In 2024, India’s real gross domestic product (GDP) growth rate was around **** percent, the highest in South Asia. In contrast, Nepal reported the lowest real GDP growth rate in the region at approximately **** percent that year, but it was forecasted to increase to **** percent in 2026.Economy in South Asia In general, South Asia encompasses Sri Lanka, Pakistan, Afghanistan, Bangladesh, Nepal, India and Bhutan. In 2020, India had a GDP of over *** trillion U.S. dollars, while Bangladesh and Sri Lanka followed. The Maldives and Bhutan were among the countries with the lowest GDP in the Asia-Pacific region. In South Asia, the main economic activities include the services sector as well as the industrial and manufacturing sectors.Society in South AsiaFrom the South Asian countries, Bangladesh had the highest share of people living below the poverty line. The Maldives and Sri Lanka exhibited the highest and second-highest GDP per capita among the South Asian countries in 2021.

The statistic shows the growth of the real gross domestic product (GDP) in India from 2020 to 2024, with projections up until 2030. GDP refers to the total market value of all goods and services that are produced within a country per year. It is an important indicator of the economic strength of a country. Real GDP is adjusted for price changes and is therefore regarded as a key indicator for economic growth. In 2024, India's real gross domestic product growth was at about 6.46 percent compared to the previous year. Gross domestic product (GDP) growth rate in India Recent years have witnessed a shift of economic power and attention to the strengthening economies of the BRIC countries: Brazil, Russia, India, and China. The growth rate of gross domestic product in the BRIC countries is overwhelmingly larger than in traditionally strong economies, such as the United States and Germany. While the United States can claim the title of the largest economy in the world by almost any measure, China nabs the second-largest share of global GDP, with India racing Japan for third-largest position. Despite the world-wide recession in 2008 and 2009, India still managed to record impressive GDP growth rates, especially when most of the world recorded negative growth in at least one of those years. Part of the reason for India’s success is the economic liberalization that started in 1991and encouraged trade subsequently ending some public monopolies. GDP growth has slowed in recent years, due in part to skyrocketing inflation. India’s workforce is expanding in the industry and services sectors, growing partially because of international outsourcing — a profitable venture for the Indian economy. The agriculture sector in India is still a global power, producing more wheat or tea than anyone in the world except for China. However, with the mechanization of a lot of processes and the rapidly growing population, India’s unemployment rate remains relatively high.

A dataset comparing the GDP, defense budget, and forex reserves of India and Pakistan during the May 2025 conflict.

Pakistan’s gross domestic product (GDP) growth was 5.77 percent in 2021 after adjusting for inflation.

GDP in developing nations

Gross domestic product measures value of all final goods and services produced within a country’s borders during a certain period of time. In developing countries, GDP should rise more quickly due to “catch-up growth”. In many developing nations, employment is shifted from agriculture to the services sector; simply shifting workers from one sector to more productive sectors increases the income of both the workers and their employers, increasing GDP. This raises GDP per capita (383750), which gives a general idea of the level of development.

International setting

Due to historic tensions, Pakistan neither imports nor exports a significant amount from its neighbor India, favoring China instead. Its other neighbors, Afghanistan and Iran, are not as economically stable at the moment. Pakistan's own GDP is also not in the best shape and is expected to drop during 2019, however, Pakistan stands to benefit from China’s Belt and Road Initiative, which would revive the trading routes that made Pakistan wealthy in past centuries. If this comes to fruition, the GDP for Pakistan is sure to increase.

The gross domestic product (GDP) in current prices in Pakistan stood at 371.41 billion U.S. dollars in 2024. Between 1980 and 2024, the GDP rose by 332.79 billion U.S. dollars, though the increase followed an uneven trajectory rather than a consistent upward trend.This indicator describes the gross domestic product at current prices. The values are based upon the GDP in national currency converted to U.S. dollars using market exchange rates (yearly average). The GDP represents the total value of final goods and services produced during a year.

A dataset summarizing the estimated financial losses for India and Pakistan from Operation Sindoor, including military costs, trade disruption, and market impact.

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.

By the year 2030, it is projected that China will eclipse the United States and have the largest gross domestic product (GDP) in the world, at 31.7 trillion U.S. dollars. The United States is projected to have the second largest GDP, at 22.9 trillion U.S. dollars.

What is gross domestic product?

Gross domestic product, or GDP, is an economic measure of a country’s production in time. It includes all goods and services produced by a country and is used by economists to determine the health of a country’s economy. However, since GDP just shows the size of an economy and is not adjusted for the country’s size, this can make direct country comparisons complicated.

