Economic Geography

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

Patterns of Income Inequality in Major U.S. Metropolitan Areas and Population Change, 2020-2022

The four U.S. states with the highest levels of income inequality are, in order, New York, Connecticut, Louisiana, and Mississippi. When mapped at the county level, however, New York and Connecticut appear to have lower levels of inequality than Louisiana and Mississippi. The seeming discrepancy is easily explained by population density. In New York and Connecticut, high GINI coefficients are found in densely populated counties that are part of the greater New York metropolitan area; counties with smaller cities, in contrast, tend to have average levels of income inequality, whereas most rural counties in these states have relatively low levels. (Unfortunately, the scale of resolution on the maps that I have used does not adequately reveal this phenomenon; most of New York City, for example, is obscured by the heavy black line that is used for state boundaries.) In Louisiana and especially Mississippi, in contrast, many rural and semi-rural counties are characterized by pronounced income inequality.

But how do the high levels of income inequality in the New York area compare to those found in and around other major U.C. cities? To address this question, I extracted details from the county-level GINI map of the United States to show the situation in the vicinity of 16 major metro areas found across the country. As can be seen, in each case the central county or counties, those with the highest population densities, have higher levels of income inequality than the more suburban and peripheral counties.

Such comparisons are made difficult, however, by the incommensurable nature of the units. In some cases, inner counties are extremely small; San Francisco County, for example, is coterminous with the city of San Francisco, whereas New York City is itself divided into multiple counties. In contrast, Phoenix tends to vanish in the vast expanse of Maricopa County.

But even with these limitations in mind, there are still some intriguing lessons to be drawn from these maps. At the high end of the inequality spectrum is Miami, followed by New York and San Francisco, where almost all counties in the greater metro areas have average to high GINI coeffiecient. Seattle, Denver, Minneapolis, and Washington DC/Baltimore, in contrast, are surrounded by suburban and peripheral counties with relatively low levels of income inequality. I was surprised to see this pattern in the Washington D.C. area, which is by some measures the wealthiest part of the country. As can be seen on the small map, Baltimore and the District of Columbia are, not surprisingly, characterized by high inequality, as is, more surprisingly, rural Talbot County in eastern Maryland. Affluent Montgomery County, in contrast, falls in the middle category.

Many of the country’s major metropolitan areas saw population decreases between 2020 and 2022. Such declines tended to be steepest in areas of pronounced inequality. The New York metro area, for example, lost 2.6 percent of its population and the San Francisco metro area 3.6 percent, the steepest drop in the country. The less unequal Seattle, Denver, Minneapolis, and Phoenix metro areas, in contrast, all gained population. But exceptions are certainly found. The Washington, D.C. area, with its relatively income-equal suburban counties, lost population, although just barely (0.21 percent), while the highly unequal Miami metro area gained population, although again just barely (0.02 percent).

Geographical Patterns of Income Inequality in the U.S. at the State and County Levels

I have long been intrigued by the geography of income inequality in the United States. As maps of the GINI coefficient show, income inequality is highest some of the country’s richest states (New York, Connecticut) and in some of its poorest (Louisiana, Mississippi). Similarly, some of the country’s most Democratic-voting states and some of its most Republican-voting ones are characterized by pronounced income inequality. Relatively low levels of income inequality are concentrated in an area that might crudely be described as the center-north-west, with four contiguous states occupying the lowest category on the map (Utah, Idaho, Wyoming, South Dakota). Low population density characterizes states with low income inequality. All of the states in the bottom two categories on this map except Hawaii have a lower-than-average population density. Politically, these states show the same mixed pattern that characterized the most economically polarized states. Although all the states in the lowest GINI category are bright red on electoral maps, two that fall into the next lowest category (Vermont, Hawaii) are bright blue.

A county-level GINI map clarifies the geography of U.S. income inequality and reveals some interesting patterns (unfortunately, the best map that I could find on this topic is somewhat dated). As can be seen, the elevated levels of income inequality found in northeastern states is largely an urban phenomenon. In the southeast, in contrast, some counties with high GINI coefficients are metropolitan (in southeastern Florida, for example), but others are markedly rural. In Western and Great Plains states characterized by relatively low income inequality, quite a few of their rural counties have high GINI scores.

In North Dakota, South Dakota, and Montana, some rural counties characterized by high income inequality also have a high percentage of Native American residents. To illustrate this correlation, I have placed a GINI map of the Dakotas next to one of indigenous population percentage. But there are a few striking exceptions to this pattern, two of which are noted on the map. As can be seen, Divide County, North Dakota has a small Native American population and a high GINI coefficient. Pete Morris’s agricultural explanation of income inequality, outlined in his comment on yesterday’s post, is probably relevant here as well. In contrast, Buffalo County, South Dakota has a large Native American population and a low GINI coefficient. Both of these counties have very small populations. Buffalo County is noteworthy for having the least populous county seat in the United States (Gann Valley, with a population of 14).

In the south-central region of the country, most counties with high levels of income inequality have large black populations. But again, interesting exceptions can be found. As can be seen, Jefferson County, Arkansas has a high percentage of Black residents and a mid-level GINI ranking. In contrast, Marshall County, Alabama has a very low percentage of Black residents and a high level of inequality. Jefferson County, intriguingly, is known for its concentration of “correctional facilities,” mostly located in and around Pine Bluff. Marshall County, Alabama, in contrast, is part of the Huntsville-Decatur Combined Statistical Area, a region noted for its many well-paid technical workers, owing largely to that presence of NASA’s Marshall Space Flight Center, the United States Army Aviation and Missile Command, and the FBI ‘s Operational Support Headquarters. Marshall’s largest city, Albertville, is mostly noted, however, as the home of the fire-hydrant-manufacturing Mueller Company. As noted by the Wikipedia article on the city, “Albertville holds the title of “Fire Hydrant Capital of the World.” To commemorate the one millionth fire hydrant, a chrome fire hydrant was placed outside the Albertville Chamber of Commerce.”

The next GeoCurrents post will examine the geography of income  inequality in the country’s largest metropolitan areas.

