At the 20th National Congress of the Chinese Communist Party last month, hundreds of Chinese officials were elevated to new positions within the Party hierarchy. This gives us a chance, among other things, to look at where within China its politicians were born, to see if any regional patterns stand out.
Let’s start with the members of the Politburo Standing Committee, the highest-ranking group in the Party:
Three Politburo members (including Xi) were born in Beijing; four were born in Fujian, where Xi spent most of his career before becoming general secretary of the Party in 2012. Xi was in Fujian for 17 years until 2002, which was more than half of his career between 1979 and 2012:
Beyond the Politburo, there is the Party Central Committee, which currently has 205 full members, roughly two-thirds of whom made it on to the Central Committee for this first time this year. I was able to find the birthplaces for 194 of those 205; the 11 I couldn’t find I will list below:
Most Politburo and Central Committee members were born in eastern or northern China – not surprisingly, where most of China’s population lives – whereas far fewer were born in the country’s western or southern provinces. See for example the difference between China’s most populous province, Guangdong, in the southeast, and China’s second most populous province, Shandong, in the northeast.
Native-born populations of provinces like Guangdong were highly under-represented on the Central Committee. This is true even after adjusting for the fact that Guangdong had not yet become the most populous Chinese province 50-70 years ago, when most of the current Committee members were born:
Part of the reason for the under-representation of provinces like Guangdong might be that when the current leadership generation was young, many fewer people in these provinces spoke Standard Northern Mandarin primarily or fluently as do today. In other words, these outcomes could be the result of regional differences that existed in the past, which no longer exist to nearly the same extent today, yet linger in the form of Party personnel simply because almost all of its top positions are filled by older men.
On the other hand, perhaps the under-representation of high-ranking officials born in certain provinces does reflect ongoing regional differences within the Party system, in which, roughly speaking, the north and east is the dominant political core of the country, in comparison to the deep south or west. Or maybe there are other explanations for these differences that are only indirectly related to politics, reflecting regional economic or cultural traits that have led people toward certain careers.
Whatever the reasons are for it, similar regional patterns hold, to varying degrees, in the birthplaces of China’s new Central Military Commission chairmen, and in the birthplaces of China’s provincial party chiefs (aka party secretaries) and government chiefs (aka provincial governors, mayors of municipalities, chairpersons of autonomous regions, or chief executives of special administrative regions):
The high-ranking central secretariat of the Party Central Committee has a different regional pattern, with none of its secretaries born in coastal provinces apart from Fujian. But with only seven secretaries, it is a small sample size:
Looking back at all of the Standing Committee members over the course of the past three decades, again the basic pattern holds, with the north and east predominating and the south and west unrepresented. Even for some of the most populous provinces like Guangdong and Sichuan, or for that matter Henan (the populous but poor interior state in north-central China), there have been zero Standing Committee members appointed at any of the past six party congresses who were born in those provinces:
In contrast, the birthplaces of the earlier, revolutionary era of the Party leadership show a different pattern, in which the north and the east do not predominate, Guangdong is not un-represented, and Hunan province in particular (Mao’s birthplace, among others) figures highly:
Countries frequently get compared to one another, and so do provinces and states and territories withincountries. But we don’t usually compare provinces or states in different countries to one another. Let’s do a bit of that now.
Above are the world’s 34 most populous ‘first-level administrative divisions‘ – provinces and states and territories and the like. (Statoids, they are sometimes called). 17 of the 34 are in China. 11 are in India, including the largest by far, Uttar Pradesh, which is home to more than 200 million people. All are in Asia except for Sao Paolo in Brazil and California in the US.
Some of the largest of these places used to be even bigger than they are now. Uttar Pradesh lost about 5 percent of its population and 18 percent of its territory when the Himalayan region Uttarakhand broke off to become a state of its own in 2000. Sichuan, formerly China’s most populous province*, lost about 26 percent of its population and 15 percent of its territory when Chongqing was separated from it in 1997. China’s most populous province today, Guangdong, lost about 8 percent of its population and 16 percent of its territory in 1988 when the island of Hainan became its own province. And Andhra Pradesh, formerly the most populous state in southern India, lost approximately 39 percent of its population and 41 percent of its territory when a new state, Telangana, was created in 2014.
