Economic Geography

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

Economic Geography of the Republic of Georgia, Part 1

Article-Grid, Economic Geography, The Caucasus / By

(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

Article-Grid, Economic Geography, Sub-Saharan Africa / By

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

Article-Grid, Atlas of Human Development, Economic Geography, South Asia / By

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.

Article-Grid, Economic Geography, South Asia / By

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

cannabis, Economic Geography, Elections, North America / By

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

Article-Grid, Economic Geography, Energy, Russia, Ukraine, and Caucasus, Southwest Asia and North Africa / By

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

Article-Grid, Cultural Geography, Economic Geography, Sub-Saharan Africa / By

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, 2002; Negash and Niehof, 2004; Tewodros 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, 2001; Kanshie, 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

Article-Grid, Economic Geography, Europe, Protest Movements / By

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

Article-Grid, Economic Geography, Elections, Europe / By

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

Article-Grid, Economic Geography, Energy, Population Geography / By

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…

Cross-Class Connectedness in the Pacific Northwest and the Proposed State of Jefferson

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On the map of “Economic Connectedness of Low-Socioeconomic-Status Individuals by County” (see the post of August 11), the Pacific Northwest appears as a highly variegated zone. Counties in Washington, Oregon, and Northern California range from the highest to the lowest category, with few obvious spatial patterns.

 

 

 

But as is true in the northern Rockies and northern Great Plains, ethnic differences underlay many of these county-level disparities. Counties with large numbers of relatively poor Hispanic farmworkers generally rank low, indicating a lack of connections across ethnic and economic lines. In agricultural southeastern Washington, counties dominated by highly mechanized dryland grain farming, such as Whitman, rank high, whereas as those dominated by more labor-intensive irrigated crops, such as neighboring Adams, rank low. Whitman’s elevated standing also reflects the presence of Washington State University. Across the country, counties with major universities tend to have relatively large numbers of cross-class friendships.

Across a sizable area of southwestern Oregon and far northern California, however, both ethnic/racial diversity and the level of economic connectedness is low. On both scores, this region looks more like southern and central Appalachia than other parts of the Pacific Northwest. As the first set of triplicate maps shows, this region has a moderate level of economic differentiation (GINI Coefficient), a relatively low level of per capita GDP, and a relatively low level of income in its top economic tier. Here as well, county-rankings in southwestern Oregon and far northern California are not dissimilar to those of central Appalachia. As the next map series shows, the region is heavily Republican-voting – although it is not as Trump-inclined as West Virginia. It also has a large percentage of people over age 65. It deviates most sharply from central Appalachia in its relatively high percentage of people with high-school diplomas.

 

 

 

Although Oregon is conventionally divided east-by-west, in the western part of the state the north/south divide is equally important. Although the fertile Willamette Valley in the northwest was settled heavily by New Englanders, most of the rest of western Oregon was substantially settled by people from the upper south. Many rural areas still have an Appalachian feel.

Not coincidentally, the low-connectedness region of southwestern Oregon and far northern California forms the core of the controversial proposed state of Jefferson, which has received local support for decades. Proponents argue that their largely rural and relatively remote region has been ignored – and bullied – by the state governments of Oregon and California. Intriguingly, Wikipedia’s article on the State of Jefferson pushes its would-be borders farther to the south than has been the norm, including even Mendocino County. Although Mendocino may have a local Jefferson movement, it receives little support. As the precinct-level electoral map of the county shows, Mendocino is distinctly blue (Democratic Party voting). As a result, most of its residents want nothing to do with the populist right-wing Jefferson movement.

Mapping Cross-Class Social Connectedness

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A new map by Harvard economist Raj Chetty and his associates has been getting a lot of attention. The map, based on a massive array of data, shows the share of friends among people below median in socioeconomic status who are above median in socioeconomic status. (See this short article for a more complete explanation; also here and here.) The conclusion of the study is simple: “Children who grow up in communities with more cross-class interaction are much more likely to rise out of poverty.” The counties in blue on the map thus have more favorable conditions for the upward mobility of the poor; those in red, more unfavorable.

