Religious Adherents: Bad Stripe Not Visible, But Is This Data Meaningful?

Found this map at Perell.com. Whenever I see cultural maps of the U.S. like this one, I look for the Bad Stripe, a coherent area that pops out as below-average in maps of human development indices. It stretches roughly from far western PA through West Virginia, Kentucky, and Tennessee across Arkansas and into Oklahoma (see more here.) My expectation would be higher religious belief across the Bad Stripe; or, at least, some pattern that makes the Bad Stripe stick out from surrounding areas. Not present at all; and typically, lower human development = more religious. Bad Stripe or not, there are some big surprises on this map, and it doesn't really align with both what most Americans would expect, as well as my own experience traveling and living in the country. West Virginia is much less religious than Western Pennsylvania? Really? Central California has a religious stripe across the middle? I've lived near both these places and find this hard to believe. The Frontier Strip is evident but the Rockies, especially to the north, are mostly less religious than other rural areas - also very suspicious is the similar level of religiousness between rural and coastal areas of Pacific states. If California is going to have religious and unreligious zones, they're more likely to run north and south parallel to the (liberal, likely less religious) coast.

One problem across all such surveys is that how one defines "religious" (or in this case "religious adherents") matters a great deal. Was it something like asking "How important is religion to you?" Or "Do you belong to a church?" Looking at this map, I strongly suspect it was the second, and that many people in some area (eg West Virginia) that do not belong or regularly attend services would say that religion is quite important to them. A place that happens to have a single large church would look very religious, whereas a place where people were very religious but did not have many churches would look very un-religious.

The Dialect of the Bad Stripe

The Bad Stripe as I've marked it out before (most recent here) is in many ways a boundary or transition zone between North and South, for example in social networks and religion. It turns out that it's a separate dialect zone too. The map can't be embedded well so click through to this dialect map of North American English, and you'll see that the Bad Stripe largely overlaps with the non-Texas part of the Inland South zone.

In many other systems (ecology and social networks) being at a phase transition is good, i.e. tidepools, savannas near jungles, being the only person who speaks both languages of two adjacent and relatively wealthy populations, etc. If the repeatedly observed "boundariness" of the Bad Stripe is not a coincidence or a historical accident, it could be that either the principle is reverse here, or that some aspects of the Bad Stripe are caused by the other negative conditions that previously obtained.

The Bad Stripe

I keep coming back to this region of the country: a strip running from West Virginia down the back (west side) of the Appalachians, through Kentucky and Tennessee, on through Arkansas to Oklahoma. I'm going to call it the Bad Stripe. Why? It's cloudier there, and people are less happy; and they also are about the only part of the country that voted Republican at higher rates in the 2008 race than they did in 2004. This is not an endorsement of one party or indictment of the other; but I would say, and I think self-described cultural conservatives would agree with me, that cultural conservatives are likely to be "angrier" than non-cultural-conservatives. Therefore, there are people are probably angrier in the more-Republican-2008-stripe than outside it.

The overlap is less exact here, but again the same Bad Stripe jumps out when looking at life expectancy. At first I thought that this map was just showing the Black Belt, but this graph is white male life expectancy:

It appears to be partly poverty, which shows patchy low-per-capita-income areas throughout that stripe.

(from HowStuffWorks)

But still: a) there are other poor parts of the country that are happier (southwest Texas) and b) many rural poor Western areas are both happier and healthier. The only thing that comes to mind is (say it with me) diet and exercise, the latter of which is much easier with the sun shining.

The Bad Stripe Continues: Overall Well-Being

In an overall well-being survey, the Bad Stripe that jumps off of maps of the U.S. of well-being, health indicators, and economics is again unfortunately represented.

Read more about the Bad Stripe here, here and here. Looking at the reverse of the map above, the photonegative of the Bad Stripe stands out in this map of frequent mental distress (Kentucky comes up worst.) In addition to the relations there, the Bad Stripe is also the boundary between three geographical social networks built by Facebook users, and it also tracks the boundary between Baptists and Methodists judging by geography-associated tags on the internet. It's tempting to speculate about the link between being a cultural boundary zone and an emotionally depressed area and what the causality might be.

That Geographic Facebook Map

...that's been making the rounds (original article here) is interesting because of the social boundaries it shows:


Two perennial questions I have about American demographic boundaries are reflected on this map:

1) Why the boundary between western Stayathomia and northern Greater Texas? Really this just revisits the Upper Midwest vs. Lower Midwest. Iowa and Minnesota are better educated, less religious, and have higher per capita incomes than Kansas and Oklahoma. Echoes of slavery are often raised, not unreasonably, as the source of many of the cultural differences between Northerners and Southerners - but that's really an argument for the Eastern Seaboard, since it was never well-established in Kansas or Oklahoma. So is the reason for this that settlers of the Upper Midwest came from the Northeast and settlers of OK and KS from the Old South or Texas? Something to do with crops there or the early discovery of oil and the subsequent impacts of those resources? The much larger Native American populations in Oklahoma and longer history of conflict in Kansas? I'm at a loss.

