Instrinsic Social Skills: Small Towns vs Big Cities

PART I. People from small towns find even setting foot in a big city scary - because you have so many more interactions with strangers, you're forced to make frequent decisions about the kind of relationship you're going to have with that person (even if it's for three seconds) and there is sometimes genuine conflict. You can split social interactions with strangers into three tiers.

Tier 1: ignoring strangers, avoiding eye contact, maybe slightly altering your direction of travel to avoid bumping into somebody. The default mode. Note that people in big cities are famous for sticking to this mode more often.

Tier 2: interactions where you acknowledge each other but that are largely ceremonial; e.g. asking someone at a restaurant if you can take a chair they're not using from their table. You'd be surprised by anything but a quick yes.

Tier 3: interacting with strangers in a situation where there are potential divergent interests to navigate, and negotiation and emotional-regulation (of both self and other party) are important; e.g., saying something when someone jumps the line, asking someone for their phone number, asking someone to move their car.


PART II. I had these reflections as I was walking back to my hotel from getting pizza on a Saturday night in Manhattan, categorizing types of social interactions (a very unlikely thing to do if you have innately high social intelligence) and realized that a place like New York does a big favor for people who do NOT have high social intelligence.

One of the things I pay attention to when I visit any big, dense city is the social perceptiveness and effectiveness of people living there. Do they read people well, and are they smoother? (How would you measure this? Not sure overall, but some proxy indicators: automatically understanding the intentions of people they interact with, rate at which they perceive new unspoken hierarchy structures, ability to defuse conflict.) My prediction would be that they're better at these things, because of practice, and they do seem to be a little bit better, but not dramatically so. (In truth, this is mostly based on my observations of New Yorkers, since differences between people in say Tokyo and a Japanese small town are to me as an American much harder to see than the same kinds differences between New York and rural Pennsylvania.)

But, there's a pretty large overlap between the social skill spectra of big cities and small towns, so that even in New York, you meet plenty of socially "slow" people. It's not dramatic, but it still always surprises me to meet a social laggard in New York, just like I'm surprised when I meet someone from Mexico who doesn't like spicy food (believe it or not, there are lots of these folks too.) All that said I'm certainly not the most innately socially intelligent person, but at this point in my life I've consciously learned a lot of tricks, much like someone who works around horses learns consciously how to read them and influence them. And the sheer volume of data a big city provides teaches many of the socially slow among us (like me) how to handle people almost as well as the innately gifted types can - that's the favor that big dense cities do.

The implication is that innately gifted people have a bigger advantage in a small town than they do in a place like New York. It's also worth pointing out that lots of other cognitive characteristics likely co-vary with innate social intelligence, and this may be part of what sorts people into "big city" types and "small town" types. If you're a socially smooth person in a small town, why go to New York? You lose part of your advantage. In a small town, the socially un-gifted have no chance to catch up with you - but in a place like New York, people like me can become almost as socially clever as you, just from social "Big Data" analysis.

Why No Dicussion of American Quilombos?

There's a rarely-told and barely-investigated history of escaped slave communities in the the southeast U.S. The significant groups are Black Seminoles (now relocated to Oklahoma and Texas), the Great Dismal Swamp maroons, and the Gullah community in South Carolina and lowland Georgia (much of which remains in the area, and which to some degree seems to have originated part of the two other populations). The Black Seminoles were closely associated with, but it seems still culturally distinct from, the other mostly native renegades who arrived in the swamps as they fled British and then American forces. These are immediately reminiscent of quilombos in Brazil, which were the same thing but along the Amazon and its tributaries.

These communities formed from escaped slaves; that is to say, from people who "suffered" from drapetomania (can you believe antebellum physicians diagnosed this condition after being asked to solve the great mystery of why slaves would try to escape?) Several things about this are striking; for example the understated influence of the Caribbean colonies on southeastern U.S. culture (listen to this Gullah speaker's accent when she's speaking English. She's a native-born South Carolinian!)