Explaining Seeming Discrepancies on County-Level Income Maps of the United States

When working on a recent GeoCurrents post that involved maps of income in the United States, I noticed a few unusual patterns. A number of counties, for example, are mapped as having relatively high per capita personal income and relatively low median household income, whereas in others the opposite pattern obtains. In part this is a matter of household size, an explanation that works particularly well for Utah. Consider, for example Utah County, Utah which is characterized by relatively low per capita personal income, relatively high median household income, and a large number of people per household. In contrast, Grand County is characterized by relatively high per capita personal income, relatively low median household income, and a small number of people per household.

In Utah, the number of people per household correlates closely with religion. Members of the LDS church (Mormons) often have high fertility rates, leading to large households. Utah County, Utah, home of Brigham Young University, is usually considered the cultural center of the LDS faith. As can be seen on the second map below, Utah County has one of the highest fertility rates in the country. In contrast, Grand County has a relatively low fertility level (which is not shown in the map due to its small population) and the lowest LDS percentage in the state. Whereas Utah as a whole is roughly 62% Mormon, in Grand County the figure is only 26%.

These easy correlations, however, collapse when one examines North Dakota. As can be seen on the map below, Cavalier County has the highest per capita personal income in the state, which is why it is outlined with a heavy white line on the map posted here. But Cavalier County is also characterized by relatively low median household income and relatively few people per household. This seeming anomaly can be explained by taking into account the different way that the two income measurements are determined. Median household income is calculated by taking the income of all households in a county and finding the middle point; per capita personal income, on the other hand, is calculated by dividing the total income of all persons in the county by the population. If a county has a small population with a few very high-income individuals, the per capita personal income figure is inflated, whereas the median household income figure will remain low if most households have lower incomes.

If this explanation is correct, one would expect Cavalier County to have a relatively high Gini Coefficient, which measures the degree of inequality. The most recent GINI map of all U.S. counties that I was able to find (posted below) indicates that this is indeed the case. Overall, North Dakota is characterized by very wide range in GINI figures, which is probably largely an attribute of the small populations of most of its counties.

 Regardless of its income level, Cavalier has not exactly been a thriving county over the past century. It had more than 15,000 people in 1920 and fewer than 4,000 in 2020.

The Unique Multiply Enclosed Back Sea, and the Crucial Grain Supply of Ancient Athens

As noted in the previous post, the “marginal sea” concept has little utility for geo-historical analysis. More useful is the idea of what might be termed an “enclosed sea,” meaning one whose entrance to the open ocean, or strait, is narrow enough that it could have been controlled by a strong state in the ancient, medieval, and early modern periods. Such enclosed seas are few. If we limit our attention to parts of the world that had states during these times, there are really only four straits that count: the Strait of Gibraltar, separating the Mediterranean from the Atlantic; the Danish straits, separating the Baltic Sea from the open margins of the Atlantic; the Strait of Hormuz separating the Persian Gulf from the Indian Ocean; and the Bab-el-Mandeb, separating the Red Sea from the Indian Ocean. Of these, the 13-kilometers-wide Strait of Gibraltar is the narrowest. The Bab-el-Mandeb, in contrast, is 26 kilometers wide at its narrowest extent, whereas the Strait of Hormuz is 39 kilometers wide at its narrowest extent. The Danish Straits do entail some narrow passages, but there are three of them, and the most important, the Great Belt, is 16 kilometers wide at its narrowest point.

 

The Mediterranean is not only the most enclosed sea, but is also the largest by far. More significant, it opens up to its own enclosed seas, all of which are connected by even narrower passages. The long and meandering Dardanelles, which links the Mediterranean’s marginal Aegean Sea to the Sea of Marmara, is only 0.75 kilometers wide at its narrowest extent, as is the Bosphorus, which connects the Sea of Marmara to the Black Sea. The Strait of Kerch, which connects the Black Sea to the Sea of Azov, is much wider, 3.1 kilometers at its narrowest extent, but is still significantly narrower than the Strait of Gibraltar.

Such observations lead to an inescapable conclusion: the Black Sea system, including Marmara and Azov, is a unique physical-geographical entity. There is nothing else remotely like it on earth, an oddly unrecognized fact. It is also noteworthy that the Black Sea lies near the center of the segment of the world that includes the other enclosed seas, as can be seen on the maps posted below.

The enclosed nature of the Black Sea system has been geopolitically important during several historical periods. Consider, for example, the situation of Athens during its heyday in the fifth and fourth centuries BCE. After the defeat of the Persian Empire, Athens was eager to secure access to the Black Sea and its many resources. The Delian League that is soon created maintained control over both the Dardanelles and the Bosporus. After its defeat by Sparta in the Peloponnesian War, Athens lost this informal Aegean empire, and thus found itself in a strained situation. It eventually cobbled together a new but less-imperial Second Athenian League, which included cities along the Dardanelles and Bosporus. It was at this time that Black Sea grain became essential for the sustenance of Athens (and several other Greek city states). Securing access to the essential grain supply also entailed maintaining a tight alliance with the culturally hybrid Greco-Scythian Bosporan Kingdom, which sat astride the Strait of Kerch (then called the Cimmerian/Kimmerian Bosporus). Fish supplies from the highly productive Sea of Azov and the rivers that flowed into it were also an important resource for Athens, underscoring the significance of its connection with the long-lived (438 BCE –527 CE) Bosporan Kingdom.

For a fascinating account of this relationship, I recommend Alfonso Moreno’s “Athenian Wheat-Tsars: Black Sea Grain and Elite Culture,” which is found in an important book entitled The Black Sea in Antiquity: Regional and Interregional Economic Exchanges. Moreno highlights the close ties between Athenian elites associated with the school of Isocrates (an extremely important although under-appreciated intellectual and political operative), and the Greco-Scythian elites of the Bosporan Kingdom. His final words are worth quoting:

Two things only were needed to ensure the permanence of this system: the good-will of the Bosporan kings, and Athenian control of the route between [the Cimmerian Bosporus and Athens]. As long as Athenian political leadership could provide this, Athens would be fed and a few of its politicians gain enormous power. If correct, we may have here a very different way of understanding this trade: an oligarchic grain supply sustaining a professedly democratic state.