2) The boundary between Dixie and Stayathomia tracks the Bad Stripe fairly well. The Bad Stripe is an area of poverty and general unhappiness trending basically along the western side of the Appalachians from West Virginia down through eastern Kentucky and Tennessee, then trending west through Arkansas and to the edge of Oklahoma. (It's not just economics; for crying out loud even the weather is worse - it's cloudier there. Most recent article here). The Stripe first came to my attention when I noticed that people there voted more strongly GOP in the 2008 presidential election than they had in 2004. This could be a coincidence, or it could be that someone in North Carolina is unlikely to be friends with a lower-status, less-educated, less-happy person in Kentucky and Tennessee, and likewise somebody in Ohio, so the chance for a connection from OH to NC through the Stripe is low. (Sorry KY and TN, those are the unpleasant realities.) It's also interesting to ask whether there's a general problem with border regions, i.e. two regions of roughly equal parity have a region between them of lower parity. Is there a similar bad stripe between, say, northern and southern Japan, or northern and southern Germany?

The Bad Stripe as Boundary Zone

The Bad Stripe is an area of the U.S. running roughly east-to-west from West Virginia, through Kentucky and Tennesee to Arkansas and eastern Oklahoma. It is Bad because human development indicators, economics, and general indicators of flourishing and happiness are depressed there relative to the rest of the U.S. (Note: it is not just the Black Belt - it is considerably inland and upland of that.) This pattern frequently jumps out of maps of the U.S. showing demographic or economic data, and one thing that has become clear is that the Bad Stripe is a boundary zone between trade regions, religions, and now dialects (previous language boundary shown here). And here we see it again: witness the border of y'all, which runs right through the Bad Stripe.


By Joshua Katz at UNC, via Business Insider.

Bad Stripe Is Evident in More QOL Indicators

New as of 2023: southern half of the Appalachian part of the Bad Stripe doing better than than northern half (divider is basically along the TN/KY, VA/NC borders.)

The Bad Stripe is a section of the US that runs from extreme southwest Pennsylania along the Appalachians, turns west and decreases in intensity through western Kentucky and Tennessee, and extends through Arkansas and into eastern Oklahoma. As noted before, it consistently shows lower values for happiness and human development indices. For US demographics and geography buffs: it's not the Black Belt, which abuts it further southeast and closer to the coast. It is clearly, however, a cultural boundary zone between north and south - basically, from the southern shore of the Ohio River to the Deep South - and the part that extends west of the Mississippi may be a result of having been settled by Appalachians, since Americans have tended to in-migrate east-to-west. But the reasons for the Strip and whether it really has resulted from the same factors remains unclear.

Below are two maps from the several earlier articles showing the frequently re-emerging Bad Stripe: increased voting GOP for president in 2008 (bright red is 15% or more increase since 2004), and self-reported by congressional district, also 2008.





So it was with great interest that I read this Medium article ("The Origin of Populist Surges Everywhere", there's another more-intense-Republican-voting map, as well as these two: death by overdose (mostly opioids, i.e. pain meds) on top, and firearm suicides on the bottom - "diseases of despair", as the author calls them.

Obesity and the Bad Stripe

Maps here. Obesity splits into two bands in the eastern U.S.; one is the Bad Stripe and one is the Black Belt. I originally noticed the Bad Stripe when it shifted more Republican for president in the 2008 election (the opposite of the rest of the country) and then when the same shape continued to appear in maps of other indicators. My initial surprise about the Bad Stripe is that it was not the Black Belt, which can be clearly seen on the obesity map.

Per Capita Income and the Bad Stripe

The Bad Stripe runs southwest from extreme SW Pennsylvania through West Virgina, turning westward through Kentucky and part of Tennessee, crossing the Mississippi through the Ozarks and into eastern Oklahoma. As seen in previous posts about it, it sticks out as a more-or-less contiguous zone of low happiness and quality of life indicators which is a border zone between North/Midwest and South, and is thought of by many as Greater Appalachian (or the greater reach of the Border Reavers, if Albion's Seed is your bag.) Long ago I thought this was just an area of contiguous mountains and hills, hence low population density and slower development, but you can't say that about western Kentucky and Tennessee or eastern Oklahoma.

