Economic Geography

Mapping zones of wealth and poverty; illustrating the global geography of economic development

Per Capita GDP and HDI in the Peruvian Election of 2026 (And More Problems with AI)

Article-Grid, Economic Geography, Elections, Latin America /

This penultimate post on the 2026 Peruvian presidential election examines the relationship between the electoral results and socio-economic development at the departmental level. Not surprisingly, the rightwing candidate Keiko Fujimori generally supported the interests of the business community and the wealthier segments of society, whereas the leftwing candidate Roberto Sánchez focused more on marginalized communities and the poorer segments of society. One might therefore expect Fujimori to have done better in Peru’s more economically productive departments, as reflected by per capita GDP figures. But as it turned out, departmental GDP per capita was a poor predictor of election results. As can be seen on the paired maps posted below, Sánchez won the most economically productive department, Moquegua, as well as many of those in the second-highest tier. He also won the lowest-ranked department, San Martin, and many of those in the second-lowest tier. By the same token, Fujimori took a majority of votes in some of the most economically productive provinces (Ica) and some of the least (Ucayali).

2023 Peru Per Capita GDP by Department Map

There are several reasons why GDP per capita at the department level does not indicate voting behavior, both in general terms and in the 2026 Peruvian election. Most important, high figures do not necessarily mean high median wages and salaries, especially in resource-dependent economies. Peru’s Moquegua Department has an elevated per capita GDP figure because it has relatively few people but highly productive copper mines and processing facilities. The productivity of the mineral sector, in turn, spurs demand for higher wages and enhanced social services, boosting leftwing candidates. Similar dynamics are at play in other Peruvian departments, such as Pasco in the central Andean region. They were formerly common in the United States, where mining-dependent counties were once reliable strongholds of the Democratic Party.

Peruvian departments with relatively low per capita GDP figures generally have small mining sectors and are characterized by poor infrastructure and extensive subsistence-oriented agriculture. As would be expected, most departments in this category supported the leftwing candidate, Roberto Sánchez. But again, there are important exceptions. The eastern lowland province Ucayali, for example, has the fourth lowest per capita GDP in Peru (according to ChatGPT), yet it supported Keiko Fujimori. Ucayali has experienced rapid population growth in recent decades, concentrated in its capital city, Pucallpa, which grew from 170,000 residents in 2000 to 326,000 in 2017. The department’s economy is heavily dependent on natural resource extraction, particularly logging. Many people in the department are concerned that the environmental and indigenous-rights policies of the political left would threaten that economic foundation. Many others, of course, are more concerned about environmental degradation and cultural survival. The election results suggest that the former group slightly outnumbers the latter (the department gave 52.56 percent of its votes to Fujimori and 47.44 percent to Sánchez).

It would be interesting to map the departments of Peru by median income and compare the resulting map with that of the 2006 election. I was not, however, able to locate reliable data. Instead, I mapped the country’s departments by the UN’s Human Development Index (HDI), which combines several social and economic indicators. I turned to AI for the most recent HDI data, but again ran into reliability issues. At first glance, the best set of numbers seemed to come from Grok, which I mapped accordingly (see below). Grok put Ancash Department in first place, but Google AI (Gemini) claims that Lima (both the province and the separate metropolitan region) rank in the top position. ChatGPT, to the contrary, put Moquegua and Arequipa in the two highest slots. More significantly, it ranked Ancash in a significantly lower position, stating that:

Áncash is not among the top five [Peruvian departments by HDI]. In the most recent UNDP report, Áncash is highlighted for having one of the largest reductions in human development once inequality is taken into account (one of the country’s highest inequality-adjusted HDI losses), even though its overall HDI is around the national middle range.

This ChatGPT response made me want to map its Peruvian HDI rankings, both in conventional and inequality-adjusted terms. But although the chatbot kept telling me that the data that I wanted is readily available, it refused to provide it. Here is its first and third responses:

ChatGPT Response 1:

I can absolutely produce:

  • A complete ranking of all 25 departments by HDI (2024 values).
  • A complete ranking of all 25 departments by inequality-adjusted HDI (IHDI/IDH-D).
  • A comparison table showing:
    • HDI
    • IHDI
    • percentage loss due to inequality
    • change in rank after adjusting for inequality.

 ChatGPT Response 3:

I can’t accurately show the full ranking because I don’t have the actual 2024 department-level values. The official 2025 UNDP Peru Human Development Report makes the complete ranking available only in its downloadable Excel annex (“Anexo 1 – IDH 2017–2024 a nivel distrital“), not in the report text or any searchable web page. The web index confirms the annex exists, but it does not expose the rows of the spreadsheet

Peru 2023 HDI by Department Map

If I had unlimited time and patience, I would turn to the “Excel annex” in question for the data that I want. But my time and patience are limited, and I had hoped that AI would be able to do such work for me. Perhaps I should pay more money for the AI services that I us.

But despite such frustrations, the basic human development patterns of Peru are clear: HDI figures are quite high along the coast and are significantly lower in the highlands and in the eastern lowlands. Such patterns do not correlate well with those found on the recent electoral maps. The high-HDI coastal region, for example, is politically divided, with the northern segment leaning right and the southern segment leaning left.

Finally, I would also note that different AI providers also gave somewhat different figures for per capita GDP by province. These differences can be assessed by comparing the data provided by Gemini (Google), ChatGPT, and Grok, which can be seen in the maps posted below. Gemini (Google) provided an actual map (sourced from Reddit), whereas the other two provided data that I mapped myself. I have also supplied a map based on 2014 data provided by Wikipedia. These various sources in combination tell us that the per capita GDP of Lima Department and Lima Metropolitan area have dropped relative to the rest of the country since 2014. This relative decline probably stems from the growing significance of the mining sector in Peru’s national economy.

2023 Peruvian GDP Per Capita by Department and 2026 Election Results Map 2

Depu 2023 Per Capita GDP by Department Map 2

Peru 2014 Per Capita GDP by Department map

Per Capita GDP and HDI in the Peruvian Election of 2026 (And More Problems with AI) Read More »

The Misleading Concept of the “Global South”

Article-Grid, Economic Geography, Uncategorized /

Dividing the terrestrial world into the “Global North” and the “Global South” is becoming increasingly common. Simple versions of this “two worlds” model have a relatively clean north/south division, with only Australia and New Zealand falling out of place as southern outliers of the North. The Wikipedia map posted below, however, includes a few additional exceptions. Israel is mapped as an exclave of the North in the red expanse of the South, as are France’s overseas departments (of which only Guiana in South American is easily seen on the map).

Wikipedia Map of the Global North and Global South

Following UNCTAD (UN Trade and Development), the Wikipedia article on the North/South division specifies that the North constitutes the wealthy part of the world and the South the poor part. As is stated in the first paragraph:

Most of the Global South’s countries are commonly identified as lacking in their standard of living, which includes having lower incomes, high levels of poverty, high population growth rates, inadequate housing, limited educational opportunities, and deficient health systems, among other issues. Additionally, these countries’ cities are characterized by their poor infrastructure.

Mapped and defined in such a manner, the North/South division poorly reflects reality. Some of the world’s richest and most developed countries are placed in the poor part of the world. Singapore, for example, is explicitly included in the Global South on the Wikipedia map, yet it is arguably the world’s richest country. If one excludes two micro-states with fewer than 50,000 inhabitants (Monaco and Liechtenstein), Singapore has the highest per capita GDP (in PPP) according to the International Monetary Fund. Other wealthy and highly developed counties are also mapped within the Global South, as can be seen in the table posted below. Similar but less extreme inaccuracies are found on the northern side of the divide. Moldova and Kosovo may not fall among the least-developed sovereign states, but they are far from wealthy by global standards. In terms of per capita GDP (in PPP), they rank in the 94th and 95th positions out of 190 tabulated countries and dependencies (again, according to the IMF).

Rich Countries in the Global South and Poor Countries in the Global North Table

The mapping of China within the Global South is particularly misleading. The World Bank ranks China as an “upper-middle-income” country, while the Asian News Network recently reported that the country “is on track to reach high-income status within one to two years.”  If classifying China as a relatively poor country with inferior infrastructure is unwarranted, putting Taiwan in the same category is absurd. Presumably, Wikipedia maps Taiwan as part of the Global South because it considers the island part of China, which is only true in the realm of diplomatic fiction. The People’s Republic of China, moreover, is not exactly a singular entity in terms of economic development. Its “special administrative regions,” Hong Kong and Macau, are fully developed by any criteria. China’s entire southern coastal zone, stretching from Guangdong to Jiangsu, is a core region of the world economy. It is also home to hundreds of billionaires. Although a relatively poor interior province of China like Gansu can arguably be placed in the Global South, the country’s coastal belt is a much better fit for the Global North.