Although the fifth century BCE is usually considered the golden age of ancient Athens, the fourth century BCE was in many respects a more intellectually vibrant period. To a large extent, the culture that allowed such intellectual flourishing was underwritten by the grain and other resources that flowed in from the Black Sea, which in turn entailed maintaining close relations with the states that controlled the crucial choke points leading from the Aegean Sea to the Sea of Azov.

Wage Differences Across the Republic of Georgia

The GeoStat data page on the Republic of Georgia includes information on the Average Monthly Remuneration in Business Sector by municipality. As Georgia is divided into many municipalities, mapping these data helps reveal the level of economic differentiation across the country (assuming that the data are accurate). As the resulting map shows, income levels in the business sector vary widely across Georgia, with a low of 301 Georgian Lari a month in Shuakhevi in the southwest to a high of 1,814 Lari a month in Bolnisi in the south-center-east. (The current exchange rate is 2.56 Lari to a US dollar).

 

Overall, the geographical patterns found on this map are vague, with high-, middle-, and low-income municipalities scattered across most reaches of the country. But some patterns can be discerned. The area in and around Tbilisi, Georgia’s capital and by far its largest city, is a relatively high-income area, as would be expected. The Black Sea cities of Batumi and Poti also have relatively high levels of (business) income, the former noted for its tourism-based econony and the latter for its port facilities. But Georgia’s other main urban-focused municipalities (Kutaisi, Rustavi, Gori, and Zugdidi) do not rank high. To some extent, this low showing reflects the industrial decline of the post-Soviet period. As the Wikipedia articles on Kutaisi and Rustavi explain:

Kutaisi was a major industrial center before Georgia’s independence on 9 April 1991. Independence was followed by the economic collapse of the country, and, as a result, many inhabitants of Kutaisi have had to work abroad. Small-scale trade prevails among the rest of the population.

The fall of the Soviet Union in 1991 proved disastrous for Rustavi, as it also caused the collapse of the integrated Soviet economy of which the city was a key part. Most of its industrial plants were shut down and 65% of the city’s population became unemployed, with the attendant social problems of high crime and acute poverty that such a situation brings.

In contrast, several primarily rural municipalities have relatively high rankings. Sitting at the top is Bolnisi, an ethnically distinctive area. Its population is primarily Azerbaijani speaking (63%). Its capital, also called Bolnisi, has an unusual ethnic history. Home around 10,000 people, Bolnisi city was established by German (Swabian) immigrants in 1818, who called their new town Yekaterinenfeld. These migrants developed the agrarian and agro-industrial infrastructure of the region, which may contribute to its current prosperity – along with gold mining. As explained in the Wikipedia article:

The main occupations of the colonist Germans were viticulture, horticulture, fruit growing and cattle breeding. At the same time, irrigation, underground drainage and irrigation canals were constructed in Yekaterinenfeld, as well as wine, cognac and cheese factories, and leather and furniture factories. The town’s contemporary economy is mostly agrarian with the notable exceptions of a winery, brewery, and a gold mine in the nearby village of Kazreti.

Several other primarily rural municipalities with relatively levels of business income have strong tourism sectors. These include Mestia in the mountainous northwest, famed for both its natural beauty and its unique architecture. As the Wikipedia article on the town of Mestia notes:

Despite its small size, the townlet was an important centre of Georgian culture for centuries and contains a number of medieval monuments, such as churches and forts, included in a list of UNESCO World Heritage Sites. The townlet is dominated by stone defensive towers of a type seen in Ushguli and Mestia proper (“Svan towers”). A typical Svan fortified dwelling consisted of a tower, an adjacent house (machubi) and some other household structures encircled by a defensive wall.

Kvareli, a high-income municipality in Georgia’s mountainous northeast, also has a number of tourism attractions, and is noted for its wine production. In west-central Georgia, high-income Kharagauli is the gateway to Borjomi-Kharagauli National Park. Nearby Zestafoni, another relatively high-income municipality, is another important wine-producing area, and is also the site of a large ferro-alloy plant that processes manganese ore. The ore is mined in adjacent Chiatura municipality, which also posts relatively high business-income figures.

These are obviously just preliminary observations, based on casual reading. Much more research would have to be conducted to make any conclusive statements. I was also unable to find any possible reasons for the low levels of business income in such municipalities as Vani and Shuakhevi.

Economic Geography of the Republic of Georgia, Part 1

(Note to Readers: As I have been invited to give a talk at an academic conference on the Black Sea region to be held in Batumi, Georgia in early June, I will be blogging extensively on this part of the world over the next two months. I begin today by posting several simple economic maps of the Republic of Georgia.)

The Republic of Georgia is a middle-middle-income country; according to the IMF, in 2022 its per capita Gross Domestic Product (in Purchasing Power Parity) was just below the global average (19,789 current international dollars for Georgia as compared to 20,886 for the world.) As country-level economic figures obscure regional variation, I looked for a map of “per capita GDP in Georgia by region” but did not find one. After some searching, I did locate an English-language version of a site called “Statistical Information by Regions and Municipalities of Georgia” that provides the data that can be used to make such a map. (Unfortunately, there are some minor informational discrepancies on this site; I used the “comparison of regions” feature rather than the map-based information portal, but I do not know which one has more accurate or up-to-date information.)

My main reason for making this map was to see if there is a significant economic distinction between eastern and western Georgia. As will be explored in later posts, these two halves of the country have very distinctive histories and geographies. I expected to find the highest levels of economic development in and around Tbilisi, located in the central part of eastern Georgia, which is by far the largest city in the country. I also expected to find a relatively high per capita GDP figure for the Adjara region in the southwest, where the tourist-oriented city of Batumi is located. Otherwise, I had no expectations.

The GDP map that I made, posted below, does show Tbilisi as having a significantly higher level of economic development than the rest of the country. Adjara also has a higher level of per capita GDP than the national average, although not by much. Overall, the map reveals Georgia as having relatively minor economic differentiation by region. Overall, the western part of the country has slightly higher per capita GDP figures than the eastern half, with the exceptions of Tbilisi and the region just to its north (Mtskheta-Mtianeti).

