95 datasets found
  1. GDP ranking

    • datacatalog.worldbank.org
    • data.amerigeoss.org
    csv, excel, pdf
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    World Development Indicators, The World Bank, GDP ranking [Dataset]. https://datacatalog.worldbank.org/search/dataset/0038130
    Explore at:
    excel, csv, pdfAvailable download formats
    Dataset provided by
    World Bankhttp://worldbank.org/
    License

    https://datacatalog.worldbank.org/public-licenses?fragment=cchttps://datacatalog.worldbank.org/public-licenses?fragment=cc

    Description

    Gross domestic product ranking table.

  2. WWII: pre-war GDP of selected countries and regions 1938

    • statista.com
    Updated Jan 1, 1998
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    Statista (1998). WWII: pre-war GDP of selected countries and regions 1938 [Dataset]. https://www.statista.com/statistics/1334182/wwii-pre-war-gdp/
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    Dataset updated
    Jan 1, 1998
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    1938
    Area covered
    World
    Description

    In 1938, the year before the Second World War, the United States had, by far, the largest economy in the world in terms of gross domestic product (GDP). The five Allied Great Powers that emerged victorious from the war, along with the three Axis Tripartite Pact countries that were ultimately defeated made up the eight largest independent economies in 1938.

    When values are converted into 1990 international dollars, the U.S. GDP was over 800 billion dollars in 1938, which was more than double that of the second largest economy, the Soviet Union. Even the combined economies of the UK, its dominions, and colonies had a value of just over 680 billion 1990 dollars, showing that the United States had established itself as the world's leading economy during the interwar period (despite the Great Depression).

    Interestingly, the British and Dutch colonies had larger combined GDPs than their respective metropoles, which was a key motivator for the Japanese invasion of these territories in East Asia during the war. Trade with neutral and non-belligerent countries also contributed greatly to the economic development of Allied and Axis powers throughout the war; for example, natural resources from Latin America were essential to the American war effort, while German manufacturing was often dependent on Swedish iron supplies.

  3. T

    LEADING ECONOMIC INDEX by Country Dataset

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 26, 2017
    + more versions
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    LEADING ECONOMIC INDEX by Country Dataset [Dataset]. https://tradingeconomics.com/country-list/leading-economic-index
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    json, csv, xml, excelAvailable download formats
    Dataset updated
    May 26, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    2025
    Area covered
    World
    Description

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

  4. T

    Japan GDP

    • tradingeconomics.com
    • tr.tradingeconomics.com
    • +17more
    csv, excel, json, xml
    Updated Dec 15, 2023
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    TRADING ECONOMICS (2023). Japan GDP [Dataset]. https://tradingeconomics.com/japan/gdp
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    xml, json, csv, excelAvailable download formats
    Dataset updated
    Dec 15, 2023
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Dec 31, 1960 - Dec 31, 2023
    Area covered
    Japan
    Description

    The Gross Domestic Product (GDP) in Japan was worth 4204.49 billion US dollars in 2023, according to official data from the World Bank. The GDP value of Japan represents 3.99 percent of the world economy. This dataset provides - Japan GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  5. T

    United States GDP

    • tradingeconomics.com
    • sv.tradingeconomics.com
    • +17more
    csv, excel, json, xml
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    TRADING ECONOMICS, United States GDP [Dataset]. https://tradingeconomics.com/united-states/gdp
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    xml, excel, json, csvAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Dec 31, 1960 - Dec 31, 2023
    Area covered
    United States
    Description

    The Gross Domestic Product (GDP) in the United States was worth 27720.71 billion US dollars in 2023, according to official data from the World Bank. The GDP value of the United States represents 26.29 percent of the world economy. This dataset provides - United States GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  6. T

    South Korea GDP

    • tradingeconomics.com
    • zh.tradingeconomics.com
    • +17more
    csv, excel, json, xml
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    TRADING ECONOMICS, South Korea GDP [Dataset]. https://tradingeconomics.com/south-korea/gdp
    Explore at:
    xml, csv, excel, jsonAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Dec 31, 1960 - Dec 31, 2023
    Area covered
    South Korea
    Description

    The Gross Domestic Product (GDP) in South Korea was worth 1712.79 billion US dollars in 2023, according to official data from the World Bank. The GDP value of South Korea represents 1.62 percent of the world economy. This dataset provides - South Korea GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  7. m