The growth of the global economy

Currently, the United States has the largest GDP in the world, at 20.5 trillion U.S. dollars. China has the second largest GDP, at 13.4 trillion U.S. dollars. In the coming years, production will become faster and more global, which will help to grow the global economy.

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

Energy is a crucial development indicator of production, consumption, and nation-building. However, energy diversification highlighting renewables remains salient in economic development across developing economies. This study explores the economic impact of renewables (RE) and fossil fuel (NRE) utilization in 17 emerging nations. We use annual data with timeframe between 1980 and 2016 and propose a bootstrap panel causality approach with a Fourier function. This allows the examination of multiple structural breaks, cross-section dependence, and heterogeneity across countries. We validate four main hypotheses on the causal links attached to the energy consumption (EC)-growth nexus namely neutrality, conservation, growth, and feedback hypotheses. The findings reveal a causal relationship running from RE to GDP for Brazil, Egypt, Indonesia, Korea, Pakistan, and the Philippines, confirming the growth hypothesis. Besides, the results validate the conservation hypothesis with causality from GDP to RE for China, Colombia, Egypt, Greece, India, Korea, South Africa, and Turkey. We identify causality from NRE to GDP for Pakistan, Mexico, Malaysia, Korea, India, Greece, Egypt, and Brazil; and from GDP to NRE for Thailand, Peru, Malaysia, India, Greece, Egypt, and Colombia. We demonstrate that wealth creation can be achieved through energy diversification rather than relying solely on conventional energy sources.

Monthly data on remittance inflow to South Asian countries (Afghanistan, Bangladesh, Bhutan, India, the Maldives, Nepal, Pakistan, and Sri Lanka) from their partner countries is collected from January 2018 to December 2022 from the Central Bank database. As an alternative to monthly GDP data, monthly Industrial Production Index (IPI) data is used instead as a proxy for GDP. This is because monthly GDP data is not available. Monthly IPI data was collected from International Financial Statistics by the International Monetary Fund (IMF) for South Asian countries and partner countries (Singapore, Malaysia, Japan, Italy, and the UK). Libya and Middle Eastern nations, however, don't have monthly IPI statistics. Since the economies of those countries are heavily dependent on oil production, we created the Oil Production Index as a proxy for GDP. World Bank and EIA monthly crude oil price and production data are used to calculate Oil Production Index. Distance and standard gravity control variables like population, contiguity, and common language are taken from the Dynamic Gravity datasets constructed by the United States International Trade Commission. Migration stock data is collected from the Bureau of Manpower Employment and Training (BMET) and the International Organisation of Migration (IOM). We collect exchange rate data from the Central Bank dataset. To tackle the issue of different currency units, a Bilateral Exchange Rate Index (BERI) is constructed, where the exchange rate of each month for each country is divided by the exchange rate of the base year of that particular country. Furthermore, COVID cases, COVID mortality, and COVID vaccination data are collected from the Our World in Data website.

The study examines export impact of Pakistan’s integration into Shanghai Cooperation Organization (SCO) on its export’s performance. We apply Poisson Pseudo-Maximum Likelihood (PPML) on augmented gravity model to estimate trade data from the period before and after permanent membership with Shanghai Cooperation Organization in 2017. The study aims to explore changes in exports volume and analyze the key mechanism through which Shanghai Cooperation Organization promotes exports. The study assesses that after integration which key exports sector such as agriculture or manufacturing sectors are affected more significantly. The initial findings suggest that SCO integration positively affect and provide access to Central Asian markets, leading to modest but noticeable promotion in exports promotion. In heterogeneity analysis we find that exports of Pakistan are more significant with low and middle-income level countries compared to higher-income level countries. Additionally, exports in the manufacturing sector benefited more than in the agriculture sector. The significant and positive findings of mechanism analysis indicate that the belt and road (B&R) initiative and bilateral trade agreements are the key factors to enhanced exports. The overall impact remains moderated by structural changes in Pakistan economy, such as poor infrastructure, deficiency in energy sector and limited trade relations with its neighbors India and Iran. The study concludes that although the SCO integration has positively promoted exports of Pakistan however, it requires to address domestic economic constraints and capitalize more effectively the benefits of SCO membership through regional cooperation mechanism. For more potential benefits in the region SCO needs to expand B&R connectivity, encourage more trade agreements, and adopt favorable environment to attract high income countries in the organization. The study provides the base for future research in depth analysis of long-term impact of SCO integration on Pakistan exports.