Regional per capita GDP figures can be misleading, however, as they do not necessarily reflect average income levels. Fortunately, the “Statistical Information by Regions and Municipalities of Georgia” website also has data on the “Average Monthly Remuneration of Employed Persons.” Mapping this information also shows relatively low levels of differentiation across the country, but in this case eastern Georgia comes out slightly ahead of western Georgia.

In both maps, the western region of Guria is shown as having Georgia’s lowest economic figures. Guria’s relatively low level of economic production might seem to defy the stereotype of the region in Georgian popular culture, which emphasizes the ability of its inhabitants to accomplish tasks very quickly. As noted by Bedisa Dumbadze in an article in Georgian Journal:

The explanation of the region’s name “the land of restless” is absolutely suitable for Gurians. Their smart and comical character is well-known throughout Georgia. The inhabitants of the area are thought to be relatively fast in contrast to the inhabitants of other regions. They have special habit of doing everything in a very fast manner. Sometimes it is really difficult to understand what Gurian person is talking about because they speak really fast. There are many jokes about Gurians always being in a hurry. As a result, they manage to do everything in a very short period of time.

Finally, I use the same data source to make a map of unemployment rates by region. As can be seen, Georgia as a whole has a high level of unemployment, with figures varying widely from region to region. I was surprised to see that Tbilisi has a higher-than-average unemployment rate. Even more unexpected was the relatively low unemployment rate it the eastern region of Kakheti, which is shown as having relatively low economic indicators on the other two maps.

I hope to reach a better understanding of these patterns as I continue to learn about the Republic of Georgia. I also want to see if clearer economic patterns might emerge through more fine-scale mapping. The data source that I used today also has information at the municipal level. As Georgia is entirely divided into 76 separate municipalities, such a map can be constructed for the entire country. Making this map will take some time, but I hope to be able to post it within the next week or two.

Africa’s Questionable Expansion of Regional Political Organizations

Africa is noted for cooperation among its many countries. All African states belong to the African Union (AU), although four are currently suspended due to recent military coups (Sudan, Mali, Burkina Faso, and Guinea). Owing in part to the AU, and its predecessor, the Organization of African Unity, Africa has few conflicts among is internationally recognized sovereign states, although it has many conflicts within them. The AU defines Africa broadly, seeking to promote solidarity and cohesion across both the continent and the nearby island countries of the Atlantic and Indians oceans.

The African Union also seeks to promote economic growth and cooperation among its member states, mainly through on its ambitious New Partnership for Africa’s Development (NEPAD). A cornerstone of NEPAD is the creation and strengthening of Regional Economic Communities (RECs), groups of neighboring countries designed to foster economic integration. In theory, such smaller organizations can cooperate more effectively than the union as a whole. The eight officially recognized RECs (mapped below) are described as the “building blocks” of the AU and its grand developmental vision. In addition, six other African political-economic blocks have not received official AU recognition. (Four of these unofficial groups are depicted in the final map in the series posted below; note that the Indian Ocean Commission also an includes France, which is not shown on the map, although two of its overseas departments, Mayotte and Réunion, are.)

Although economic cooperative among neighboring countries can help propel economic and social development, the utility of Africa’s RECs is questionable. Several of them continue to add new members, becoming unwieldly in the process. Overlap is now pronounced. Democratic Republic of Congo, a country that hardly manages to govern itself, now belongs to four of these “communities.” Barely functional Somalia belongs to three and has applied for membership in a fourth. Several of the RECs have expanded well beyond the regions that supposedly define them. Consider CEN-SAD: The Community of Sahel-Saharan States. As can be seen on the map posted below, its original members were all located in the Sahara-Sahel belt, a region faced with many similar environmental and economic challenges. But CEN-SAD now includes countries such as Liberia and Sierra Leone that are far removed from the hyper-arid Sahara and the semi-arid Sahel located immediately south of the great desert.

The main problem with Africa’s regional-political approach to economic development is that it is relatively expensive and requires a lot of attention from governmental officials who might be better off focusing on domestic issues. Such complications are noted in several relevant Wikipedia articles. The one on the RECs mentions that “multiple and confusing membership creates duplication and sometimes competition in activities, while placing additional burdens on already over-stretched foreign affairs staff to attend all the various summits and other meetings.” The article on the New Partnership for Africa’s Development has more pointed wording:

More recently, NEPAD has also been criticised by some of its initial backers, including notably Senegalese President Abdoulaya Wade who accused NEPAD of wasting hundreds of millions of dollars and achieving nothing. Like many other intergovernmental bodies, NEPAD suffers from slow decision-making, and a relatively poorly resourced and often cumbersome implementing framework. The great lack of information about the day-to-day activities of the NEPAD secretariat—the website is notably uninformative—does not help its case.

Creating such regional organizations is a tempting and understandable developmental strategy. Doing so makes it seem as if African leaders are deeply committed to peace, international cooperation, and economic betterment. But such a strategy can easily be overextended, with rapidly diminishing utility as the number of organizations and their geographical coverage increases. It would seem that such a situation has been reached in Africa.

Per Capita GDP in Nepal and the Rest of South Asia

The most recent GeoCurrents post compared Nepal with the other political units of the southern Himalayan region on the basis of the Human Development Index (HDI). Today’s post does the same in terms of per capita GDP. The map below shows the per capita GDP standings (in Purchasing Power Parity) in 2020-2021 of the independent countries of greater South Asia along with the states of India (and India’s two largest union territories). This map is problematic in that the data for the states of India and for the region’s independent countries are not completely comparable, as is explained in the map legend. But the general pattern is clear: Nepal continues to lag behind its Himalayan neighbors on this metric, just as it does in regard to the HDI. The gap between Nepal and the Indian state of Sikkim is stark, especially when one considers the close cultural and physiographic similarities of these two polities. Sikkim is actually more Nepali than Nepal, in that only 44.6 percent of the people of Nepal speak Nepali as their first language whereas 66.6% of those in Sikkim do (with only 6.9 speaking Sikkimese). It is also noteworthy that Nepal falls into the same category on this map as the Indian union territory of Jammu and Kashmir (demoted from state status in 2019). On the HDI map, Jammu and Kashmir has a significantly higher standing than Nepal. Finally, note that Pakistan scores much better in this regard than it does in terms of HDI.