Some of the spatial patterns seen on the map are stark. The socioeconomic connectedness of lower-level individuals is low across most of the southern third of the country, with the exception of much of central Texas and Oklahoma. Anomalously high-connectedness counties within this low-connectedness zone are generally suburban to some extent (for example, Williamson County in Tennessee, just south of Nashville’s Davidson county). But even many affluent suburban counties in this “greater south” post below average levels, including Ventura and Santa Barbara in southern California.

A corridor of high socio-economic connectedness extends from central Virginia to southern Maine (excluding the Delmarva Peninsula and southernmost New Jersey). This region is highly urbanized, with many major cities. Anomalously low-connectedness counties within this high-connectedness zone generally contain cities with relatively poor urban cores, such as Springfield, Massachusetts in Hampden County. The several counties of New York City all rank relatively low; only Richmond County (Staten Island) appears in a shade of blue. Intriguingly, the suburban counties around Washington DC and Philadelphia rank higher than those near New York.

A much larger although less populous area of high socio-economic connectedness is found the north-center-west portion of the country, centered on the western Great Lakes, northern Great Plains, and northern Rockies regions. This is, contrastingly, a largely rural and mostly agricultural area, although it does contain a few major cities, including Denver and Minneapolis-St. Paul. Anomalously low-connectedness countries within this high-connectedness macro-region generally contain large Native American or Hispanic populations.

To a certain extent, the patterns found on this map replicate those found on a map of per capita income. The main reason is simple: poorer people living in rich countries meet relatively high socioeconomic status people far more often than do poor people living in poor countries. But there are many exceptions to this crude generalization. Several wealthy counties in southern Florida and southern California, for example, have low rates of cross-class connectivity. In contrast, much of Kentucky and southern Indiana have higher rates of connectivity than might be expected based on their socioeconomic characteristics.

In many parts of the county, the closest connection with class connectivity seems to be educational levels. This point is illustrated by blocking off roughly the same “north-center-west” macro-region on Chetty’s map and on a map of the percentage of people with high school diplomas. But again, the correlation does not hold everywhere. The paired Kentucky maps, for example, do show a general correlation between education and connectivity, but several counties, such as Grayson, have low numbers of high-school-educated residents but healthy levels of cross-class friendship.

 

 

 

 

 

 

 

 

 

 

 

 

In the United States as a whole, the map of cross-class friendships correlates poorly with race. The “whitest” American countries have some of the highest and some of the lowest levels of connectivity. Overall, however, Black, Hispanic, and Native American areas rank low on Chetty’s map. And in “north-center-west” zone of high connectivity, race/ethnicity seems to be the crucial variable. As the four juxtaposed maps showing the region where Minnesota, Iowa, South Dakota, and Nebraska converge illustrate, counties with large Hispanic and Native American populations have much lower rates of cross-class friendship than those dominated by Euro-Americans. Many of the counties in this part of the country that have large Hispanic populations are the sites of major meat-packing facilities. Workers in these plants tend to be socially isolated from the surrounding community. In early 2020, COVID-19 outbreaks were often particularly severe in these areas. As the Minnesota Department of Health noted:

In April 2020, early on in the COVID-19 pandemic, a COVID-19 outbreak temporarily shut down the JBS pork plant in Worthington, Minnesota [in Nobles County]. Employees at this pork plant identify as Hispanic or Latinx, African, or Asian immigrants, communities that have been hardest hit by COVID-19 due to many systemic barriers and challenges. Over 600 employees tested positive, leaving the small community in Nobles County with a ripple effect that was incalculable at the time.

   In tomorrow’s post, we will look at socioeconomic connectivity in the Pacific Northwest.

The Income of the One Percent Across the United States (and in Montana)

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I was anticipating that yesterday’s post would conclude the current series on county-level maps of the United States, with a focus on Montana, but I came across another fascinating map that cannot be ignored. Posted on the graphics-rich Visual Capitalist webpage, this map shows the average annual income of the top one percent of residents in each U.S. county. The map, however, does have problems; note how much of California’s Bay Area – a place where the elite tend be very wealthy indeed – has been oddly erased.