*Sichuan was also formerly the world’s most populous province, before Uttar Pradesh overtook it around 1960. Back then, both had about 70 million people; today Sichuan has 80 million, whereas Uttar Pradesh has ∼233 million.
Provincial Population as a Percentage of National Population
This chart above shows the size of countries’ largest provinces or states in relation to their overall populations. In the US, for example, it shows that the largest state (California) is home to approximately 12 percent of the country’s total population. In Canada, by contrast, the largest province (Ontario) is home to about 38 percent of the Canadian population. Argentina has a similarly high percentage of its population living in its largest province (Buenos Aires), but it also has a much bigger divide between its largest and second largest provinces than Canada or most other countries have.
The only country ahead of Argentina on the graph above is Pakistan, where the largest region (Punjab) has about 47 percent of the country’s population and the second largest (Sindh) has about 27 percent. But then, Pakistan only has 7 regions, whereas Argentina has 24 provinces.
I’ve tried to take this into consideration in the graph below. In this graph, the x-axis shows the number of first-level administrative divisions that each country has, while the y-axis shows the percentage of the country’s population that lives in its largest administrative division:
You can see that Argentina is still an outlier here. (As is Turkey, on the opposite end of the chart. Turkey has 81 provinces, but a sizeable chunk of its population lives in its largest one, Istanbul). In fact, not only is Buenos Aires by far the most populous of Argentina’s 24 provinces, but it also surrounds the “Autonomous City of Buenos Aires”, which is itself the fourth most populous administrative division in the country:
Combined, the two Buenos Aires’ account for about 45 percent of Argentina’s population. This partly reflects the fact that Argentina is a highly urbanized country; its population is tied with Japan’s and the Netherlands’ at 92 percent urban, according to the World Bank, which is higher than in any other major country. In Argentina’s closely contested presidential elections in 2015, the two candidates vying to become president were the governor of the province of Buenos Aires and the Chief of Government of the Autonomous City of Buenos Aires, respectively. (The current president, elected in 2019, previously served as a legislator in the Autonomous City of Buenos Aires). Buenos Aires also directly borders the country’s second and third most populous provinces, Cordoba and Santa Fe. Together Buenos Aires and its neighbours account for about 75 percent of Argentina’s population.
Argentina’s long neighbour Chile is similarly urbanized (88 percent of its population lives in an urban area), and similarly has more than 40 percent of its population living in the largest of its (16) regions, the Region Metropolitana de Santiago, where the country’s largest city is located.
Brazil too is highly urbanized (87 percent urban), but unlike Argentina and Chile, its second largest city, Rio de Janeiro, is not so much smaller than its largest city, Sao Paolo. Brazil has 27 first-level administrative divisions, the largest of which, Sao Paolo state, is home to about 22 percent of the country’s population. The country’s three most populous states (Sao Paulo, Minas Gerais, and Rio de Janeiro) directly border one another, and together account for 40 percent of the population.
In other big countries, like the United States, China, and India, the most populous provinces or states account for a smaller share of the total population. Guangdong is home to about 9 percent of China’s total population, California 12 percent of the US population, Uttar Pradesh 16.5 percent of India’s population.
In the US, even clusters of states are fairly small: California and its immediate neighbours combined are home to only about 15 percent of the US population. A similar 15 percent is in New York state and its immediate neighbours, or – overlapping somewhat with New York – in Pennsylvania and its immediate neighbours. Texas and its immediate neighbours account for only about 12 percent of the US population.
By comparison, Guangdong and its immediate neighbours are home to about 24 percent of China’s population. In the more populous northern part of China, the province of Henan and its immediate neighbours have about 33 percent of China’s population. And in India, Uttar Pradesh and its immediate neighbours have about 42 percent of the country’s population, not counting Nepal, which it also borders. Uttar Pradesh’s southern neighbour, Madhya Pradesh (“central state”, whereas Uttar Pradesh means “northern state”) and Madhya Pradesh’s neighbours together have an even higher 46.5 percent of India’s population.