This dataset provides a detailed view of South Asian countries' socio-economic, environmental, and governance metrics from 2000 to 2023. It compiles key indicators like GDP, unemployment, literacy rates, energy use, governance measures, and more to facilitate a comprehensive analysis of each country’s growth, stability, and development trends over the years. The data covers Bangladesh, Bhutan, India, Pakistan, Nepal, Sri Lanka, Afghanistan, and Maldives.

Key Indicators Economic Metrics: Includes GDP (both total and per capita in USD), annual GDP growth rates, inflation, and foreign direct investment. These metrics offer insight into economic health, growth rate, and international investment trends across the region. Employment and Trade: Tracks unemployment rates as a percentage of the labor force and trade (as a percentage of GDP), helping assess workforce stability and international commerce engagement. Income and Poverty: Features the Gini index (for income inequality) and poverty headcount ratio at $2.15/day, showing income distribution and poverty levels. These indicators reveal disparities and poverty within each country. Population Statistics: Includes total population, annual population growth, and urban population percentage, capturing demographic trends and urbanization rates. Social Indicators: Covers literacy rates, school enrollment in primary education, life expectancy at birth, infant mortality rates, and access to electricity, basic water, and sanitation services. These data points help measure the population’s health, education levels, and access to essential services. Environmental and Energy Metrics: Tracks CO2 emissions, PM2.5 air pollution, renewable energy consumption, and forest area. This environmental data is crucial for analyzing air quality, sustainable energy use, and forest coverage trends. Governance Indicators: Includes metrics such as control of corruption, political stability, regulatory quality, rule of law, and voice and accountability. These indicators reflect each country’s governance quality and institutional stability. Digital and Technological Growth: Measures internet usage rates, research and development spending, and high-technology exports. These statistics indicate digital access, innovation, and technological progress. This dataset, sourced from the World Bank DataBank, provides a robust foundation for studying South Asia's socio-economic, environmental, and governance progress. By analyzing these diverse indicators, researchers and policymakers can gain a deeper understanding of the region’s development path and identify areas that need improvement.

The Fiscal Monitor surveys and analyzes the latest public finance developments, it updates fiscal implications of the crisis and medium-term fiscal projections, and assesses policies to put public finances on a sustainable footing.

Country-specific data and projections for key fiscal variables are based on the April 2020 World Economic Outlook database, unless indicated otherwise, and compiled by the IMF staff. Historical data and projections are based on information gathered by IMF country desk officers in the context of their missions and through their ongoing analysis of the evolving situation in each country; they are updated on a continual basis as more information becomes available. Structural breaks in data may be adjusted to produce smooth series through splicing and other techniques. IMF staff estimates serve as proxies when complete information is unavailable. As a result, Fiscal Monitor data can differ from official data in other sources, including the IMF's International Financial Statistics.

The country classification in the Fiscal Monitor divides the world into three major groups: 35 advanced economies, 40 emerging market and middle-income economies, and 40 low-income developing countries. The seven largest advanced economies as measured by GDP (Canada, France, Germany, Italy, Japan, United Kingdom, United States) constitute the subgroup of major advanced economies, often referred to as the Group of Seven (G7). The members of the euro area are also distinguished as a subgroup. Composite data shown in the tables for the euro area cover the current members for all years, even though the membership has increased over time. Data for most European Union member countries have been revised following the adoption of the new European System of National and Regional Accounts (ESA 2010). The low-income developing countries (LIDCs) are countries that have per capita income levels below a certain threshold (currently set at $2,700 in 2016 as measured by the World Bank's Atlas method), structural features consistent with limited development and structural transformation, and external financial linkages insufficiently close to be widely seen as emerging market economies. Zimbabwe is included in the group. Emerging market and middle-income economies include those not classified as advanced economies or low-income developing countries. See Table A, "Economy Groupings," for more details.

Most fiscal data refer to the general government for advanced economies, while for emerging markets and developing economies, data often refer to the central government or budgetary central government only (for specific details, see Tables B-D). All fiscal data refer to the calendar years, except in the cases of Bangladesh, Egypt, Ethiopia, Haiti, Hong Kong Special Administrative Region, India, the Islamic Republic of Iran, Myanmar, Nepal, Pakistan, Singapore, and Thailand, for which they refer to the fiscal year.

Composite data for country groups are weighted averages of individual-country data, unless otherwise specified. Data are weighted by annual nominal GDP converted to U.S. dollars at average market exchange rates as a share of the group GDP.

