The $86 Trillion World Economy in One Chart
The world economy is in a never-ending state of flux.
The fact is that billions of variables — both big and small — factor into any calculation of overall economic productivity, and these inputs are changing all of the time.
Buying this week’s groceries or filling up your car with gas may seem like a rounding error when we are talking about trillions of dollars, but every microeconomic decision or set of preferences can add up in aggregate.
And as consumer preferences, technology, trade relationships, interest rates, and currency valuations change — so does the final composition of the world’s $86 trillion economy.
Country GDPs, by Size
Today’s visualization comes to us from HowMuch.net, and it charts the most recent composition of the global economic landscape.
It should be noted that the diagram uses nominal GDP to measure economic output, which is different than using GDP adjusted for purchasing power parity (PPP). The data in the diagram and table below come from the World Bank’s latest update, published in July 2019.
The Top 15 Economies, by GDP
|Rank||Country||GDP (Nominal, USD)||Share of World Total (%)|
|#1||🇺🇸 United States||$20.49 trillion||23.89%|
|#2||🇨🇳 China||$13.61 trillion||15.86%|
|#3||🇯🇵 Japan||$4.97 trillion||5.79%|
|#4||🇩🇪 Germany||$4.00 trillion||4.66%|
|#5||🇬🇧 United Kingdom||$2.83 trillion||3.29%|
|#6||🇫🇷 France||$2.78 trillion||3.24%|
|#7||🇮🇳 India||$2.73 trillion||3.18%|
|#8||🇮🇹 Italy||$2.07 trillion||2.42%|
|#9||🇧🇷 Brazil||$1.87 trillion||2.18%|
|#10||🇨🇦 Canada||$1.71 trillion||1.99%|
|#11||🇷🇺 Russian Federation||$1.66 trillion||1.93%|
|#12||🇰🇷 Korea, Rep.||$1.62 trillion||1.89%|
|#13||🇦🇺 Australia||$1.43 trillion||1.67%|
|#14||🇪🇸 Spain||$1.43 trillion||1.66%|
|#15||🇲🇽 Mexico||$1.22 trillion||1.43%|
The above 15 economies represent a whopping 75% of total global GDP, which added up to $85.8 trillion in 2018 according to the World Bank.
Most interestingly, the gap between China and the United States is narrowing — and in nominal terms, China’s economy is now 66.4% the size.
A Higher Level Look
The World Bank also provides a regional breakdown of global GDP, which we helps to give additional perspective:
|Rank||Geographic Region||GDP (Nominal, USD)||Global Share|
|World Total||$85.8 trillion||100.0%|
|#1||East Asia & Pacific||$25.9 trillion||30.2%|
|#2||Europe & Central Asia||$23.0 trillion||26.8%|
|#3||North America||$22.2 trillion||25.9%|
|#4||Latin America & Caribbean||$5.8 trillion||6.8%|
|#5||Middle East & North Africa||$3.6 trillion||4.2%|
|#6||South Asia||$3.5 trillion||4.1%|
|#7||Sub-Saharan Africa||$1.7 trillion||2.0%|
The organization breaks it down by income levels, as well:
|Income Level||GDP (Nominal, USD)||Global Share|
|World total||$85.8 trillion||100.00%|
|High income countries||$54.1 trillion||63.1%|
|Upper middle income countries||$24.4 trillion||28.4%|
|Lower middle income countries||$6.7 trillion||7.8%|
|Low income countries||$0.6 trillion||0.7%|
The low income countries — which have a combined population of about 705 million people — add up to only 0.6% of global GDP.
Looking Towards the Future
For more on the world economy and predictions on country GDPs on a forward-looking basis, we suggest looking at our animation on the Biggest Economies in 2030.
It is worth mentioning, however, that the animation uses GDP (PPP) calculations instead of the nominal ones above.
Ranked: The Autonomous Vehicle Readiness of 20 Countries
This interactive visual shows the countries best prepared for the shift to autonomous vehicles, as well as the associated societal and economic impacts.
For the past decade, manufacturers and governments all over the world have been preparing for the adoption of self-driving cars—with the promise of transformative economic development.
As autonomous vehicles become more of a looming certainty, what will be the wider impacts of this monumental transition?
Which Countries are Ready?
Today’s interactive visual from Aquinov Mathappan ranks countries on their preparedness to adopt self-driving cars, while also exploring the range of challenges they will face in achieving complete automation.
The Five Levels of Automation
The graphic above uses the Autonomous Vehicles Readiness Index, which details the five levels of automation. Level 0 vehicles place the responsibility for all menial tasks with the driver, including steering, braking, and acceleration. In contrast, level 5 vehicles demand nothing of the driver and can operate entirely without their presence.
Today, most cars sit between levels 1 and 3, typically with few or limited automated functions. There are some exceptions to the rule, such as certain Tesla models and Google’s Waymo. Both feature a full range of self-driving capabilities—enabling the car to steer, accelerate and brake on behalf of the driver.
The Journey to Personal Driving Freedom
There are three main challenges that come with achieving a fully-automated level 5 status:
- Data Storage
Effectively storing data and translating it into actionable insights is difficult when 4TB of raw data is generated every day—the equivalent of the data generated by 3,000 internet users in 24 hours.
- Data Transportation
Autonomous vehicles need to communicate with each other and transport data with the use of consistently high-speed internet, highlighting the need for large-scale adoption of 5G.
