100+ datasets found
  1. w

    Correlation of GDP and population by country

    • workwithdata.com
    Updated May 8, 2025
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    Work With Data (2025). Correlation of GDP and population by country [Dataset]. https://www.workwithdata.com/charts/countries?chart=scatter&x=population&y=gdp
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    Dataset updated
    May 8, 2025
    Dataset authored and provided by
    Work With Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This scatter chart displays GDP (current US$) against population (people). The data is about countries.

  2. Countries with the largest gross domestic product (GDP) per capita 2025

    • statista.com
    • ai-chatbox.pro
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    Statista, Countries with the largest gross domestic product (GDP) per capita 2025 [Dataset]. https://www.statista.com/statistics/270180/countries-with-the-largest-gross-domestic-product-gdp-per-capita/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2025
    Area covered
    Worldwide
    Description

    In 2025, Luxembourg was the country with the highest gross domestic product per capita in the world. Of the 20 listed countries, 13 are in Europe and five are in Asia, alongside the U.S. and Australia. There are no African or Latin American countries among the top 20. Correlation with high living standards While GDP is a useful indicator for measuring the size or strength of an economy, GDP per capita is much more reflective of living standards. For example, when compared to life expectancy or indices such as the Human Development Index or the World Happiness Report, there is a strong overlap - 14 of the 20 countries on this list are also ranked among the 20 happiest countries in 2024, and all 20 have "very high" HDIs. Misleading metrics? GDP per capita figures, however, can be misleading, and to paint a fuller picture of a country's living standards then one must look at multiple metrics. GDP per capita figures can be skewed by inequalities in wealth distribution, and in countries such as those in the Middle East, a relatively large share of the population lives in poverty while a smaller number live affluent lifestyles.

  3. H

    Latent Estimates of Historic Gross Domestic Product, GDP per capita, Surplus...

    • dataverse.harvard.edu
    • search.dataone.org
    Updated Aug 1, 2024
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    Christopher Fariss; Jonathan Markowitz; Miriam Barnum (2024). Latent Estimates of Historic Gross Domestic Product, GDP per capita, Surplus Domestic Product, and Population Data Version 1 [Dataset]. http://doi.org/10.7910/DVN/FALCGS
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 1, 2024
    Dataset provided by
    Harvard Dataverse
    Authors
    Christopher Fariss; Jonathan Markowitz; Miriam Barnum
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Gross Domestic Product (GDP), GDP per capita, and population are central to the study of politics and economics broadly, and conflict processes in particular. Despite the prominence of these variables in empirical research, existing data lack historical coverage and are assumed to be measured without error. We develop a latent variable modeling framework that expands data coverage (1500 A.D--2018 A.D) and, by making use of multiple indicators for each variable, provides a principled framework to estimate uncertainty for values for all country-year variables relative to one another. Expanded temporal coverage of estimates provides new insights about the relationship between development and democracy, conflict, repression, and health. We also demonstrate how to incorporate uncertainty in observational models. Results show that the relationship between repression and development is weaker than models that do not incorporate uncertainty suggest. Future extensions of the latent variable model can address other forms of systematic measurement error with new data, new measurement theory, or both.

  4. India: Development and forecast GDP / Population

    • statista.com
    Updated Jan 27, 2010
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    Statista (2010). India: Development and forecast GDP / Population [Dataset]. https://www.statista.com/statistics/266450/development-and-forecast-for-gdp-and-population-in-india/
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    Dataset updated
    Jan 27, 2010
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2000 - 2009
    Area covered
    India
    Description

    The graph shows the trend in population growth and growth of gross domestic product in India until 2009, as well as a forecast until 2015. See annual figures on India's economic growth here.

