On Twitter Chris Mims expresses the entirely reasonable proposition that China’s low fertility is a prescription for long term socioeconomic disaster (they’re already beyond “peak worker”), with a link to an article in Quartz, China’s ratio of boys to girls is still dangerously high—and it’s the Chinese government’s fault. First, I’ve noted before that in East Asian societies where male preference was the norm this can shift very quickly. It happened to South Korea over the past 10 years, and it happened in Japan a generation ago. To my knowledge this was more of a matter of “bottom-up” cultural changes than government policy.
Second, the one child policy matters less than we think it does.
There’s another Census Projection out. Yes, I understand that the character of the children born today is going to have obvious impacts on the nature of the population 50 years from now, but we really need to heed the stupidity of past projections. Here’s a piece from 1930, A Nation of Elders in the Making:
To explain convincingly why we believe that we shall certainly not have more than 185,000,000 people here in 2000 A.D. and why we further believe that our population may cease to grow before that time, it is only necessary to make a rapid survey of our national trend of births and deaths….
There was a question below in regards to the high fertility of some extreme (“ultra”) religious groups, in particular Haredi Jews. The commenter correctly points out that these Jews utilize the Western welfare system to support large families. This is not limited to just Haredi Jews. The reason Somalis and Arabs have fertility ~3.5 in Helsinki, as opposed to ~1.5 as is the norm, is in part to due to the combination of pro-natalist subcultural norms, and a generous benefits state. Of course we mustn’t overemphasize economics. Israel’s decline in Arab Muslim fertility but rise in Jewish fertility in the 2000s has been hypothesized to be due to different responses to reductions in child subsidies by Muslims and the Haredi Jews. In short, the former reacted much more strongly to economic disincentives in relation to the latter.
A bigger question is whether exponential growth driven by ideology can continue indefinitely. I doubt it. Demographics is inevitable, but subject to a lot of qualifications. Haredi political power in Israel grants some benefits, but at the end of the day basic economics will serve as a check on the growth of the population of this sector. Similarly, barring massive productivity gains we’ll see some structural changes to the provision of government services across the aging developed world.
Below are some fertility numbers from the GSS. You see the median number of children for non-Hispanic whites born before 1960 from the year 2000 and later. I’ve compared the demographics of fundamentalists, non-fundamentalists, and those who are skeptical of the revealed nature of the Bible.
The readers of this weblog are relatively non-fecund, at least going by reader surveys. But I was curious nonetheless about the attitudes toward number of children, and realized goals of number of children, in the General Social Survey. I decided to look at two variables:
The former asks the respondent how many children they had, the latter how many they’d like to have. I restricted the sample to whites ages 45-65 for every survey year. I then combined all the years of a particular decade, so you have 1970s, 1980s, 1990s, and 2000s. For demographics I looked at highest educational attainment, and household income indexed to 1986 real value dollars (so they are comparable across decades).
Two major takeaways:
1) Education matters more than income in terms of number of children. Having lots of education tends to reduce family size. No great surprise.
2) Ideal number of children increased in the 2000s, but the decline in average number of children continued.
There is often talk in the literature on the disjunction between ideal family size in Third World nations and the realized family size, with a larger number of children than women may want. What is less discussed is the inverse discussion. It seems that Americans want larger families than they manage to have. Of course, there is the distinction between avowed and realized preferences here.
A few years ago I put up a post, WORDSUM & IQ & the correlation, as a “reference” post. Basically if anyone objected to using WORDSUM, a variable in the General Social Survey, then I would point to that post and observe that the correlation between WORDSUM and general intelligence is 0.71. That makes sense, since WORDSUM is a vocabulary test, and verbal fluency is well correlated with intelligence.
But I realized over the years I’ve posted many posts using the GSS and WORDSUM, but never explicitly laid out the distribution of WORDSUM scores, which range from 0 (0 out of 10) to 10 (10 out of 10). I’ve used categories like “stupid, interval 0-4,” but often only mentioned the percentiles in the comments after prompting from a reader. This post is to fix that problem forever, and will serve as a reference for the future.
First, please keep in mind that I limited the sample to the year 2000 and later. The N is ~7,000, but far lower for some of variables crossed. Therefore, I invite you to replicate my results. After the charts I will list all the variables, so if you care you should be able to replicate displaying all the sample sizes in ~10 minutes. I am also going to attach a csv file with the raw table data. As for the charts, they are simple.