The global North/South division stems from the 1980 Brandt Report, issued by the Independent Commission on International Development Issues. The map that the commission produced, dividing the globe into the “developed countries” and the “developing countries,” made much more sense at the time than it does today. After the break-up of the Soviet Union, the “developed world” of the Brandt Reports was changed to the “Global North” by removing the former-Soviet states of Central Asia and the Caucasus. South Korea was later transferred from the South to the North, reflecting its successful economic development. Wikipedia’s placement of Fiji in the developed North, however, is inexplicable. So too is the classification of the Canary Islands, the Azores, and Madeira in the South. Slotting European Turkey (Türkiye) in the North and Asiatic Turkey in the South reflects continental rather than developmental differences. The map, in short, is a conceptual mess.

Brandt Report Map

The other maps of the “Global South” that appeared at the top of a Google image search are reproduced at the end of this post. The first, from Britannic, is essentially the same as the Wikipedia map of the Brandt Line. The second, from Maps of the World, puts all of Turkey in the North, along with Taiwan and France’s overseas departments. The Shutterstock map follows the Wikipedia model but divides the South into continental divisions. It seems to put Israel in the South, but the small size of the country makes it difficult to be sure. The Institute for Political and International Studies map follows the Brandt line but in a clumsy manner, placing much of the southwestern United States in the “Poor South” and part of North Korea as well as most Melanesian countries in the rich North. It also depicts a waterway between Mexico and Guatemala and apparently cedes Georgia, Armenia, Azerbaijan, Ecuador, Haiti, El Salvador, Bulgaria, Montenegro, and Slovenia to the sea. The Sight map crudely divides North from South along straight lines, cutting through national territories. It also puts much of North Korea, one of the Solomon Islands, Jamaica, Vanuatu, and Fiji in the Global North.

I find it interesting that the global divisions between “the North” and “the South” retains currency even though it poorly reflects actual economic and developmental differences. Such inaccuracies partly stem from intellectual laziness, reflecting a failure to update one’s mental map as global circumstances change. It might also indicate bias against certain parts of the world.

The Misleading Concept of the “Global South” Read More »

The Global Geography of Immense Personal Wealth 3: Mapping the Primary Residences of Persons with Assets Between Six and Ten Billion U.S. Dollars 

Article-Grid, Economic Geography, World /

The past several GeoCurrents posts have examined the geography of the world’s wealthiest people by mapping their primary residences. As these posts showed, those with fortunes greater than $20 billion are primarily concentrated in the United States, west-central Europe, and maritime East Asia, with secondary concentrations in “greater Mumbai,” Dubai, and Moscow. Similar patterns are found for those with fortunes between $10 and $20 billion, although here Dubai and Mumbai decline in significance.

This post continues the same theme, moving down the ladder to map the primary residence of those with assets between $6 and $10 billion. Because the number of individuals increases as assets decline, I have divided this bracket into three groups and mapped them separately. Even so, so many billionaires are concentrated in a few metropolitan areas that it becomes difficult to map them using the techniques that I have employed here. On the three maps posted below, for example, the New York City region appears as something of a black blur composed of numerous overlapping circles. This problem is most evident on the third map, where the Frankfurt region of western Germany is blanketed by more than 15 circles, each representing one mega-billionaire, and thus appears as a black blob. (The concentration of mega-billionaires in this area, particularly in the small city of Ingelheim, is explained in the previous GeoCurrents post.)

Map of the Primary Residence of Persons with Assets from $8-$10 Billion in May 2026

Map of the Primary Residence of Persons with Assets from $7-$8 Billion in May 2026

Map of the Primary Residence of Persons with Assets from $6-$7 Billion, May 2026

The geographical patterns found in these maps are roughly similar to those seen in the higher wealth categories. A large majority of those with assets between $6 and $10 billion still reside in the United States, west-central Europe, and maritime East Asia. To be sure, there are some intriguing differences. In today’s maps, East Asia and the United States show a higher degree of clustering in a few metropolitan areas than they did in the maps depicting higher levels of wealth. In the U.S., southeastern Florida, the San Francisco Bay Area, and, especially, the New York City region are particularly prominent. In East Asia, primary clusters are found in the lower Yangtze and the greater Hong Kong/Shenzhen regions of China, with secondary knots in Beijing and northern Taiwan. I was surprised by the relative paucity of billionaire in these tiers in South Korea and, especially, Japan. In Europe, the map of fortunes in the $8-$10 billion category shows a somewhat dispersed pattern, but clustering in the continent’s central swath is seen again on the following two maps. In the three maps posted here, I was struck by the relatively lack of circles centered on London, unlike the earlier maps showing larger fortunes. Throughout the entire sequence of maps, the former communist zone of east-central Europe is notable for its absence of mega-billionaires, with Prague in Czechia forming the sole exception.

As one moves down the list of billionaires, an increasing number of cities outside the core zones of extreme private wealth appear on the map. Overall, however, I was surprised at how small this tally is. For the entire 696-person category of those with $6 billion or more in assets (as of mid-May, 2026), most of the world remains blank. Other than three mega-billionaires in Nigeria and two in South Africa, sub-Saharan Africa is unrepresented. It is a similar story in North Africa and Southwest Asia. Dubai is home to many super-wealthy individuals, while Tel Aviv has seven, Riyadh two, and Istanbul one; otherwise, the region has no representatives. India is the only country in South Asia to make the list. Southeast Asia has a handful of mega-billionaires, almost all of whom live in Singapore, Bangkok, Jakarta, and western peninsular Malaysia. Central America has no representatives while South America has only a few. All but one of Russia’s ultra-wealthy persons lives in Moscow. Additional cities outside the core zones that are home to more than two mega-billionaires include Delhi (with 6), Mexico City (4), Almaty (in Kazakhstan, with 3), São Paulo (3), and Sydney (3).

Are the same patterns repeated, as I suspect they are, as one moves futher down the list? This is an interesting question that deserves consideration. I have, however, growth weary of making these maps, although I am still considering mapping the distribution of mega-billionaire in the United States. Perhaps I should learn to work with AI agents and have them do the task for me. I do wonder how capable they would be.

The Global Geography of Immense Personal Wealth 3: Mapping the Primary Residences of Persons with Assets Between Six and Ten Billion U.S. Dollars  Read More »

Which City Has the Highest Per Capita Number of Billionaires? Monaco? San Francisco? Or Could It Be Ingelheim in Germany or Billund in Denmark?

Article-Grid, Economic Geography, Europe /

When I turned to AI to answer the question in the title to this post, ChatGPT replied “Monaco,” as did Grok, while Gemini (Google) came back with “San Francisco.” Gemini, however, specified that it had surveyed only “major” cities. When asked to include all cities, it too indicated Monaco. AI provided different numbers when asked how many billionaires currently live in the small city (and country). Gemini and Grok replied “two,” while ChatGPT gave a much higher figure and a more nuanced answer: “most current estimates put the number of resident billionaires in Monaco at roughly 15–30 people/families, depending on methodology and whether family fortunes are counted individually.” Gemini and Grok also claim that Monaco has seen a decline in the number of its billionaires in recent years, whereas ChatGPT tells me that “Monaco appears to have remained stable or become even more attractive to ultra-wealthy residents since the early 2020s.”* Intriguing, several YouTube videos try to convince their viewers that the gilded little principality is currently in fast decline, being abandoned by its hyper-wealthy residents.

Given such disparate answers, all such assessments should be treated with skepticism. It may be impossible, moreover, to find sold answers to these questions, given the secrecy of many billionaires as well as their propensity to maintain homes in multiple places and frequently move from one to another.

I have, however, gained some insight into this issue by mapping the primary residences of the ultra-wealth, as can be seen in the previous two GeoCurrents post and another that is forthcoming. Thus far I have mapped only those with current fortunes above $6 billion. For this rarified category, Monaco is clearly not in the top position. It is instead occupied by either Ingelheim, Germany or Billund, Denmark. It is also possible that Monaco is surpassed by one or both of these cities when it comes to the class of all billionaires. Although Grok initially told me that Monaco has the highest per capita number, it changed its (non)mind when I provided more information and asked for an explicit comparison with Ingelheim. Here are its original and revised responses:

  1. Monaco: Data varies slightly by source (Forbes vs. Henley/New World Wealth), definition (city proper vs. metro), and residency rules (primary vs. secondary homes). Billionaires are mobile, so counts fluctuate. Monaco’s extreme concentration makes it the clear per-capita leader.
  2. Ingelheim. Its per capita rate is roughly 140–400+ billionaires per million residents(or about1 per 2,400–7,000 people), making it one of the highest in the world for a small town—far exceeding Monaco’s rate … “

In mapping the primary residences of the ultra-wealthy, I have been surprised by how many of them are aggregated in a few little-known cities. Such cases generally result from multiple family members sharing a massive inheritance and remaining primarily lodged in a city dominated by a single company that generated their wealth. A good example is the provincial Danish city of Billund (population 7,484), home of the Lego Group. Four persons with fortunes greater than six billion US dollars reportedly reside primarily in this modest town: Kjeld Kirk Kristiansen, Thomas Kirk Kristiansen, Sofie Kirk Kristiansen, and Agnete Kirk Thinggard. Billund might have the world’s highest per capita number of billionaires, with one per 1,871 residents.

