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Less than even two! Image credit: Yoshi Canopus

A few years ago Greg Cochran mentioned to me how he perceives the two child family to be the new bourgeois normal, enforced by the professional class and blue-haired ladies alike (this impression is informed by the fact that he has more than two children). This seems to align with my own general sense, but then again how normal is my socioeconomic milieu? So I decided to look at the General Social Survey. I limited the sample to non-Hispanics whites age 45 and over, constrained to the interval 2000-2012,* and broke the data into male and female classes. I crossed the number of children, binned 0, 1, 2, 3, 4, and 5+, with the highest educational attainment of the individual.** In other words I limited the data set, and looked at how the number of children of individuals varied as a function of education.


For males the sample sizes were ~432 with no high school degree, ~1,592 high school degree, ~226 junior college, ~618 bachelor’s degree, and ~461 with graduate educations, for a total of ~3,329.*** The equivalent numbers for females were ~452, ~2,124, ~300, ~628, ~434, and ~3,939.

The results below:

Nothing too surprising. It seems that non-Hispanic white women without high school educations are particularly fecund (or perhaps they don’t have high school educations because of their fecundity?)

 

* Selection Filter(s): age(45-*) year(2000-*) race(1) hispanic(1)

** Row, childs(r:0;1;2;3;4;5-*), column, degree

*** The ~ is due to the fact that they’re weighted N’s.

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Fertility, Social Science 
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Egg freezing enters clinical mainstream:

Egg freezing is no longer an experimental procedure, according to the American Society for Reproductive Medicine (ASRM), which on 22 October issued new guidelines on the controversial practice. The change in policy is expected to accelerate the growth of clinics that offer egg freezing to women who face fertility-damaging treatment for cancer or other conditions, and to women wishing to delay having a baby — although the society stopped short of endorsing the procedure for that purpose

You can read the full guidelines, with caveats, online. Last I checked this costs on the order of $10,000. Nothing to sneeze at, but definitely not insane when you consider how much money many couples spend on fertility technologies when women are between 35 and 40.

And of course I recommend freezing sperm too. That’s far less costly.

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Fertility, Health 
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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.


Attitudes toward Bible and median fertility
Word of God Inspired Word Book of Fables
No College 2.58 2.29 2.17
College 2.21 2.05 1.65
Mean real income, indexed to 1986
$0-$15000 2.63 2.27 1.97
$15001-$30000 2.50 2.19 2.00
$30001-$50000 2.28 2.29 1.92
$50000> 2.53 2.11 1.85
WORDSUM (vocab test) score
0-4 (dumb) 2.71 2.08 2.23
5-8 (average) 2.54 2.26 2.07
9-10 (smart) 2.58 2.07 1.69

These data imply to me that the secular are getting idiocratic faster than the fundamentalists.

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Data Analysis, Demographics, Fertility 
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Neuroskeptic has a post up, The Coming Age of Fetal Genomics:

So they don’t. Instead, they buy a $100 test kit, they each provide a small blood sample and send it off to one of the companies offering fetal genome testing. At the testing lab, they can separate out the mother’s DNA from that of the fetus, both of which are present in the mother’s blood. By comparing the fetal genome to the mother’s and father’s, it’s easy to spot de novo mutations. If a certain gene doesn’t match either the mother or the father’s sequence, it’s mutated.

A few days later the results are back. There are several mismatches detected. Most are benign – they’re not predicted to have any biological effects. But there’s one, a deletion of a few thousand bases in a gene involved in brain development. This deletion is predicted to raise the risk of epilepsy and autism from 1% to 10% apiece. The parents now have a decision to make. The mutation is a one off, it’s not inherited. If they conceive again… roll the dice again… and it’ll be gone. Do they terminate?

Like the adverts say, “Some people disagree with this, but we say there’s only one person who really matters: your baby.”


Probably not too surprising to readers of this weblog. Years ago I joked that Armand Leroi was a “demon geneticist” for broaching the topic of neo-eugenics. At this point his article isn’t really timely, it’s almost passé! Recently on Facebook an evangelical Christian friend from high school posted a photo of a child with Down Syndrome, making the case for the value of such a life. We’re beyond thought experiment stage, CVS and some of the non-invasive methods are “online.” If Armand was a dark creature, we live in the age of Gog and Magog already. The media just isn’t reporting it for whatever reason.

But I’m not here to scare you. Rather, there is a positive and ethically uncontroversial method by which we can reduce the expected mutational load of any future fetus for a wide swath of Americans. This applies particularly to people who are the core audience of this weblog. Not only am I going to put a proposition out here, but I considered the cost vs. benefit for myself (ultimately, I decided that it wasn’t worth it for various reasons). Let me go to the section of the post which highlights what I’m getting at:

….new mutations, out of the blue, they can affect any family. A clear family history is no protection. They don’t discriminate by race or lifestyle. It’s just the luck of the draw – except that older parents are at much higher risk, especially older fathers. In the case of our couple, she’s 28 and he’s 32. Perfectly normal for this day and age – but very old in biological terms. Humans evolved to be grandparents by 32, not parents….