- Verifying Deep Neural Networks
The safety of these vehicles will be dictated by their ability to distinguish between a vehicle and a person, but they currently rely on algorithms which are not yet fully understood.
Which Countries are Leading the Charge?
The 20 countries were selected for the report based on economic size, and their automation progress was ranked using four key metrics: technology and innovation, infrastructure, policy and legislation, and consumer acceptance.
The United States leads the way on technology and innovation, with 163 company headquarters, and more than 50% of cities currently preparing their streets for self-driving vehicles. The Netherlands and Singapore rank in the top three for infrastructure, legislation, and consumer acceptance. Singapore is currently testing a fleet of autonomous buses created by Volvo, which will join the existing public transit fleet in 2022.
India, Mexico, and Russia lag behind on all fronts—despite enthusiasm for self-driving cars, these countries require legislative changes and improvements in the existing quality of roads. Mexico also lacks industrial activity and clear regulations around autonomous vehicles, but close proximity to the U.S. has already garnered interest from companies like Intel for manufacturing autonomous vehicles south of the border.
How Autonomous Vehicles Impact the Economy
Once successfully adopted, autonomous vehicles will save the U.S. economy $1.3 trillion per year, which will come from a variety of sources including:
- $563 billion: Reduction in accidents
- $422 billion: Productivity gains
- $158 billion: Decline in fuel costs
- $138 billion: Fuel savings from congestion avoidance
- $11 billion: Improved traffic flow and reduction of energy use
Transportation will be safer, potentially reducing the number of accidents over time. Insurance companies are already rolling out usage-based insurance policies (UBIs), which charge customers based on how many miles they drive and how safe their driving habits are.
Long distance traveling in autonomous vehicles provides a painless alternative to train and air travel. The vehicles are designed for comfort, making it possible to sleep overnight easily—which could also impact the hotel industry significantly.
- Real Estate
An increase in effortless travel could lead to increased urban sprawl, as people prioritize the convenience of proximity to city centers less and less.
With the adoption of autonomous vehicles projected to reduce private car ownership in the U.S. to 43% by 2030, it’s disrupting many other industries in the process.
What is a Commodity Super Cycle?
The prices of energy, agriculture, livestock and metals tell the story of human development. Learn about the commodity super cycle in this infographic.
Visualizing the Commodity Super Cycle
Since the beginning of the Industrial Revolution, the world has seen its population and the need for natural resources boom.
As more people and wealth translate into the demand for global goods, the prices of commodities—such as energy, agriculture, livestock, and metals—have often followed in sync.
This cycle, which tends to coincide with extended periods of industrialization and modernization, helps in telling a story of human development.
Why are Commodity Prices Cyclical?
Commodity prices go through extended periods during which prices are well above or below their long-term price trend. There are two types of swings in commodity prices: upswings and downswings.
Many economists believe that the upswing phase in super cycles results from a lag between unexpected, persistent, and positive trends to support commodity demand with slow-moving supply, such as the building of a new mine or planting a new crop. Eventually, as adequate supply becomes available and demand growth slows, the cycle enters a downswing phase.
While individual commodity groups have their own price patterns, when charted together they form extended periods of price trends known as “Commodity Super Cycles” where there is a recognizable pattern across major commodity groups.
How can a Commodity Super Cycle be Identified?
Commodity super cycles are different from immediate supply disruptions; high or low prices persist over time.
In our above chart, we used data from the Bank of Canada, who leveraged a statistical technique called an asymmetric band pass filter. This is a calculation that can identify the patterns or frequencies of events in sets of data.
Economists at the Bank of Canada employed this technique using their Commodity Price Index (BCPI) to search for evidence of super cycles. This is an index of the spot or transaction prices in U.S. dollars of 26 commodities produced in Canada and sold to world markets.
- Energy: Coal, Oil, Natural Gas
- Metals and Minerals: Gold, Silver, Nickel, Copper, Aluminum, Zinc, Potash, Lead, Iron
- Forestry: Pulp, Lumber, Newsprint
- Agriculture: Potatoes, Cattle, Hogs, Wheat, Barley, Canola, Corn
- Fisheries: Finfish, Shellfish
Using the band pass filter and the BCPI data, the chart indicates that there are four distinct commodity price super cycles since 1899.
The first cycle coincides with the industrialization of the United States in the late 19th century.
The second began with the onset of global rearmament before the Second World War in the 1930s.
The third began with the reindustrialization of Europe and Japan in the late 1950s and early 1960s.
- 1996 – Present:
The fourth began in the mid to late 1990s with the rapid industrialization of China
What Causes Commodity Cycles?
The rapid industrialization and growth of a nation or region are the main drivers of these commodity super cycles.
From the rapid industrialization of America emerging as a world power at the beginning of the 20th century, to the ascent of China at the beginning of the 21st century, these historical periods of growth and industrialization drive new demand for commodities.
Because there is often a lag in supply coming online, prices have nowhere to go but above long-term trend lines. Then, prices cannot subside until supply is overshot, or growth slows down.
Is This the Beginning of a New Super Cycle?
The evidence suggests that human industrialization drives commodity prices into cycles. However, past growth was asymmetric around the world with different countries taking the lion’s share of commodities at different times.
With more and more parts of the world experiencing growth simultaneously, demand for commodities is not isolated to a few nations.
Confined to Earth, we could possibly be entering an era where commodities could perpetually be scarce and valuable, breaking the cycles and giving power to nations with the greatest access to resources.
Each commodity has its own story, but together, they show the arc of human development.
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