  5. Global Country Information 2023

    • zenodo.org
    • data.niaid.nih.gov
    csv
    Updated Jun 15, 2024
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    Nidula Elgiriyewithana; Nidula Elgiriyewithana (2024). Global Country Information 2023 [Dataset]. http://doi.org/10.5281/zenodo.8165229
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    csvAvailable download formats
    Dataset updated
    Jun 15, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Nidula Elgiriyewithana; Nidula Elgiriyewithana
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Description

    This comprehensive dataset provides a wealth of information about all countries worldwide, covering a wide range of indicators and attributes. It encompasses demographic statistics, economic indicators, environmental factors, healthcare metrics, education statistics, and much more. With every country represented, this dataset offers a complete global perspective on various aspects of nations, enabling in-depth analyses and cross-country comparisons.

    Key Features

    • Country: Name of the country.
    • Density (P/Km2): Population density measured in persons per square kilometer.
    • Abbreviation: Abbreviation or code representing the country.
    • Agricultural Land (%): Percentage of land area used for agricultural purposes.
    • Land Area (Km2): Total land area of the country in square kilometers.
    • Armed Forces Size: Size of the armed forces in the country.
    • Birth Rate: Number of births per 1,000 population per year.
    • Calling Code: International calling code for the country.
    • Capital/Major City: Name of the capital or major city.
    • CO2 Emissions: Carbon dioxide emissions in tons.
    • CPI: Consumer Price Index, a measure of inflation and purchasing power.
    • CPI Change (%): Percentage change in the Consumer Price Index compared to the previous year.
    • Currency_Code: Currency code used in the country.
    • Fertility Rate: Average number of children born to a woman during her lifetime.
    • Forested Area (%): Percentage of land area covered by forests.
    • Gasoline_Price: Price of gasoline per liter in local currency.
    • GDP: Gross Domestic Product, the total value of goods and services produced in the country.
    • Gross Primary Education Enrollment (%): Gross enrollment ratio for primary education.
    • Gross Tertiary Education Enrollment (%): Gross enrollment ratio for tertiary education.
    • Infant Mortality: Number of deaths per 1,000 live births before reaching one year of age.
    • Largest City: Name of the country's largest city.
    • Life Expectancy: Average number of years a newborn is expected to live.
    • Maternal Mortality Ratio: Number of maternal deaths per 100,000 live births.
    • Minimum Wage: Minimum wage level in local currency.
    • Official Language: Official language(s) spoken in the country.
    • Out of Pocket Health Expenditure (%): Percentage of total health expenditure paid out-of-pocket by individuals.
    • Physicians per Thousand: Number of physicians per thousand people.
    • Population: Total population of the country.
    • Population: Labor Force Participation (%): Percentage of the population that is part of the labor force.
    • Tax Revenue (%): Tax revenue as a percentage of GDP.
    • Total Tax Rate: Overall tax burden as a percentage of commercial profits.
    • Unemployment Rate: Percentage of the labor force that is unemployed.
    • Urban Population: Percentage of the population living in urban areas.
    • Latitude: Latitude coordinate of the country's location.
    • Longitude: Longitude coordinate of the country's location.

    Potential Use Cases

    • Analyze population density and land area to study spatial distribution patterns.
    • Investigate the relationship between agricultural land and food security.
    • Examine carbon dioxide emissions and their impact on climate change.
    • Explore correlations between economic indicators such as GDP and various socio-economic factors.
    • Investigate educational enrollment rates and their implications for human capital development.
    • Analyze healthcare metrics such as infant mortality and life expectancy to assess overall well-being.
    • Study labor market dynamics through indicators such as labor force participation and unemployment rates.
    • Investigate the role of taxation and its impact on economic development.
    • Explore urbanization trends and their social and environmental consequences.
  6. f

    Data Sheet 1_Understanding how population change is associated with...