    Dataset of development of business during the COVID-19 crisis

    • data.mendeley.com
    • narcis.nl
    Updated Nov 9, 2020
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    Tatiana N. Litvinova (2020). Dataset of development of business during the COVID-19 crisis [Dataset]. http://doi.org/10.17632/9vvrd34f8t.1
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    Dataset updated
    Nov 9, 2020
    Authors
    Tatiana N. Litvinova
    License

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

    Description

    To create the dataset, the top 10 countries leading in the incidence of COVID-19 in the world were selected as of October 22, 2020 (on the eve of the second full of pandemics), which are presented in the Global 500 ranking for 2020: USA, India, Brazil, Russia, Spain, France and Mexico. For each of these countries, no more than 10 of the largest transnational corporations included in the Global 500 rating for 2020 and 2019 were selected separately. The arithmetic averages were calculated and the change (increase) in indicators such as profitability and profitability of enterprises, their ranking position (competitiveness), asset value and number of employees. The arithmetic mean values of these indicators for all countries of the sample were found, characterizing the situation in international entrepreneurship as a whole in the context of the COVID-19 crisis in 2020 on the eve of the second wave of the pandemic. The data is collected in a general Microsoft Excel table. Dataset is a unique database that combines COVID-19 statistics and entrepreneurship statistics. The dataset is flexible data that can be supplemented with data from other countries and newer statistics on the COVID-19 pandemic. Due to the fact that the data in the dataset are not ready-made numbers, but formulas, when adding and / or changing the values in the original table at the beginning of the dataset, most of the subsequent tables will be automatically recalculated and the graphs will be updated. This allows the dataset to be used not just as an array of data, but as an analytical tool for automating scientific research on the impact of the COVID-19 pandemic and crisis on international entrepreneurship. The dataset includes not only tabular data, but also charts that provide data visualization. The dataset contains not only actual, but also forecast data on morbidity and mortality from COVID-19 for the period of the second wave of the pandemic in 2020. The forecasts are presented in the form of a normal distribution of predicted values and the probability of their occurrence in practice. This allows for a broad scenario analysis of the impact of the COVID-19 pandemic and crisis on international entrepreneurship, substituting various predicted morbidity and mortality rates in risk assessment tables and obtaining automatically calculated consequences (changes) on the characteristics of international entrepreneurship. It is also possible to substitute the actual values identified in the process and following the results of the second wave of the pandemic to check the reliability of pre-made forecasts and conduct a plan-fact analysis. The dataset contains not only the numerical values of the initial and predicted values of the set of studied indicators, but also their qualitative interpretation, reflecting the presence and level of risks of a pandemic and COVID-19 crisis for international entrepreneurship.

  8. World Bank: International Debt Data

    • kaggle.com
    zip
    Updated Mar 20, 2019
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    World Bank: International Debt Data [Dataset]. https://www.kaggle.com/theworldbank/world-bank-intl-debt
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    zip(0 bytes)Available download formats
    Dataset updated
    Mar 20, 2019
    Dataset authored and provided by
    World Bankhttp://worldbank.org/
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context

    The World Bank is an international financial institution that provides loans to countries of the world for capital projects. The World Bank's stated goal is the reduction of poverty. Source: https://en.wikipedia.org/wiki/World_Bank

    Content

    This dataset contains both national and regional debt statistics captured by over 200 economic indicators. Time series data is available for those indicators from 1970 to 2015 for reporting countries.

    For more information, see the World Bank website.

    Fork this kernel to get started with this dataset.

    Acknowledgements

    https://bigquery.cloud.google.com/dataset/bigquery-public-data:world_bank_intl_debt

    https://cloud.google.com/bigquery/public-data/world-bank-international-debt

    Citation: The World Bank: International Debt Statistics

    Dataset Source: World Bank. This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

    Banner Photo by @till_indeman from Unplash.

    Inspiration

    What countries have the largest outstanding debt?

    https://cloud.google.com/bigquery/images/outstanding-debt.png" alt="enter image description here"> https://cloud.google.com/bigquery/images/outstanding-debt.png

  9. T

    Iran GDP

    • tradingeconomics.com
    • it.tradingeconomics.com
    • +17more
    csv, excel, json, xml
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    TRADING ECONOMICS, Iran GDP [Dataset]. https://tradingeconomics.com/iran/gdp
    Explore at:
    excel, xml, csv, jsonAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Dec 31, 1960 - Dec 31, 2023
    Area covered
    Iran
    Description

    The Gross Domestic Product (GDP) in Iran was worth 404.63 billion US dollars in 2023, according to official data from the World Bank. The GDP value of Iran represents 0.38 percent of the world economy. This dataset provides - Iran GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  10. w