Billund, Denmark

Other than Monaco, Billund’s main rival for this dubious distinction is the small German city of Ingelheim am Rhein, with a population of roughly 36,000. Its case is particularly complicated. The Forbes tally of “real time billionaires” lists 15 individuals in a row with fortunes pegged at $6.5 billion, all of whom reside primarily in Ingelheim, at least according to Gemini (as of May 18, 2026; see the table below). Intriguingly, all 15 have the surnames of “Boehringer” or “von Baumbach.” But because these intertwined families are notoriously secretive, it is difficult to determine where their wealthiest members primarily reside or how large their fortunes actually are. It is not coincidental that no photographs are available for any of them in the segment of the Forbes list posted below. Grok AI summarizes the situation nicely:

Forbes and related analyses (e.g., mapping of German billionaires) indicate Ingelheim appears with a notable cluster [of billionaires]—potentially 5–15+ depending on how family members are counted individually vs. aggregated, as the company is privately held by the Boehringer, Liebrecht, and von Baumbach families with wealth split among ~15+ heirs in total.

Ingelheim Billionaires

Location Map of Ingelheim, Germany

Although Ingelheim is apparently home to more billionaires than Billund, it is a far less provincial city, making its concentration of extreme wealth less exceptional. The driving distance from Copenhagen to Billund is roughly 260 kilometers (160 miles), and the nearest substantial city, Aarhus, is approximately 90 kilometers distant.  Ingelheim, on the other hand, is a mere 46 kilometers (29 miles) from Frankfurt (straight-line distance) and only 14.6 kilometers (9.1 miles) from Mainz, a city of more than 200,000 residents. Put differently, it is squarely situated in the Rhine-Main Metropolitan Region, a conurbation with almost six million inhabitants – and quite a few additional billionaires.

The source of the Ingelheim’s vast private wealth is C.H. Boehringer Sohn AG & Co. KG, the parent company of the Boehringer Ingelheim group. Boehringer Ingelheim is the world’s largest privately held pharmaceutical firm, with 54,000 employees in 76 countries. Founded by Albert Boehringer in 1885, the company is still owned by his descendants, now in the fourth generation.

I am embarrassed to admit that I had never heard of this important company before I began working on this project. Judging from what I have read (and watched), Boehringer Ingelheim had a decidedly mixed reputation. Often praised for its long-term planning and dedication to cutting-edge research, it is also criticized for its intense secrecy. The company has also been faulted for its history of close cooperation with the German Empire (1871-1918) and the Nazi regime (1933-1945). Such criticism is perhaps unfair, as the company had little choice but to work with these authoritarian regimes. It is a different matter, however, when it came to the hiring of Fritz Ernst Fischer in 1954. As noted in Fischer’s Wikipedia article:

Fritz Ernst Fischer (1912-2003) was a Nazi German medical doctor who performed medical atrocities on inmates of the Ravensbrück concentration camp. He was tried and convicted of war crimes and crimes against humanity in the 1947 Doctors’ Trial; he was sentenced to life imprisonment, but his sentence was commuted to 15 years and he was released in 1954. … Fischer subsequently regained his license to practice medicine and started a new career at the chemical company Boehringer in Ingelheim, where he stayed until his retirement:

*These answers came in response to being asked where the number of billionaires living in Monaco has decreased in recent years.

Which City Has the Highest Per Capita Number of Billionaires? Monaco? San Francisco? Or Could It Be Ingelheim in Germany or Billund in Denmark? Read More »

The Geography of Immense Personal Wealth 2; Fortunes Between $10-$20 Billion

Article-Grid, Economic Geography, World /

The previous GeoCurrents post showed that most of the world’s wealthiest persons live in just a few areas, with primary concentrations in the United States, west-central Europe, and maritime East Asia, and secondary concentrations in Moscow, Dubai, and “Greater Mumbai” (see the map posted below). The post concluded by asking whether the same patterns would be found at the next tier of wealth. To provide an answer, I mapped the primary residences of those with assets valued between $10 and $20 billion, using the same Forbes list of “the world’s real-time billionaires.” Because this category is so large, I had to cover it in two maps, one showing fortunes between $15 and $20 billion and the other between $10 and $15. These maps are also posted below.

World Regions of Vast Personal Fortunes

Map of the Primary Residences of Persons with Fortunes Between $15 and $20 Billion

Map of the Primary Residences of Persons with Fortunes Between $10 and $15 Billion

As can be seen by comparing the original map of fortunes over $20 billion and these new maps, slightly different spatial patterns emerge in these slightly lower levels of the global wealth hierarchy. To be sure, a large majority of those with fortunes between $10 and $20 billion still live in the three primary regions originally identified: the United States, west-central Europe, and maritime East Asia. Relatively few, however, reside in what I called the “secondary centers,” with only four in Moscow, two in Dubai, and two in Mumbai.

More intriguing to my mind is the lower degree of dispersion found within the three primary regions at this level of wealth. Let us begin with the United States. In the $15-20 B. category, for example, there are more representatives living in California and the corridor extending from Philadelphia to Boston than in the rest of the country put together. In $10-15 B. category, distinct concentrations can be seen in a few metro areas: the San Francisco Bay Area, Houston, southeastern Florida, and, especially, New York City and its inner suburbs. Intriguingly, the Seattle area, which figures prominently on the map of fortunes above $20 B., has no representatives in these lower categories, although nearby Vancouver and Victoria in Canada have one each.

Somewhat similar patterns are found in the other two global regions of vast personal fortunes.  “Maritime East Asia” is reduced in size on the maps showing the $10-$20 B. range, with no representatives in Japan and only four in South Korea (all of whom live in Seoul). On the $15-$20 B. map, one sees a clear concentration in coastal southern China, a region extending from the lower Yangtze region to the Hong Kong/Shenzhen area. On the $10-$15 B. map, this region essentially breaks down into two clumps, one at its northern extremity and the other at its southern. In west-central Europe, two pronounced concentrations are seen on the $10-$15 B. map, one in southwestern England, clearly centered on London, and the other in Switzerland.

Giver these intriguing differences in residential patterns by wealth level among the world’s richest people, I have decided to see what emerges at the next tier of vast fortunes. Stay tuned ….

The Geography of Immense Personal Wealth 2; Fortunes Between $10-$20 Billion Read More »

The Global Geography of Immense Personal Wealth

Article-Grid, Economic Geography, World /

The United States is well known for its concentration of wealth at the upper end of the spectrum. A household in the United States must have a net worth of roughly 13 to 14 million US dollars to be in the “top one percent,” whereas in Germany, France, and the United Kingdom the comparable figures are around 3.5 million, at least according to the AI assessments that I have consulted. The imbalance is even greater at the uppermost peak of personal wealth. The constantly updated Forbes list of “the world’s real-time billionaires” informed me that on May 12, 2016, the top eleven mega-billionaires all reside in the United States. Intriguingly, just a day earlier the same list placed France’s Bernard Arnault (along with several unspecified members of his family) in tenth place (see the table posted below). Evidently, the Arnaults were bypassed within 24 hours by both Jim Walton (& family) and Warren Buffett. (As can be inferred from the preceding sentence, the Forbes list is primarily based on individual wealth but sometimes ranks of the basis of family assets. I have ignored this important distinction in the maps and text that follow, as I have no way to disentangle personal from family wealth.)

Forbes List of the World’s Wealthiest People

Scanning through this list of the world’s richest people made me curious about the global geography of vast personal fortunes. I therefore decided to map the locations of the primary residences of the top 138 billionaires, those with assets valued at or above 20 billion US dollars on May 11, 2026. I used the same technique that I employed last December when mapping the world’s top publicly traded corporation by market capitalization; in both cases, I placed a hollow circle over the approximate main locations of those in question, with the circles roughly scaled to monetary “worth.” If multiple billionaires (primarily) live in the same city, their circles have been slightly displaced to maintain visibility. I relied on Google’s AI service (Gemini) to determine the locations of the current main residences of these 138 mega-billionaires.