In Germany, the fifth most populous German state, Hesse, directly borders all five of the other most populous German states (North Rhine-Westphalia, Bavaria, Baden-Wurttemburg, Lower Saxony, and Rhineland-Palatinate). Together Hesse and its neighbours account for 78 percent of Germany’s total population. Hesse’s chief city is Frankfurt, a European finance and transport hub. The most populous of Germany’s 16 states, however, is North Rhine-Westphalia, home to 21.5 percent of the country’s population. Its largest city is Cologne. It is also the only state to border both the Netherlands and Belgium, both of which are densely populated too.
In France, Paris’ Île-de-France region similarly has just under 20 percent of the population of France’s 13 non-overseas regions, with about 12 million inhabitants. Along with its five neighbouring regions Île-de-France has almost half of France’s total population. (France also divides its territory into 101 departments, 5 of which are overseas. The biggest department – with 2.6 million people – borders Belgium; the second biggest is in Paris).
On the graph earlier, I included England, rather than Britain as a whole. Britain has four constituent countries (England, Scotland, Wales, and Northern Ireland), England of course being the largest of these, with 84 percent of Britain’s population. Within England, none of the nine regions shown in the map above has more than 15 percent of the English population. The three southeastern regions – London and its two surrounding regions – have about 45 percent of the English population (and so about 38 percent of Britain’s total population).
A less demographically lopsided archipelago is Japan, where the largest regions are located in the centre of the country. This map shows 8 regions and47 prefectures; the largest region (Kanto, shown in green) accounts for about 34 percent of Japan’s population; the largest prefecture in that region (Tokyo) accounts for about ten percent of Japan’s population. The three central regions (Kanto, Chubu, and Kansai, shown in green, turquoise, and purple here) together are home to 97 million people, about 77 percent of the country’s population.
Above are 34 of the largest provincial economies, ranked by gross domestic product (in nominal terms). 13 of the 34 are in the USA, 9 are in China, and 13 are in other countries. Japan’s Tokyo prefecture had the largest GDP here apart from the three largest American states and Chinese provinces, but if we were to have used Japan’s biggest ‘region’, Kanto, in which Tokyo is located, it would have had a larger GDP than any state or province other than California. Then again, if we were to add Hong Kong’s economy to that of its close neighbour Guangdong, its nominal GDP would be about the same size as Japan’s Kanto region.
The largest of these places have economies bigger than those of major countries. California’s nominal GDP is greater than Britain’s, France’s, or India’s. Combined, the first-level administrative divisions shown on this chart account for between a quarter and a third of global economic output.
Finally, here are the 30 largest administrative divisions in terms of territorial size (in square kilometres) on land. All 30 of these are larger than France. The largest of all, Russia’s Republic of Sakhka (also known as Yakutia), is nearly as large as India. 7 of the 30 places on this list are in Russia. 7 are in Canada. 5 are in Australia (that’s every Australian state apart from Victoria – where Melbourne is – and the island-state Tasmania). 4 are in China, 4 are in Brazil, 2 are in the US, and 1 is in Chad.
Before 1999, when Canada’s largest administrative division, Nunavut, broke off from the Northwest Territories to become its own territory, the Northwest Territories was the world’s largest region. Its population, however, was tiny; it had only about 70,000 people. Yakutia’s population, in contrast, is roughly 1 million. Alaska’s population is roughly 730,000.
Combined, these 30 administrative divisions occupy approximately 27 percent of the world’s land outside of Antarctica or Greenland. Yet they are home to only about 2.5 percent of the world’s population, 195 million people; roughly two-thirds of whom live in Texas, Xinjiang, Inner Mongolia, Minas Gerais, or Ontario.
This article uses death tolls as a point of comparison between natural disasters. I know doing this can come across as callous, or simplistic. But I hope that it can help to put events usefully in context.