The second map is limited to the states and larger union territories of India, showing their per capita GDP in PPP for 2020-2021. Here there are no problems with data comparability. What I find surprising about this map is the relatively low standing, compared to those of neighboring states, of Maharashtra and Punjab. Maharashtra is often considered to be India’s economic pacesetter, and it clearly has India’s largest GDP in total. Punjab, in earlier decades, stood near the top of the per capita GDP list of Indian states. It is interesting that Punjab has lagged behind its neighbor, Haryana. Together, these two states are the core area of India’s agricultural green revolution, and until recently they had more similar developmental indicators.

Bihar, not surprisingly, stands at the bottom of the per capita GDP list for India. Bihar comes in last place in almost every socio-economic indicator in India. I once quipped when teaching that Bihar has been described as India’s Mississippi, meaning that it is in the bottom position in almost everything. That statement deeply offended a student in the classroom from Mississippi, leading me to stop making such comparisons in the classroom.

It is also notable that the small state of Manipur in far eastern India comes in at a much lower ranking on the per capita GDP map than it does on the HDI map. Manipur, like its highland neighbors, has relatively high levels of education, which propels it into a higher overall developmental position than its economic figures alone would warrant.

In the classroom, I like to complement maps of per capita GDP with ones showing per capita income. Per capita GDP can be quite misleading, as regions that have high levels of economic output based on a few key economic sectors, such as mining, often appear much more prosperous than they really are. China’s region of Inner Mongolia exemplifies this problem. I therefore made a map of India showing per capita income based on the most recent data that I could easily find (2017-2018). As can be seen, however, this map is very similar to the 2020-2021 per capita GDP map.

Human Development Index Mapped for Greater South Asia and the Southern Himalayan Belt.

A recent GeoCurrents post on Nepal noted that the country has experienced less development than the rest of the southern Himalayan region, which was illustrated with an old map of per capita GDP. A more recent map of the Human Development Index (HDI) makes the same point: Nepal scores worse on this metric than either Bhutan or any of India’s Himalayan states.

The 2021 map of the Human Development Index (HDI) across greater South Asia shows the Himalayan belt in general ranking significantly higher than the adjacent lowlands of north-central and northeastern India. These results may seem paradoxical, as highland areas of rough topography are often much less developed than nearby areas of flat topography, which typically have much better infrastructure. But in many parts of the world, this generalization does not hold. As can be seen in the map below, the mountains of far-northeastern India have much higher levels of human development than the adjacent lowlands, whether in India, Bangladesh, or Burma. India’s small states along the Burmese boundary have relatively high HDI scores despite their rugged topography, problems with ethnic insurgency, and history of relative isolation. This seeming anomaly is partially explained by the educational focus of Christian missionaries in the region. Nagaland, Mizoram, and Meghalaya all have solid Christian majorities, while Manipur is almost half Christian and Arunachal Pradesh has a Christian plurality. Recent Indian infrastructural investments, along with the gradual reduction in insurgency, have also boosted human and economic development in the region.

The densely populated lowland states of north-central India have the country’s lowest levels of human development, despite forming the historical core of South Asia. This area of low HDI also extends into the mostly lowland state of Assam in northeastern India. Somewhat higher levels of human development, however, are encountered in the lowland Bengali-speaking zone encompassing Bangladesh and the Indian states of West Bengal and Tripura. This area was until recently one of the poorest and least developed parts of South Asia, but it has experienced significant improvements in recent years. It is probably not coincidental that Bengalis have a well-deserved reputation for educational interest and intellectual engagement. To reflect the relatively high position of the Bengali-speaking zone in lowland northeastern South Asia, I have reconfigured the South Asia HDI map to depict Bengal as if it were a separate polity.

The partition of British India in 1947 was also a partition of Bengal, and the violence and economic destruction associated with it long held back the Bengali-speaking zone. A similar event occurred on the other side of South Asia, as the partition of British India was also a partition of Punjab. But here an entirely different pattern emerged. The parts of pre-partition Punjab that went to India (Punjab State, Haryana, and Himachal Pradesh) have all experienced striking improvements in human well-being. The large Pakistani province of Punjab, on the other hand, has lagged behind, as has most of the rest of the country in which it is located. This pattern is not easy to explain. From 1947 to 1971, when Pakistan and Bangladesh formed one country, what was then West Pakistan was far ahead of what was then East Pakistan (now Bangladesh) on almost every economic and human-developmental score. But while Bangladesh experienced substantial improvements, Pakistan has struggled.

To illustrate the human-developmental gap between Pakistan and India/Bangladesh, I made another iteration of the HDI map that breaks down both Pakistan and India into their largest constituent units. I had to go back to 2019 to find easily accessible HDI data at this level, and I am not sure if the data are fully comparable. What the map shows, however, is stark, with Pakistani Punjab and most of the rest of the country coming in with scores much lower than almost any part of India. The extraordinarily low HDI figure for Balochistan is highly significant, helping explain the long-running insurgency of this resource-rich region.

Pakistan’s higher HDI values are found in the mountainous northern regions of the country. Other than tiny Islamabad, the country’s highest HDI levels are in Azad Kashmir and Gilgit-Baltistan (areas claimed by India). Gilgit-Baltistan is noted for his extremely rugged topography and, until recently, its relative isolation from the rest of the world. It has, however, seen remarkable gains in education and social development more generally over the past several decades. Pakistani infrastructural investments, aimed at securing access to western China, have no doubt play a role. More important have been the developmental projects of the Aga Khan Foundation. Many of the people of Gilgit-Baltistan are Nizari Ismai’li Shia Muslims, a group headed by the Aga Khan. The Nizari Ismai’lis in general are a cosmopolitan, liberal, and well-educated people, and their leaders are keen to help their co-religionists in the most remote and rugged corners of northern Pakistan.

The final map in this post is the base map on which all of the other maps are constructed. Like all GeoCurrents maps, it is made in simple presentation software, Apple Keynote (equivalent to PowerPoint). Before long, I hope to make this map available for free on this website in both Keynote and PowerPoint formats. It is a very simple matter to click on any of the units and change their color or their boundaries in any way one sees fit. Similarly, the place names can be deleted, and others can be added, very easily.

