, Malaysia, Thailand, Singapore, and the Philippines) to facilitate trade and economic growth, as well as promote cultural development and social structures in the region. To date, they have been joined by another five nations. The ASEAN marketThe founding of the ASEAN organization provides the collaborating nations with more autonomy and influence on the global economy than they would have had by themselves. Additionally, struggling participating countries, such as Laos, are given an opportunity to grow on an ASEAN single market.

This dataset provides values for GDP PER CAPITA reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Malaysia's GDP per capita based on its purchasing power parity (PPP) for 2020 amounted to about ** thousand current international dollars, indicating that on average, Malaysian inhabitants own more money to spend than their neighboring countries Indonesia, Thailand, Vietnam, and the Philippines.

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.

Human capital is a nation’s primary source of inner strength to achieve sustainable economic growth and development. Meanwhile, income inequality is a critical issue preventing sustainable economic growth and social transformation, especially in developing countries. This paper investigates the effect of human capital on income inequality in both the short and long term using the mean group, pooled mean group, and threshold regressions for the ASEAN-7 (including Indonesia, Laos, Malaysia, the Philippines, Singapore, Thailand, and Vietnam) from 1992 to 2018. The paper develops a theoretical linkage between human capital and income inequality by combining the learning theory and the Kuznets hypothesis. This linkage is then tested using data from the ASEAN countries. Findings from the paper indicate that human capital reduces income inequality in the short run in the ASEAN countries. However, the effect is reverted in the long run, suggesting that human capital may increase the income gap in these countries. Particularly, the inverted U-shaped relationship between human capital and income inequality is established for the ASEAN countries whose GDP per capita is lower than USD 8.2 thousand per year. In contrast, the U-shaped relationship is found for the countries with income per capital of more than USD 8.2 thousand. All these findings suggest that social policies targeting reducing income inequality should be prioritized and stay at the centre of any economic policies to achieve sustainable economic growth and development in the ASEAN countries.

This study investigates the asymmetric effects of business cycles (measured by real GDP per capita) on population health (measured by life expectancy at birth) from the ASEAN countries, namely, Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand, and Vietnam. The panel vector error correction model, together with various panel unit root tests and cointegration tests, suggested a hidden cointegrated relationship between life expectancy at birth and the positive and negative components of real GDP per capita, and the asymmetric effects of business cycles on population health were identified in both in the short run and in the long run. Policymakers should focus on the harmful effects of business cycles on population health, and government interventions should be more forceful in times of economic expansion than during periods of economic recession.

The file contains the dataset used for the empirical analysis of the study titled "Economic Growth and Corruption in Emerging Markets: Does Economic Freedom Matter?”. The dataset includes annual data from 19 countries of Latin America (Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Ecuador, El Salvador, Guatemala, Haiti, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Dominican Republic, Uruguay, and Venezuela), 9 countries of Asia (China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, Thailand, and Vietnam), and 2 countries of Oceania (Australia and New Zealand). The investigation period spans 2000 through 2017. The data consists about economic, social, demographic, corruption, political e freedom related indexes and variables [Natural logarithm of Gross Domestic Product per capita; Corruption Perception Index; Economic Freedom Index; Economic Freedom of the World; Foreign Direct Investment as % of GDP (net inflows); Gross fixed capital formation as % of GDP; Inflation Rate as ∆% of consumer price indices; Schooling as average number of years of education received by people ages 25 and older; % of the population living in urban areas; Number of years a newborn infant would live; Number of births per woman (average); Annual population growth rate (%); Index that reflects perceptions of the extent to which a country's citizens are able to participate in selecting their government, as well as freedom of expression/media; Index that reflects perceptions of the likelihood of political instability or politically motivated violence, including terrorism; Index that reflects perceptions of the quality of public and civil services; Index that reflects perceptions of the ability of the government to formulate and implement policies and regulations that promote the development of the private sector; Index that reflects perceptions of the extent to which agents have confidence in and abide by the rules of society (contract enforcement, property rights, police and justice); Index that measures a mature and internally coherent democracy vs. autocracies sharply restrict that suppress competitive political participation; HDI_dummy: Human Development Index related; Tropical_Dummy: related to country’s geographic position (located between the Tropics of Cancer and Capricorn)].