Map of the World’s Largest Personal Fortunes

As the map shows, the primary residences of those with immense personal fortunes are concentrated in three major regions of the world (the United States, west-central Europe, and maritime East Asia) and three minor regions (Dubai, Moscow, and “Greater Mumbai”). As the map also indicates, only 15 of the 138 top billionaires live outside of these six regions. Their primary residences are indicated in pink text on the map.

The United States is clearly the world’s top region of immense personal fortunes, with the largest number of mega-billionaires controlling the largest stockpiles of wealth. It is also the most extensive region of these regions, as its mega-billionaires are more spatially dispersed than those of maritime East Asia and, especially, west-central Europe. I will further examine the distribution of huge fortunes in the U.S. in a later post. (Note that I have intentionally limited this region to the United States, excluding the one Canadian mega-billionaire, who is based in nearby Toronto. I have done so largely because of the strikingly different economic and political environments of the two countries, although this was not an easy judgement call.)

The compact region of huge fortunes that I have labeled “west-central Europe” extends from London south to southeastern France and eastward to Czechia. It is anchored by Switzerland and southern Germany. Despite appearances, Italy is not represented on the map. Three Italians are included, but they have evidently relocated their primary residences to nearby countries. This disjunction shows both the hazard of relying on AI for such information (see the figure below) and the propensity of the super-wealthy to seek favorable countries for their primary residences. Note also that one of the largest circles in Europe falls outside this core region. It represents the 132.5-billion-dollar fortune of Amancio Ortega, a pioneer of “fast fashion” who is most closely identified with the Zara retail chain. Ortega lives primarily in an apartment in the peripheral Spanish city La Coruña (officially, “A Coruña” in the local Galician language). He moved there with his family at the age of 14, leaving school and apprenticing himself to a local shirtmaker. Intriguingly, the other outlying circle in Europe, which is centered on Stockholm, represents another fortune derived from “fast fashion,” that of Stefan Persson, former chair of H&M.

Do the Richest Italians Live In Italy? Contradictory AI Answers

The region that I label “maritime East Asia” is anchored on coastal China but extends across South Korea (with one circle) to Japan (with four). Intriguingly, one of these circles in Japan represents a prominent Chinese businessman, Jack Ma; as Gemini tells me, “As of 2026, Alibaba co-founder Jack Ma has been primarily living in Tokyo, Japan, following a long-term, low-profile lifestyle away from China after regulatory crackdowns on his businesses. He frequently travels to other locations, with his family recently acquiring a £19.5 million mansion in London’s Belgravia district.” This maritime East Asian region is also depicted as including Hanoi in northern Vietnam, which is home to Nhật Vượng, leader of the Vingroup conglomerate. It does not include the (supposedly) autonomous region of Ningxia in central China, which is home to Dang Yanbao, chairman of an important coal and chemical company (residing in the city of Yinchuan).

The three secondary regions of mega-billionaire concentration are focused on a single city. All Russian oligarchs with fortunes greater than $20 billion live in Moscow. Most Indian mega-billionaires live in Mumbai, although one resides in nearby Pune and another in Ahmedabad, Gujarat, which is not too far off (hence “Greater Mumbai”). Dubai, in the United Arab Emirates, has a growing number of foreign-born mega-billionaires, most of whom are attracted by its low taxes and business-friendly policies.

Outside of these six core regions, only three countries are home to more than one mega-billionaire: Australia (with three); Mexico (with two); and Singapore (with two). Interestingly, two of Australia’s three representatives live in Perth, far from the country’s southeastern core. This seeming oddity is indicative of Western Australia’s vast mineral resources. As can be seen on the map, only one mega-billionaire lives in South America, although the fortune of Chile’s Iris Fontbona is vast indeed (over $50 billion). Africa is represented only by Aliko Dangote of Lagos, Nigeria. His firm, the Dangote group, is noted for its interests in cement, sugar, fertilizer, and oil refining.

I am curious about whether these geographical patterns hold when one moves down the list to consider fortunes between 10 and 20 billion US dollars, which are still extraordinarily large. This may be the topic of a future GeoCurrents post.

Finally, in the interest of legibility I have divided these data into four categories, mapping each one separately. The first map posted below shows fortunes greater than $50 billion, the second those between $30 and $50 billion, the third those between $25 and 30 billion, and the fourth those between $20 and 25 billion.

Primary Residence of Persons with More that $20 Billion

Primary Residence of Persons with $30-$50 Billion, Map

Primary Residence of Persons with $25-$30 Billion, Map

Primary Residence of Persons with $25-$30 Billion, Map

The Global Geography of Immense Personal Wealth Read More »

The Changing Geography of Top Corporate Headquarters in the U.S., 1890-2025

Article-Grid, Economic Geography, North America /

(Note: Last December I began work on a series of posts focusing on the geography of wealth and corporate power. After a single post on the location of corporate headquarters, I had to suspend my work on this topic. This post includes maps that I made at that time, based on data from late 2025.)

In the GeoCurrents post of December 11, 2025, I mapped the locations of the headquarters of world’s largest publicly traded corporations (by market capitalization). As these maps show, most of these firms are headquartered in the United States. Most of the top U.S.-based firms, in turn, are located in the West Coast and Texas. I was surprised at how few have their head offices in New York, the historical core of American capitalism. I then decided to make a historical series of maps showing the changing locations of the corporate headquarters of the top 25* publicly traded companies in the United States (again, by market capitalization). Finding the necessary data, however, proved impossible in the time period that I allotted for the task. As an expedient, I turned to AI, getting the information that I needed from ChatGPT. As such information is not necessarily reliable, these maps should be considered preliminary.

The first map shows the situation in 1890, when railroad companies dominated the list. As can be seen, New York City was then the core of American capitalism, with nine of 24 top corporate headquarters. Chicago was in clear second place, with two railroad-oriented firms and two meatpackers. (as Carl Sandburg’s famous poem opens, “Chicago: Hog Butcher for the World, … Player with Railroads and the Nation’s Freight Handler”). The only other city with multiple top-25 corporate headquarters was San Francisco, with only two. The sole city in the south was Durham, home of the monopolistic American Tobacco. The smallest city on the map was Butte, Montana, which at the time had 10,723 residents (although that figure would rise to almost 40,000 in twenty years). Butte reached this position because of the extraordinarily rich ores extracted by the Anaconda Copper Company. The key role of railroads in 1890 can be seen by the location of leading firms in secondary cities in the western Midwest: Omaha (population 140,452 in 1890), Topeka (31,007), and Saint Paul (133,156).  New England, the original heartland of the American industrial revolution, is notable for its lack of major corporate headquarters.

1890: Location of the Top 25 Publicly Traded Companies in the United States

The map of major corporate headquarters in 1920 shows some major changes from that of 1890. Over the intervening thirty years, railroad companies declined in importance, largely replaced by heavy-industrial firms. New York and Chicago retained their positions, and a clear belt of corporate power had emerged across the mid-Atlantic and southern Great Lakes regions. The rise of the automobile industry is reflected by the addition of Detroit, South Bend, and Akron to the map (note that only General Motors is mapped in Detroit; Ford is missing because it was a privately held company at the time).

1920: Location of the Top 25 Publicly Traded Companies in the United States

The map showing the situation in 1960 is surprisingly little changed from that of 1920. A small city far from the corporate heartland hasd, however, joined the list: Bartlesville, Oklahoma, with 27,893 residents in 1960. Bartlesville owed this position to Phillips Petroleum, which was founded on the productive oilfields of northeastern Oklahoma. Today, its two descendant companies, Phillips 66 and ConocoPhillips, are based in Houston, which has emerged as the core city of the U.S. oil industry.

1960: Location of the Top 25 Publicly Traded Companies in the United States

By 1990, the New York City metropolitan area had further cemented itself as the center of American corporate capitalism. Slightly more than half of the country’s largest publicly traded companies were at the time headquartered there, as were seven of the top ten. In contrast, the upper Midwest saw a substantial drop from 1920, reflecting the relative decline of heavy industries. In contrast, pharmaceutical and consumer-oriented firms had come to occupy a more prominent position. Because of this shift, the South appears on the map for the first time since 1890, represented by Coca-Cola in Atlanta and Walmart in the small city of Bentonville, Arkansas (population 11,257 in 1990). The only corporation in the western half of the country that made the 1990 map was Chevron, an oil company based at the time in San Francisco. In 2024, Chevron announced that it would relocate to Houston.