Cannabis Legalization in the U.S. Elections of 2022

The 2022 midterm elections in the United States had mixed results for cannabis legalization. Voters in Maryland and Missouri approved legalization measures, easily in the first case and by a relatively narrow margin in the second (see the charts below). Missouri thus became the third solidly “red state” to allow cannabis consumption without a medical recommendation, following Alaska and Montana. Voters in Arkansas and South Dakota, however, rejected legalization, with a 56% “no” vote in the former state and a 55% “no” vote in the latter. The South Dakota vote took many by surprise, as just two years earlier a legalization referendum passed, which was later invalidated in court. South Dakota voters will again take on the issue in the fall of 2023, but indications for legalization are not positive. As reported by Benzinga.com, “a statewide poll conducted this summer revealed that South Dakotans’ general sentiment toward legalizing recreational marijuana has shifted over the past two years, signaling that a referendum on the issue this fall could fail.” At the federal level, meanwhile, congressional efforts to eliminate the de jure cannabis prohibition stalled out, yet again.

The failure of federal cannabis legalization, and in some states as well, seems to defy the general public will. Opinion polls conducted by a variety of organizations show overwhelming support. An October 2021 Gallup poll found that even 50% of Republicans favor full legalization, with Democrats and independents offering overwhelming approval (83% and 71%). Similar results have been obtained by other polling agencies. A 2022 CBS/YouGov poll found a 66% level of support for legalization at both the federal and state levels. According to this poll, Republicans overall narrowly oppose legalization (51% to 49%), but those below the age of 45 solidly support it (59%). A 2022 Pew survey found that only 10 percent of Americans think that cannabis should be illegal for all purposes. According to the same poll, Americans in every age bracket except that of the elderly (75+) favor full legalization.

Given these numbers, along with the fact that American voters are roughly evenly divided among Republicans, Democrats and independents, the persistence of federal anti-cannabis laws is difficult to explain. In this arena, seems that Congress is defying the public will. Quandaries also emerge at the state level. Even in deep blue Hawaii and Delaware, cannabis remains legal only for medical uses, and in several purplish states it remains fully illegal (Wisconsin, North Carolina, and Georgia). How can these results be squared with public opinion polls that shows overwhelming support for legalization?

A variety of factors are probably at play. Simple inertia probably plays a role, and as a result it seems likely that Hawaii and Delaware will opt for legalization before too long. More important, however, is the concerted opposition of anti-cannabis forces. A sizable minority of Americans is vehemently opposed, with many regarding marijuana as nothing less than the “devil’s weed.”* As is often the case, the desires a vehement minority can override the less passionate concerns of a substantial majority. It is significant that legalization has often occurred through popular referenda rather than through legislation, as legislators can be more easily swayed by interest groups than the voters at large.

But another factor may be involved as well. Legalization, it turns out, has often yielded discouraging or even disastrous results. With revenues much lower than expected, chaotic business environments, and a thriving black market, states like California demonstrate the potential hazards of a poorly formulated legal regime. As a result, some legislators, and many voters, may ultimately favor legalization, yet still reject whatever proposal is put before them, skeptical that it gets it right. These issues will be examined in much greater detail in later posts

*The term “devil’s weed” is used most often for Datura, or jimsonweed, which contains several powerful and poisonous psychoactive substances. For a religiously informed discussion of cannabis as the “devil’s weed,” see Marijuana – The Devil’s Weed?, by Dr. Joe Fawcett.

Turkey’s Dependence on Russian Energy, and Its Recent Natural Gas Discoveries

Turkey (officially, Türkiye) is an energy-poor country. Roughly 85% of its energy supply comes from fossil fuels, roughly equally divided among coal, oil, and natural gas. Coal is mined domestically and imported, but almost all of Turkey’s natural gas and oil comes from other countries. Russia supplies roughly half of its natural gas. Unlike most NATO countries, Turkey has not placed sanctions on Russia, and as a result its natural gas imports continue unabated.

Turkey also figures prominently in Russia’s global energy strategy. Two major pipelines transport Russian natural gas to Turkey, one of which (TurkStream) was recently completed (2020). Moscow and Ankara have hoped to turn Turkey into a major natural gas hub, allowing Russia to export gas to southern Europe without having to move it across Ukraine. The Ukraine War has complicated but not undermined such plans. As recently reported by Natural Gas Intelligence, “Russia is turning to Turkey as a potential natural gas hub partner with a new sense of urgency to find new export outlets for volumes left stranded by damages to the Nord Stream pipelines in September.” The Russian-Turkish energy partnership extends beyond natural gas. In 2021, Russia was Turkey’s second largest supplier of coal, following Colombia. Turkey’s first nuclear power plant (Akkuyu), has been jointly built by the Russian firm Atomstroexport and the Turkish construction company Özdoğu; it is expected to come online in 2023.  Financing has been almost entirely provided by Russian investors.

Political tensions between Russia and Turkey have periodically intruded on their energy collaboration. Most recently, Ankara irritated Moscow by asking for a 25 percent discount on natural gas payments and requesting that all payments be delayed until 2024 due to domestic economic problems. Building a Turkish hub for Russian gas exports also faces external economic and geopolitical obstacles, particularly from other NATO countries. As recently noted by Natural Gas Intelligence:

A Russia/Turkey gas hub would have to secure financing for the billions of dollars needed to construct new subsea pipelines under the Black Sea, which is currently in a war zone. Without access to Western technology and financing, a new pipeline project could take years to build.

Turkey’s energy prospects, however, have recently been transformed by substantial natural gas discoveries in its Black Sea Exclusive Economic Zone. In the final week of 2022, an estimated 170 billion-cubic-meter gas reserve was found at the Çaycuma-1 field. Combined with previous recent discoveries in the Sakarya field, Turkey’s natural gas reserves have been elevated to 710 billion cubic meters. Gas from these fields should become available sometime in 2023, alleviating Turkey’s energy crunch. Discoveries to date, however, are not adequate to meet long-term needs, as the country consumes 50 to 60 billion cubic meters of gas every year. To put recent Turkish discoveries in global context, Russia has proven natural gas reserves of some 50,000 cubic kilometers.