The question is why the quilombos seem to be a much more present part of Brazilian history than these communities are a part of American history. Both countries have a history of slavery; there must be something else associated with this difference.

U.S. City Population Growth and Location, 2010-2014

Statistics from the Wikipedia list of U.S. cities by population, with numbers for 2010 and 2014 for cities 100,000 and over. My analysis excludes Kent, WA and Macon, GA which had non-organic annexations.

Cities that gained population had, on average, 297,130 people. Cities that lost had, on average, 223,384 people. The smaller you are, the smaller you get. A scatter plot (log or absolute population) was not very informative, other than to show that the shrinking cities were all smaller. The largest city that lost population was (hold your breath) Detroit, which lost 33,522, or 4.7% over 4 years - that annualizes to 1.2% lost per year.

Cities of 100,000 or more added 4,099,428, a 5.02% growth rate for growing cities for 2010-2014 (annualized to 1.23%).1111


In the same period, cities of 100,000 or more lost 65,007, a -1.46% loss rate for shrinking cities for 2010-2014 (annualized to -0.366%).

This means on net, cities over 100,000 added a total of 4,034,421 people, for an overall growth rate of 4.68% (annualized to 1.15%).

Compare this, for the same period, to a US population growth of 3.28% (0.809% per year). Cities above 100,000 grew faster than the country as a whole.


The center of growth was at 36.232 N, 99.661 W (western Oklahoma).

The center of shrinking, on average, were at 38.145, 84.188 (suburbs of Lexington, KY). Not surprising that there's more growth to the west (and somewhat to the south).

Weighting it by % gain or loss, it doesn't move very much. The center of shrinking moves about 40 miles, and the center of growth moves less than that.

New World, Non-Malthusian Population More Determined by Historical Accident Than Climate

Above: the Frontier Strip - the westernmost U.S. states before the Rockies - contain the 100th meridian (bold vertical line in maps) which is often used a marker of low precipitation and therefore low agricultural productivity. The argument has been that the population therefore drops off to the west of this; but if that's the case, then why does Canada not follow the same pattern?



It is commonly believed that the population drop-off seen in the United States at the 100th parallel has to do with changes in rainfall and agricultural productivity as one moves west in North America. This article shows that this is probably not the case. It more likely has to do with historical accident - about the time Americans had expanded west to the 100th meridian, we started building trains, and people could move to the more pleasant climates of the West Coast. Note that the "population distribution is by historical accident" theory applies more to the New World than the Old, because of the introduction of intensive agriculture and lack of a Malthusian limit. Maybe over time, there will be a smoother population gradient - it would be easier to argue that with thousands of years of agriculture, longer-term Malthusian limited populations in Asia and Africa populations do reflect agricultural productivity, and therefore also rainfall and longitude-degrees from ocean.

Presumably the same applies to latitude, although for different reasons. Very high latitudes are not great places to grow food. Latitude is still going to be affected by geography (if you're near coastline at 25 degrees latitude, life is much more pleasant than if you're inland) - but the solar radiation remains constant so the effect of latitude is a little less subject to being obscured by the details of geography than longitude would be. (Note that there may be constraints on population growth other than calories that I'm completely neglecting; e.g., maybe agriculture at the equator is better than 30 degrees, but disease slows population growth once you drop below the 30s.)



Geography junkies have likely already seen maps like the one above showing population by latitude, and the assumption is that agriculture just produces more calories at certain latitudes (similar to the provincial precipitation distribution that obtains in North America and which was assumed to influence our own population distribution). But if we're trying to pull out first principles, absolute population doesn't help much - what if there's just a lot of land at certain latitudes? That doesn't tell us whether that latitude is good for agriculture and therefore modern humans, it tells us where the land is on Earth's surface. If your denominator for population density includes ocean, then it doesn't really tell us anything about the carrying capacity of land at that latitude. So population alone won't work - it needs to be population density.