- The x-axis is a WORDSUM category, ranging from 0 to 10
- The y-axis is the percent of a given demographic class who received that score. I’ve labelled some of them where the chart doesn’t get too busy
All of the charts have a line which represents the total population in the sample (“All”).
A few months ago I listened to Frank Newport of Gallup tell Kai Ryssdal of Marketplace that upper class Americans tend to be Democrats. Ryssdal was skeptical, but Newport reiterated himself, and explained that’s just how the numbers shook out. This is important because Newport shows up every now and then to offer up numbers from Gallup to get a pulse of the American nation.
Frankly, Newport was just full of crap. I understand that Thomas Frank wrote an impressionistic book which is highly influential, What’s the Matter with Kansas, while more recently Charles Murray has come out with the argument in Coming Apart that the elites tend toward social liberalism. I’m of the opinion that Frank is just wrong on the face of it, but that’s OK because he’s an impressionistic journalist, and I don’t expect much from that set beyond what I might expect from a sports columnist for ESPN. Murray presents a somewhat different case, as outlined by Andrew Gelman, in that his “upper class” is modulated in a particular manner so as to fall within the purview of his framework. Neither of these qualifications apply to Frank Newport, who is purportedly presenting straightforward unadorned data.
When the “average person on the street” thinks upper class they think first and foremost money. This is not all they think about, but in the rank order of criteria this is certainly first on the list. We can argue till the cows come home as to whether a wealthy small business owner in Iowa who is a college drop out is more or less elite than a college professor in New York City who is bringing home a modest upper middle class income (very modest adjusting for cost of living). But to a first approximation when we look at aggregates we had better look at the bottom line of money. After that we can talk details. And the first approximation is incredibly easy to ascertain. Below is a table and chart which illustrate the proportion of non-Hispanic whites after 2000 who align with a particular party as a function of family income, with family income being indexed to a 1986 value (so presumably $80,000 hear means what $80,000 would buy in 1986, not the aughts).
Prompted by Andrea Mitchell’s complaint that Iowa is not representative of America in racial terms the Audacious Epigone probed an American state’s typicality in terms of racial demographics, using the overall American population as a measure. One of the major issues with judging the typicality of a given state is that there is a great deal of residential segregation in even “diverse” regions. This comes up in our personal choices too. In 2008 ~10 percent of non-Hispanic whites married someone who was not a non-Hispanic white. Obviously more than ~10 percent of the population, particularly in the prime marrying demographic, are non-Hispanic whites, so you’re seeing a fair amount of homogamy. In some ways the homogamy is even more striking for minorities. ~31 percent of Asian Americans in this period married a non-Asian American. But, one has to keep in mind that using the American population as representative over 90 percent of the potential marriage partners are not Asian American!
The quest for a state that “looks like America” is understandable, but the reality of lived life is more complex. And not just in racial terms (e.g., the division in politics between the white suburbs of Maryland vs. Virginia on either side of D.C.). But keeping race in mind, one consistent finding in social science is that Americans actually tend to overestimate the number of minorities. Iowa is actually more typical than we think, despite the fact that it is not typical. In the year 2000 the General Social Survey asked respondents to estimate the number of various groups in the USA. The finding of a tendency to overestimate minorities, and underestimate non-Hispanic whites, was confirmed. But, I decided to break this down by demographic. The results are below in a table.
The first row are real counts from the 2000 Census. All the following rows are average estimates of a set of respondents in the year 2000.
Fascinating story about the re-identification of people of Eurasian ancestry as white to get into elite universities. Some Asians’ college strategy: Don’t check ‘Asian’:
Lanya Olmstead was born in Florida to a mother who immigrated from Taiwan and an American father of Norwegian ancestry. Ethnically, she considers herself half Taiwanese and half Norwegian. But when applying to Harvard, Olmstead checked only one box for her race: white.
Asian students have higher average SAT scores than any other group, including whites. A study by Princeton sociologist Thomas Espenshade examined applicants to top colleges from 1997, when the maximum SAT score was 1600 (today it’s 2400). Espenshade found that Asian-Americans needed a 1550 SAT to have an equal chance of getting into an elite college as white students with a 1410 or black students with an 1100.