    • frontiersin.figshare.com
    docx
    Updated Dec 11, 2024
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    Jasmina M. Buresch; Danielle Medgyesi; Jeremy R. Porter; Zachary M. Hirsch (2024). Data Sheet 1_Understanding how population change is associated with community sociodemographics and economic outcomes across the United States.docx [Dataset]. http://doi.org/10.3389/fhumd.2024.1465218.s001
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    docxAvailable download formats
    Dataset updated
    Dec 11, 2024
    Dataset provided by
    Frontiers
    Authors
    Jasmina M. Buresch; Danielle Medgyesi; Jeremy R. Porter; Zachary M. Hirsch
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States
    Description

    This study examines how population change is associated with changes in sociodemographics and economic outcomes across diverse geographic contexts in the United States from 2000 to 2020. Using Census Tract-level data and generalized additive models (GAMs), we found that communities experiencing population growth showed significant improvements in socioeconomic indicators: for example, a 50% population increase in Northeast metropolitan non-coastal areas was associated with a $10,062 rise [95% confidence interval (CI) = $9,181, $10,944] in median household income. Conversely, areas with population decline faced increasing challenges to community composition: communities experiencing a 50% population decline in West coastal metropolitan areas saw their median age increase by 2.556 years (95% CI = 2.23, 2.89 years), indicating an accelerated aging population. We observed a positive relationship between population growth and local economic growth, with areas experiencing population decline or slow growth showing below-average economic growth. While population change alone explained 10.1% of the variance in county-level GDP growth, incorporating sociodemographic shifts alongside population change using a partial least squares regression (PLSR) more than doubled the explanatory power to 21.4%. Overall, we often found the strength of relationships and sometimes the direction varied by geographic context: coastal areas showed distinct patterns from inland regions, and metropolitan areas responded differently than rural ones. For instance, the percentage of owner-occupied housing was negatively associated with population growth in metropolitan areas, but positively associated in non-metropolitan areas. Our research provides valuable insights for policymakers and planners working to address community changes, particularly in the context of anticipated climate-induced migration. The results suggest that strategies for maintaining economic vitality need to consider not just population retention, but also demographic profiles and socioeconomic opportunities across different geographic contexts.

  7. GDP-BY-COUNTRY-2022

    • kaggle.com
    Updated Oct 24, 2024
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    Muneeb_Qureshi3131 (2024). GDP-BY-COUNTRY-2022 [Dataset]. https://www.kaggle.com/datasets/muneebqureshi3131/gdp-by-country/discussion
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Oct 24, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Muneeb_Qureshi3131
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    This dataset provides key economic indicators for five of the world's largest economies, based on their nominal Gross Domestic Product (GDP) in 2022. It includes the GDP values, population, GDP growth rates, per capita GDP, and each country's share of the global economy.

    Columns: Country: Name of the country. GDP (nominal, 2022): The total nominal GDP in 2022, represented in USD. GDP (abbrev.): The abbreviated GDP in trillions of USD. GDP growth: The percentage growth in GDP compared to the previous year. Population: Total population of each country in 2022. GDP per capita: The GDP per capita, representing average economic output per person in USD. Share of world GDP: The percentage of global GDP contributed by each country. Key Highlights: The dataset includes some of the largest global economies, such as the United States, China, Japan, Germany, and India. The data can be used to analyze the economic standing of countries in terms of overall GDP and per capita wealth. It offers insights into the relative growth rates and population sizes of these leading economies. This dataset is ideal for exploring economic trends, performing country-wise comparisons, or studying the relationship between population size and GDP growth.

  8. w

    Correlation of GDP and female population by country and year in Americas and...

    • workwithdata.com
    Updated Apr 9, 2025
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    Work With Data (2025). Correlation of GDP and female population by country and year in Americas and in 2021 [Dataset]. https://www.workwithdata.com/charts/countries-yearly?chart=scatter&f=2&fcol0=continent&fcol1=date&fop0=%3D&fop1=%3D&fval0=Americas&fval1=2021&x=population_female&y=gdp
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    Dataset updated
    Apr 9, 2025
    Dataset authored and provided by
    Work With Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Americas
    Description

    This scatter chart displays GDP (current US$) against female population (people) in the Americas. The data is filtered where the date is 2021. The data is about countries per year.