    Global Financial Inclusion (Global Findex) Database 2021 - Gabon

    • microdata.worldbank.org
    • catalog.ihsn.org
    • +1more
    Updated Dec 16, 2022
    + more versions
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    Development Research Group, Finance and Private Sector Development Unit (2022). Global Financial Inclusion (Global Findex) Database 2021 - Gabon [Dataset]. https://microdata.worldbank.org/index.php/catalog/4643
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    Dataset updated
    Dec 16, 2022
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2021
    Area covered
    Gabon
    Description

    Abstract

    The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

    The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

    The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

    Geographic coverage

    National coverage

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

    In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

    In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

    The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

    For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    Sample size for Gabon is 1020.

    Mode of data collection

    Mobile telephone

    Research instrument

    Questionnaires are available on the website.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

  11. Annual GDP and real GDP for the United States 1929-2022

    • statista.com
    Updated Jul 4, 2024
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    Statista (2024). Annual GDP and real GDP for the United States 1929-2022 [Dataset]. https://www.statista.com/statistics/1031678/gdp-and-real-gdp-united-states-1930-2019/
    Explore at:
    Dataset updated
    Jul 4, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    On October 29, 1929, the U.S. experienced the most devastating stock market crash in it's history. The Wall Street Crash of 1929 set in motion the Great Depression, which lasted for twelve years and affected virtually all industrialized countries. In the United States, GDP fell to it's lowest recorded level of just 57 billion U.S dollars in 1933, before rising again shortly before the Second World War. After the war, GDP fluctuated, but it increased gradually until the Great Recession in 2008. Real GDP Real GDP allows us to compare GDP over time, by adjusting all figures for inflation. In this case, all numbers have been adjusted to the value of the US dollar in FY2012. While GDP rose every year between 1946 and 2008, when this is adjusted for inflation it can see that the real GDP dropped at least once in every decade except the 1960s and 2010s. The Great Recession Apart from the Great Depression, and immediately after WWII, there have been two times where both GDP and real GDP dropped together. The first was during the Great Recession, which lasted from December 2007 until June 2009 in the US, although its impact was felt for years after this. After the collapse of the financial sector in the US, the government famously bailed out some of the country's largest banking and lending institutions. Since recovery began in late 2009, US GDP has grown year-on-year, and reached 21.4 trillion dollars in 2019. The coronavirus pandemic and the associated lockdowns then saw GDP fall again, for the first time in a decade. As economic recovery from the pandemic has been compounded by supply chain issues, inflation, and rising global geopolitical instability, it remains to be seen what the future holds for the U.S. economy.

  12. GDP growth per region 1870-1913 (as a share of 1820's GDP)

    • statista.com
    Updated Dec 31, 2006
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    Statista (2006). GDP growth per region 1870-1913 (as a share of 1820's GDP) [Dataset]. https://www.statista.com/statistics/1238526/gdp-growth-region-1820-1913/
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    Dataset updated
    Dec 31, 2006
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    In 1870, the GDP of the U.S., Canada, Australia, and New Zealand was eight times larger than in 1820, and by 1913 it was almost 42 times larger. Although Europe had the largest share of global GDP in 1913, it had only grown by 5.4 times since 1820. GDP in the Asia-Pacific region did not double over this period, as it was not until the latter half of the twentieth century when industrialization began on a large scale.

  13. w

    Global Financial Inclusion (Global Findex) Database 2017 - Afghanistan,...

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Jun 13, 2022
    + more versions
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    Global Financial Inclusion (Global Findex) Database 2017 - Afghanistan, Albania, Algeria...and 133 more [Dataset]. https://microdata.worldbank.org/index.php/catalog/3324
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    Dataset updated
    Jun 13, 2022
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2017
    Area covered
    Afghanistan, Algeria...and 133 more, Albania
    Description

    Abstract

    Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.

    By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

    Geographic coverage

    See Methodology document for country-specific geographic coverage details.

    Universe

    The target population is the civilian, non-institutionalized population 15 years and above.

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    The indicators in the 2017 Global Findex database are drawn from survey data covering almost 150,000 people in 144 economies-representing more than 97 percent of the world’s population (see Table A.1 of the Global Findex Database 2017 Report for a list of the economies included). The survey was carried out over the 2017 calendar year by Gallup, Inc., as part of its Gallup World Poll, which since 2005 has annually conducted surveys of approximately 1,000 people in each of more than 160 economies and in over 150 languages, using randomly selected, nationally representative samples. The target population is the entire civilian, noninstitutionalized population age 15 and above. Interview procedure Surveys are conducted face to face in economies where telephone coverage represents less than 80 percent of the population or where this is the customary methodology. In most economies the fieldwork is completed in two to four weeks.