In the article Steve Hsu observes that the Ivy League universities have a suspiciously similar proportion of Asians, about 2/3 of the fraction of a “race blind” admissions college like Cal Tech. Here’s Alex Tabarrok with the numbers: “At Yale the class of 2013 is 15.5 percent Asian-American, at Dartmouth 16.1 percent, at Harvard 19.1 percent, and at Princeton 17.6 percent.” I assume that the “Asian Quota” will start to change as the current generation of Asian American students become established as alumni donors.
I’m not a big fan of the “Asian Quota” personally. But, I do think one can make a case for it based on the fact that children from families with an Asian background have a strong bias toward optimizing measured outcomes. But, this entails making a profile, or “stereotype,” of a population. I’m not someone who actually objects to this on principle, but I find the hypocrisy on this issue rather annoying, because the same administrators who would decry stereotypes feel they have to employ them implicitly for practical (so the alumni don’t see their university overwhelmed by “yellow hordes,” and so reduce giving) and idealistic reasons (to maintain some ethnic balance).
COMMENTS NOTE: Any comment which misrepresents the material in this post will result in banning without warning. So you should probably stick to direct quotes in lieu of reformulations of what you perceive to be my intent in your own words. For example, if you start a sentence with “so what you’re trying to say….”, you’re probably going to get banned. I said what I tried or wanted to say in the post. Period.
One of the things I really hate are unqualified linear projections. They’re so useless most of the time. A science fiction magazine will give you more insight about the future than the United Nations population projection for the year 2100. This is just as much of an issue when it comes to American Census demographic projections. As I’ve noted before population projections of the coming non-Hispanic white minority 2040 to 2050 are sensitive to the assumptions behind the basic parameters. The logic of the projection is crystal clear and airtight, but just because a certain set of assumptions holds today, does not mean that those assumptions will hold indefinitely (though the Census projections are much more plausible than the United Nations projections because two generations are so much more strongly impacted by by the inertia of current conditions that four generations). In the 18th and 19th century white Americans, and especially the Anglo-Saxon founding stock, were a highly fertile folk. They took over the American Southwest and the Northwest in large part due to their demographic assault. In New England the 30,000 of 1650 became the 700,000 in 1790 in large part due to fertility rates on the order of 7 per woman! Today no one would expect that Anglo-Saxon Americans would be so fertile, let alone the New Englanders who were prominent in the population control movements of the 20th century. In the 17th and 18th century the Jews of Eastern Europe were a highly prolific group, and the gentile majority in places like Poland viewed the waxing of the proportion of this minority with great suspicion. Today no one views the Ashkenazi Jews as demographic engines, though in places like Israel the fecund Haredi have now helped close the “birth gap” with the Arab population, as its fraction of the Jewish population keeps increasing. I can give you other “counter-intuitive” examples from the recent past, but a little history goes a long way in teaching suspicion (e.g., in the Balkans in the late 19th century rural Christian populations had much higher fertility than urban Muslim ones).
These sorts of reversals are not inexplicable. Fertility shifts occur, sometimes within a generation or two. This is why Thomas Malthus turned out to be wrong: he didn’t predict the demographic transition. But we shouldn’t be complacent and assume we’ve reached the “end of history” when it comes to fertility transitions. In the early 20th century there was great terror in the American elite due to the immigration of what would later be termed “ethnic whites,” in particular Jews and Southern Europeans. And yet the Jewish proportion of the American population peaked in the late 1940s at ~5%. What about the other groups? The General Social Survey has large sample sizes for some ethnic groups, so I decided to look there.
If you have not read my post “To the antipode of Asia”, this might be a good time to do so if you are unfamiliar with the history, prehistory, and ethnography of mainland Southeast Asia. In this post I will focus on mainland Southeast Asia, and how it relates implicitly to India and China genetically, and what inferences we can make about demography and history. Though I will touch upon the Malay peninsula in the preliminary results, I have removed the Indonesian and Philippine samples from the data set in totality. This means that in this post I will not touch upon spread of the Austronesians.
I present before you two tentative questions:
- What was the relationship of the spread of Indic culture to Indic genes in mainland Southeast Asia before 1000 A.D.?
- What was the relationship of the spread of Tai culture to Tai genes in mainland Southeast Asia after 1000 A.D.?