Leaving aside Covid-19, no single natural disaster in the past decade caused more than 50,000 deaths. In the past two decades however, at least eight natural disasters have done so. The deadliest of these was most likely the Indian Ocean earthquake and tsunami in 2004, which caused an estimated 230,000 deaths, most of them in Indonesia but many also in Sri Lanka and other countries in the region. This was followed by the 2005 Kashmir earthquake (~87,000 deaths), the 2008 Burma cyclone (~138,000 deaths), the 2008 Sichuan earthquake (~88,000 deaths), the 2010 Haiti earthquake (~46,000-316,000 deaths) and a heat wave, drought, and wildfires in Russia in 2010 (~56,000 deaths). An earlier heat wave in Europe in 2003 resulted in an estimated 70,000 deaths.
One obvious pattern here is the destructiveness of earthquakes and earthquake-triggered tsunamis. They caused four out of these eight disasters, including the two deadliest.
Financially too, earthquakes have usually been the most devastating disasters. The most expensive natural disaster in modern history was the earthquake and tsunami in Japan in 2011, which caused approximately 16,000 deaths (2,203 of which were related to the Fukushima nuclear disaster the tsunami caused) and an estimated 411 billion inflation-adjusted dollars worth of damage, according to Wikipedia. (The 2010 Northern Hemisphere heat waves, if viewed as being a single natural disaster, may have been even costlier). That same year, the Christchurch earthquake in New Zealand cost an estimated $44 billion, itself one of the most expensive modern-day disasters. The second most expensive disaster was another Japanese earthquake, in 1995 in Kobe (~6,400 deaths; ~$330 billion worth of damage). Third costliest was the 2008 earthquake in Sichuan, China (~88,000 deaths; ~$176 billion).
The five most expensive natural disasters apart from these earthquakes may all have been hurricanes in America, each one taking place since 2005 (Katrina); three taking place in 2017 alone (Harvey, Maria, and Irma). Yet even the 2017 hurricane season as a whole cost less than either of Japan’s big earthquakes.
A good source on natural disasters is Vaclav Smil‘s book Global Catastrophes and Trends: The Next Fifty Years, published in 2006. It looks closely at the dangers posed by many different types of disasters, including low-probability, high-impact events like asteroid strikes, supernovae explosions, and mega-volcanic eruptions. According to Smil, the most common disasters of late have been floods and storms, but the deadliest have been earthquakes:
Of course, these do not come near the figures of the deadliest modern epidemics, not just Covid-19 or the Spanish Flu of 1918-1920, but also others such as the 1957-1958 Asian flu (~2 million deaths), the 1968-1969 Hong Kong flu (~1 million deaths), and the AIDS epidemic (~32 million deaths in its 60 years, for an average of 530,000 deaths per year, with a peak of 1.7 million deaths in 2004, most occurring in southern Africa). Nor do they approach the number of deaths from other horrible, avoidable problems, such as road accidents (~1.3 million deaths per year in recent years), indoor air pollution (~2-4 million deaths per year), or war (~30,000-200,000 deaths worldwide per year during the relativelypeaceful past decade). They also do not come near the death tolls from the very worst natural disasters, like the floods that occurred in northern China in 1887 (~900,000-2 million deaths, perhaps half of which were caused by a resulting pandemic and famine) or in 1931 (~400,000-4 million deaths).
These lists of disasters do not include food crises or famines, the causes of which are often more political than environmental. The deadliest food crises to occur in recent years were the droughts in East Africa in 2011, which resulted in an estimated 50,000-250,000 deaths, and perhaps also in the Middle East in 2011 and 2012, which may or may not have been a major cause of the Syrian civil war. The worst cases to occur in recent decades include the famines in North Korea from 1994-1998 (~240,000-3.5 million deaths), in Ethiopia from 1983-1985 during part of its civil war (~1.2 million deaths), and above all in China from 1959-1961 during the Great Leap Forward (~15-55 million deaths).