1990: Location of the Top 25 Publicly Traded Companies in the United States

The 2025 map reveals a completely transformed geography of major corporate headquarters, deviating sharply from all other maps in this series. The New York City area dropped precipitously, to be replaced by the San Francisco Bay Area, home to most leading high-tech companies. Austin and Seattle gain a prominent position for the same reason. Together, the Bay Area and the Seattle metro area were home to the top six firms. Overall, this map is more geographically balanced than any of the preceding ones. Intriguingly, the only company and city found on both the 1890 and 2025 maps is the consumer-products giant Procter & Gamble of Cincinnati. Procter & Gamble’s roots extend to the time when fat from hogs was used to make soap. As early as 1840, Cincinnati had become the world’s largest pork-processing hub, earning it the nickname “Porkopolis.”

2025: Location of the Top 25 Publicly Traded Companies in the United States

The geography of leading corporate headquarters is continuing to experience rapid shifts. The prominence of California’s Bay Area might soon be heightened, owing to the widely anticipated initial public offerings (IPOs) of the AI firms OpenAI and Anthropic. Both are based in San Francisco, and both are expected to be valued at up to one trillion dollars, easily putting them in the top twenty-five. OpenAI, however, is currently embroiled in a major lawsuit with Elon Musk that might threaten its future.

But as the map also shows, several leading companies have recently left the San Francisco Bay Area. Their departure was largely due to concerns about taxation and regulation. Tesla relocated to Austin in 2021, as did Oracle. Texas will likely gain another top-25 firm when SpaceX undergoes its expected IPO. SpaceX began its relocation from Hawthorn, California to Starbase, Texas in 2024. Starbase, located near the southern tip of the state, is, however, more of an industrial facility than a city or even town, with an estimated population of 500. If SpaceX subsequently merges with Tesla, as many expect, its headquarters will almost certainly remain in Texas.

The pace of corporate relocation may be increasing. Oracle, for example, recently announced that it will be moving to Nashville by 2030, even though it had moved to Austin only in 2021. The military technology firm Palantir, with a current market capitalization of around $350 billion, transferred its headquarters from Palo Alto, California to Denver in 2020, largely because of the protests that it had experienced in California. Only four years later – after facing additional rounds of protest in Denver – it announced its relocation to Miami.

* Or 24 in the case of 1890, due to data limitations.

The Changing Geography of Top Corporate Headquarters in the U.S., 1890-2025 Read More »

Responses to the Environmental Crisis of the Aral Sea Region, and Spatial Variations in Its Intensity  

Article-Grid, Central Asia, Economic Geography, Environmental Geography, Uncategorized /

The desiccation of the Aral Sea is a widely reported and well-known environmental disaster. Before the late twentieth century, this so-called sea was vast lake that supported major fisheries. Over the past seventy years, most of the flow of the two rivers that drain into it, the Amu Darya and Syr Darya, have been diverted to irrigate cotton and other crops. Now only three remnant water bodies remain, two of which are too salty to support fish. But the third, the North Aral Sea in Kazakhstan, has been revitalized in recent years. The construction of dikes has prevented its waters from spreading across and evaporating over the salt flats that now cover what was once the main body of the lake. Other restoration projects undertaken by Kazakhstan have also had some success. According to a recent report, “the volume of water in the Northern Aral Sea has increased to 24.1 billion cubic metres from 2023 to the present.” The same publication also notes that twenty species of fish that had vanished from the northern lake have recently reappeared.

North Aral Sea and Environs map

Contrastingly, the linked environmental crisis that has devastated the historical Khwarazm region south of the Aral Sea is seldom reported and poorly known. The Wikipedia article on Karakalpakstan, a supposedly autonomous region of Uzbekistan that covers much of this once fertile and prosperous area, starkly summarizes the situation:

Crop failures have deprived about 48,000 people of their main source of income and shortages of potable water have created a surge of infectious diseases. … [C]limate change over the centuries, accelerated by human-induced evaporation of the Aral Sea in the late 20th century has created a desolate scene in the region. The ancient oases of rivers, lakes, reed marshes, forests and farms are drying up and being poisoned by wind-borne salt and by fertilizer and pesticide residues from the dried bed of the Aral Sea. … The rates of incidence of anemia, respiratory diseases, and other health problems have risen dramatically.

Not surprisingly, the impoverished and environmentally ravaged region of Karakalpakstan has experienced periodical political unrest in recent years. Large protests in July 2022 led to hard repression. According to a recent scholarly article: “Uzbekistan’s authorities restricted internet use, cut off the region from the rest of the country, censored media reporting about the protests, and used lethal force against the demonstrators, leaving several people dead.” The same article further notes that the government of Uzbekistan subsequently changed the country’s constitution, “factually depriv[ing] Karakalpakstan, … of its nominal autonomy.”

More recently, Uzbekistan has been trumpeting its effort to bolster Karakalpakstan’s economy and alleviate its environmental crisis. A recent announcement from its president, Shavkat Mirziyoyev, paints a positive picture, outlining foreign investment and tourism opportunities and touting recent economic gains and infrastructural investments. Some of Uzbekistan’s plans for Karakalpakstan are surprisingly ambitious, including “projects to establish a modular intelligent computing center in the Takhiatash district for the AI ​​sector…” The Times of Central Asia tells us that “the new phase of IT Park [in Karakalpakistan] will accommodate AI-focused startups and modern data centers equipped with high-performance graphic processors capable of handling large-scale data processing,” while reporting that “authorities are targeting global tech firms such as Google, Microsoft, Meta, and Amazon to establish data operations in Uzbekistan.” But considering the region’s water crisis and political tensions, such plans seem unrealistic. More credible is a recently announced United Nations Development Programme (UNDP) project designed to “facilitate the introduction of upland rice in the Republic of Karakalpakstan, which will reduce water consumption by up to 40% compared to traditional rice cultivation.”

Reports on the environmental devastation experienced by (historical) Khwarazm usually focus on Karakalpakstan, ignoring the rest of this region located further to the south and east (Daşoguz in Turkmenistan and Khorazm in Uzbekistan). Most of the settled areas of these two regions are upstream from Karakalpakstan and are thus farther away from the bed of the former Aral Sea, the source of the pesticide- and salt-laden dust storms that plague the region. Presumably, they also have better and more reliable water supplies. As a result, I have assumed that these regions have experienced less environmental degradation and damage to human health than Karakalpakstan.

For a crude and preliminary test of this hypothesis, I carefully examined satellite images from the region, looking mostly for evidence of abandoned agricultural fields. I found many such signs in Karakalpakstan, especially in areas that are relatively close to the former Aral Sea. Contrastingly, I found few indications of field abandonment in either Daşoguz or Khorazm, regions that ad formed the core of historical Khwarazm. (I captured some of these images and have placed them at the end of this post, along with a map showing their locations.)

Such simple evidence, of course, would have to be subjected to rigorous “ground-truthing” to be given credence. It is, however, suggestive. I have included four satellite images of apparently abandoned fields in Karakalpakstan at the end of this post, along with a map that shows their approximate locations. For comparative purposes, I have also included a satellite image of an upstream area in Uzbekistan’s Khorazm region, located near the core of ancient Khwarazm. Here one sees many active farms along with several rural residential areas.

I also looked for reports on environmental and health issues in Daşoguz and Khorazm, but had little luck. As I am eager to move on to other issues, I turned to AI as a final expedient. Grok told me that although “Karakalpakstan is the epicenter” of the Aral agricultural disaster, the same problems blight the entire area. As it reported: “Salt storms in 2018, for example, affected Karakalpakstan, Khorezm, and Dashoguz simultaneously. In short, the degradation is not isolated to Karakalpakstan—it is a regional crisis rooted in the shared hydrology and history of the Khwarazm/Aral Sea basin. The problems are very much present (and actively addressed) in Khorazm and Dasoguz as well.”

I do not doubt this AI assessment. But I still suspect that the crisis is significantly less pronounced in the upstream areas than it is Karakalpakstan. This would make an interesting research project for a younger scholar, although I somehow doubt that it would be welcomed by local and national officials.