The two maps above show the distribution of Austro-Asiatic and Tai languages in mainland Southeast Asia. Observe that when you join the two together in a union they cover much of the eastern 2/3 of mainland Southeast Asia. The fragmented nature of Austro-Asiatic languages in the northern region, edging into the People’s Republic of China, implies to us immediately that it is likely that in the past there was a continuous zone of Austro-Asiatic speech in this region. From the histories and mythologies of the Tai people we know that this group migrated from the southern fringes of China around ~1000 A.D. This is obvious when we note that there are still Tai people in southern China, and the expansion of the Tai across what is today Thailand is to some extent historically attested. Between 1000 and 1500 there was a wholesale ethnic reorganization of the Chao Phray river basin. Was that a matter of demographic replacement, or cultural assimilation, or some of both?
Second, what was the impact of Indians upon mainland Southeast Asia? One of the easiest ways to ascertain Indian influence is script. Burmese, Thai and Cambodian scripts all derive from Grantha, an archaic Tamil script (non-Islamic scripts in island Southeast Asia, such as Javanese and Balinese, are also derive from South Indian precursors). The Indian religious influences also are more southern than northern, manifesting in the southern forms of Shaivite Hinduism and Sri Lankan Theravada Buddhism.
Image Credit: Anirudh Koul
One of the great things about the mass personal genomic revolution is that it allows people to have direct access to their own information. This is important for the more than 90% of the human population which has sketchy genealogical records. But even with genealogical records there are often omissions and biases in transmission of information. This is one reason that HAP, Dodecad, and Eurogenes BGA are so interesting: they combine what people already know with scientific genealogy. This intersection can often be very inferentially fruitful.
But what about if you had a whole population with rich robust conventional genealogical records? Combined with the power of the new genomics you could really crank up the level of insight. Where to find these records? A reason that Jewish genetics is so useful and interesting is that there is often a relative dearth of records when it comes to the lineages of American Ashkenazi Jews. Many American Jews even today are often sketchy about the region of the “Old Country” from which their forebears arrived. Jews have been interesting from a genetic perspective because of the relative excess of ethnically distinctive Mendelian disorders within their population. There happens to be another group in North America with the same characteristic: the French Canadians. And importantly, in the French Canadian population you do have copious genealogical records. The origins of this group lay in the 17th and 18th century, and the Roman Catholic Church has often been a punctilious institution when it comes to preserving events under its purview such as baptisms and marriages. The genealogical archives are so robust that last fall a research group input centuries of ancestry for ~2,000 French Canadians, and used it to infer patterns of genetic relationships as a function of geography, as well as long term contribution by provenance. Admixed ancestry and stratification of Quebec regional populations:
Population stratification results from unequal, nonrandom genetic contribution of ancestors and should be reflected in the underlying genealogies. In Quebec, the distribution of Mendelian diseases points to local founder effects suggesting stratification of the contemporary French Canadian gene pool. Here we characterize the population structure through the analysis of the genetic contribution of 7,798 immigrant founders identified in the genealogies of 2,221 subjects partitioned in eight regions. In all but one region, about 90% of gene pools were contributed by early French founders. In the eastern region where this contribution was 76%, we observed higher contributions of Acadians, British and American Loyalists. To detect population stratification from genealogical data, we propose an approach based on principal component analysis (PCA) of immigrant founders’ genetic contributions. This analysis was compared with a multidimensional scaling of pairwise kinship coefficients. Both methods showed evidence of a distinct identity of the northeastern and eastern regions and stratification of the regional populations correlated with geographical location along the St-Lawrence River. In addition, we observed a West-East decreasing gradient of diversity. Analysis of PC-correlated founders illustrates the differential impact of early versus latter founders consistent with specific regional genetic patterns. These results highlight the importance of considering the geographic origin of samples in the design of genetic epidemiology studies conducted in Quebec. Moreover, our results demonstrate that the study of deep ascending genealogies can accurately reveal population structure.
The New York Times has a piece up, Defusing India’s Population Time Bomb, which reiterates what I was trying to get at yesterday, India’s demographic problems are localized to particular regions, not the nation as a whole. First, let’s review the world’s population growth & fertility rates:
Now let’s focus on a few nations:
Less than a high school diploma: 14.5%
High school with no college: 10.8%
Some college or associates degree: 8.2%
Bachelor’s or higher: 4.9% (this is near full employment from an economic perspective).
If you read the media sometimes it seems like the past recession was total hell in the white-collar sector, but really it wasn’t (comparatively). For what it’s worth, 84% of readers of my weblogs have university degrees or higher….
(Yes, I know the issues in regards to underemployment, part-time employment and those who have dropped out of the labor force, but all the issues seem more relevant to those with less education from what I’ve seen. Correction with data welcome)