The county-level per capita income map shows a poorer area roughly paralleling the Bad stripe, along with some of the Black Belt to the south and east of the Southern fall line cities.

The Bad Stripe Continues: Human Development Index

The largest contiguous area (8 states) of lowest-category development index is found in the Bad Stripe, and this tracks many other health, education and economic indicators (play with the map and data yourself.) One very ineresting mismatch: violent crime per capita absolutely does not track the Bad Stripe. Neither does property crime.

Gini coefficient is highest in the southern U.S. and California. Guess: different causes for the South and California. In California it's ongoing immigration from a developing country, and in the South it's a holdover from agriculture. It would be interesting to see this same map, but only for people born in the U.S. California would probably blend into the rest of the country, and the South would remain. Thesis topic if it hasn't already been done: relationship between caste-system agrarianism and high Gini, two centuries later, in multiple countries (India, slavery areas in the U.S., Russia's serf system, etc.) Countries could serve as their own controls by comparing parts of the country with similar agrarian output but different caste traditions.

Other interesting trend: western states have more women legislators in their state legislatures than eastern states. This seems to be true regardless of whether the states are left- or right-leaning. Why? That these states were founded later when women's suffrage was a reality or close to it, and that value was fixed in political habits through the generations? In any event it seems less strange in light of this to contemplate that Wyoming was the first state which gave the franchise to women.

Sunlight and Happiness

Take an African animal and put it in Norway , or Seattle. Do you think it would be happy in that climate? But that's us. Growing up in Pennsylvania, I was familiar with the long summer days and long winter nights of temperate regions - but the week between Christmas and New Year, standing in Regent's Park in London during my first visit to the U.K., and looking at the tired glow of the sun through the clouds barely shoulder-high on the horizon at 11 in the morning - I started to realize why humans are so eager to to reduce their latitudes.

In the U.S., much of which is at sunnier latitudes, estimates of sufferers of clinical seasonal affect disorder or just winter blues run 10-15%. There are also claims that alcoholism correlates positively with latitude.

So I was not surprised when I looked at a sunshine map of the U.S., and saw a stripe of cloudiness along the Appalachians that matched (somewhat) with a portion of the unhappy stripe in a recent happiness survey:





The unhappy stretch extends from the west side of the Appalachians in Tennessee and Kentucky all the way through Arkansas and Oklahoma, which aren't as gloomy. I often point out to whiners in the Pacific Northwest that they aren't any cloudier than the poor folks in West Virginia and central/western PA.

Oddly enough, I noticed earlier that the unhappy stripe correlated even better with voting Republican for President in the 2008 U.S. elections.

The Bad Stripe and Sexual Curiosity

That's a heat map from okcupid showing the density of self-identified straight people who have had, or would like to have, a same-sex experience. Note the appearance of the Bad Stripe again: markedly less adventurous. Richard Florida has frequently shown positive correlations between economic growth, innovation as measured by number of patents, education and property values between gay-tolerant attitudes in cities and states, the assumption being that this reflects the post-scarcity values that promote innovation in a modern economy. (You can see the Bad Stripe jumping out at you again in this map, and others before it.) No surprise to most that West Virginia, Mississippi and Oklahoma are not the places to start your software company or make discoveries about yourself.

The Bad Stripe = "Greater Appalachia"

The Bad Stripe I've identified based on voting out of sync with the rest of the country and even the rest of their states, and a consistent cluster of low human development indicators - and it appears on Jayman's blog, more or less, as his Greater Appalachia. Is it because it's a boundary zone? Settled by Border Reivers?



Above: the yall zone, the border of which is basically the Bad Stripe. Note the correspondence with northern Greater Appalachia.

Dry Counties - Roughly Track the Bad Stripe

Above, map of dry counties in the US (Wiki.) Compare to one of many Bad Stripe maps, a map of Well-Being, below. This stripe pops out on various maps as a coherent region of the US ("Greater Appalachia") with various unique cultural characteristics and poor human development characteristics, here.

Happiness by State in the US, 2018

A study done by Wallethub (their image below) using their own 31-factor happiness index shows the Bad Stripe, along with a few other interesting patterns.


1) The Bad Stripe (West Virgina, Kentucky and Tennessee, Missouri, Arkansas, and Oklahoma) is evident as a negative outlier as usual. These make up 6 of the bottom 11. For fans of Albion's Seed, this is where the Reavers are, i.e. Greater Appalachia. This also shows the limitation of a state-level analysis. There is significant structure within the states. Pennsylvania's southwest if taken separately would very likely look like West Virginia. The southeast if taken separately would be much more like New York and New Jersey. Same thing for Missouri - the northern part of the state is likely more like the Upper Midwest, and the southern part is the Ozarks, part of the Bad Stripe and more like Arkansas.

