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This dataset is extracted from https://en.wikipedia.org/wiki/List_of_countries_by_GDP_-PPP-_per_person_employed. Context: There s a story behind every dataset and heres your opportunity to share yours.Content: What s inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too. Acknowledgements:We wouldn t be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.Inspiration: Your data will be in front of the world s largest data science community. What questions do you want to see answered?
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This dataset is extracted from https://en.wikipedia.org/wiki/List_of_countries_by_past_and_projected_GDP_-PPP-. Context: There s a story behind every dataset and heres your opportunity to share yours.Content: What s inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too. Acknowledgements:We wouldn t be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.Inspiration: Your data will be in front of the world s largest data science community. What questions do you want to see answered?
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.
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This dataset is extracted from https://en.wikipedia.org/wiki/List_of_regions_by_past_GDP_-PPP-. Context: There s a story behind every dataset and heres your opportunity to share yours.Content: What s inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too. Acknowledgements:We wouldn t be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.Inspiration: Your data will be in front of the world s largest data science community. What questions do you want to see answered?
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License information was derived automatically
Analysis of ‘GapMinder - Income Inequality’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/psterk/income-inequality on 28 January 2022.
--- Dataset description provided by original source is as follows ---
This analysis focuses on income inequailty as measured by the Gini Index* and its association with economic metrics such as GDP per capita, investments as a % of GDP, and tax revenue as a % of GDP. One polical metric, EIU democracy index, is also included.
The data is for years 2006 - 2016
This investigation can be considered a starting point for complex questions such as:
This analysis uses the gapminder dataset from the Gapminder Foundation. The Gapminder Foundation is a non-profit venture registered in Stockholm, Sweden, that promotes sustainable global development and achievement of the United Nations Millennium Development Goals by increased use and understanding of statistics and other information about social, economic and environmental development at local, national and global levels.
*The Gini Index is a measure of statistical dispersion intended to represent the income or wealth distribution of a nation's residents, and is the most commonly used measurement of inequality. It was developed by the Italian statistician and sociologist Corrado Gini and published in his 1912 paper Variability and Mutability.
The dataset contains data from the following GapMinder datasets:
"This democracy index is using the data from the Economist Inteligence Unit to express the quality of democracies as a number between 0 and 100. It's based on 60 different aspects of societies that are relevant to democracy universal suffrage for all adults, voter participation, perception of human rights protection and freedom to form organizations and parties. The democracy index is calculated from the 60 indicators, divided into five ""sub indexes"", which are:
The sub-indexes are based on the sum of scores on roughly 12 indicators per sub-index, converted into a score between 0 and 100. (The Economist publishes the index with a scale from 0 to 10, but Gapminder has converted it to 0 to 100 to make it easier to communicate as a percentage.)" https://docs.google.com/spreadsheets/d/1d0noZrwAWxNBTDSfDgG06_aLGWUz4R6fgDhRaUZbDzE/edit#gid=935776888
GDP per capita measures the value of everything produced in a country during a year, divided by the number of people. The unit is in international dollars, fixed 2011 prices. The data is adjusted for inflation and differences in the cost of living between countries, so-called PPP dollars. The end of the time series, between 1990 and 2016, uses the latest GDP per capita data from the World Bank, from their World Development Indicators. To go back in time before the World Bank series starts in 1990, we have used several sources, such as Angus Maddison. https://www.gapminder.org/data/documentation/gd001/
Capital formation is a term used to describe the net capital accumulation during an accounting period for a particular country. The term refers to additions of capital goods, such as equipment, tools, transportation assets, and electricity. Countries need capital goods to replace the older ones that are used to produce goods and services. If a country cannot replace capital goods as they reach the end of their useful lives, production declines. Generally, the higher the capital formation of an economy, the faster an economy can grow its aggregate income.
refers to compulsory transfers to the central governement for public purposes. Does not include social security. https://data.worldbank.org/indicator/GC.TAX.TOTL.GD.ZS
Gapminder is an independent Swedish foundation with no political, religious or economic affiliations. Gapminder is a fact tank, not a think tank. Gapminder fights devastating misconceptions about global development. Gapminder produces free teaching resources making the world understandable based on reliable statistics. Gapminder promotes a fact-based worldview everyone can understand. Gapminder collaborates with universities, UN, public agencies and non-governmental organizations. All Gapminder activities are governed by the board. We do not award grants. Gapminder Foundation is registered at Stockholm County Administration Board. Our constitution can be found here.