    In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used.

    Respondents are randomly selected within the selected households. Each eligible household member is listed and the handheld survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer’s gender.

    In economies where telephone interviewing is employed, random digit dialing or a nationally representative list of phone numbers is used. In most economies where cell phone penetration is high, a dual sampling frame is used. Random selection of respondents is achieved by using either the latest birthday or household enumeration method. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    Mode of data collection

    Other [oth]

    Research instrument

    The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup Inc. also provided valuable input. The questionnaire was piloted in multiple countries, using focus groups, cognitive interviews, and field testing. The questionnaire is available in more than 140 languages upon request.

    Questions on cash on delivery, saving using an informal savings club or person outside the family, domestic remittances, and agricultural payments are only asked in developing economies and few other selected countries. The question on mobile money accounts was only asked in economies that were part of the Mobile Money for the Unbanked (MMU) database of the GSMA at the time the interviews were being held.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar, and Jake Hess. 2018. The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution. Washington, DC: World Bank

  14. World Bank Doing Business Measuring Regulatory Quality and Efficiency

    • data.subak.org
    csv
    Updated Feb 16, 2023
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    The World Bank (2023). World Bank Doing Business Measuring Regulatory Quality and Efficiency [Dataset]. https://data.subak.org/dataset/world-bank-doing-business-measuring-regulatory-quality-and-efficiency
    Explore at:
    csvAvailable download formats
    Dataset updated
    Feb 16, 2023
    Dataset provided by
    World Bankhttp://worldbank.org/
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    This dataset contains the World Bank Doing Business Measuring Regulatory Quality and Efficiency for the period 2004 - 2020. Data from World Bank.

    Follow datasource.kapsarc.org for timely data to advance energy economics research.

    Going Beyond Efficiency finds that entrepreneurs in 123 economies saw improvements in their local regulatory framework last year. Between June 2013 and June 2014, the report, which measures 189 economies worldwide, documented 230 business reforms, with 145 reforms aimed at reducing the complexity and cost of complying with business regulation, and 85 reforms aimed at strengthening legal institutions - with Sub-Saharan Africa accounting for the largest number of such reforms. Read about business reforms. Tajikistan, Benin, Togo, Côte d’Ivoire, Senegal, Trinidad and Tobago, the Democratic Republic of Congo, Azerbaijan, Ireland and the United Arab Emirates are among the economies that improved the most in 2013/2014 in areas tracked by Doing Business. Together, these 10 top improvers implemented 40 regulatory reforms making it easier to do business. Sub-Saharan Africa accounts for 5 of the 10 top improvers in 2013/14. The region also accounts for the largest number of regulatory reforms making it easier to do business in the past year—75 of the 230 worldwide. More than 70% of its economies carried out at least one such reform. For the first time this year, Doing Business collected data for 2 cities in 11 economies with more than 100 million inhabitants. The economies are: Bangladesh, Brazil, China, India, Indonesia, Japan, Mexico, Nigeria, Pakistan, the Russian Federation, and the United States. The added city enables a subnational comparison and benchmarking against other large cities. Differences between cities are more common in indicators measuring the steps, time and cost to complete a standardized transaction where local agencies play a larger role, finds the report. Case studies highlighting good practices in 8 of the areas measured by Doing Business indicator sets are featured in the report: the growing efficiency of company registries in starting a business; zoning and urban planning in dealing with construction permits; measuring quality of land administration in registering property; importance of registries in getting credit; going beyond related-party transactions in protecting minority investors; trends before and after the financial crisis in paying taxes; judicial efficiency supporting freedom of contract in enforcing contracts; and measuring strength of insolvency laws in resolving insolvency. See all case studies. The report this year expands the data in three of the 10 topics covered, with further plans to expand on five topics in next year’s report. The Doing Business rankings are now based on a distance to the frontier measure. Each economy from the 189 economies measured is evaluated based on how close their business regulations are to the best global practices. A higher score indicates a more efficient business environment and stronger legal institutions.

    Note: In recent years, Doing Business introduced improvements to all of its indicator sets. In Doing Business 2015, getting credit and protecting minority investors broadened their existing measures. In Doing Business 2016, dealing with construction permits, getting electricity, registering property and enforcing contracts also introduced new measures of quality, and trading across borders introduced a new case scenario to increase the economic relevance. In Doing Business 2017, paying taxes introduced new measures of postfiling processes.