2) The Upper Midwest and Utah stand out as positive outliers, as usual. Moynihan's Law - is it the result of Yankee settlers (again Albion's Seed), non-British Isles North European immigrants, or some combination? (Map below from Wiki on German Ancestry in the USA and Canada.)



3) Very interesting that two demographically similar states like the Carolinas could be so different in this rating. North Carolina has done better economically than South Carolina, and culturally does tend to move in sync with Virgina (perhaps most famously in the 2008 presidential election predicted by Nate Silver) - which makes sense because South Carolina was largely settled from Georgia initially, and North Carolina from Virginia. Still, they're not THAT different, and they have a very different happiness outcome.

4) I can't argue for similar historical links to the Reavers for Mississippi, Alabama and Louisiana, who as always fare very poorly. You'll have to develop your own theory for that!

Why Is the Frontier Strip Where It Is

Summary: Climate continues to have a profound impact on the distribution and economic activities of humans. There is a rapid population density decrease in the Frontier Strip states. Moving westward, there is a sharp increase in population when the Pacific coast is reached. This is usually attributed to difficulty of farming in the country's interior as the 100 W meridian is approached. I show here that this is not consistent with current agricultural productiveness of Frontier Strip and Pacific states on a per person or per area basis. I also show that in the Frontier Strip, temperature, precipitation and latitude are poor predictors of agricultural output but strong predictors of population density. Population density and agricultural output do not predict each other.

Since the 100 W theory of population density drop-off appears falsified, other explanations must be sought. The appearance of easier transportation during the settlement of the Frontier Strip, as well as the depression are explored and discarded. Further research with better agricultural output data and higher resolution climate data may support the hypothesis that investments in agricultural capital came too early in the Frontier Strip to benefit from irrigation technology, and that modern transportation and U.S. population preferences of climate as well as the coastal location of large population centers with service economies combine to keep the Frontier Strip the low-population boundary of the U.S. interior.



PART 1. I've written enough about the Bad Stripe recently so I thought I'd move to another grouping of U.S. states: the Frontier Strip. The Frontier Strip is the north-south line of states including the Dakotas, Nebraska, Kansas, Oklahoma and Texas, identified retrospectively in the 1890 census as having been the frontier in 1880. I've been interested in the idea ever since I visited Scottsbluff, Nebraska on a road trip two years ago. Like many places in the High Plains, Scottsbluff is proud of its pioneer heritage, although you have to ask how proud you want to be of being famous for being on the way to somewhere else. Inspection of a population density map of the U.S. shows that there is a dramatic drop-off as you move west across the Frontier Strip states, which never "recovers" until you hit the coastal cities of Washington, Oregon and California. The precipitation map is underneath it for comparison.

The geographers' conventional wisdom on this phenomenon involves the hundredth meridian west, which I've drawn in as a black stripe. It does seem to track just to the west of the density drop-off. The argument is that precipitation drops off to the west of this area, so agriculture becomes less productive. In earlier times economies were more strongly dependent on agriculture; consequently, large cities would not tend to develop in these dry regions and, even if they did, could not be supplied with food. Therefore further settlement coming from the East passed these areas and continued to the (contiguous) Pacific coast states. This argument also assumes that the potential agricultural productivity of an area has been realized by settlement and farming, i.e. it is at steady-state, and North Dakota's population isn't about to explode due to settlement by new farmers.

I've always found this argument dubious. First of all, most of these assumptions are not addressed explicitly in discussions of the 100 W boundary. But the most direct thing to do would be to look at agricultural output and see how it stacks up by state. Because states differ in population and size, we should look at output per person and per area. This information comes from the 2010 Census. There is not an obvious unit of "agricultural output" (if we include tobacco, none of the Frontier Strip or Pacific states will do very well) so I used combined receipts for the four principal products that the Census tracks by state (beef cattle, dairy products, corn and broiler chickens). Yes, wheat is an obvious omission but I couldn't find data for it by state, so it's possible these numbers are off by virtue of neglecting important crops.

So, if we have cause to doubt the traditional 100 W explanation, the Frontier Strip states should do the same or better than the Pacific states in agricultural output, meaning that it's not such a farm productivity death sentence to be near 100 W. Here's how the Frontier states and Pacific states stack up when ordered by agricultural value produced per-person.

State	Ag $/person
Nebraska	6,040
South Dakota	3,954
Kansas	2,846
North Dakota	2,091
Oklahoma	890
Oregon	590
Texas	451
Washington	286
Arizona	233
California	229

(I include Arizona because I'll use it later as an example.)