Most of the patterns evident on this map are not all that surprising. But it is interesting to see the huge variations in the income level of the “one percent” at the county scale. The callouts, which point to the counties with the highest income levels, are useful. Note how the figure found in Teton County, Wyoming – the site of Jackson Hole – dwarfs all others. Many other Wyoming counties also rank quite high, yet Wyoming still has the third lowest level of income inequality in the country (as reflected in its  GINI Coefficient). I have a difficult time understanding why Wyoming, a wealthy state with an abundance of natural beauty, has avoided the recent population surge that has occurred in neighboring Idaho, Utah, Colorado and Montana. In 1980, the state had a mere 469,557 residents; in 2020, the number had increased only to 576,851.

Several other natural-amenity counties in the West are also near the top of the chart, including Summit County, Utah (Park City); Blaine County, Idaho (Sun Valley); and Pitkin County, Colorado (Aspen). (As its Wikipedia article notes, when “measured by mean income of the top 5% of earners, [Pitkin] is the wealthiest U.S. county.) A more surprising listing is Douglas County, Nevada, located just east of the Sierra Nevada crest. Scenic Douglas has seen rapid growth over recent decades, surging from fewer than 7,000 residents in 1970 to almost 50,000 in 2020. Many of its newcomers are wealthy former California residents seeking a low-tax haven.

Quite a few sparsely populated counties fall into the top tiers on this map despite having few natural or culturally amenities. Many are in energy-producing areas, but others are largely agricultural. Across the Great Plains, figures very widely. South Dakota, for example, has several counties in the second-highest tier and several in the lowest. Union County SD, with fewer than 17,000 residents, posts an elevated figure of 4.1 million. Also in the top tier is Minnehaha, two counties to the north. Minnehaha contains booming Sioux Falls, South Dakota’s largest city (population 197,000). Sioux Falls has emerged as an important financial hub, particularly for credit-card companies, owing largely to South Dakota’s relaxed usury laws. South Dakota’s extraordinarily relaxed residency and taxation laws help explain its other centers of wealth. As the South Dakota Residency Center webpage notes:

Unlike many states in the Union, which don’t make being a full-time traveler easy, South Dakota welcomes full-time travelers to its ranks. Here are some of our favorite reasons why South Dakota has become one of the most popular places for travelers to establish residency.

We don’t have state income tax, pension tax, personal property tax, or inheritance tax. 

That’s right, South Dakota is one of the lowest taxed states in the country! When you consider all the different types of taxes, South Dakota comes in well below the average. Plus, you can’t beat the 0% personal income tax.

With only 24 hours of actually being in the state, you can become a resident for at least five years before you’ll need to renew your driver’s license again.

It’s easy to license and register your vehicle.

Not only are our fees for licensing and registration low, but you can also complete your license and registration remotely. That means you don’t have to make a special trip to the state whenever you need to update your registration or register a new vehicle. Plus, you don’t have to undergo yearly vehicle inspections.

 

Most counties in the upper-interior south post relatively low income levels for their top earners. Although levels are somewhat higher in Kentucky’s storied Bluegrass region, noted for its horse breeding operations, none of its counties make the top tiers. In the Ozarks, one county does rank very high: Benton County, Arkansas, in the extreme northwestern corner of the state. Not coincidentally, Benton is the home of several major corporations: Walmart, JB Hunt Transport Services, Tyson Foods, and Simmons Foods. Unlike the rest of the state, northwestern Arkansas has been booming over the past few decades.

I find the Montana map of high earners quite surprising. The dark blue counties along the state’s eastern border are energy producers, and are thus expected to fall into a high category. But Powder River County is in a very low category even though its GINI Coefficient (see yesterday’s post) is very high and its poverty rate is moderately low. I am not sure how these figures could add up. I also find it mystifying that Gallatin County (Bozeman) would not make the top tier, and would be exceeded by Missoula County. The level of wealth among the rich people of Bozeman – and especially of Big Sky – is staggering. If the map is indeed accurate, I can only conclude that most of Gallatin’s wealthiest property owners maintain their official residences in other states. (South Dakota, perhaps?)

In conclusion to this series, I would like to thank William and Linda Wyckoff, who have been my mentors in the geography of Montana. Invaluable lessons have been given in fieldtrips and brew-pub conversations. Bill’s knowledge of the American West is unparalleled. I strongly recommend all of his books, but would like to draw special attention to How to Read the American West: A Field Guide. As noted on the book’s Amazon page:

From deserts to ghost towns, from national forests to California bungalows, many of the features of the western American landscape are well known to residents and travelers alike. But in How to Read the American West, William Wyckoff introduces readers anew to these familiar landscapes. A geographer and an accomplished photographer, Wyckoff offers a fresh perspective on the natural and human history of the American West and encourages readers to discover that history has shaped the places where people live, work, and visit.