And even just population density per latitude won't work - it has to be population density per actual land area found at that latitude. I couldn't find population density per land area data. Fortunately this Brookings Institute Paper quotes World Bank 1997 figures for land area and population in bands of 10 degrees latitude (see pp 49-51), and I back-calculated population density per actual land area at this level of granularity.



Thinking it might be interesting to see how things stack up when the northern and southern latitude bands are combined, I did so:



(There wasn't full data below 40s south or above 50s north, which means we can't even do 50s when we combine them, which non-ideally eliminates most of Europe.) The question that emerges is, what's wrong with you people in the 30s and 40s south? Up here on the correct side of the world we certainly seem to be able to get along alright in those latitudes. The lion's share of the land in the 30s and 40s south is to be found in the southern half of Australia, most of Argentina and Chile, and South Africa. These aren't bad places to live - note that this contains 3 of the world's 5 Mediterranean climate zones! Again, even trying to smooth things out, historical details matter. These are places where intensive agriculture was only introduced in the last few centuries by Europeans. And geographical details matter, even after using population density instead of population - Australia is an ancient craton with terrible soil, and Argentina is drier than it might otherwise be due to the rainshadow of the Andes. That said, in the Malthusian future, we should expect to see the Pampas filling up much like another Mediterranean climate zone (California) is filling up as we speak.

Finally, it's worth glancing at Malthusian long-term intensive agriculture countries, to see whether this holds up. I've put population density, precipitation and elevation next to each other. China's marked parallels are 40-30-20. India's are just 30-20. (10 crosses near the southern tip of the subcontinent.)





The precipitation relationship holds up better for India than for China, but both of them follow elevation. This may be more true in rice-farming areas than other grains. The relationship of population to elevation has been profitably studied elsewhere; there's a notable outgroup in the central Mexican plateau, where grains that enjoy dry conditions are grown and near to where agriculture began in North America.

Fully stated then, the theory can then be summarized as "Population distribution is strongly influenced by agriculture which in turn is determined by climate and therefore latitude, but a) until Malthusian limits are reached millennia after the introduction of intensive agriculture, distribution will be mostly by historical accident as in the New World and b) precipitation and especially elevation dramatically affect the distribution as well."

Wealth and Coastline, Part 2: The United States

Previously I showed that the average income in the set of 138 countries for which I had income data, countries that do have some saltwater coastline is $13,562, vs $9,040 for those with no coastline. This is not surprising, to the extent that you'd expect places with globally linked economies established by their historical presence on the seas to do well, as you would expect for places that were non-extractively colonized (they'll often be the same places, i.e. the U.S.) So it might be worth asking, is there a similar effect in the U.S.?

Yes. In general, the coastal states have higher per capita incomes than the landlocked states. But the scatter plot is interesting. There's a U-shaped trend to this data, of distance of each state capital from American saltwater, versus per capita income (U.S. Census). I say "American saltwater" because there are two states (New Mexico and Arizona) where it's faster to go to the Gulf of California. Even including that as the closest saltwater doesn't change much.



You notice the income minimum at 607 miles from saltwater? It's not just a curve artifact - if you look at the states with capitals 500-700 miles from saltwater, they have a lower per capita among them ($24,141) vs the country as a whole ($28,051). These 7 states with capitals 500-700 miles are the sparsely populated and therefore small service economies of the northern Rockies (Utah, Montana, Idaho), as well as part of the Bad Stripe in the Appalachians (Tennessee, Kentucky, Indiana), and post-industrial Michigan. Is there something worse about being 600 miles from the sea, as opposed 1000 or more? (6 states: Iowa, Colorado, Wyoming, Minnesota, South Dakota, and North Dakota, the latter the furthest at 1,235 miles.) But it's possible that it's just a historical accident, as with the supposed effect of rainfall at 100 degrees west longitude causing the population to drop off toward the west. In the case of 100 degrees west, Americans had settled to about that distance inland when the rail lines were completed. (Read the history of towns in western Texas and you will usually see a discussion of which rail line it was on; true for most of the Frontier Strip.)