Obviously these Wikipedia statistics need to be taken with a large grain of salt. They often range widely: the death toll estimates for the recent 2010 Haiti earthquake, for example, run from 46,000-85,000 (according to a report made by the US Agency for International Development) to 160,000 (according to a University of Michigan study) to 316,000 (based on numbers from the Haitian government). The death toll from the 1976 North China earthquake, perhaps the deadliest post-WWII natural disaster, ranges from 240,000-650,000.
All of these estimates may also overlook indirect causes of death and destruction, and certainly they do not include the significant non-fatal consequences disasters usually cause. The 2015 Nepal earthquakes, for example, led to around 8,000 deaths, but 3.5 million people were made at least temporarily homeless by them. The heat waves in Europe and Russia in the 2000s killed tens of thousands of people, but many of those who they killed were already seriously ill. The 2011 earthquake and tsunami and nuclear disaster in Japan led not only to death and destruction directly, but also to increased pollution from coal and lignite, as it caused Japan and Germany to shutter most of their nuclear power plants.
Historically speaking, northern China and Japan have suffered some of the deadliest earthquakes, though in China’s case this has had more to do with the country’s population density than with the intensity or frequency with which it tends to experience earthquakes, which has generally been lower than that faced by Japan and other countries along the Pacific rim. Before the terrible earthquakes in Sichuan in 2008 and Hebei in 1976, there was the Gansu-Ningxia earthquake in 1920 (~273,000 deaths). Three years after that, the 1923 Great Kanto earthquake in Japan caused ~100,000-143,000 deaths, destroyed large parts of Tokyo, and was, at the time, probably the most destructive disaster experienced by a modern industrial city. (The next big one that hits Tokyo will be far more destructive yet, as the city is much larger now than it was a century ago. But it will also be less deadly, because safety measures have improved). Possibly the deadliest ever earthquake occurred in Shaanxi, in northern China, in 1556, killing more than 800,000 people.
Along with the 1976 Hebei earthquake, the other deadliest disasters in the late twentieth century were the 1991 Bangladesh cyclone (~140,000 deaths), the 1975 typhoon and resulting collapse of the Banqiao Dam in central China (~230,000 deaths) and the 1970 East Pakistan (now Bangladesh) cyclone (~500,000+ deaths). That East Pakistan cyclone, which is likely the deadliest cyclone to have ever occurred, may also have triggeredBangladesh’s war of independence the following year. The cyclone struck just one month before Pakistan’s first ever democratic election was held at the end of 1970, and the poor flood-relief efforts by the Pakistani military government in the immediate aftermath of the cyclone is thought to have helped influence a large majority of Bengalis to vote for the Bengali nationalist Awami League. This in turn led to an alleged genocide being carried out by Pakistan against Bengalis, and ultimately to a brief but deadly war being fought between India and Pakistan.
Bangladesh and the Philippines are notable here, as being arguably the most prone to natural disasters, of various kinds, of any large countries. The Philippines in particular regularly experiences earthquakes, tsunamis, cyclones, and volcanic eruptions. Even as Bangladesh suffered one of its deadly cyclones in 1991, in the Philippines that same year the eruption of Mount Pinatubo, just outside of Manila, killed 847 people and caused “the largest stratospheric disturbance since the Krakatoa eruption in 1883, dropping global temperatures and increasing ozone depletion”, according to Wikipedia. It was the second largest known eruption in the twentieth century, trailing only the eruption of Novarupta in Alaska in 1912.
At least ten times greater than these eruptions however was the Mount Tambora explosion in Indonesia in 1815, the only volcano in recorded history other than Krakatoa to result in a death toll above 30,000. The Tambora eruption is estimated to have killed 70,000-250,000+ people, mostly through its impact on the global climate: it may have caused the famines of the “Year Without a Summer” in the Northern Hemisphere in 1816. Nearby Krakatoa too killed most of its victims indirectly, by triggering what may have been the third deadliest tsunami in recorded history (~36,000–120,000 deaths). The only deadlier tsunamis were caused by the Indian Ocean earthquake in 2004 and by the Messina earthquake in Sicily in 1908 (~75,000-123,000 deaths).