  9. w

    Correlation of GDP and population by region in Americas

    • workwithdata.com
    Updated Apr 9, 2025
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    Work With Data (2025). Correlation of GDP and population by region in Americas [Dataset]. https://www.workwithdata.com/charts/regions?chart=scatter&f=1&fcol0=continent&fop0=%3D&fval0=Americas&x=population&y=gdp
    Explore at:
    Dataset updated
    Apr 9, 2025
    Dataset authored and provided by
    Work With Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Americas
    Description

    This scatter chart displays GDP (current US$) against population (people) in the Americas. The data is about regions.

  10. Gross domestic product (GDP) per capita in the United States 2030

    • statista.com
    • ai-chatbox.pro
    Updated May 21, 2025
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    Statista (2025). Gross domestic product (GDP) per capita in the United States 2030 [Dataset]. https://www.statista.com/statistics/263601/gross-domestic-product-gdp-per-capita-in-the-united-states/
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    Dataset updated
    May 21, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The statistic shows the gross domestic product (GDP) per capita in the United States from 1987 to 2024, with projections up until 2030. In 2024, the gross domestic product per capita in the United States amounted to around 85,812.18 U.S. dollars. Thus, the United States is one of the countries with the largest GDP per capita worldwide. See the U.S. GDP growth rate here and the US GDP for further information. For comparison, per capita GDP in China had reached about 5,553 U.S. dollars in 2011. Gross domestic product of the United States The gross domestic product (GDP) of a country is an economic key figure, as it represents the market value of goods and services produced in a country within one year. The United States’ GDP) is increasing consistently, and it is expected to continue growing. On a global scale, the U.S. share of GDP adjusted for Purchasing Power Parity has been in the range of 20 percent over the last few years, give or take a few percentage points. The United States has the largest GDP worldwide, with a significant lead over China, Japan and Germany. Gross domestic product per capita is annual GDP divided by the average population from the same year, which allows for a GDP calculation per inhabitant of a country. Thus, a country with a high GDP, like the United States, can still have a low GDP per capita. Consequently, if compared to other countries, the United States does not rank among the top ten on this list .

  11. GDP growth rate SEA 2018-2026, by country

    • statista.com
    Updated Jul 2, 2025
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    Statista (2025). GDP growth rate SEA 2018-2026, by country [Dataset]. https://www.statista.com/statistics/621011/forecasted-gross-domestic-product-growth-rate-in-southeast-asia-2017/
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    Dataset updated
    Jul 2, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Asia
    Description

    In 2024, the real gross domestic product (GDP) in Vietnam grew by approximately **** percent, marking the highest growth rate in Southeast Asia. In comparison, Myanmar's real GDP growth rate dropped by **** percent. Southeast Asia, a tapestry of economic and cultural complexity Historically a critical component of global trade, Southeast Asia is a diverse region with heterogeneous economies. The region comprises ** countries in total. While Singapore is a highly developed country economy and Brunei has a relatively high GDP per capita, the rest of the Southeast Asian countries are characterized by lower GDPs per capita and have yet to overcome the middle-income trap. Malaysia is one of these countries, having reached the middle-income level for many decades but yet to grow incomes proportionally to its economic development. Nevertheless, Southeast Asia’s young population will further drive economic growth across the region’s markets. ASEAN’s economic significance Aiming to promote economic growth, social progress, cultural development, and regional stability, all Southeast Asian countries except for Timor-Leste are part of the political and economic union Association of Southeast Asian Nations (ASEAN). Even though many concerns surround the union, ASEAN has avoided trade conflicts and is one of the largest and most dynamic trade zones globally. Factors such as the growing young population, high GDP growth, a largely positive trade balance, and exemplary regional integration hold great potential for future economic development in Southeast Asia.