Thanks to gapminder.org for organizing the above datasets.
Below are some research questions associated with the data and some initial conclusions:
Research Question 1 - Is Income Inequality Getting Worse or Better in the Last 10 Years?
Answer:
Yes, it is getting better, improving from 38.7 to 37.3
On a continent basis, all were either declining or mostly flat, except for Africa.
Research Question 2 - What Top 10 Countries Have the Lowest and Highest Income Inequality?
Answer:
Lowest: Slovenia, Ukraine, Czech Republic, Norway, Slovak Republic, Denmark, Kazakhstan, Finland, Belarus,Kyrgyz Republic
Highest: Colombia, Lesotho, Honduras, Bolivia, Central African Republic, Zambia, Suriname, Namibia, Botswana, South Africa
Research Question 3 Is a higher tax revenue as a % of GDP associated with less income inequality?
Answer: No
Research Question 4 - Is Higher Income Per Person - GDP Per Capita associated with less income inequality?
Answer: No, but weak negative correlation.
Research Question 5 - Is Higher Investment as % GDP associated with less income inequality?
Answer: No
Research Question 6 - Is Higher EIU Democracy Index associated with less income inequality?
Answer: No, but weak negative correlation.
The above results suggest that there are other drivers for the overall reduction in income inequality. Futher analysis of additional factors should be undertaken.
--- Original source retains full ownership of the source dataset ---
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This dataset is extracted from https://en.wikipedia.org/wiki/List_of_OECD_regions_by_GDP_-PPP-_per_capita. Context: There s a story behind every dataset and heres your opportunity to share yours.Content: What s inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too. Acknowledgements:We wouldn t be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.Inspiration: Your data will be in front of the world s largest data science community. What questions do you want to see answered?
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Our source data are from several places. Big Mac prices are from McDonald’s directly and from reporting around the world; exchange rates are from Thomson Reuters; GDP and population data used to calculate the euro area averages are from Eurostat and GDP per person data are from the IMF World Economic Outlook reports.
The Big Mac Index is published by The Economist as an informal way of measuring the purchasing power parity (PPP) between two currencies and provides a test of the extent to which market exchange rates result in goods costing the same in different countries. It "seeks to make exchange-rate theory a bit more digestible."
The Big Mac PPP exchange rate between two countries is obtained by dividing the price of a Big Mac in one country (in its currency) by the price of a Big Mac in another country (in its currency). This value is then compared with the actual exchange rate; if it is lower, then the first currency is under-valued (according to PPP theory) compared with the second, and conversely, if it is higher, then the first currency is over-valued.
Compare countries by seeing how long person has to work for to buy a big mac: https://www.economist.com/news/2020/07/15/the-big-mac-index
The city of Paris in France had an estimated gross domestic product of 757.6 billion Euros in 2021, the most of any European city. Paris was followed by the spanish capital, Madrid, which had a GDP of 237.5 billion Euros, and the Irish capital, Dublin at 230 billion Euros. Milan, in the prosperous north of Italy, had a GDP of 228.4 billion Euros, 65 billion euros larger than the Italian capital Rome, and was the largest non-capital city in terms of GDP in Europe. The engine of Europe Among European countries, Germany had by far the largest economy, with a gross domestic product of over 4.18 trillion Euros. The United Kingdom or France have been Europe's second largest economy since the 1980s, depending on the year, with forecasts suggesting France will overtake the UK going into the 2020s. Germany however, has been the biggest European economy for some time, with five cities (Munich, Berlin, Hamburg, Stuttgart and Frankfurt) among the 15 largest European cities by GDP. Europe's largest cities In 2023, Moscow was the largest european city, with a population of nearly 12.7 million. Paris was the largest city in western Europe, with a population of over 11 million, while London was Europe's third-largest city at 9.6 million inhabitants.
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https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
This dataset is extracted from https://en.wikipedia.org/wiki/List_of_countries_by_GDP_-PPP-_per_person_employed. Context: There s a story behind every dataset and heres your opportunity to share yours.Content: What s inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too. Acknowledgements:We wouldn t be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.Inspiration: Your data will be in front of the world s largest data science community. What questions do you want to see answered?