  15. T

    GDP by Country in ASIA

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 29, 2017
    + more versions
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    TRADING ECONOMICS (2017). GDP by Country in ASIA [Dataset]. https://tradingeconomics.com/country-list/gdp?continent=asia
    Explore at:
    xml, json, csv, excelAvailable download formats
    Dataset updated
    May 29, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    2025
    Area covered
    Asia
    Description

    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.

  16. Import/Export Trade Data in North America

    • datarade.ai
    Updated Mar 13, 2020
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    Techsalerator (2020). Import/Export Trade Data in North America [Dataset]. https://datarade.ai/data-products/import-export-trade-data-in-north-america-techsalerator
    Explore at:
    .json, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Mar 13, 2020
    Dataset provided by
    Techsalerator LLC
    Authors
    Techsalerator
    Area covered
    Belize, Saint Pierre and Miquelon, Nicaragua, Costa Rica, Panama, Mexico, Greenland, El Salvador, Bermuda, Honduras, North America
    Description

    Techsalerator’s Import/Export Trade Data for North America

    Techsalerator’s Import/Export Trade Data for North America delivers an exhaustive and nuanced analysis of trade activities across the North American continent. This extensive dataset provides detailed insights into import and export transactions involving companies across various sectors within North America.

    Coverage Across All North American Countries

    The dataset encompasses all key countries within North America, including:

    1. United States

    The dataset provides detailed trade information for the United States, the largest economy in the region. It includes extensive data on trade volumes, product categories, and the key trading partners of the U.S. 2. Canada

    Data for Canada covers a wide range of trade activities, including import and export transactions, product classifications, and trade relationships with major global and regional partners. 3. Mexico

    Comprehensive data for Mexico includes detailed records on its trade activities, including exports and imports, key sectors, and trade agreements affecting its trade dynamics. 4. Central American Countries:

    Belize Costa Rica El Salvador Guatemala Honduras Nicaragua Panama The dataset covers these countries with information on their trade flows, key products, and trade relations with North American and international partners. 5. Caribbean Countries:

    Bahamas Barbados Cuba Dominica Dominican Republic Grenada Haiti Jamaica Saint Kitts and Nevis Saint Lucia Saint Vincent and the Grenadines Trinidad and Tobago Trade data for these Caribbean nations includes detailed transaction records, sector-specific trade information, and their interactions with North American trade partners. Comprehensive Data Features

    Transaction Details: The dataset includes precise details on each trade transaction, such as product descriptions, quantities, values, and dates. This allows for an accurate understanding of trade flows and patterns across North America.

    Company Information: It provides data on companies involved in trade, including names, locations, and industry sectors, enabling targeted business analysis and competitive intelligence.

    Categorization: Transactions are categorized by industry sectors, product types, and trade partners, offering insights into market dynamics and sector-specific trends within North America.

    Trade Trends: Historical data helps users analyze trends over time, identify emerging markets, and assess the impact of economic or political events on trade flows in the region.

    Geographical Insights: The data offers insights into regional trade flows and cross-border dynamics between North American countries and their global trade partners, including significant international trade relationships.

    Regulatory and Compliance Data: Information on trade regulations, tariffs, and compliance requirements is included, helping businesses navigate the complex regulatory environments within North America.

    Applications and Benefits

    Market Research: Companies can leverage the data to discover new market opportunities, analyze competitive landscapes, and understand demand for specific products across North American countries.

    Strategic Planning: Insights from the data enable companies to refine trade strategies, optimize supply chains, and manage risks associated with international trade in North America.

    Economic Analysis: Analysts and policymakers can monitor economic performance, evaluate trade balances, and make informed decisions on trade policies and economic development strategies.

    Investment Decisions: Investors can assess trade trends and market potentials to make informed decisions about investments in North America's diverse economies.

    Techsalerator’s Import/Export Trade Data for North America offers a vital resource for organizations involved in international trade, providing a thorough, reliable, and detailed view of trade activities across the continent.