Sperm are replicated throughout your life. There’s a hypothesis that it is through the male germline that genetic load tends to creep into the population (or, more positively, mutations which ultimately may be the source of variation which drives evolution). Circumstantial evidence implies the children of older males may have decreased quality of life (e.g., higher rates of cancer). I recently asked a researcher who has looked into the question of genetic load in humans, and he seems to lean toward the proposition that sperm quality does decrease as a linear function beyond one’s early 20s. If you are a forward thinking person I assume you’ll already have anticipated me: massive banking of the sperm of young men may result in greatly reduced later life aggregate morbidity on the social scale.

Obviously some of the same applies to eggs, but that’s a more difficult and expensive procedure. And, the storage conditions have to be optimal. But I don’t see this as an insurmountable engineering problem. You should extend this to pre-implantation genetic diagnosis as well, take the zygote(s) with the lowest mutational load values and implant them. But that would be more controversial, due to the expense and the ethics.

I began thinking of this only a year or two back when I was going about starting a family, relatively late in life. Since I’m already “in the game,” and I can’t go back into the past to get my young sperm, I didn’t do this. And long term storage isn’t available in all locales. But if you are a young man who lives in a large urban area and has a decent disposable income, why not? Your symmetrical children with low mutational load will thank you for it.

(Republished from Discover/GNXP by permission of author or representative)
 
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In my post below on selection for the “better” zygote Michelle observes that “This would be relatively easy for the father, not so much for the mother.” I took her to mean either of two things,

1) Extraction of eggs is a major surgical affair. Extraction of sperm is not.

2) Males generally have many more sperm to contribute than females.

The latter issue made me go look for data on human females, by age. The paper A systematic review of tests predicting ovarian reserve and IVF outcome had what I was looking for. First, let’s review the cumulative distribution of fertility curves for women:


The way I read the figure 50% of women are sterile at 41. 50% begin their fertility drop at 31. Note that a small, but significant, minority of women are already sterile by age 35. People talk about fertility curves, but less weight is given to the fact that the curve varies in terms of its chronology!

Second, let’s look at the number and quality of ovarian follicles over time (they correspond to number of incipient eggs):

This figure is not easy to read. But you can see that at age 20 there are ~100,000 follicles. That number seems to drop by a little less than half by 30, and is at 20,000 by 40. But by this point 25 percent are of “poor quality.”

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Fertility, Medicine 
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In the post below I stumbled upon a weird datum. Kuwait’s total fertility is now below 3. The average estimates seem to be ~2.5 or so. This surprised me, as my impression was that Gulf Arab petroleum based states tended to encourage pro-natalism. This was both a matter of ideology, and also because the small and wealthy native populations lived off rents, and had not had to modify their neo-medieval ideologies to foster productivity driven economic growth. But perhaps Kuwait is an anomaly? Well, it turns out that the Saudi fertility rate is now below 3 as well. Again, depending on which numbers you trust a value of ~2.5 seems plausible. In 1980, at the peak of OPEC’s power and a period when Saudi Arabia was flush with incredible per capita wealth the fertility rate was north of 7.0. But even in the mid-1990s Saudi Arabia’s fertility remained a robust 5.0. Obviously one has to account for the fact that some of the “Arab” nations are not very Arab. The UAE has huge South Asian and Persian populations, not to mention all other sorts. So its fertility of 1.80 can be chalked up to its unique demographics. But would you have guessed that Lebanon’s fertility rate is now the same as Finland’s?

Below the fold is a chart which shows the trends among Arab nations and Finland over the past 40 years. The shading of the bars is proportional to life expectancy.

Image Credit: Denise Chan

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Data Analysis, Fertility 
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I just finished reading My Fertility Crisis, which is excerpted from a longer piece you can get on Kindle for $1.99. The author is a single woman in her early 40s who is going through IVF treatments, without success so far. She outlines the choices she made over her life which may have influenced her current situation.

After reading the piece I came back to an issue I’ve wrestled with before: it’s often really hard to find information on probability of pregnancy online in the form of charts. The reason is that there’s so much information, and much of it is skewed toward people who are undergoing treatment for infertility. But why look when you can generate your own visualization? I found a pregnancy probability calculator online which I cross-validated with some of the literature. Here is the best case scenario for probability of pregnancy if you are trying in the natural fashion (the probabilities exclude women who are clinically infertile, which is a rather slippery category strongly dependent on age, so the older cohorts are probably much larger overestimates than the younger ones):

The main focus is really the decade of the 30s for women. Here is a figure from Ovarian Aging: Mechanisms and Clinical Consequences which shows a finer-grain decline in fertility:


An issue mentioned in the piece above is that there is a focus on the successes of IVF as opposed to the failures. I don’t really buy that narrative. But, there is a tendency not to focus too much on the fact that many IVF successes for women in their 40s are due to donor eggs. A clear example of this phenomenon is that very few in the media highlighted the likelihood that Elizabeth Edwards’ last two children were conceived with the help of donor eggs. She was 49 and 51 when they were born.