Locations of Satellite Images of Abandoned Fields in Karakalpakstan

Abandoned Fields Karakalpakstan B

Abandoned Fields Karakalpakstan C

Abandoned Fields Karakalpakstan D

Agricultural Fields Khorazm Uzbekistan

Responses to the Environmental Crisis of the Aral Sea Region, and Spatial Variations in Its Intensity   Read More »

The Key Role of Azerbaijanis in Iran

Article-Grid, Economic Geography, Ethnicity, Linguistic Geography, Southwest Asia and North Africa /

The previous post argued that the “Persian” (or Farsi-speaking) provinces of Iran are not necessarily more prosperous and economically developed than the “non-Persian” provinces, focusing on the relatively affluent but non-Farsi-speaking Caspian region, particularly Mazandaran province. The Azeri-speaking (or Azerbaijani-speaking) northwestern region of Iran also economically ranks somewhat higher than average.  It is, however, less economically developed than the neighboring Azeri-speaking country of Azerbaijan.

Iranian Azerbaijan Income Map

 

Iranian Azerbaijan Per Capita GDP Maps

Rather than framing the issue of Iran’s uneven economic development around the distinction between Farsi- and non-Farsi speakers, it is better to organize it around the distinction between “core Iranian ethnic groups” and “non-core ethnic groups.” The Mazandaranis, for example, are not Farsi-speakers, but they are so integral to the Iranian nation that they have often been classified as “Persian.” The Wikipedia article on the Iranian province of Golestan, for example, claims that “The Mazandaranis who inhabit the foothills … were subsumed under the rubric ‘Persian’ by these official statistics.”

Although the Azeris, who speak a Turkic language, are never classified as Persians, they have been central players in the Iranian state and nation for centuries. According to many sources, Azeris are, if anything, over-represented in the country’s elite population. In the core provinces of Tehran and Alborz, Azeris constitute up to a quarter of the population. The actual percentage of Azeri-speakers in these provinces, however, is difficult if not impossible to determine due the prevalence of intermarriage and bilingualism. To be sure, cultural conflicts occasionally arise, such as the 2006 “cartoon cockroach controversy” analyzed in a previous GeoCurrents post. Overall, however, they are of little significance.

Azerbaijani language map

Although Azeri is in the Turkic language family, most of the inhabitants of “greater Azerbaijan” (northwestern Iran and independent Azerbaijan) seem to have spoken the Iranian language of Old Azeri (or Azari) up to the early-modern period. The region had been fully part of the Persian cultural sphere, and it largely remained so after the switch to a Turkic tongue.

For more information on this important region and its linguistic history, I recommend the blogpost “Turko-Iranica: The Shifting Faces of Iranian Azerbaijan and its Idiom,” by Afsheen Sharifzadeh. As this essay notes:

The “Old Azari” language–previously one of the major Iranian languages–comprised a sprachbund of dialects distributed in a broad range between lake Urmia in the west and the Caspian littoral in the east. Old Azari seems to have shared a genetic affinity with the ancestor of the modern Talysh language, and it further appears to form a broader group with the so-called “Northwestern” branch of Iranian including modern Gilaki, Māzanderāni, Semnāni, and Zaza-Gorani. Some linguists hold that the southern Tāti varieties of Iranian Azerbaijan … are peripheral remnants of Old Azari. As such, this language has been spoken in the region of Azerbaijan for at least three millennia.

…

It appears Old Azari only lost its status as the majority language between the 16th-17th centuries with the ascent of the Qizilbash-backed Safavids. The subsequent influx of numerous Turkic military elements into the region further spread Turkic at the detriment of Old Azari, which in turn receded and ceased to be used, at least in the major urban centers. Notwithstanding the city of Tabriz maintained a number of distinctly Old Azari-speaking neighborhoods well into the Safavid period with the poet Ruhi Anārjānī composing a compendium of the language as late as the 17th century. However by the turn of the 20th century the Turkification of Azerbaijan was near completion, with the old Iranic speakers found exclusively in remote recesses of the mountains or other isolated areas such as Harzand village in Marand. Lamentably, language shift is currently in progress and the remaining Tāti dialects face a state of attrition and imminent endangerment.

Afsheen Sharifzadeh also notes that the Azerbaijani dialects of northwestern Iran and independent Azerbaijan are currently diverging:

The Northern and Southern varieties of Azerbaijani are moderately mutually intelligible without training. Since, for several decades, there has been little, if any, cultural exchange between the two parts of Azerbaijan, the mutual intelligibility is decreasing. Today the two languages are remarkably distinct in phonology, morphology, syntax, and source of loanwords; purist efforts upon the Northern variety have uprooted numerous Persianisms in favor of Russianisms and revisionist Turkic models, while the Southern variety continues to rely upon Persian much as it has since its arrival to the region.

The Key Role of Azerbaijanis in Iran Read More »

Are “Non-Persian” Regions of Iran Poorer than Persian Regions? The Counter-Case of Mazandaran

Article-Grid, Economic Geography, Ethnicity, Linguistic Geography, Southwest Asia and North Africa /

The previous GeoCurrents post showed that the location of oil and natural gas deposits provides a partial explanation of the differences in the distribution of wealth and economic productivity across the country. But other factors must also be considered. Could language and ethnicity play a role? It has often been argued that the Persian, or Farsi-speaking, central area of Iran is more developed than the non-Persian peripheries. In 2017, for example, the Kurdish Human Rights Association asserted that “Persian province are the richest and non-Persian provinces are the poorest,” arguing that discrimination against Kurds and other minority groups explains this pattern.

But is it actually true that “the Persian province” are the richest parts of Iran? Although this assertion does have some validity, it is also misleading, as we will see in the next few GeoCurrents posts.

A little background on the ethnic situation is first needed. Iran is a multi-lingual country with a well-established sense of common national identity across most of its ethnic groups. Farsi, or Persian, is the national language and is spoken by almost everyone in the country. But it is the mother tongue of only around 50 to 62 percent of Iran’s population. According to some estimates, as many as twenty-five percent speak Azeri, or Azerbaijani, as their first language (see the pie chart below), although most sources put the figure at around 15 percent. The modified Wikipedia map posted below shows the distribution of the most important languages of Iran. As can be seen, Farsi/Persian dominates the central region, with minority languages located in most peripheral areas.

 

Iran Languages Map

Iran Language Pie Chart

For the next set of maps, I have isolated the Farsi/Persian-speaking region from the language map posted above so that it can be compared with the economic maps of Iran analyzed in the preceding GeoCurrents posts. The second figure below compares the map of Farsi speakers with two maps of per capita GDP, and the first compares it with a map of per capita average income. As these comparisons show, there is a correlation between Persian ethnicity and higher-than-average economic productivity and income, but it not particularly strong. Several non-Persian areas, for example, have elevated economic figures.

 

Iran Farsi-Speaking Areas and Average Income Map

Iran Farsi-Speaking Area and Per Capita GDP map

The rest of today’s post examines the relatively prosperous but non-Farsi-speaking Caspian region of north-central Iran. As the per capita income map shows, the largest contiguous block of counties in the highest per-capita-income category is found in north-central Iran. This relatively prosperous region is anchored by Tehran and Alborz provinces, Iran’s political and economic core. But it also extends across the formidable Alborz (Elburz) mountains to encompass Mazandaran province on the south shore of the Caspian Sea. Some high-income counties are also found in Gilan Province, located to the northwest of Mazandaran. Mazandaran is also shown on most maps as having higher-than-average per capita GDP.

Iran Caspian Region Mazandaran Average Income Maps

Iran Caspian Region Per Capita GDP Maps

Physical Map of Iran with Tehran, Alborz, and Mazandaran Provinces Highlighted

The Caspian region of Iran is highly distinctive and linguistically diverse. Mazandaran has its own language, Mazandarani, which is related to Farsi but far from interintelligible with it. The Caspian coastal plain is densely populated, with the highest rural population density in Iran by a wide margin. Mazandaran province has no large cities, but it does have a well-developed network of medium-sized urban centers. The Caspian region also has a highly productive agricultural economy, focused on rice, citrus and other fruits, vegetables, tea, and aquiculture. Much of this production is only possible because this region, quite unlike the rest of Iran, has a humid subtropical climate. Most of its mountainous areas are covered by lush, broadleaved forests. Until the 1950s, Caspian tigers lived in this region, and leopards still do.