Before we get excited and declare 100 W theory dead, it should be noted that the above table probably isn't that interesting. We're looking at 2010 data, and even if California really is more productive than the Frontier states (as the traditional theory predicts), it might be masked in this table: states with large populations are likely to have higher proportions of people in other sectors, i.e. doing something other than agriculture. What really counts is the potential productivity of the land itself (owing to climate); that's the crux of the argument. So here's how they stack up when look at agricultural value produced per land area:

State	Ag $/Area
Nebraska	55,405
Kansas	38,319
California	21,154
Oklahoma	18,765
Texas	16,698
South Dakota	16,364
Washington	11,128
Oregon	9,080
North Dakota	7,598
Arizona	5,059

This doesn't look good for the 100 W theory. Yes, California is productive per land area, but still, if you're in Nebraska or Kansas, why go west? You're better off in the High Plains! There are possible explanations for this, besides the limited four-product index I'm using: a) The farming business has changed a lot over the past century and a half, and what used to be family-owned farms are now gigantic industrial facilities. So what makes Nebraska so productive now might not matter to people economically today (if it's all going to one or two corporations) or it might be different from conditions a century ago. b) You could also make the argument that dollars produced per area is a weak proxy indicator, because the land isn't being used for valuable crops, because the value of crops has changed over time, or (least likely) the areas haven't reached steady state and are still being developed by settlers agriculturally.


Additional point: agricultural productivity cannot depend entirely on precipitation, i.e. on proximity to 100 W. Length of growing season has something to do with it as well, which as you might guess has a strong north-south trend. This map shows number of days below freezing:

That map is a little small so, if we can assume 1911 was typical, here's a larger map showing basically the same thing, the day of the last killing frost:



As it turns out, there is a north-south population density trend in the Frontier Strip. Looking further north to Canada, any semblance of a 100 W-population boundary disappears. In fact the population density along the country's southern border increases beyond 100 W, after having dropped off in Ontario well to the east. Again, black line is 100 W.

You might make several arguments to explain this: 1) The 100W boundary is in fact country-specific, due to different development policies, and/or 2) that as latitude increases, the strength of the association of precipitation becomes relatively weaker and latitude becomes stronger. (Who cares about number of days below freezing when you go from 30 to 50? Precipitation makes a bigger difference. But when you go from 120 to 140, latitude makes a bigger difference.) 3) The western part of Ontario isn't yet at steady state and its population will growin the future when settlers arrive to realize its agricultural potential, and the precipitation-driven east-west density gradient will assert itself.

Rather than speculate, I did linear regressions on the Frontier Strip and Frontier plus Pacific and Arizona, using latitude, rainfall (not including snow), days below freezing, average annual temperature, lowest average monthly low, highest average monthly high, and population density, and their correlation to agricultural dollars per area. Rather than take up space with a bunch of ugly scatter plots I made a table of R^2 values. This is exploratory so there's no fancy Bonferroni corrections going on, but in any event none are strong correlations.

	All	Frontier
Latitude	0.0077	0.0039
Rainfall	0.0205	0.1513
Frz Days	0.0986	0.0014
Ave Temp	0.0216	0.0003
Lowest Mnth Lo	0.1123	0.0004
Highest Mnth Hi	0.0006	0
Pop Dens	0.0358	0.0125

Since agricultural output is just a proxy for the original question we're concerned with (population density), I used that as the output and looked at the same factors. Wow. The R's are much stronger.

	All	Frontier
Latitude	0.1355	0.9463
Rainfall	0.0484	0.4844
Frz Days	0.5628	0.9773
Ave Temp	0.2918	0.9475
Lowest Mnth Lo	0.6001	0.9577
Highest Mnth Hi	0.0117	0.8587
Ag Output/Area	0.0358	0.0125

First: agricultural output and population density do not seem to be strongly related. Furthermore if rainfall is the reason 100 W is significant, it's interesting that rainfall is a much weaker predictor than temperature. These are both problems for the traditional 100 W theory.

Second, for the "inputs" with R's above 0.9, here's what they mean in terms of population density.

- For every day of the year where the temperature drops below freezing, the population density is lower by 0.197 people per square kilometer.

- For every degree lower the lowest monthly low is, the population density is lower by 0.863.

- For every degree the average annual temperature drops, the population density drops by 1.33.

- For every degree of latitude gained, the population density drops by 2.05.