Economic Disparities in Montana (and the Rest of the United States)

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Although out-of-date and without a numerical scale, Wikipedia’s map of per capita income in the United States reveals some interesting patterns. As would be expected, income levels are high in major metropolitical areas (particularly in their suburban countries) and across the northeastern corridor extending from southern Maine to central Virginia. Western amenity counties also stand out, particularly Blaine County, Idaho, home of the Sun Valley ski resort. Many energy-producing counties also rank high, as can be seen most clearly in western North Dakota. North Dakota as a whole also ranks high, as does Wyoming. Agricultural counties in the northwestern Midwest tend to have higher per capita income levels than those further to the east; compare, for example, Iowa and Indiana. Low income levels are concentrated in rural counties in the South and in agricultural counties in the West that are home to large numbers of farm workers. Most counties with large Native American reservations also rank low.

The Montana map of per capita income yields some surprises. In 2014, Gallatin County, now the state’s center of wealth, ranked only in the second tier, with several lightly populated rural countries in the southwest and northeast falling in a higher slot. Relatively large payrolls from mining operations help explain some of these seeming discrepancies. The high figure posted for Jefferson County, located to the northwest of Gallatin, may be connected to its Golden Sunlight gold mine. High income levels in northeast Montana might be linked to the oil economy of western North Dakota. Still, to find Daniels County, ranked as the most rural county in the U.S. in 2000, in the top tier is surprising. Low income levels in Montana are concentrated in counties with large American Indian populations. Many rural counties in the Great Plains also rank relatively low. Overall, Montana is characterized by large gaps among its 56 counties.

The maps of median household income are similar to those of per capita income, but with some interesting differences. Much of Utah, for example, ranks higher on the former map than on the latter, reflecting the state’s relatively large families. The oil-rich Permian Basin of west Texas stands out clearly on the national map. In Montana, Stillwater County in the south-center surprisingly falls in the top tier. The Stillwater and East Boulder platinum and palladium mines, with a workforce of almost 3,000, probably plays a major role here. These mining operations are also carried out in neighboring Sweetgrass County, which, as we shall see below, has the state’s lowest poverty rate.

County-level per capita GDP maps are often misleading, as a single facility can make a lightly populated county look wealthier than it actually it. Several high per-capita-GDP rural oddities on the national map reflect productive mining and energy-drilling operations. Eureka Country Nevada, prominent on this map, is the site of the Mt. Hope Molybdenum Project, which contains “one of the world’s biggest and highest-grade molybdenum deposits.” In Montana, Rosebud County, the site of major coal-mining and power-generation operations, stands out. Rosebud does not, however, rank high on per capita income map, mostly because income levels are low on the Northern Cheyenne Reservation, mostly located in the county. Surprisingly, many western Montana countries rank quite low on this map, which is partly a reflection of their large number of retirees.

 

The patterns seen on poverty-rate maps are familiar, requiring little explanation. Montana counties range from the top to the bottom tier. Those with high levels of poverty all have major Native American communities. I was surprised that the poverty rate in Yellowstone County is as low as it is, as Billings has a reputation elsewhere in Montana as a rough town with relatively high crime and poverty rates. Note that in nearby Sweetgrass County the poverty rate falls below five percent

 

 

Finally, maps of the GINI Coefficient give a sense of income disparities. On the maps posted here, red coloration indicates relatively small income gaps while purple indicates relatively large ones. (If the GINI coefficient is “0,” all residents have the same income; if it is “1,” one person earns everything.) In the United States as a whole, the highest GINI figures are found in some of the richest states (New York, Connecticut, California) and in some of the poorest (Louisiana, Mississippi), while the lowest figures are found in the Western states of Utah, Idaho, and Wyoming. The LDS (Mormon) Church runs extensive economic programs for its members, which help account low GINI figures in Utah and Idaho.  County-level maps do not convey these GINI patterns very well, however, mostly because the largest gaps tend to be found in major cities that disappear in the county matrix.