Also of note: I used driving distance to saltwater, but this is not a great approximation. Even if we were going to use driving distance to saltwater regardless of country, you couldn't include Hudson Bay as North Dakota's closest, because you can't drive there! And just because you can drive to coastline doesn't mean there's a port there, or geography that allows ports to be built. Furthermore, the Great Lakes states are de facto on saltwater because canals and locks connect shipping all the way through to Minnesota.

If you count states in the discrete category of whether they're landlocked and how landlocked they are (1 state away from saltwater? 2 states?) it's clear that the median income of saltwater states is higher - $29,551 vs $26,073. However, among the landlocked states, the U-shaped curve appears again: for the land-locked states, there's no trend for more isolated = lower income; if anything it's the opposite (isolated means the more states you have to go through to get to saltwater from there). The only state 4 states away from Saltwater is Minnesota which at 30,656 has a higher PCI than the median of the coastal states., the better its income. (1 state away, $25,275; 2 states away, $26,695; 3 states away, $26,545.)

Graphic Tool for Inmigration, United States, 2012

At the site where it's published you can mouse over individual states to see the flows for that state. Note that each line between a pair of states is the total exchange regardless of direction. Below is a freeze-frame of California, which again has a net loss; this correlates with the interesting fact that in 2010, for the first time since the Gold Rush, CA had more native-born residents than migrants.

The First City in the World, Today

Hey, you wanna talk about urban decay, well Detroit's got nothing on this place! [rimshot.] This is Eridu in the Fertile Crescent.


View Larger Map

Urbanization in the U.S. and Canada

Australia is often used by demographers as an example of a highly urbanized country, but the contrast between Canada and the U.S. is perhaps more interesting, because we're on the same continent.  And indeed, looking at a biggest cities comparison list of both countries, it's striking: of the 3 biggest cities in North America, 2 are in Canada. But as you include more cities of decreasing size, the % of Canadian cities in the rank list converges toward 0.1.  (Y axis is cumulative % of Canadian cities in the list of biggest cities in North America, of cities with at least 100,000 inhabitants.)  Canada's smaller population is enriched for bigger cities.





Even better than the rank list is the difference in urbanization, i.e. the percent population in cities by size.  And there it's even more striking:  Canada's biggest city alone contains 16.2% of the country's population.  To get to that level of % urbanized population in the U.S. you have to add up the first 60 cities.Y axis is % of population in cities, counting cities of decreasing size up to that point (again, as far down as cities of population 100,000).





Climate?  Less of a homesteading policy in Canadian history?  Less aggressive property purchase incentives in the automobile era?  Or Canadian agriculture taking off only post-mechanization (and hence never requiring settlement by large numbers of people in the first place) since the climate is harsher?  The thing to do to start distinguishing between these alternatives would be to generate a 3D surface of this last plot with historical data to see if there are any obvious inflection points.  And with the last possibility, the question is whether the prairie provinces have areas losing population in the same way that the post-mechanization Midwest has in the U.S.  (More on agriculture and settlement of central North America here.)

2012 - Electoral Results and Density

From Omniorthogonal. He observes that the handful of low-density counties that went Democratic are almost all minority-dominated; very often those are Native American - those are the blue ones west of the Mississippi in New Mexico, Arizona and South Dakota. You can also see the Black Belt and the lower Mississippi agricultural area pretty clearly too.

Previous analysis by density here, for 2008 - I speculated then that what we're looking at is not density per se but "encounters with minorities", or forced ethnic mixing. Consequently infamously diverse California (using intermarriage and likelihood of whites having non-white neighbors as an index) is a mess on the scatterplot of non-whiteness vs electoral vote at the county level, but in Mississippi, demography does depressingly equal destiny.

That said, in 2008 the combined % Evangelical+Mormon was more predictive at the state level than even density.