Going back all the way to Mount Vesiuvus’ destruction of Pompei and Herculaneum in 79 AD, only ten volcanic eruptions are estimated to have killed more than 10,000 people — a far lower figure than the number of deadly earthquakes, storms, or famines. Since Krakatoa in 1883 there have been only two very deadly eruptions, one in Colombia in 1985 and the other on the Caribbean island of Martinique in 1902. The Martinique eruption killed all but two of the 28,000 inhabitants of the town of Saint-Pierre – one of the survivors a prisoner in a jail cell who had been arrested the previous night. The Colombia eruption resulted in an estimated 23,000 deaths, and led to the creation of the Volcano Disaster Assistance Program in the United States, which six years later helped evacuate 75,000 people from around Mount Pinatubo in the Philippines, keeping the death toll from that much larger eruption low.
Two months before the eruption in Colombia, which was the deadliest natural disaster in Colombian history, Mexico experienced the deadliest disaster in its history, the 1985 Mexico City earthquake, which caused an estimated 5,000-45,000 deaths. A number of other disasters in recent decades have had death tolls within a similar range. These include earthquakes in Gujarat, India, in 2001 (~13,000-20,000 deaths; India’s current prime minister Narendra Modi was given his first big job in politics because of the perceived inability of his predecessor to handle the aftermath of this earthquake), in Turkey in 1999 (~17,000 deaths), in Iran in 1990 (~50,000 deaths), and Armenia in 1988 (~28,000 deaths). Apart from earthquakes, it also includes cyclones in Central America and Mexico in 1998 (~11,000 deaths), Bangladesh and India in 2007 (~15,000 deaths) and southeastern India in 1977 (~10,000-50,000 deaths), and flash flooding and landslides in Venezuela in 1999 (~10,000-30,000 deaths).
The United States, in contrast to these countries, has been mostly spared from deadly natural disasters. The Great Galveston hurricane in 1900 was the probably the deadliest disaster in American history, resulting in the deaths of 8,000-12,000 people. Heat waves in 1901, 1936, 1980, and 1988 may each have resulted in 1000-10,000 deaths. And the country does face a significant risk from earthquakes, particularly in the Pacific Northwest. (This Pulitzer-prize-winning New Yorker article about this topic is worth reading). Thus far however the deadliest earthquake the US has experienced, in San Francisco in 1906, resulted in a relatively low number of deaths (~700-3000). The next deadliest, in Alaska in 1946, caused 165 deaths. Alaska then experienced the world’s second-highest-magnitude earthquake of the past century, in 1964 – a magnitude 9.4 – which caused 143 deaths.
Like Alaska, certain places in the world have been struck repeatedly by large earthquakes. The most notable of these may be Valdivia, in Chile. It experienced the most powerful earthquake on record, in 1960, an earthquake so powerful that by itself it accounted for roughly 25 percent of the world’s seismic energy released in the 20th century. (The next two biggest in the century, in Alaska and Sumatra, together accounted for roughly another 25 percent). The first really big earthquake ever recorded was also in Valdivia, in 1575, according to Wikipedia.
The next three big ones after that, all in the 1600s, were in Chile as well, including one in the capital, Santiago. Valparaiso (in central Chile, near Santiago) was then hit with big ones in 1730 and 1822, and Conception (on the coast between Valdivia and Valparaiso) in 1751 and 1835.
The other area to flag in this regard is the island of Sumatra, in Indonesia. It has been hit with one of the only two recent earthquakes with a magnitude of at least 9; namely, the deadly Indian Ocean earthquake and tsunami in 2004. (The other magnitude 9+ earthquake was the costly Japan earthquake in 2011; until then most experts had not believed that an earthquake above 8.4 was even possible in Japan). Before that, no 9+ magnitude earthquakes had occurred since Alaska in 1964 or Chile in 1960. A magnitude 9 is about 33 times more seismically powerful than a magnitude 8, and over 1000 times more powerful than a magnitude 7. Sumatra was also hit by two of the only three recent earthquakes in the magnitude-8 range (in 2012 and 2005). The other was just off the coast of Conception in Chile, in 2010. Before 2004, there were no magnitude 8+ earthquakes since Alaska in 1964.