In overall-terms, Montana  falls near the middle on the GINI rankings.It is not surprising that Madison County in southwest Montana has a strikingly high GINI figure. This particularly scenic rural county has been attracting high-income earners for several decades, driving up housing prices and forcing many local people out of the market. Why Powder River County in the southeast would post such a high figure is a bit of a mystery. But with only 1,694 residents, it would not take many high earners to skew the number upwards. On the Wikipedia’s list of notable residents of Powder River, three of the four persons noted gained their fame in rodeo competitions, but it seems unlikely that this would be a major factor in its GINI ranking. Owners of oil and gas leases are probably more important. It is interesting that the sparsely settled counties of eastern Montana post both high and low GINI figures.

Areas of Relatively High Human Development in Greater South Asia

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Today’s post continues the GeoCurrents series on the Human Development Index (HDI), focusing initially on greater South Asia. Here we look at areas with relatively high HDI figures.

For decades, the region’s highest human development levels have been found in the far south and southwest, specifically in the Indian states of Kerala and Goa and in Sri Lanka. All invested heavily in health and education, reaping substantial rewards. For decades, Kerala was well ahead of the rest of India, especially in female literacy. This patterns partly reflects the region’s social structure, which has long been less male dominated than most of the rest of India.

Sri Lanka has also long outpaced other parts of South Asia, but its edge has been steadily slipping. In 1990, Sri Lanka posted an HDI figure of .629, substantially ahead of Goa’s .552 and Kerala’s .544, and well ahead of Tamil Nadu’s .471. By 2019, Sri Lanka has advanced to .782, but it was now behind Kerala’s .790 and just ahead of Goa’s .761. At the time, Tamil Nadu’s HDI figure had surged to .708. Give Sri Lanka’s current political crisis and economic meltdown, it would not be surprising to see Tamil Nadu and several other Indian states overtake it in the next few years.

 

 

In northern India, the adjacent states of Punjab and Haryana, along with the National Capital Territory of New Delhi, exhibit relatively high HDI numbers, and have done so for decades. These two states are at the center of India’s agricultural “green revolution,” and are the site of substantial agro-industrial economic growth. Although neither Punjab nor Haryana top of the list agricultural production by Indian state, their relative productivity becomes apparent when population is factored in (see the chart posted here). These two states were also the hub of the massive 2020-2021 farmer protest movement that roiled India and caused its government to backtrack on planned prom-market agricultural reforms.

 

 

The neighboring state of Himachal Pradesh also exhibits a relatively high HDI figure, but the factors behind its development are distinctive. Whereas Punjab and Haryana are lowland states with fertile soils, Himachal Pradesh is a land of rugged topography, located in the Himalayan mountains and foothills. Its developmental ascent, moreover, has been much more recent. Through the 1960s, its indicators remained relatively low. A World Bank report credits its transformation on effective and non-corrupt political leadership, female empowerment, and mass electrification based on hydropower. Intriguingly, the population of Himachal Pradesh is overwhelmingly rural, with the state posting one of India’s lowest urbanization rates. In general, both in India and the world at large, low urbanization correlates with low social and economic development. This seeming paradox has received relatively little attention, and as a result it will be the subject of a future GeoCurrents post.

 

 

Higher than average HDI figures are posted across greater southwestern India. This large region has been the site of most of India’s recent industrial and financial expansion. As the next map shows, it is also contains almost all of India’s major tech hubs.

 

 

 

 

 

A far different situation is found in India’s far northeastern periphery. This is another rugged area that was long noted for its relative isolation, poorly developed infrastructure, and numerous ethnic insurgencies. Yet its human development indicators are now well above the average for the country. Many of the so-called tribal peoples of this region converted from animism to Christianity under the influence of missionaries during the colonial period, and three of its states (Nagaland, Mizoram, and Meghalaya) now have solid Christian (mostly Protestant) majorities. Missionaries stressed education, resulting in mass literacy. Women also have a relatively high social position in these societies, which are more culturally related to those of Southeast Asia than they are to those of South Asia. Recent infrastructural initiatives by the Indian and local governments, especially in electrification and road construction, have significantly improved economic conditions.

 

In neighboring Burma, several rugged and so-called tribal regions with Christian majorities or large minorities also post higher than expected HDI figures.