More on the Coast-Interior Divide

From here.  Many of these currently unemployed were "masked" by the housing boom in the late 90s and aughts.  And do we think the economy will be more or less based on human capital (and education) ten years from now?  An interesting metric is education-years per square mile, which has been shown to correlate better with per capita patents than just average education.  Seattle has higher average education than San Francisco but SF is denser, and produces more patents.

A low-education, low-density area shows little promise for economic growth, and produces voting patterns that aren't promising in terms of rescuing things.

The Real, New Polarization in the U.S.: Coast vs. Interior

Until 1980 or so, the political coalition that formed the Democratic Party was a strange one.  Liberals aligned with blue collar industrial labor and conservative Southerners who were still sore over the Civil War.  Nixon's Southern Strategy changed that.  By the 1990s the Republican Party had absorbed the culture conservatives in the South, and it's now been argued, we're back to our national pre-1865 condition:  a country whose politics is polarized along clear regional lines.  This does not bode well for functioning government in a two-party system where there is never a reason to compromise.

But is it really a North-South divide?  One could forgive a naive but observant foreigner for looking at this population-weighted map of the 2008 election and thinking it's really the coasts vs. the interior, with an island in the north just west of the Great Lakes (the Madison-Minneapolis axis):


Now that not just financial but human capital is highly mobile, the increasing division is between the educated social liberals on the coast and the trade workers in the interior. The exchange has slowed down over the past five years; we've gotten to where we're going. Note also that if you live on the coast and you just can't believe the dismal economic prospects you keep hearing plumbers and factory workers talking about in the interior...it's because you live on the coast. The structural unemployment of semi-skilled and unskilled labor that was masked for a decade by the housing boom is now back in full force, and it's not going anywhere.

The final irony is that the liberals on the coasts (who, by this categorization, I am one of) have created policies which make housing scarce, attract high-earning professionals who further drive up prices, and accelerate this polarization. Everywhere near saltwater is becoming San Francisco and New York in terms of their housing markets. California is a perfect example, and is no longer the most non-Malthusian territory on the planet; the easy living in Beach Boys songs doesn't resemble the state that I see today. Just ask a middle class family that's moved out of California and headed for the interior. Emigration was greater than immigration from 2000-2009, and for the first time since the Gold Rush, there are more native-born Californians here than immigrants like myself. I am a high-earning professional* from the other coast. Coincidence? That pattern you see from the 2008 election is going to repeat itself for several decades at least. *I was, and will be again once I finish this damn MD.

Map of U.S. Postal Codes Connected Sequentially

ZipScribbles by Robert Kosara.

When I was young I wondered if all the ZIP codes connected in order, and wanted to walk them in that order.  Even if they did I wouldn't want to now.  Woe adulthood!

Asian Students Not Checking "Asian"

Asian and part-Asian students, aware of the well-studied bias against high-performing Asian students in college admissions, are now avoiding checking Asian on their applications. Things are only going to get worse for Asian applicants: the Obama administration has recently relaxed restrictions on the use of race in college admissions, and in California specifically, Jerry Brown wants to go further. Of course, many of these students have ambivalent feelings about this.

Ambivalent Asian students: I'm going to solve this for you. Don't check Asian. Why is it okay for you to do this?


- First and foremost, because you're dealing with a badly immoral system. Let the admissions offices squeal all they want - the day they stop discriminating against you based on your race is the day you'll stop not checking your true background. If you woke up two centuries in the past, and the house you were in was harboring escaped slaves, would you lie to the police who came looking for them? Of course you would. Just like you're going to lie to the people who are treating groups of people differently today based on ethnic background.

- One concern seems to be that somehow students are "selling out", "selling their soul", or "turning their back on their community". Seriously? A mark on one piece of paper has that much effect on the identity you'll project in your life? Either don't complete that section, or say "not Asian", and forget about it. If your surname gives you away, then, and I mean this seriously, do a legal name change. Then change it back once you're in. Again, seriously. You have to weigh the annoying paperwork against the 250 SAT point advantage you'll get.