  12. w

    Correlation of GDP and female population by region

    • workwithdata.com
    Updated Apr 9, 2025
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    Work With Data (2025). Correlation of GDP and female population by region [Dataset]. https://www.workwithdata.com/charts/regions?chart=scatter&x=population_female&y=gdp
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    Dataset updated
    Apr 9, 2025
    Dataset authored and provided by
    Work With Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This scatter chart displays GDP (current US$) against female population (people). The data is about regions.

  13. Supplement, data and code: "Is temperature adversely related to economic...

    • figshare.com
    pdf
    Updated Jul 16, 2024
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    David Stadelmann (2024). Supplement, data and code: "Is temperature adversely related to economic development? Evidence on the short-run and the long-run links from sub-national data" [Dataset]. http://doi.org/10.6084/m9.figshare.26311237.v1
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    pdfAvailable download formats
    Dataset updated
    Jul 16, 2024
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    David Stadelmann
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This fileset contains the supplement, the data and the replication code for the paper "Is temperature adversely related to economic development? Evidence on the short-run and the long-run links from sub-national data"Abstract: We examine the effect of rising temperatures on regional economic development, using annual sub-national data for over 1500 regions in 152 countries between 1990 and 2017. In a panel setting with region- and country-year fixed effects, we find no evidence of a homogeneous or heterogeneous effect of rising temperatures on economic development as measured by regional per capita income. Additionally, we find no non-linear relationship between temperature and economic development. We also employ a long-difference approach that is attuned to exploring the long-run relationship between rising temperatures and regional income. Results indicate that rising temperatures have a negative long-run impact on regional per capita income for a minority of regions located in countries with weak economic, legal and political institutions. Furthermore, these vulnerable regions experience a decline in long-term population and human capital development. The use of alternative regional per capita GDP data from 1950 onwards yields similar empirical results. Our findings suggest that negative economic effects of temperature increase with time, only becoming apparent in the long run for regions in already disadvantaged countries. Thus, country-specific conditions may moderate regional economic vulnerability to future temperature increases due to global climate change.

  14. f

    S1 Data -

    • plos.figshare.com
    xlsx
    Updated Jun 22, 2023
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    Mukhtar A. Ijaiya; Adebanjo Olowu; Habibat A. Oguntade; Seun Anjorin; Olalekan A. Uthman (2023). S1 Data - [Dataset]. http://doi.org/10.1371/journal.pgph.0000544.s001
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    xlsxAvailable download formats
    Dataset updated
    Jun 22, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Mukhtar A. Ijaiya; Adebanjo Olowu; Habibat A. Oguntade; Seun Anjorin; Olalekan A. Uthman
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    HIV literature has grown exponentially since it was named the virus that causes acquired immunodeficiency syndrome (AIDS). Bibliometric analysis is a practical approach for quantitatively and qualitatively assessing scientific research. This work aims to describe HIV research output in Africa by country from 1986 until 2020. We conducted a search of the PubMed database in June 2021 for a 35-year period spanning 1986 to 2020. We comparatively weighed for countries’ populations, gross domestic product (GDP), and the number of persons living with HIV (PLHIV) by calculating the ratio of the number of publications from each country. We used Poisson regression models to explore the trends in countries’ HIV research output over the study period. The Pearson correlation analysis assessed the association between research output, population size, GDP, and the number of PLHIV.A total of 83,527 articles from African countries on HIV indexed in PubMed were included for analysis. Republic of South Africa, Uganda, Kenya, and Nigeria account for 54% of the total indexed publications with 33.2% (26,907); 8.4% (7,045); 7.3% (6,118); and 5.1% (4,254), respectively. Africa’s proportion of the world’s total HIV publications increased from 5.1% in 1986 to 31.3% in 2020. There was a strong positive and statistically significant correlation between the total indexed HIV publications and countries’ GDP (r = 0.59, P

  15. Gross domestic product (GDP) per capita in Canada 2029

    • statista.com
    Updated Nov 29, 2024
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    Statista (2024). Gross domestic product (GDP) per capita in Canada 2029 [Dataset]. https://www.statista.com/statistics/263592/gross-domestic-product-gdp-per-capita-in-canada/
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    Dataset updated
    Nov 29, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Canada
    Description