Coal remains one of Turkey’s major energy sources, thwarting its ability to decrease its carbon emissions. Turkey’s domestic coal industry is highly subsidized in order to reduce natural gas imports. Lignite, the least energy-dense and most polluting form of coal, predominates. Coal production surged from 2015 to 2019 but has declined since then. To meet the country’s growing demand, imports have surged in recent years. The war in Ukraine, however, has disrupted supplies and increased costs, generating economic hardship. Particularly hard hit is Turkey’s large and energy-intensive cement industry. CemNet reported in March 2022 that the Turkish cement industry was facing an “imminent crisis.”  In 2014, Turkey was the world’s fifth largest cement producer, following only China, India, the United States, and Iran.

Turkey has made relatively modest investments in renewable energy. Hydropower has long provided roughly 20 percent of its electricity, but recent droughts have reduced the supply. Turkey’s has good climatological potential for solar and wind, and wind power is now growing, providing about 10 percent of the country’s electricity. In 2021 the energy think tank Ember reported that “it is now cheaper to build new wind or solar for power generation in Turkey than running even the most efficient hard coal power plant that relies on coal imports.” Ember’s analysts thus foresee an accelerating transition to renewable power, with a “win-win-win situation” resulting in “lower import bills, lower emissions, [and a] lower carbon levy by the EU.” Such hopes may be overstated. Energy intermittency and the lack of economically feasible storage still poses a major obstacle to solar and wind energy development in Turkey – as in the rest of the world.

Famine in Ethiopia and the Enset Solution in the Southern Highlands

Ethiopia is a notoriously drought and famine plagued country. Although the western highlands receive abundant precipitation, the densely populated eastern highlands are much drier. Almost all the precipitation that this area receives falls in a brief window during the summer. When summer rains are inadequate, as they frequently are, famine typically results. Ethiopia’s most densely populated areas are in the southern highlands, an ethnolinguistically diverse area that has long been both politically and economically marginalized. Despite its rapid economic growth since 2003, Ethiopia is still a very poor country, and the southern highlands is one of its poorer areas. One would therefore expect it to be particularly vulnerable to famine.

Yet despite all of these disadvantages, the southern highlands are much less prone to famine than Ethiopia’s core zone in the northern and central highlands. The answer to the seeming paradox is simple, found in the area’s staple crop. The people of the northern and central highlands subsist largely on grain, which is highly vulnerable to dry weather during the growing season. Those of the southern highlands, in contrast, subsist largely on enset, which is far more resilient. This crop, unique to Ethiopia, is a close relative of bananas and plantains. It is not cultivated for its fruit, however, but rather for its carbohydrate-rich leaf sheaths and corms.

            The advantages of enste are nicely explained in a recent article entitled “Enset in Ethiopia: A Poorly Characterized But Resilient Starch Staple.” As the authors write:

Enset has historically been ascribed as a ‘tree against hunger’ (Brandt et al., 1997), due to the domesticated plant having important attributes that support the food security of communities that cultivate it. These attributes were evident during the devastating famines of the 1980s, where enset-growing communities reported little-to-no food insecurity (Dessalegn, 1995). Most significant is the apparent ability of enset to withstand environmental stress, including periods of drought (Quinlan et al., 2015). Enset can also be harvested at any time of the year and at any stage over several years (including when it is immature), and enset-derived starch can also be stored for long periods (Birmeta, 2004). Enset also provides fibres, medicines, animal fodder and packaging material (Brandt et al., 1997). It stabilizes soils and microclimates (Abate et al., 1996) and is culturally significant (Kanshie, 2002Negash and Niehof, 2004Tewodros and Tesfaye, 2014). Enset has a complex management system supported by extensive ethnobotanical knowledge (Borrell et al., unpubl. res.). In a comparison of starch crops, enset has been reported to produce the highest yield per hectare in Ethiopia (Tsegaye and Struik, 2001Kanshie, 2002) with relatively low inputs and management requirements. Enset therefore has the ability to support a larger population per unit area than regions relying on growing cereals (Yirgu, 2016). As a result of these qualities, enset farming provides a long-term, sustainable food supply capable of buffering not only seasonal and periodic food deficits, with minimum off-farm input, but also demonstrates potential that exceeds its current utilization in South-West Ethiopia.

Enset could be cultivated in many tropical areas. If it were to spread, food security could be significantly enhanced in some very poor and marginalized areas. Unfortunately, most international agricultural research has focused on a handful of crops, particularly wheat, rice, and corn (maize). If more attention could be given to highly productive minor crops such as enset, major benefits could probably be gained.

William: Not Just Prince of Wales But Also Duke of Cornwall

Now that Charles has become king, Prince William has become Prince of Wales. That title is customarily given to the heir apparent by the reigning monarch. The day after he became King, Charles bestowed the title on his eldest son. The position is not without controversy. Thousands of Welsh people have signed a petition calling for the abolition of the title, which they see as an insult to Welsh national and historical identity. Many want much more than that: the independence of Wales. In late September, an estimated 10,000 people marched for Welsh sovereignty in Cardiff.

Public opinion polls, however, show that only around a quarter of Welsh people want independence, a much lower figure than that found in Scotland. Another poll found that 55 percent of the Welsh people also approve of the seemingly antiquated title of the royal heir, “Prince of Wales.” But Wales is not doing well economically and is now one of the poorest parts of the United Kingdom. As a result, the desire for Welsh independence does seem to be growing. As Welsh journalist Will Hayward recently argued:

Most [independence] supporters have simply looked at the state of the United Kingdom, seen that it isn’t working for Wales, and view independence as the most effective vehicle for fixing Wales’s problems. That doesn’t mean independence necessarily is the answer, just that the status quo is leaving the country both impoverished and unable to fix [its] problems…

“Prince of Wales” is not the only title held by William. When Charles became king, William automatically became Duke of Cornwall. Although the former is the more illustrious title, the latter is in some ways more consequential. Being Duke of Cornwall does not give any power over Cornwall, but it does bring financial rewards. This Dutchy controls landholdings of some 135,000 acres (55,000 hectares) as well as a portfolio of financial assets. All told, it is worth about $1.3 billion. In 2021, it provided Prince (and Duke) Charles with an income of some $25 million.