Iran Population Density Map

Iran Rural Population Density Map

Humid Subtropical Caspian Iran

Humid Subtropical Forests of Iran Map

Iran’s Caspian region also has a distinctive political history. It resisted conquest by the Umayyad Caliphate and did not come under Muslim rule until 760 CE/AD, more than a century after the rest of Iran. According to the Wikipedia article on “Tabaristan” (the historical name of Mazandaran):

For a certain period, the Caspian shore of Iran served as a center for ancient Iranian national consciousness. In 783, during a rebellion in Tabaristan, the locals gave up their Arab husbands to the rebels. Dynasties such as the Bavandids and Ziyarids continued to commemorate their pre-Islamic background, with traditional Iranian festivals such as Nowruz and [Zoroastrian] Mehregan continuing to exist in Tabaristan

Long after Islamization, moreover, the Caspian generally remained partly or entirely autonomous, as well as culturally distinctive and sophisticated. The Wikipedia article on Tabaristan also notes that:

The writing tradition of the [Mazandarani] language is approximately as old as that of New Persian. This was due to the long-lasting independent and semi-independent local kingdoms, ruled by the ispahbads

But despite its profound cultural, historical, and environmental differences from the rest of Iran, the Caspian region is still part of the larger core region of the country. Its people consider themselves, and considered by others, to be an integral part of the Iranian nation. Iran’s powerful sense of national identity, in other words, is by no means limited to the Farsi- or Persian-speaking population, as it transcends most language boundaries in the country. The Azeri region of northwestern Iran is also tightly integrated with the Iranian national project, as we will see in the next post.

Are “Non-Persian” Regions of Iran Poorer than Persian Regions? The Counter-Case of Mazandaran Read More »

The Ambiguous Role of Oil and Natural Gas in the Economic Geography of Iran

Article-Grid, Economic Geography, Energy, Southwest Asia and North Africa /

Not surprisingly, the distribution of oil and natural gas provides one of the main explanations of Iran’s spatial pattern of economic productivity. As noted in the previous post, the coastal provinces of southwestern Iran post some of the highest production figures relative to population in the country. According to official Iranian data from 2020, the per capita GDP of Bushehr was more than twice that of the country’s second-ranked province. As can be seen on the paired maps below, Bushehr has a sizable share of Iran’s oil, and an even larger portion of its natural gas. It also contains Kharg Island, which exports around 90 percent of Iran’s oil products.

Maps of Iran’s Oil and Natural Gas Fields

Iran GDP Per Capita by Province, 2020

But if the map posted below can be trusted and is still accurate, per capita income in Bushehr does match the province’s economic productivity. This is also not surprising, as the main benefits of natural-resource extraction often flow out of the resource-endowed regions. But as can also be seen on this map, the three southernmost counties of Bushehr – Jam, Kangan, and Asaluyeh – had some of the country’s highest average-income figures from 1998 to 2018. They almost certainly still do. Located here is massive Kangan Gas Field and, more important, the “Kangan Ethane Recovery & Cracker Plant – Kangan Petro Refinery.” As the Wikipedia article on Jam County notes, “The fast-growing city of Jam … is home to workers at the nearby … Kangan industrial complex [and] is growing exponentially and affluently.” More surprisingly, the same article goes on to claim that “most of the workers in the city, and on the farms and gardens around the city, are Afghan migrant workers.” I doubt that Afghan migrants are receiving a sizable share of whatever affluence the region enjoys.

Iran Average Income Per Capita by County 2018 Map

The geography of oil in Iran also explains the anomalously high per capita GDP of Kohgiluyeh and Boyer-Ahmad province found in some datasets (see the previous GeoCurrents post). As the per capita income map indicates, this small and mountainous province was relatively poor up to 2018. It probably still is. Artificial Intelligence (Grok) tells me that “Multiple studies group KBA [Kohgiluyeh and Boyer-Ahmad] with provinces facing disadvantages in employment participation, entrepreneurship, rural poverty, and overall opportunities.” But Grok also claims that “The province holds about 13% of Iran’s total oil reserves and it contains 8 oil fields. … Recent government investments (e.g., €260 million planned for boosting output by 40,000 barrels/day) underscores its strategic role.” Kohgiluyeh and Boyer-Ahmad thus seems to be a resource-rich province that has recently experienced substantial extractive investments without experiencing proportional economic development. Globally speaking, this is not an uncommon situation.

Iran Average Per Capita Income by County 2018, KBA

The oil map of Iran posted above also shows significant fields in Lorestan, another relatively poor province. Lorestan oil production, however, remains modest. According to AI, large shale oil deposits have recently been discovered in the province, but they are not economically viable at this time.

The Ambiguous Role of Oil and Natural Gas in the Economic Geography of Iran Read More »

The Economic Geography of Iran: Attempting to Map Per Capita GDP

Article-Grid, Economic Geography, Southwest Asia and North Africa /

(Note: GeoCurrents has been on an extended hiatus due to personal issues and teaching obligations. I now hope to resume regular posting. My initial focus will be on Iran, for obvious reasons).

Iran is usually regarded as a middle-income country. According to the International Monetary Fund, its per capita GDP (in purchasing power parity) at the beginning of 2026 was 21,882 current international dollars. This figure places it in the 91st position out of 190 counties listed, between Ukraine and Kosovo. In nominal terms, however, Iran’s per capita GDP was only US$ 4,250 (IMF) in early 2026, putting it in the 129th position. Considering Iran’s high levels of education and massive natural resource endowment – with the third highest proven oil reserves and the second highest proven natural gas reserves – these are low figures. As the maps posted below show, nearby countries with similar advantages have far more productive economies. It would seem that the Iranian regime’s repressive nature and focus on military expenditure have undermined its economic development.

Southwest Asia GDP PPP Per Capita by Country 2026

Southeast Asia Nominal Per Capita GDP by Country 2026

As might be expected of a large (ranking in 17th position) and populous (also 17th) country, Iran exhibits substantial internal variation in economic productivity. Finding reasonably accurate information on Iran’s per capita GDP by province, however, is difficult. Wikipedia features such a map (below), but the data is from 2012. For the most part, however, the patterns seen on this map still seem to hold. Economic productivity is highest in the north-central and south-coastal parts of the country, and lowest in the far southeast and northwest.

 

Iran Per Capita GDP by Province 2012 Map

In trying to find recent province-level economic data for Iran, I turned to Artificial Intelligence – and was soon disappointed. ChatGPT told me that such information is not available from authoritative sources, but it did provide a list of five tiers of provinces by per capita GDP. Google AI (Gemini) provided a more limited set of three tiers, which included only “key economic” provinces. Grok gave actual per capita GDP figures, but only for 20 provinces.

Iran Per Capita GDP by Province ChatGPT map

Iran Per Capita GDP by Province Google AI

Iran Per Capita GDP by Province Grok

I have mapped all these AI-derived lists (above). As can be seen, there are some profound differences among them. Grok claims that the most economically productive region of is the small and mountainous province of Kohgiluyeh and Boyer-Ahmad (its nominal per capita GDP is listed at US$ 21,124, whereas second-place Tehran is placed at only US$ 14,544). In contrast, ChatGPT puts Kohgiluyeh and Boyer-Ahmad in the bottom tier of provinces, as does the 2012 Wikipedia map. ChatGPT ranks the large, centrally located province of Yazd in the second-highest tier of provinces, whereas Grok puts it in a much lower position. All three chatbots, however, agree that the coastal, oil-oriented provinces of Khuzestan and Bushehr are among Iran’s most economically productive regions. Tehran and some of the provinces near it rank high in all three assessments. Google, Grok, and ChatGPT also agree that Sistan and Baluchestan in the southeast falls at or near the bottom of the chart.

Although recent information from the Iranian government is evidently not available, IranOpenData does list per capita GDP by province from 2020, which I have also mapped (below). This dataset shows a gap of almost an order of magnitude between the most productive province (Bushehr) and the least productive (Sistan and Baluchestan). More surprising is the assertion that the per capita GDP of Bushehr is more than twice that of second-place Yazd, (1,072,595 thousand rials vs 400,518). The information found in IranOpenData fits relatively well with the Iranian economic patterns depicted on a MapPorn map of per capita GDP by province for all the countries of southwestern Asia. A YouTube map comparing Iran and Turkey (Türkiye) on this issue is also similar, although it ranks Yazd in a much lower position. Both comparative maps place Kohgiluyeh and Boyer-Ahmad in a relatively high position, with the YouTube map matching Grok’s first-place assessment.

Iran Per Capita GDP by Province 2020

Southwest Asia Per Capita GDP by Province map

Turkey and Iran Per Capita GDP by Province map

Despite numerous contradictions among the sources consulted, there are some clear patterns in the geography of economic productivity in Iran. The possible reasons underlying these patterns will be explored in the next GeoCurrentspost.

The Economic Geography of Iran: Attempting to Map Per Capita GDP Read More »

Almost All of the World’s Top Companies by Market Valuation Are Based in the United States

Article-Grid, Economic Geography /

I was recently surprised to learn the extent to which the United States dominates the list of world’s largest corporation by market capitalization. As the chart posted below shows, the seven most valuable companies are headquartered in the U.S., as are 16 of the top 20. It is an open question as to whether this preponderance is due mainly to the underlying dynamics of the American economy or to the over-valuation of the U.S. stock market stemming mainly from unrealistic optimism about AI. Presumably time will tell.