Going further back into human history, Sumatra also has the honour of being where Mount Toba erupted, around 75,000 years ago, in an explosion at least a dozen times greater than even Tambora’s was in 1815. The Toba catastrophe theory “holds that this event caused a global volcanic winter of six to ten years and possibly a 1,000-year-long cooling episode. In 1993, science journalist Ann Gibbons posited that a population bottleneck occurred in human evolution about 70,000 years ago [with fewer than 10,000 humans left alive in the world], and she suggested that this was caused by the eruption.” This theory is still debated today. It may serve as a reminder – as if we needed another one – that it pays to keep an eye on all the things that can go disastrously wrong in the world.
The idea for this post came from the picture above. As you can see, the fastest population growth in the United States has been in southern and western states, led by Nevada, Arizona, and Florida. Northern and central states have grown much more slowly, and West Virginia’s population even shrank a little bit. In the following charts, I’ve graphed the data above, and added in Canadian provinces, Mexican states, and Caribbean countries to provide further points of comparison. The x-axis shows population growth between 1950-2016 in percentage terms, the y-axis shows total population size as of 2016 (in millions).
This first chart shows just American states and Canadian provinces:
The big standouts in the US are California, Texas, Florida, Arizona, and Nevada. In Canada too, the southernmost province, Ontario, and the westernmost provinces, Alberta and British Columbia, grew the fastest. But, Canadians not having a proper Sunbelt to move to, even Quebec’s growth rate was faster than all but nine US states.
Now let’s add in Caribbean and Central American countries, and Puerto Rico:
The populations of these countries grew faster than most American states, though none matched the growth of Arizona or Nevada. The most notable standouts were Colombia, Venezuela, Honduras, and Guatemala; the Caribbean islands grew more slowly.
Now let’s add in the Mexican states. Mexico has 32 states, but the following chart shows only 29 of them; I could not find the relevant statistics for the states Oaxaca or Durango, and did not include the state of Quintana Roo here because its growth has been so incredibly rapid since Cancun was developed in the 1970s that to include it would have distorted the entire chart. (You can see what that looks like further below).
As with the Caribbean and Central America, Mexican states have grown faster than American ones. As in the US, the fastest-growing Mexican states have tended to be near the US-Mexico border, and near California and Arizona in particular. These include the two Baja California’s, Sonora, and Neuvo Leon.
The big standout, however, is Estado de Mexico (State of Mexico), which includes part of Mexico City. In contrast, Ciudad de Mexico, which includes the historic centre of Mexico City, had one of the slowest-growing populations. This is similar to America’s District of Columbia, the population of which has actually shrunk since its peak in 1950, even as the population of Washington’s metropolitan area in Virginia and Maryland has grown relatively quickly.
Now, let’s add in the outlier that is Quintana Roo. Its growth, based on Cancun, is similar to Nevada’s Vegas-driven growth. But whereas Nevada’s population in 2016 was around 17 times larger than it was in 1950, Quintana Roo’s was nearly 70 times larger than it was in 1950:
Finally, let’s compare the growth of US states to countries worldwide. Here is the population growth rate of some of the biggest countries in the world, compared to five of the fastest-growing American states:
While Nevada’s growth rate has been about the same as Kuwait’s, the comparison between sin cities Las Vegas and Dubai (in the United Arab Emirates, the biggest growth outlier in the world) might be the most apt.