    The statistic shows the gross domestic product (GDP) per capita in Canada from 1987 to 2023, with projections up until 2029. In 2023, the gross domestic product per capita in Canada was around 53,607.4 U.S. dollars. Canada's economy GDP per capita is a measurement often used to determine economic growth and potential increases in productivity and is calculated by taking the GDP and dividing it by the total population in the country. In 2014, Canada had one of the largest GDP per capita values in the world, a value that has grown continuously since 2010 after experiencing a slight downturn due to the financial crisis of 2008. Canada is seen as one of the premier countries in the world, particularly due to its strong economy and healthy international relations, most notably with the United States. Canada and the United States have political, social and economical similarities that further strengthen their relationship. The United States was and continues to be Canada’s primary and most important trade partner and vice versa. Canada’s economy is partly supported by its exports, most notably crude oil, which was the country’s largest export category. Canada was also one of the world’s leading oil exporters in 2013, exporting more than the United States. Additionally, Canada was also a major exporter of goods such as motor vehicles and mechanical appliances, which subsequently ranked the country as one of the world’s top export countries in 2013.

  16. w

    Correlation of GDP and population by year in Burkina Faso

    • workwithdata.com
    Updated Apr 9, 2025
    + more versions
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    Work With Data (2025). Correlation of GDP and population by year in Burkina Faso [Dataset]. https://www.workwithdata.com/charts/countries-yearly?chart=scatter&f=1&fcol0=country&fop0=%3D&fval0=Burkina+Faso&x=population&y=gdp
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    Dataset updated
    Apr 9, 2025
    Dataset authored and provided by
    Work With Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Burkina Faso
    Description

    This scatter chart displays GDP (current US$) against population (people) in Burkina Faso. The data is about countries per year.

  17. w

    Correlation of GDP and population by year in Gabon and in 2021

    • workwithdata.com
    Updated Apr 9, 2025
    + more versions
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    Work With Data (2025). Correlation of GDP and population by year in Gabon and in 2021 [Dataset]. https://www.workwithdata.com/charts/countries-yearly?chart=scatter&f=2&fcol0=country&fcol1=date&fop0=%3D&fop1=%3D&fval0=Gabon&fval1=2021&x=population&y=gdp
    Explore at:
    Dataset updated
    Apr 9, 2025
    Dataset authored and provided by
    Work With Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Gabon
    Description

    This scatter chart displays GDP (current US$) against population (people) in Gabon. The data is filtered where the date is 2021. The data is about countries per year.

  18. f

    Results of regression.

    • plos.figshare.com
    xls
    Updated Aug 8, 2024
    + more versions
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    Yang Shuang; Muhammad Waris; Muhammad Kashif Nawaz; Cheng Chan; Ijaz Younis (2024). Results of regression. [Dataset]. http://doi.org/10.1371/journal.pone.0301829.t005
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    xlsAvailable download formats
    Dataset updated
    Aug 8, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Yang Shuang; Muhammad Waris; Muhammad Kashif Nawaz; Cheng Chan; Ijaz Younis
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Economic welfare is essential in the modern economy since it directly reflects the standard of living, distribution of resources, and general social satisfaction, which influences individual and social well-being. This study aims to explore the relationship between national income accounting different attributes and the economic welfare in Pakistan. However, this study used data from 1950 to 2022, and data was downloaded from the World Bank data portal. Regression analysis is used to investigate the relationship between them and is very effective in measuring the relationship between endogenous and exogenous variables. Moreover, generalized methods of movement (GMM) are used as the robustness of the regression. Our results show that foreign direct investment outflow, Gross domestic product growth rate, GDP per capita, higher Interest, market capitalization, and population growth have a significant negative on the unemployment rate, indicating the rise in these factors leads to a decrease in the employment rate in Pakistan. Trade and savings have a significant positive impact on the unemployment rate, indicating the rise in these factors leads to an increase in the unemployment rate for various reasons. Moreover, all the factors of national income accounting have a significant positive relationship with life expectancy, indicating that an increase in these factors leads to an increase in economic welfare and life expectancy due to better health facilities, many resources, and correct economic policies. However, foreign direct investment, inflation rate, lending interest rate, and population growth have significant positive effects on age dependency, indicating these factors increase the age dependency. Moreover, GDP growth and GDP per capita negatively impact age dependency. Similarly, all the national income accounting factors have a significant negative relationship with legal rights that leads to decreased legal rights. Moreover, due to better health facilities and health planning, there is a negative significant relationship between national income accounting attributes and motility rate among children. Our study advocated the implications for the policymakers and the government to make policies for the welfare and increase the social factors.