It seems strange that there could be such a strong connection between climate and population but not agricultural output, especially in states where a huge fraction of the economy depends on agriculture. That connection could very well be concealed here by the limited set of agricultural products I'm considering. Really, what I should be using is climate and agriculture output data at the county level, and the agriculture data should be the value of all commercial livestock and crops. But I leave that to someone with access to real data and real software. It would also be interesting to crunch these numbers for every decade from 1850, and see how the R's and slopes for each of these change over time if at all. Maybe the weak predictiveness between climate factors and agricultural output is real, but it used to be much stronger.


PART 2. Other Possible Explanations

Explanation #1. The population drop-off is a result of timing, i.e. improvements in transportation and communication. Couldn't it just be that just as the Frontier Strip was getting settled, trains and telegraph lines were built? Finally, you could find out whether there were jobs in San Francisco, and you could get there. (Assuming that independent of mineral extraction revenues*, loss of population is equivalent to loss of economic growth, this is the root of productivity paradoxes that exist between areas with free movement of people and goods.

If this were the case, you would expect to see a shift westward from the Frontier Strip at least by the 1880s. The Transcontinental railroad was completed in 1869 and it was connected to Los Angeles in 1876. In fact this is not what we see. First, here are the population densities of all Frontier Strip states and Pacific coast states, and then the average density of both groups.

After the 1920s, the Pacific states never looked back. Among the Frontier states, Texas is by far the strongest performer, owing probably to a longer growing season, early discovery of mineral wealth, and ports to make transportation cheaper (though I suspect immigration from Mexico is also a contributor there; Texas Hispanics are 35.9% of the population, compared to 6.1% in neighboring Oklahoma and comparable or lower northward.) Furthermore, you can see there was a local optimum in every Frontier state except Texas sometime in the teens. I don't know of any events that would explain this drop, nor if people were heading further west. Bottom line, the fact that the drop happened so late argues against the railroads having been the contributor, and the roads weren't yet developed enough that cars could have been the explanation.

Initially I was also skeptical because of Arizona. Arizona is clearly not a state blessed with rainfall, and yet it had (and still has) a strong citrus growing industry (thanks to irrigation), and its population density passed the Frontier Strip's in the 1980s and is still growing. It's worth asking why irrigation doesn't also cause a sudden increase in the relatively wetter Frontier Strip's population; climate and sunshine preference are likely to play a part, and we could make a guess based on sources of internal immigration for Arizona. This would suggest that in some ways, transportation and information about local conditions do make a difference, but the precondition is that the area can't have been settled prior to modern irrigation technology (because capital commitments are made in the agricultural infrastructure), and it has to have sunlight. I think that the real explanation will have something to do with the random impact of the historical timing of technological progress, if not transportation, then commitment to pre-existing agricultural infrastructure, shifting of economic importance to other sectors, and population preferences that make a greater difference in more recent history due to increased mobility.

Explanation #2. The Okie Effect. Can farm abandonment and consolidation during the Depression and Dustbowl explain it? See graphs above. These economic/agricultural events may have contributed but the trend was already underway at least a decade earlier.

*I give the caveat about mineral wealth because Texas and to a lesser extent Oklahoma have big oil sectors that impact their populations. In addition, most of North Dakota's counties are losing population and the state is just barely growing but recent oil discoveries have made the state profitable. Research suggestion: to what degree can sub-national entities be subject to the resource curse? What institutions or cultural features are protective against resource-curse type damage to economies?

Physical Topography (of the American West) Associated with Human Personality

You can find the paper here. I have only read the abstract since there's a paywall. Questions: how does this correlate with the settlement patterns discussed in Albion's Seed, in this genetic analysis, or the Bad Stripe? (The Bad Stripe roughly correlates with Greater Appalachia in the former article, or the Border Reavers in Albion's Seed.)

Götz, F.M., Stieger, S., Gosling, S.D. et al. Physical topography is associated with human personality. Nat Hum Behav (2020). https://doi.org/10.1038/s41562-020-0930-x

Big Five Personality Traits, Outliers and Per Capita Income in the U.S.

I went back and played with the data from that survey of Big Five personality traits by state (the OCEAN traits) and the NYT has a neat gadget; data below from there. Per capita income data comes from the Census. Automatically you start thinking about correlations between the Big Five and other things like income.


- Big Five traits and per capita income.
- Interestingly the strongest correlation at the state level both in terms of goodness of fit and slope (strength of influence) in a linear model is an inverse one with conscientiousness. Want to make money? Be lazy! Who knows the causal relationship here if any, so I won't hand-wave. With an R^2 of 0.2646, the regression says the state's per capita rises $236.87 for every rank lower you go on the conscientiousness scale. You also get money for being disagreeable ($221.87 for every rank the state drops, R^2 = 0.2321), although you also get money for being open-minded ($182, R^2=0.1566). This is probably largely the Northeast talking, although it might be interesting to look at the correlation between education and openness.