The land holdings of the Dutchy of Cornwall are not actually concentrated in Cornwall, the historical county located in far southwestern England. As is typical of such premodern and essentially feudal holdovers, they are widely scattered. Roughly half of the estate is located in Dartmoor, a scenic low plateau located in Devon, the county just to the east of Cornwall. Most of Dartmoor is administered as a national park. Unlike national parks in the United States, those of the UK include considerable private properties. But, also unlike in the United States, private land holders in the UK are not always allowed to exclude the public from enjoying their lands.


Economic and Class Factors in the 2022 Italian Election

Historically, leftwing political parties and movements have championed the working class and, in turn, have received its support. But as cultural and social issues have increased in importance, this connection has weakened and now seems to be disappearing. In Europe, concerns about immigration and European integration have also pushed working-class voters from the political left to the right.

Such dynamics were clearly evident in the 2022 Italian election. As the graph posted above shows, the most left-leaning of the major Italian parties, the Greens and Left Alliance, found the bulk of its support in the higher income quintiles. The Democratic Party, the heart of the left coalition, did poorly with lower-income voters. Higher-income voters were much more inclined than low-income voters to support the pro-EU, centrist “Action/Viva Italia” alliance. The one left-leaning party to gain most of its support from the working class was the neo-populist Five Star Movement. But while the Five Star Movement supports economic redistribution and many other leftist policies, it is also hostile to immigration and suspicious of the European Union. As a result, it has sometimes been shunned by the other left-leaning parties.

Parties belonging to the victorious rightwing coalition received a significant amount of support from the working class. Giorgia Meloni’s right-populist (or national conservative, sometimes deemed post-fascist) Brothers of Italy did well across the income spectrum but appealed most strongly to those in the lower-middle income quintile. Surprisingly, Silvio Berlusconi’s Forza, an establishment oriented, pro-business party, did best among those in the lowest quintile. Matteo Salvini’s populist and regionalist/federalist Lega party also had slightly higher support among lower-income voters.

Patterns of economic geography are less visible in the Italian election returns of 2022. As can be seen on the map of multi-member electoral constituencies posted above, the left-populist Five Star Movement received most of its support in the south, which is by far the poorest part of Italy. In northern Italy, however, no economic correlations are apparent. The three richest provinces of Italy, as assessed by per capita GDP in 2019 (see the map posted below), supported different parties. Bologna gave most its votes to the leftwing coalition, as it always does. Monza and Brianza, just north of Milan, supported the rightwing coalition, as it generally does. In the far north, the Autonomous Province of Bolzano (or South Tyrol) supported its own regionalist party, as it almost always does. South Tyrol is very distinctive from the rest of Italy, mostly because more than half of its people speak German as their first language.

  

Urbanization, Economic Productivity, and the Industrial Revolution

Levels of urbanization and levels of economic development roughly correlate. As can be seen on the paired maps, countries with very low levels of urbanization tend to have low levels of economic productivity (as measured by per capita GDP in Purchasing Power Parity). Burundi, for example, has the world’s second lowest urbanization rate (13.7 in 2020) and the lowest level of per capita GDP ($856 in 2022). Conversely, Singapore is completely urbanized and has the world’s second highest level of per capita GDP ($98,526 in 2022). The linkage is strong enough that urbanization is sometimes used as a proxy for economic development, especially for earlier time periods. Consider, for example, this passage from a recent study published by the Hoover Institution at Stanford University:

We find that a vector of exogenous factors that were binding constraints on food production, transport, and storage within the densely populated nuclei from which nation states later emerged account for 63 percent of the cross-country variance in per capita GDP today. Importantly, this vector accounts for progressively less of the variance in economic development (as measured by urbanization ratios) going back in time. [emphasis added]

 

This maneuver is understandable, but its validity is questionable. Historical urbanization rates are difficult to determine, and the figures produced are often controversial. Even today, measuring urbanization is often tricky, due mainly to variations in the population-size and population-density thresholds for urban standing. More important, the correlation between urbanization and economic development is not particularly strong. Some primarily rural countries have moderately high levels of developmental, while some primarily urban countries have low levels. One finds such deviations at both the top and bottom of the urbanization spectrum. Germany, for example, is more than twice as economically productive as Argentina, but is significantly less urbanized. Sri Lanka is (or was, in 2020) is almost six times more economically productive than The Gambia, but is far less urbanized.

Non-urban areas can be very economically productive, especially if they have relatively high population density, good transportation networks, and proximity to larger markets. Britain’s industrial revolution itself began in rural landscapes. Although maps of the industrial revolution usually emphasize coal and iron ore deposits, industrialization was originally dependent on hydropower, which requires abundant precipitation and significant drops in elevation. Areas around the Pennine Chain, the “backbone of England,” were thus selected for the first mechanized mills, despite their lack of urban infrastructure. The first modern factory, a water-powered cotton spinning mill, was built in the village of Cromford in Derbyshire, England in 1771; others quickly followed elsewhere in the Derwent Valley. Factory owners had to build housing for their workers due to the region’s rural nature. Despite its early economic productivity, Cromford never urbanized, and today has fewer than 2,000 residents

 

 

As industrialization proceeded and coal supplanted hydropower, small and mid-sized towns in northern and central England transformed into major cities. Proximity to markets and ports allowed the factories of Lancashire to supplant those of Derbyshire, and by the second half of the nineteenth century the water-powered mills of the Derwent Valley were mostly abandoned. Today the area is a world heritage site, commemorating the industrial revolution. Currently, hydropower is being restored to make the site more economically sustainable. On August 1 of this year, the BBC reported that :

 

 

Hydroelectric power is due to return to a textile mill which helped spark the industrial revolution.

Cromford Mill in Derbyshire – built in 1771 by Sir Richard Arkwright – was the world’s first successful water-powered cotton spinning mill.

The Arkwright Society has secured a total of £330,000 from Severn Trent Water and Derbyshire County Council.

Work is due start in September with the aim of being fully operational by June 2023.

The project will involve reinstating a waterwheel and installing a 20kW hydro-turbine to power the buildings…