  19. f

    Table 1_Spatiotemporal heterogeneity of the association between...

    • frontiersin.figshare.com
    docx
    Updated May 21, 2025
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    Yu Yang; Rongxin He; Liming Li (2025). Table 1_Spatiotemporal heterogeneity of the association between socioeconomic development and birth rate: a geographically and temporally weighted regression modeling study in China.docx [Dataset]. http://doi.org/10.3389/fpubh.2025.1587358.s001
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    docxAvailable download formats
    Dataset updated
    May 21, 2025
    Dataset provided by
    Frontiers
    Authors
    Yu Yang; Rongxin He; Liming Li
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    China
    Description

    BackgroundThe birth rate is an important indicator of the health of the population. However, persistently low birth rate has become a pressing demographic challenge for many countries, including China. This has significant implications for sustainable population planning.MethodsThis study applied hot spot analysis and the spatiotemporal geographically weighted regression (GTWR) modeling, used panel data of 286 cities in China from 2012 to 2021 to explore the spatiotemporal heterogeneity of the relationship between the socioeconomic development and birth rate.ResultsThe research has found that 2017 was an important turning point in China’s demographic transition. The hot spot analysis reveals that the birth rate hot spots are characterized by a multipolar kernel distribution, shifting from spatial diffusion to convergence, with the cold spots mainly located in the northeast. And the GTWR modeling found that the relationship between socioeconomic development and birth rate varies and change dynamically over space and time. Key findings include: (1) the negative impact of GDP per capita on birth rates has intensified; (2) housing prices exhibit both wealth and crowding-out effects on birth rates, and there are obvious regional differences between the north and the south; (3) fiscal education expenditure on birth rates has the most pronounced income effect in the eastern region.ConclusionThis study adopts spatiotemporal perspective to reveal the spatiotemporal heterogeneity of the association between socioeconomic development and birth rate. It provides new evidence on the influence of macro factors on fertility in China. And emphasizes the importance of incorporating regional variations into population policy design.

  20. w

    Correlation of GDP and population by year in Romania and in 2021

    • workwithdata.com
    Updated Apr 9, 2025
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    Work With Data (2025). Correlation of GDP and population by year in Romania and in 2021 [Dataset]. https://www.workwithdata.com/charts/countries-yearly?chart=scatter&f=2&fcol0=country&fcol1=date&fop0=%3D&fop1=%3D&fval0=Romania&fval1=2021&x=population&y=gdp
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    Dataset updated
    Apr 9, 2025
    Dataset authored and provided by
    Work With Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Romania
    Description

    This scatter chart displays GDP (current US$) against population (people) in Romania. The data is filtered where the date is 2021. The data is about countries per year.

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Work With Data (2025). Correlation of GDP and population by country [Dataset]. https://www.workwithdata.com/charts/countries?chart=scatter&x=population&y=gdp

Correlation of GDP and population by country

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Dataset updated
May 8, 2025
Dataset authored and provided by
Work With Data
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

This scatter chart displays GDP (current US$) against population (people). The data is about countries.

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