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Ranked: The Megaregions Driving the Global Economy

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Ranked: The Megaregions Driving the Global Economy

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Ranked: The Megaregions Driving the Global Economy

If you’ve ever flown cross-country in a window seat, chances are, the bright lights at night have caught your eye. From above, the world tells its own story—as concentrated pockets of bright light keep the world’s economy thriving.

Today’s visualization relies on data compiled by CityLab researchers to identify the world’s largest megaregions. The team defines megaregions as:

  • Areas of continuous light, based on the latest night satellite imagery
  • Capturing metro areas or networks of metro areas, with a combined population of 5 million or higher
  • Generating economic output (GDP) of over $300 billion, on a PPP basis

The satellite imagery comes from the NOAA, while the base data for economic output is calculated from Oxford Economics via Brookings’ Global Metro Monitor 2018.

It’s worth pointing out that each megaregion may not be connected by specific trade relationships. Rather, satellite data highlights the proximity between these rough but useful regional estimates contributing to the global economy—and supercities are at the heart of it.

From Megalopolis to Megaregion

Throughout history, academics have described vast, interlinked urban regions as a ‘megalopolis’, or ‘megapolis’. Economic geographer Jean Gottman popularized the Greek term, referring to the booming and unprecedented urbanization in Bos-Wash—the northeast stretch from Boston and New York down to Washington, D.C.:

This region has indeed a “personality” of its own […] Every city in this region spreads out far and wide around its original nucleus.

Gottmann, Megalopolis (1961)

By looking at adjacent metropolitan areas rather than country-level data, it can help provide an entirely new perspective on the global distribution of economic activity.

Where in the world are the most powerful urban economic clusters today?

The Largest Megaregions Today

The world’s economy is a sum of its parts. Each megaregion contributes significantly to the global growth engine, but arguably, certain areas pull more weight than others.

MegaregionCitiesRegionPopulationEconomic Output (EO)EO per Capita
Total602.2M$28,135B$46,720
1. Bos-WashNew York, Washington, D.C., BostonNorth America 47.6M$3,650B$76,681
2. Par-Am-MunParis, Amsterdam, Brussels, MunichEurope43.5M$2,505B$57,586
3. Chi-PittsChicago, Detroit, Cleveland, PittsburghNorth America32.9M$2,130B$64,742
4. Greater TokyoTokyoAsia39.1M$1,800B$46,036
5. SoCalLos Angeles, San DiegoNorth America22M$1,424B$64,727
6. Seoul-SanSeoul, BusanAsia35.5M$1,325B$37,324
7. Texas TriangleDallas, Houston, San Antonio, AustinNorth America18.4M$1,227B$66,685
8. BeijingBeijing, TianjinAsia37.4M$1,226B$32,781
9. Lon-Leed-ChesterLondon, Leeds, ManchesterEurope22.6M$1,177B$52,080
10. Hong-ShenHong Kong, ShenzhenAsia19.5M$1,043B$53,487
11. NorCalSan Francisco, San JoseNorth America 10.8M$925B$85,648
12. ShanghaiShanghai, HangzhouAsia 24.2M$892B$36,860
13. TaipeiTaipeiAsia16.7M$827B$49,521
14. São PaoloSão PaoloSouth America33.5M$780B$23,284
15. Char-LantaCharlotte, AtlantaNorth America 10.5M$656B$62,476
16. CascadiaSeattle, PortlandNorth America8.8M$627B$71,250
17. Ista-BursIstanbul, BursaMENA14.8M$626B$42,297
18. Vienna-BudapestVienna, BudapestEurope12.8M$555B$43,359
19. Mexico CityMexico CityNorth America24.5M$524B$21,388
20. Rome-Mil-TurRome, Milan, TurinEurope13.8M$513B$37,174
21. Singa-LumpurSingapore, Kuala LumpurAsia12.7M$493B$38,819
22. Cairo-AvivCairo, Tel AvivMENA19.8M$472B$23,838
23. So-FloMiami, TampaNorth America 9.1M$470B$51,648
24. Abu-DubaiAbu Dhabi, DubaiMENA5M$431B$86,200
25. Osaka-Nagoya (tied)Osaka, NagoyaAsia9.1M$424B$46,593
25. Tor-Buff-Chester (tied)Toronto, Buffalo, RochesterNorth America8.5M$424B$49,882
27. Delhi-LahoreNew Delhi, LahoreAsia27.9M$417B$14,946
28. Barcelona-LyonBarcelona, LyonEurope7M$323B$46,143
29. ShandongJinan, Zibo, DongyingAsia14.2M$249B$17,535

Altogether, these powerhouses bring in over $28 trillion in economic output.

Unsurprisingly, Bos-Wash reigns supreme even today, with $3.6 trillion in economic output, over 13% of the total. The corridor hosts some of the highest-paying sectors: information technology, finance, and professional services.

The largest city in Brazil, São Paulo, is the only city in the Southern Hemisphere to make the list. The city was once heavily reliant on manufacturing and trade, but the $780 billion city economy is now embracing its role as a nascent financial hub.

On the other side of the world, the cluster of Asian megaregions combines for $8.7 trillion in total economic output. Of these, Greater Tokyo in Japan is the largest, while Shandong might be a name that fewer people are familiar with. Sandwiched between Beijing and Shanghai, the coastal province houses multiple high-tech industrial and export processing zones.

