The map above displays the world’s countries sized by international tourism receipts in 2017. The top ten can be seen in tabular view below:
A few things jump out. The US gains more from international tourism than any other country by a factor of 3 and China spends more aboard than any other country by a factor of 2! Macau (ranked 9th) has three times the gambling revenue of Las Vegas, with much of this money origination in mainland China and spend ‘internationally’ in Macau. (Hong Kong ranks 11th with 33 billion in receipts in 2017) If Hong Kong, Macau, and Taiwan were counted as one country on this list, it would rank 2nd with 81 billion in receipts.
Visit the link to interactively play with the data: https://public.tableau.com/profile/brad.ballard#!/vizhome/Top50CitiesbyGDPComparision/Dashboard
We often see lists of GDP by country, but rarely by city. This is puzzling because most countries are empty space and GDP output is concentrated in a few small areas. For example, about 50% of US GDP is generated on only 2% of its area – namely: cities. This is also the case around the world.
To put the importance of these 50 cities into perspective. The top 25 cities in the world generate 15.5 trillion dollars in GDP or 20.1% of total world GDP (2014 numbers). They do this with only 4.7% of world population and have a GDP per capita of 44 thousand dollars (4 times world average). The top 50 cities in the world generate 22.6 trillion dollars in GDP or 29.4% of total world GDP (2014 numbers). They do this with only 8.2% of world population and have a GDP per capita of 37 thousand dollars (3.5 times world average).
The GDP centers are clustered in geographic regions in North America, Western Europe, and Eastern Asia. Only a few cities are represented from the southern hemisphere and none from Africa or the Middle East. Asian cities tend to be larger in population, number of skyscrapers, and lower in GDP per capita. North American and Europen cities tend to have small-to-medium populations, low density, and a high GDP per capita.
Above is two snapshots of the number of people living in extreme poverty for various countries around the world. Countries are colored by the geographic region they are in — East Asia & Pacific, South Asia, etc. The first snapshot is from 1993 and the other is 20 years later in 2013. What is striking the decrease in extreme poverty in China and for the East Asia/Pacific region generally. For a comparison, China and India have comparable population 1.4 billion and 1.3 billion respectively — however, China has been much more successful in lifting a much larger proportion of its citizens out of poverty; presumably due to double-digit GDP growth year after year over this period.
Another comparison: Africa has a population of 1.2 billion, again comparable in size to both India and China. Yet, the number of people in extreme poverty has actually increased over the past 20 years with the largest gains coming from Nigeria (Africa’s most populous country) and the Democratic Republic of the Congo. Economic growth numbers are typically hard to come by for many countries in Africa due to a large proportion of the workforce working in the informal economy (black market). Although, the poverty numbers (shown above) and the GDP per capita estimates (shown below) seem to indicate that African’s experienced negative GDP per capita growth throughout the 1970s, 1980s, and early 1990s.
The map above is color-coded by each country’s largest export. Most countries are grouped into a few categories: Fuel, Food, Transportation, Electronics, or Mineral exports. Europe is a large exporter of cars, East Asia of Computers/Electronics, Sub-Sahara Africa of Minerals and Food. The largest export in the world and the one involved with the most countries is Petroleum/Fuel. It is the largest export in the Middle East, North Africa, India, Russia, the US, and Canada.
The map above is color-coded by each country’s largest import. Most countries are grouped into a few categories: Fuel, Food, Transportation, or Electronics imports. The western world’s (the US, Canada, western Europe, Australia) largest import is Transportation/Cars. Developing Asia and Latin America’s largest import is Fuel/Petroleum. Northern Africa is an importer of Food and Southeast Asia an importer of Electronics.
Above is a map of Europe displaying whether a country has a GDP per capita less than or greater than Turkey. The data is from the IMF in Oct 2017. Turkey has a GDP per capita of $24,912 at Purchasing Power Parity (PPP). The data displays the income divide Europe where all of western Europe and Russia (labeled in Blue) have a higher standard of living than Turkey and most the former USSR and former Yugoslavia countries (labeled Red) have a lower standard of living than Turkey. The income differences help to explain some of the internal migration within Europe.
Above is a map of the world displaying each country’s currency projected on top of the country’s territory. There are 180 currencies in the world – the British pound is the world’s oldest currency that’s still in use, dating back to the 8th century! Despite all these currencies, the exchange market is dominated by only a few (shown in the bar chart below). The US dollar and Euro makeup between 60-70 percent of the market and additionally about 30 percent of the world use the USD/Euro or have their currency pegged to one of them.
Above is a map of Europe (broken into sub-country subdivisions) displaying the number of patent applications per one million people. This measure can be used as an innovation proxy metric. It appears that southern Germany, Switzerland, and Southern Scandavaniva are the most innovative locations within Europe.
The above map was created on howmuch.net (https://howmuch.net/) showing how much a working class family can save or be indebted living in various cities across the United States. The software allows you to select different criteria – such as the number of working adults in the household, how much they earn, the number of children, amount spent on food, and size of the house in square feet – the algorithm then produces a map (such as the one above) that displays where the most and least affordable places for your family to live. The size of the bubbles are a larger dark shade of red for unaffordable locations or are a larger dark shade of green for affordable locations. For example, the map above is generated for a family of four with two incomes – a home appliance repairer and a manicurist/pedicurist with a low-cost food plan living in a 1500 sq ft home. This family would need an additional $91.2K annually to afford to live in New York City or additional $83.3K to live in San Francisco. Conversely, the family could save $10.1K annually if they lived in Glendale, Arizona.
Above is a graph displaying the percentage of people that commute by public transit on the x-axis and the percentage commuting by car on the y-axis for various cities around the United States. The size of the bubble relates the workforce population of each city. There doesn’t appear to be a relationship between the size of the city’s population and the percentage of those taking public transit, but if one looks at city density a relationship is clear. Of the top 20 cities in the US by population, the highest density in order are: New York City, San Francisco, Boston, Chicago, Miami, Philadephia, and Washington DC. With exception of Miami (commute data not listed), all of top 6 highest density cities also have the highest fraction of their workforce commuting by public transit.