- Combinations of Big Five traits by state. If you do scatterplots with each of the Big Five characteristics against the others, several states appear repeatedly as outliers at the "corners" of the scatter - DC is one and Alaska is another. The whole reason that the study which initially generated this data is interesting is because it shows that there actually is a geographical difference in personality types (whether that's because of memes or genes is another question entirely). But it stands to reason that if gene and/or culture flow can explain this, then we should see outliers at the geographical extremities. It also stands to reason that the outliers on the coasts won't necessarily be outliers in the same way. While the map of openness does bear a similarity to the Red/Blue presidential voting distribution, there is no other obvious correlation between other characteristics or states.

So I looked at the coastal states (those with a saltwater port) against the non-coastal states, excluding Hawaii and Alaska. If geographic extremes correlate with personality type "outliers", then the saltwater states (which are farther from each other) should also be more dissimilar to each other than the interior states. By my count there are 26 interior and 23 saltwater states, so all other things being equal, the saltwater states should look more similar to each other, since there are fewer of them.

Indeed, the standard deviations for 3 of the 5 big 5 are smaller for the interior. They're the same for the other 2. As far as the averages, the interior states are more extraverted, agreeable and conscientious than the coastal states. (Those first two are consistently a shock to me.) The noncoastal states are on average less neurotic and less open to new experiences and ideas.

- Combinations of Big Five traits by region. If you do scatterplots with combinations of Big Five scores by region, then the Northeast (DC to Maine) is frequently an outlier (conscientiousness vs neurotic, conscientiousness vs openness, consciousness vs extraversion; more on this in a bit). The contiguous Pacific states are a major outlier on agreeableness vs openness; otherwise they land near the other states in and west of the Rockies. The Frontier Strip lands with the Midwest and the Bad Stripe tends to sort with the South, except that it's much less open than other Southern states.

- Per capita income distribution and average, coastal vs. non-coastal. It's also worth pointing out that the per capita incomes of non-coastal states were a) more similar to each other than the coastal states' were and b) on average lower, by $5,128. This is not surprising, as land-locked countries also have lower per capitas than those with coastline. 2/3 of all Alpha and Beta cities are on saltwater (or a river delta leading into saltwater), so, par for the course.

Education Ratings by State

This is from Education Week. No Bad Stripe visible here, but the Northeast sure does stand out. Looks like those Puritans and Midlanders are doing something right! To ask this more provocatively: are educators demanding to find out what they're doing in the Northeast so we do it everywhere? If not, why not? (Not that genes and geography are destiny - I have no ready explanations for Wyoming and Idaho, aside from good and bad policy decisions respectively.)

Pennsylvania Economic Growth - Appalachia vs the Urban Northeast, Together in One State

There's a report out from Alter, Fuller, Sontheimer and Seigworth at Penn State, with good summary coverage by Jeff McGaw at the Reading Eagle. It shows how there are really two Pennsylvanias, economically speaking. While this isn't surprising, the degree and timing of the divergence is.

Besides being my home state, Pennsylvania might interest you because it's a swing state, which is in turn directly related to the mix of cultures and economies that comprise it. Pennsylvania is part Northeast/Mid-Atlantic, part inner Midwest/Rustbelt, and - often ignored, but quite important in these numbers - part Appalachia. Overall the state is lagging all of its Northeastern neighbors except for one (more on that in a second), because Pennsylvania's numbers are an average of two regions - the sucessful region (Philly and southeastern PA, which have done quite well after the 2008 recession) and then the rest of the state.

You can see the figures at the report and article, but here are two instructive maps. The top is the county-level 2016 presidential election data. On the bottom is (from Alter et al's article) county resident employment in the post-recession period 2008-2016. Even if you don't know PA geography, the resemblance is obvious.



[Added later: more here at this great Philly.com article, with better geographical resolution, returns in more kinds of races, and 2014-2018 comparison gadgets.]

It turns out the only state that Pennsylvania beats in the Northeast group is West Virginia. That's not a coincidence. The central-and-western PA counties have numbers that look remarkably similar to West Virginia's post-recession numbers in terms of jobs lost and unemployment, but when averaged with Philly and suburbs, these quite-bad numbers are obscured and you end up with one mediocre-looking state, instead of a very depressed large rural region, and a very successful metropolitan area. West Virginia comes across as struggling much more clearly, because it's the only state entirely within the Appalachians. (The Bad Stripe, a demographic region of bad quality-of-life and human development indicators, roughly corresponds to "Greater Appalachia" and does extend a bit into Pennsylvania.)