The data is even more interesting when broken down into economic output per capita—Abu-Dubai churns out an impressive $86,200 per person. Meanwhile, Delhi-Lahore is lowest on the per-capita list, at $14,946 per person across nearly 28 million people.

Where To Next?

This trend shows no sign of slowing down, as megacities are on the rise in the coming decade. Eventually, more Indian and African megaregions will make its way onto this list, led by cities like Lagos and Chennai.

Stay tuned to Visual Capitalist for a North America-specific outlook coming soon, and a deep dive into the biggest factors contributing to the growth of these megaregions.

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Cities

Form and Function: Visualizing the Shape of Cities and Economies

Economies create distinct spatial patterns. This week’s chart visualizes the relationships businesses and industry imprint on the urban environment.

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Visualizing the Shape of Cities and Economies

The Industrial Revolution changed the form and function of cities. New patterns of work resulted in massive wealth and distinct advantages for certain regions. Urbanization emerged as a defining characteristic of this age.

During the latter part of the Industrial Revolution, Cambridge School economist Alfred Marshall looked at a particular question: why did certain industries concentrate in specific places?

Marshall argued that the local concentration of industry created powerful economies promoting technical dynamism and innovation.

This Chart of the Week highlights the spatial patterns and business relationships created at the urban scale. Marshall’s insights from the past help us understand present-day tech and media economies and the massive growth of urban regions.

The Logic of Concentration

Marshall observed that industrial concentration led to long-term tendencies such as increasing returns on capital and compounding regional advantages.

The heart of this observation is that knowledge resides within the companies that make up a particular industry. Over time, these companies can accumulate even more information and direct the flow of new and innovative ideas. This creates local specialization and increasing profits, while also concentrating success, knowledge, and wealth into one key locale.

He defined this pattern as a Marshallian Industrial District.

An Evolving Landscape: Four Patterns

Marshall’s work would later influence the work of Ann Markusen, who created a typology of three additional industrial patterns. The patterns identify what makes a city attractive or repellent to income-generating activities.

District Type: Description: Example:
Marshallian Industrial District This is a clustering of firms in a similar industry, operating within a certain geographic area. Social media marketing companies in San Francisco
Satellite Platform District A set of unconnected branches with links beyond regional boundaries, each part of its own globally oriented supply chain. Suburban neighborhoods
Hub and Spoke District An industrial sector with suppliers clustering around one, or several, dominant firms. Airplane manufacturer Boeing and the region of Seattle.
State-anchored District Industrial activities are anchored to a region by a public or non-profit entity, such as a military base, a university, or a concentration of public laboratories or government offices. Madison, WI and Columbus, OH are examples of university towns, as are many cities with large defense installations such as Pearl Harbor in Hawaii.


There are both benefits and problems—called “externalities”—associated with the spatial agglomeration of physical capital, companies, consumers, and workers:

Advantages Disadvantages
  • Low transport costs
  • A great local market
  • A large supply of labor
  • Increased chance of supply and demand for labor
  • Lower search costs and fast matching of products and labor
  • Knowledge spillovers between firms
  • Strong environmental pressures
  • High land prices
  • Bottlenecks in public goods (e.g. poor/overburdened infrastructure)
  • Corruption
  • High competitive pressure
  • Economic inequality

Clusters for a Digital Age

In the past, the physical constraints of an area defined the structure of cities. Now that so many companies are free from the shackles of producing physical goods, does geography still matter?

Researcher Marlen Komorowski re-examined the concept of clustering with this question in mind. Here are five types of media clusters identified in her research.

The Shape of Media Clusters

District Type: Description: Example:
The Creative Region A metropolitan region that provides advantages due to readily available infrastructures and institutions, and encourages the development of face-to-face interaction and collaboration networks. Berlin, Singapore, Amsterdam
The Giant Anchor A location defined by the activities of one or several large media institutions, which attract complementary firms to agglomerate. Similar to the hub-and-spoke cluster model. Seattle, (Microsoft, Amazon), and Cambridge (Harvard, MIT)
The Specialized Area A media cluster that is located either in a neighborhood within a big metropolitan area or in a small urbanized area. The Specialized Area is marked by a readily available, large pool of employees from a specialized field. Soho (London), Silicon Valley
The Attracting Enabler Determined by the location of certain facilities or resources that can be shared that enable media activities. Movie studios are a prime example. Los Angeles, Vancouver
The Real Estate This type of cluster is centered around office space, sometimes purpose-built for media and creative companies. This space can also include incubators / accelerators. Dubai Media City, Dublin’s Digital Hub


Four rationales drive these patterns: agglomeration, urbanization, localization economies. and artificial formation.

The Shadow of the Industrial Revolution

Alfred Marshall made the argument that local concentration of industry can offer powerful economies and technical dynamism and innovation.

We now see this pattern with the emergence of megacities that accrue the majority of the financial and knowledge returns. These megaregions set the perfect stage for dynamic economic exchanges between skilled labor, technology, and networks.

What does your city look like?

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Automation

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.

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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:

  1. 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.
  2. 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.
  3. 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
    • 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.

      • Insurance
        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.
      • Travel
        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.
        • Defining the parameters for this emerging industry will present significant and unpredictable challenges. Once the initial barriers are eliminated and the technology matures, the world could see a new renaissance of mobility, and the disruption of dozens of other industries as a result.

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