One of the good things about the Biden presidency has been the reduction in Trump-oriented small talk. This has left old favourites (the weather) and new upstarts (Covid vaccination) as the big small talk items. And really, it is easy to see how hand in hand these two topics go. Locking down has been especially tough in the cold. Restaurant owners have seen their patios empty, tired parents have had to struggle to get (and keep) their toddlers’ jackets and gloves and hats and snowpants on, front-line workers have had to wait outside for the bus or scrape ice and snow off their cars at the start and end of a stressful day, deliverymen and women have had to unpack groceries or bike over meal deliveries in freezing weather, homeless people have had to take refuge in shelters vulnerable to Covid, elderly people and disabled people have been unable to go to the mall or gyms or cafes when it’s too icy or windy to walk or use a wheelchair outside, basement apartment dwellers have gotten limited sunlight and their ceilings stamped on by their working-from-home neighbours upstairs. More generally, anybody living with a bad home situation or in a crowded apartment has found it harder to find some peace and privacy, or socialization, by simply going outside.
With all of this in mind, I’ve made a chart that shows both winter weather and vaccination rates in various countries. The y-axis shows average daily high temperatures for capital cities during the month of February, the x-axis vaccination rates in those same countries as of March 1. Obviously, this chart isn’t meant to yield any great insights. It’s just…making small talk.
Here we can see the sunny outliers, Israel with its 90+ percent vaccination rate and warm winter weather, and the United Arab Emirates, with its 60 percent vaccination rate and even warmer weather. And we can also see the opposite extreme, the minus-10 degree daily high temperatures in the capital cities of Mongolia (Ulaanbaatar) and Kazakhstan (Nur Sultan, aka Astana, aka Akmola), and almost no vaccinations. (Mongolia has at least had one of the lowest Covid death rates of any country in the world, about 100 times lower than in Kazakhstan and about 1000 times lower than in countries like the US, the UK, and Italy).
The US and UK are also outliers in vaccination however, and, at least in London and in the southern US, are also enjoying fairly warm weather. Perhaps more of a surprise is Serbia, which is next to the US and the UK here. Serbia has been open to vaccines coming not just from American pharmaceutical companies but also from Russia (the Sputnik vaccine, which has not yet been used much even in Russia) and China (the Sinopharm vaccine). (In terms of Covid death rates, Serbia has been a middle-of-the-pack country; its death rate is only about a third as high as in the US, the UK, or its own next-door neighbours Hungary and Montenegro, and it is roughly equal with those of countries like Canada and Israel).
Chile, where it is still summer, is another country that has had a relatively successful vaccination campaign. A number of small, warm island states, like the Maldives, Barbados, Bahrain, and Malta, have as well. In contrast, none of the countries where daily high temperatures average below zero in February, such as Finland, Norway, Canada, Russia, and Ukraine, are ahead in vaccinations. Outside of southern Canada, these countries are not just cold but also extremely dark during the winter.
Daylight-Patio Savings In countries like Russia and Canada, it will be at least 2 more months before warm weather or significant rates of vaccination occur. (As I finish writing this now, on March 15 in Toronto, around noon, it is minus-2 outside, and 5% of Canadians have received a first dose of a vaccine). On the bright side, there is now a bright side: with the days getting longer, there is more sun to go around, especially on the south-facing side of streets. Which brings me, in a roundabout way, to the two other big city-small talk topics of conversation: traffic/parking, and restaurants.
With indoor dining closed, and with patios needing to provide a responsible amount of social distance space (at the very least, so as to not scare away potential customers), restaurant-adjacent sunny patio space may be a precious commodity this spring. After all, you get cold quickly when sitting down in the shade. And yet, if the patio policy that existed in autumn is any indication, the vast majority of sunshine will be given to car-driving lanes and street parking, leaving most patios either in shadier areas or with less-than-ideal social distancing.
A maximally restaurant-friendly patio policy, in contrast, would take today’s 4-lane east-west main streets (for example) and make them temporarily 2-lane streets, so that the entire south-facing half of the street could become a sunny springtime patio and pedestrian area.
I’ve left out, of course, the smallest-talk subject of all: daylight savings. This year it’s not just about the farmers. Restauranteurs too can benefit from more sunlight during dinnertime, if we give patios the space they need. This is something they, and we, could all enjoy a after a long, difficult winter. So, let’s make a slight addition to the old mnemonic this year. Spring ahead, put the cars in the shade.