  17. T

    China GDP

    • tradingeconomics.com
    • it.tradingeconomics.com
    • +17more
    csv, excel, json, xml
    Updated Dec 15, 2023
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    TRADING ECONOMICS (2023). China GDP [Dataset]. https://tradingeconomics.com/china/gdp
    Explore at:
    csv, json, excel, xmlAvailable download formats
    Dataset updated
    Dec 15, 2023
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Dec 31, 1960 - Dec 31, 2023
    Area covered
    China
    Description

    The Gross Domestic Product (GDP) in China was worth 17794.78 billion US dollars in 2023, according to official data from the World Bank. The GDP value of China represents 16.88 percent of the world economy. This dataset provides - China GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  18. T

    Vietnam GDP

    • tradingeconomics.com
    • pt.tradingeconomics.com
    • +17more
    csv, excel, json, xml
    Updated Dec 15, 2024
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    TRADING ECONOMICS (2024). Vietnam GDP [Dataset]. https://tradingeconomics.com/vietnam/gdp
    Explore at:
    csv, excel, json, xmlAvailable download formats
    Dataset updated
    Dec 15, 2024
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Dec 31, 1985 - Dec 31, 2023
    Area covered
    Vietnam
    Description

    The Gross Domestic Product (GDP) in Vietnam was worth 429.72 billion US dollars in 2023, according to official data from the World Bank. The GDP value of Vietnam represents 0.41 percent of the world economy. This dataset provides the latest reported value for - Vietnam GDP - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  19. w

    Global Financial Inclusion (Global Findex) Database 2017 - Rwanda

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Nov 1, 2018
    + more versions
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    Development Research Group, Finance and Private Sector Development Unit (2018). Global Financial Inclusion (Global Findex) Database 2017 - Rwanda [Dataset]. https://microdata.worldbank.org/index.php/catalog/3317
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    Dataset updated
    Nov 1, 2018
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2017
    Area covered
    Rwanda
    Description

    Abstract

    Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.

    By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

    Geographic coverage

    National coverage

    Analysis unit

    Individuals

    Universe

    The target population is the civilian, non-institutionalized population 15 years and above.

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    The indicators in the 2017 Global Findex database are drawn from survey data covering almost 150,000 people in 144 economies-representing more than 97 percent of the world's population (see Table A.1 of the Global Findex Database 2017 Report for a list of the economies included). The survey was carried out over the 2017 calendar year by Gallup, Inc., as part of its Gallup World Poll, which since 2005 has annually conducted surveys of approximately 1,000 people in each of more than 160 economies and in over 150 languages, using randomly selected, nationally representative samples. The target population is the entire civilian, noninstitutionalized population age 15 and above. Interview procedure Surveys are conducted face to face in economies where telephone coverage represents less than 80 percent of the population or where this is the customary methodology. In most economies the fieldwork is completed in two to four weeks.

    In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used.

    Respondents are randomly selected within the selected households. Each eligible household member is listed and the handheld survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

    In economies where telephone interviewing is employed, random digit dialing or a nationally representative list of phone numbers is used. In most economies where cell phone penetration is high, a dual sampling frame is used. Random selection of respondents is achieved by using either the latest birthday or household enumeration method. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    The sample size was 1000.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup Inc. also provided valuable input. The questionnaire was piloted in multiple countries, using focus groups, cognitive interviews, and field testing. The questionnaire is available in more than 140 languages upon request.

    Questions on cash on delivery, saving using an informal savings club or person outside the family, domestic remittances, and agricultural payments are only asked in developing economies and few other selected countries. The question on mobile money accounts was only asked in economies that were part of the Mobile Money for the Unbanked (MMU) database of the GSMA at the time the interviews were being held.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar, and Jake Hess. 2018. The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution. Washington, DC: World Bank

  20. T

    Canada GDP

    • tradingeconomics.com
    • es.tradingeconomics.com
    • +17more
    csv, excel, json, xml
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    Canada GDP [Dataset]. https://tradingeconomics.com/canada/gdp
    Explore at:
    excel, xml, csv, jsonAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Dec 31, 1960 - Dec 31, 2023
    Area covered
    Canada
    Description

    The Gross Domestic Product (GDP) in Canada was worth 2142.47 billion US dollars in 2023, according to official data from the World Bank. The GDP value of Canada represents 2.03 percent of the world economy. This dataset provides - Canada GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Share
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World Development Indicators, The World Bank, GDP ranking [Dataset]. https://datacatalog.worldbank.org/search/dataset/0038130
Organization logo

GDP ranking

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32 scholarly articles cite this dataset (View in Google Scholar)
excel, csv, pdfAvailable download formats
Dataset provided by
World Bankhttp://worldbank.org/
License

https://datacatalog.worldbank.org/public-licenses?fragment=cchttps://datacatalog.worldbank.org/public-licenses?fragment=cc

Description

Gross domestic product ranking table.

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