- From a purely selfish standpoint, I as an American adult want you to get into a good school where your potential is realized, based on your actual academic performance. Do it for me, and do it for yourself, for your country and future economy.

Centrality of State Capitals Doesn't Matter

The center of population of the United States over time, migrating progressively west from Washington D.C. Does this matter?

Political entities try to locate their capital cities centrally, assuming that this facilitates administration of the entire territory. Consequently, we would expect to see that development indicators would correlate with centrality of capitals. I looked at data from American states, which are more standardized culturally and otherwise than the full set of world capitals would be. Using U.S. state data, the central capital assumption is false.

I compared per capita income, well-being, and Gini data for each U.S. state against the distance between from the geographic center of each state to the capital of each state, both in absolute terms and adjusted for the size of the state (against the square root of the total area including water).

As seen below, the R-squareds for linear correlations are very weak. If not, then what correlations there are, are almost invariably the opposite of what the central capital assumption would predict. (Correlations are shown by + or - in the tables.) That is, the further the capital is from the center of the state, the higher the well-being and per capita income, and the lower the income inequality. I'm not going to take up space with the noisy scatter plots so here's a table of the correlation strengths:

Measure	R squared, Absolute	Adjusted
Well-being	+, 0.0751	+, 0.0651
Per cap income	+, 0.0099	+, 0.0773
Gini	-, 0.066	-, 0.0266

Because geographic center in this case is really a proxy for center of population - does it really matter if the capital is equally near an empty quarter as to an urban area? - I also compared these metrics to capital-to-population center distance, with similar lack of correlation.

Measure	R squared, Absolute	Adjusted
Well-being	+, 0.0311	+, 0.0004
Per cap income	+, 0.0131	+, 0.0738
Gini	-, 0.0126	+, 0.0086

(Data can be provided upon request.)
See here for a map of population centers.

Of course there are outliers on the scatter-plots in terms of distance from capital to population or geographic center (especially Florida and Alaska) but removing them never resulted in significant changes and often actually lowered the already near-zero R-squared. Sometimes taking out the outliers reversed the correlation, but again the R-squared didn’t change much (biggest R-squared improvement with outliers where the correlation reversed was 0.0385 for Gini relating to capital distance from population center as opposed to 0.0126 with outliers, and the correlation went from negative to positive; still no signal.)


What are the implications or explanations here?

- The obvious one: that access to the capital doesn't matter for human development.

- That there are confounding factors; especially since the size of states varies non-randomly with their location and date of entry into the Union, which in turn non-randomly varies with their population density and types of economies.

- That in fact there has been sufficient wealth redistribution by the central national government to erase differences introduced by differing access to the capital (i.e. that having non-central capitals might have indeed hurt some states, but they get support from the Federal government that conceals this.)

- That geographic centrality is only a proxy for proximity to population that's being served, which is rarely distributed exactly evenly throughout a territory; perhaps doing this same analysis and taking into account center of population would give different and/or stronger correlations.


At the national level, I've often wondered what if any harm has been done in leaving the American capital in the original center of the U.S. (along the central East Coast) rather than moving it to Kansas City. Barring scale effects, based on this data, it's more likely that the answer is none at all.

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?

Native-Born Californians Regain Majority Status

For the first time since the Gold Rush. LA Times story here. Interestingly during the 2000-2009 Census period, California LOST 1,509,708 people due to internal em/immigration. Only international immigration kept the population-due-to-em/immigration above water (by about 1% of the state's total population.) Many of these are Latin American, but a large number of high-skill well-to-do Asian immigrants are coming on 747s.

Suggested research*: relationship between proportion of ethnic populations who are legal immigrants or permanent legal residents vs. citizens, and per capita income in those populations; relationship between prevalence of international immigrants or incidence of international immigration in last decade and per capita income change. Also, distribution within California by country of origin of new international immigrants.

*"Suggested research" translates to "someone else do the work, I'm not a frickin demographics grad student over here".

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?