List of Top 20 Global Firms by Market Capitalization, December 2025

This discovery prompted me to begin mapping the locations of the world’s top companies and how these geographical patterns changed over time. My initial efforts will be focused on market capitalization, which limits me to publicly traded companies. If privately held companies could be considered in an assessment the world’s top companies by valuation, the results would probably be similar but not the same. Difficulties in estimating the value of private companies, however, preclude this option [1].

The map posted below shows the locations of the headquarters of companies with current (December 2025) market capitalization of over one trillion U.S. dollars. Nine of these eleven firms are American. More surprising, all nine have headquarters west of the Mississippi River. The west coast, particularly the San Francisco Bay Area, dominates the map. This preponderance would have been more pronounced if Tesla had not moved from Palo Alto, California to Austin, Texas in 2021. (Note that these circles are not precisely placed; if two or more firms are located in the same city or even the same metro area, their corresponding circles are simply offset from each other so that they are all visible. Forthcoming posts will examine smaller areas to allow more precisely mapping.)

Map of the Locations of Companies with Market Capitalizations Over One Trillion US dollars, Dec. 2025

The next issue is whether similar geographical patterns hold for companies in the next tier down, those with market capitalization between $500 billion and $999 billion. As the next map shows, only seven companies fall in this category. All but one are located in the United States. Of these six firms, four are headquartered west of the Mississippi River. Only one, however, is in the San Franciso Bay Area, whereas two are in Texas. But until 2020, Oracle’s corporate headquarters had been on the shore of San Francisco Bay; it is now in Austin, Texas.

Map of Companies with Market Capitalizations Between 500 and 999 Billion US Dollars, Dec. 2025

The final map combines the spatial information found in the first two and adds two additional circles to cover the full top-twenty list (found in the first illustration). These circles represent Samsung, headquartered in Seoul, South Korean, and Johnson & Johnson, headquartered in New Brunswick, New Jersey, on the outskirts of the New York City. What strikes me most about this map is the absence of circles in Europe and Japan. To what extent does this pattern hold as we move down the list of the top companies by market capitalization? That will be the topic of the next GeoCurrents post.

Map of the Locations of the World’s Top 20 Companies by Market Capitalization, December 2025

[1] ChatGPT tells me that OpenAI would rank in 18th place, at $500 billion estimated private valuation, with SpaceX ($400 billion) not far behind – although the same chatbot also states that “recent discussions [of SpaceX] point toward ~ $800 billion in a share sale/secondary sale,” which would put it in 15th place. Grok agrees with the $500 billion figure for OpenAI and the $400 billion figure for SpaceX, but claims an estimated valuation of $480 billion for China’s ByteDance, which ChatGPT pegs at $220 billion, indicating both the depth of the problem and the limits using AI for such information.

A more severe difficulty arises with secretive private companies that are enormous in terms of revenue, but whose valuation remains highly uncertain. According to ChatGPT, the top firms in this category are Vitol, based in Switzerland and the Netherlands, and Singapore-based Trafigura.

(Note: Shortly after this post went up, I read that SpaceX is planning an initial public offering in 2026, “with a report suggesting the company would target a $1.5 trillion valuation.” SpaceX is headquartered in far southern Texas, in the town of Starbase, formerly Boca Chica Village, with an estimated population of 500.

Almost All of the World’s Top Companies by Market Valuation Are Based in the United States Read More »

Canadian Provinces and U.S. States Economically Compared

Article-Grid, Economic Geography, North America /

As noted in the previous GeoCurrents post, Alberta is Canada’s most prosperous and economically productive province. But it does have, as might be expected, by the country’s highest cost of living. Although living costs in Alberta are above the national average, they are below those of Ontario, Canada’s most populous province. The major factor is the cost of housing. As can be seen on the map posted below, the average price of a house in both Ontario and British Columbia far exceeds Alberta’s figure, owing largely to expensive real estate of Toronto and Vancouver.

Canada House Cost by Province map

But despite its prominent economic position in Canada, Alberta ranks in a middling level when compared with the states of the U.S. Although the United States and Canada have historically maintained rough economic parity, their relative positions began to diverge in the second decade of the twenty-first century, as can be seen in the graphs posted below. As the following maps show, per capita GDP and median income levels are now substantially lower across the provinces of Canada than across the states of the United States. Canada’s Atlantic provinces occupy a particularly low position, below those of the poorest U.S. states. But it is also true that the cost of living is, on average, higher in the United States than in Canada, owing in part to elevated medical costs in the U.S.

(Note: In making the maps posted below, I used ChatGPT to convert Canadian dollars to U.S. dollars, which might have resulted in erroneous figures.)

U.S. and Canada Economically Compared graphs

U.S. Canada Median Household Income map

U.S. States Canadian Provinces Per Capita GDP map

Canadian Provinces and U.S. States Economically Compared Read More »

Mapping China’s Debated Fertility Figures

Article-Grid, East Asia, Economic Geography, Population Geography /

According to the United Nations Population Fund, China’s 2024 Total Fertility Rate (TFR: the expected number of children per woman) was 1.2. Among sovereign states, only Singapore and South Korea are ranked below China (at 1.1 and 0.9 respectively). Some sources, however, contend that China’s fertility rate is considerably lower. Database Earth, for example, gives a  current figure of 1.02. Conversely, other sites report higher figures. Macrotrends claims that China’s TFR is currently over 1.7 – and that is has been slowly increasing for a quarter century (see the graph posted below). Macrotrends’ analysis is ostensibly based on UN data, specifically from its “World Population Prospects 2024” website. But the graph of China’s TFR on this UN website does not square with that of Macrotrends. It does show China’s TFR slowly increasing from the late 1990s to the late 2010s, eventually reaching around 1.7, but it then depicts a sharp drop-off that has continued to the present. The same UN graph, however, then projects China’s TFR as slowly increasing over the rest of this century at various estimated rates, although likely remaining below replacement level. Evidently, there is a lot of unacknowledged uncertainty about global fertility rates, especially when it comes to future projections. Overall, previous UN projections have severely underestimated the pace of global fertility decline.

China 2024 TFR Database Earth

Macrotrends China TFR graph

China UN TFR projection graph

One of the more prominent sources arguing for fertility rates below those reported by the UN is the data-rich X account called Birth Gauge. In October 2024, Elon Musk referenced Birth Gauge in warning that low birth rates “will lead to mass extinction of entire nations.” The author of Birth Gauge uses information on birth numbers reported by individual countries to calculate up-to-date TFR figures. I cannot assess the accuracy of these assertions, but I must say that the author’s estimate of the Philippines’ TFR falling to 1.3 in 2024 seems unlikely (see the table below); the UN, after all, still pegs the Philippines’ TFR at 2.7.

Birth Gauge 2024 TFR Data Table

Birth Gauge TFR figures are usually but not always below those of the UN. Most of its higher numbers pertain to Central Asia. For example, it posts a 2024 figure of 3.57 for Kyrgyzstan, as opposed to the UN’s 2.9. Also of note is Birth Gauge’s admission, given in an April 7, 2023 X post, that actual TFR figure may end up being higher than what it and other sources report: “When women shift their births to higher ages, the conventional TFR underestimates how many children they will really have in the end, which is the ‘tempo effect.’”

Birth Gauge pegs China’s 2024 TFR at 1.10, a slight uptick from its 2023 figure of 1.02. It provides a useful data table of China’s estimated TFR figures for 2023 by region, which I have converted into a map (see below). As can be seen, all China’s province-level administrative districts are evidently below the replacement level. Only Tibet, with a reported figure of 1.97, comes close. As a comparison with the second map posted below shows, which depicts per capita GDP by region, fertility patterns in China have little connection with economic productivity. Extremely low birth rates are found in some of China’s wealthiest provinces (Jiangsu) and in some of its poorest (Heilongjiang). Regions with relatively high fertility, however, do tend to be less economically productive than average. Intriguingly, the coast/interior dichotomy, prominent on the GDP map, does not appear on the TFR map. The latter map, however, does show a muted differentiation between the lower-fertility north and the higher-fertility south. Particularly notable are the extraordinarily low birth rates in China’s northeastern “rust belt” (Manchuria). This was the most economically productive part of China in the mid-twentieth century, noted for its heavy industry. It did not, however, share proportionally in the economic boom of the 1990s and early 2000s, and is now known for its depressed conditions.

China 2023 Total Fertility Rate by Province Map

China 2023 GDP by Province Map

Mapping China’s Debated Fertility Figures Read More »