In many countries, fiscal data follow the IMF's Government Finance Statistics Manual 2014. The overall fiscal balance refers to net lending (+) and borrowing ("") of the general government. In some cases, however, the overall balance refers to total revenue and grants minus total expenditure and net lending.

The fiscal gross and net debt data reported in the Fiscal Monitor are drawn from official data sources and IMF staff estimates. While attempts are made to align gross and net debt data with the definitions in the IMF's Government Finance Statistics Manual, as a result of data limitations or specific country circumstances, these data can sometimes deviate from the formal definitions.

Categorization of vessels-Recycling beneficiary owners (BO) are defined as the owning nations such as India,Pakistan, Bangladesh, China, and Turkey that mostly dismantle ships.-Popular flag BO represents nations that are familiar as popular flagging nations, such as Liberia, Panama and others.-Developing country BO represents nations that have GDP per capita lower than 8000 USD per year in 2016.-Developed country with facility represents nations that have GDP per capita above 800 USD per year in 2016 and possess a ship demolition facility. European countries (For example, UK, France, Netherlands etc.) fall into this category. -Countries that have high GDP per capita but have no ship demolition facility are included in the Developed country without facility category.-BO flag countries are those ships flagged by the owning nations.-Popular flag countries are top thirty countries that flagged most of the ships.-Non-popular flag countries are those nations that are not popular flag bearing countries.Source: Mizanur Rahman S.M. & Junbeum Kim, 2020. Circular economy, proximity, and shipbreaking: A material flow and environmental impact analysis. Journal of Cleaner Production, Elsevier, 2020, pp.120681.

The current health expenditure as a share of the GDP in Pakistan was forecast to continuously decrease between 2024 and 2029 by in total **** percentage points. The share is estimated to amount to **** percent in 2029. According to Worldbank health spending includes expenditures with regards to healthcare services and goods. It is depicted here in relation to the total gross domestic product (GDP) of the country or region at hand.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to *** countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the current health expenditure as a share of the GDP in countries like India and Bangladesh.

Explore the Penn World Table dataset featuring key economic indicators like real GDP, population, human capital index, and more. Access detailed information and analysis for various countries.

Expenditure, GDP, PPP, output, Population, working hours, Index, Household, Consumption, Capital , IRR, prices

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, Comoros, Congo, Costa Rica, Croatia, Cyprus, Denmark, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, 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, Latvia, Lebanon, Lesotho, Liberia, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Mauritania, Mauritius, Mexico, Moldova, Mongolia, Montenegro, Morocco, Mozambique, Myanmar, Namibia, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, North Macedonia, Norway, Oman, Pakistan, Panama, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Saint Kitts and Nevis, Saint Lucia, Sao Tome and Principe, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovakia, Slovenia, South Africa, Spain, Sri Lanka, Sudan, Suriname, Sweden, Switzerland, Syria, Tajikistan, Tanzania, Thailand, Togo, Trinidad and Tobago, Tunisia, Turkey, Turkmenistan, Uganda, Ukraine, United Arab Emirates, United Kingdom, Uruguay, Uzbekistan, Venezuela, Yemen, Zambia, Zimbabwe, World Follow data.kapsarc.org for timely data to advance energy economics research. When using these data, please refer to the following paper:Feenstra, Robert C., Robert Inklaar and Marcel P. Timmer (2015), "The Next Generation of the Penn World Table" American Economic Review, 105(10), 3150-3182, available for download at www.ggdc.net/pwt

The gross domestic product (GDP) per capita in Bangladesh amounted to 2,618.68 U.S. dollars in 2024. Between 1980 and 2024, the GDP per capita rose by 2,307.59 U.S. dollars, though the increase followed an uneven trajectory rather than a consistent upward trend. The GDP per capita will steadily rise by 1,324.5 U.S. dollars over the period from 2024 to 2030, reflecting a clear upward trend.This indicator describes the gross domestic product per capita at current prices. Thereby, the gross domestic product was first converted from national currency to U.S. dollars at current exchange rates and then divided by the total population. The gross domestic product is a measure of a country's productivity. It refers to the total value of goods and service produced during a given time period (here a year).

The heterogeneity tests (Agriculture and manufacture exports).

The current health expenditure as a share of the GDP in Bangladesh was forecast to continuously increase between 2024 and 2029 by in total **** percentage points. The share is estimated to amount to **** percent in 2029. According to Worldbank health spending includes expenditures with regards to healthcare services and goods. It is depicted here in relation to the total gross domestic product (GDP) of the country or region at hand.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to *** countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the current health expenditure as a share of the GDP in countries like Pakistan and India.