[Added later: Reddit user Anpanboy uploaded thisvmap of population growth 2018-19,whicu follows the economic growth pretty well.]

So these maps tell two stories. First, it's a cliche of campaign strategists and the cultural commentariat that Pennsylvania is "Philly on one end, Pittsburgh on the other, and Alabama in between." But that's not quite right. Pennsylvania is Appalachia, with Philly and suburbs in one corner. And remember all those angry unemployed coal miners we've heard so much about? They live in Appalachia. Second, the late 90s/early aughts began the renaissance of the Northeastern American city, and even the recession couldn't stop that positive momentum. The divergence you see in these numbers and maps of Pennsylvania is both these stories, playing out in the same state and hidden by being averaged together.

The problem is that coal has been dead in PA for decades, and many of the people demanding its return at this point have never even worked in the industry - more likely, their fathers did, and that's what they view as important valuable work. It's a cultural problem. We all know that coal is not coming back and that it has everything to do with changing technology and nothing to do with regulations, a narrative that people in this part of the country have a hard time accepting. (Abstract economic forces are much harder to viscerally hate than bad people hurting you by design.) What's worse, the big cities like Philly, filled with untrustworthy people unlike you, have come roaring back; worse still, this happened just as media became all-pervasive and started constantly reminding you that these people look down their noses at you. At least before, you might have been unemployed and living in Clearfield County, without being constantly reminded you were on the bottom of a status hierarchy that was exactly inverted, with the most immoral people at the top.[1]

The reality is, for all us blue-staters in the suburbs and cities, these numbers show you that even though your suburb might be getting better all the time, things really are bad out there in the hinterlands, and this is why they were so desperate for a change they voted for Trump. And they're going to vote for Trump again as long as we don't show some solidarity with our countrymen, instead of ignoring their problems or even dismissing them with active contempt,[2] which I admit I've been tempted to do myself. It may be taking a while for people to accept that coal is dead, but it's certainly not their fault. I don't have a clear policy prescription for how to help life get better in interior Pennsylvania, but taking people's problems seriously seems like a good place to start - which I deeply hope the Democrats can do in 2018 and 2020, or Trump will get re-elected.


[1] Many people called the 2008 recession a "man-cession", with men disproportionately hit relative to women. Nowhere was this more likely to be true than Pennsylvania, with effects lingering until today. Construction and construction-adjacent industries were propped up by capital flowing in from the cities, and now that those easy loans have dried up, construction isn't coming back either. This region is part of the "health belt", because it has an overabundance of older people, and the one source of capital coming into this region that has grown is Federal dollars in the form of Medicare disbursements. Therefore, many of the un- and under-employed men in the regions lost their construction-related jobs, and have wives working in nursing or other healthcare fields who became the breadwinners, a final slap in the face.

[2] More than once, both online and in person, I've seen urban and suburban centrists or liberals express sympathy for the plight of people in another country whose luck has gone south for economic reasons out of their control, e.g. when the local mineral deposit was played out; then in the same conversation, say about their fellow Americans (essentially): "Coal is dead, get over it losers." If Democrats want to win elections at some point, this attitude has to stop, because human beings are good at detecting contempt - especially human beings going through tough times - and they don't react well to it.

[3] Mountainous regions tend to be poorer than non-mountainous regions because it's hard to grow crops there - and the difficulty of agriculture means little opportunity for a service economy to develop on top of a farming and trading population. There are exceptions to the rule (e.g. Jackson, WY) but those are based on outside capital brought in by wealthy in-migrants or tourists in recent times. Out of curiosity I looked at Colorado to see if a similar relationship exists between election returns, economics and mountains, as in PA (the eastern half of CO is flat prairie and the western half is the Rockies.) Eyeballing it, there may be some pattern, but certainly not as clear as for PA. Speculatively, it could be that PA's mountains are smaller, and have been settled for (generations) longer, therefore producing an actual population that shows the impact of "bad mountain economies" - as opposed to CO, which has a much more thinly scattered population and may be more mobile relative to what resources there are. Concretely: a coal mine opens in the PA Appalachians in 1850 and a town grows up around it, which doesn't just evaporate when the mine is played out by 1970 - by this point the families have been there for generations, and the climate isn't so harsh, and leaving just isn't really considered. (Although counter to my theory, there are ghost towns in PA.) Versus CO, where an unobtainium mine opened in 1950, and today is just about played out - but the settlement around it is a high-turnover one of mostly youngish men who aren't living at 10,000 feet elevation for fun, and they clear out (or a few remain and develop the area for tourism, e.g. Leadville.)