Recently a friend asked me about the value proposition of freezing eggs in the case of a 35-year-old female friend. I think it’s something that many people in the developed world really need to consider. Yes, the cost is going to be in the range of tens of thousands, but that’s the magnitude of a car, and far less than a home. A healthy child seems to me much more valuable than either of these objects to people who want to have children.

One of the implications that many people take away from these results is that society should aid those who wish to have children at later ages. I’m broadly sympathetic to this viewpoint. The type of people that I know personally are often in this class; they have delayed starting families to finish their extended educations and invest in their own human capital. In 15 states the law requires than health insurance cover infertility treatment. But we must not ignore the class ramifications of these policies. Mandating the coverage of infertility may alter the behavior of some individuals (just as the existence of ART has changed the stance of many people toward the “reproductive clock” more generally), but it is operationally a transfer from those who have children earlier, and are generally of lower socioeconomic status, toward those who have delayed childbearing toward later ages and are usually of higher socioeconomic status. The counterargument could be that higher socioeconomic status individuals pay greater taxes already.

The General Social Survey has a variable, AGEKDBRN, which asks respondents when their first child was born. Below I limited the data set as follows:

1) All responses are from the year 2000 and later

2) All responses are from women

All the x-axes on the plots are age of the mother when the first child was born, while the y-axes are proportions across classes. I’ve smoothed the data some. In the first plot ~10% of women whose family wealth is less than $100,000 had their first child at 20. For women whose family wealth as more than $100,00 the proportion was ~8%. For the last plot I categorized “Dull”, “Not Dull” and “Smart” with WORDSUM, which is a 10 question vocabulary test which has a 0.70 correlation with I.Q. The dull category encompasses the bottom 35% of the distribution, the not dull encompasses the middle 53% of the distribution, and the smart the top 12% of the distribution.

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Culture, Data Analysis, Fertility, GSS, Health 
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Poking around Google Data Explorer I reacquainted myself with an interesting fact: though the teen birth rate in Bangladesh is greater than that in Pakistan, the total fertility rate is far lower. The disjunction has emerged over the last generation, as Bangladesh’s TFR has dropped much faster than Pakistan’s. To the left you see a scatter plot, which shows teen fertility rates (age 15-19) as a function of total fertility rates. I’ve labeled a few nations, and also added the color coding by region. It is notable that the nations above the trend line seem to be Latin American, while those below are disproportionately Middle Eastern. That means that Latin American nations have higher teen fertility in relation to their total fertility, while Middle Eastern nations have lower teen fertility in relation to their total fertility. Sweden actually has a rather high fertility rate in relation to its teen birth rate. The expectation is generated by world wide patterns, so I thought I’d look more closely at the original data sets from the The World Bank. All the data is from 2008. The teen birth rates are per 1,000 of teens in the age range, with TFR’s are per woman.

My contention is this: those nations with high overall fertility despite low teen fertility rates indicate an ideological or operational pro-natalist cultural stance. That means that mature adult women in marriages are presumably having many children. The high teen fertility rates in Bangladesh vis-a-vis Pakistan is probably simply due to lower aggregate development (Pakistan is still higher up on the HDI ranking, though the gap is closing).

Below are some charts. First, a plot with lines of best fit (as generated by R’s loess function). Then, absolute deviations from the line of best fit as a function of fertility. Also, percentage deviations from the line of best fit as a function of fertility. I provide the weighted trend line, but rely on the unweighted fit for the rest of the charts.


[nggallery id=28]

Next, let’s compare percentage and absolute deviation from the trend line on the same plot.

[nggallery id=29]

Finally, a table with the “top 15.”


Country Teen births/1,000 TFR Population Deviation % Deviation
Top 15 absolute deviation above the trend line
Nicaragua 112.09 2.72 5667325 61.11 54.52
Dominican Republic 108.18 2.65 9952711 58.93 54.48
Brazil 75.07 1.88 191971506 45.83 61.05
Nepal 98.51 2.9 28809526 44 44.67
Venezuela 89.67 2.54 27935000 43.28 48.27
Cape Verde 93.36 2.73 498672 42.15 45.14
El Salvador 82.22 2.32 6133910 41.28 50.2
Ecuador 82.6 2.56 13481424 35.69 43.21
Costa Rica 66.9 1.96 4519126 35.47 53.02
Honduras 92.26 3.26 7318789 35.47 38.44
Panama 81.95 2.55 3398823 35.3 43.07
Jamaica 76.62 2.39 2687200 33.94 44.3
Gabon 88.6 3.31 1448159 31.68 35.76
Colombia 73.75 2.43 45012096 30.13 40.85
Mexico 64.33 2.1 106350433.7 29.21 45.4
Top 15 percentage deviation above the trend line
Brazil 75.07 1.88 191971506 45.83 61.05
Cuba 45.36 1.51 11204735 26.13 57.6
Bulgaria 41.6 1.48 7623395 23.18 55.71
Nicaragua 112.09 2.72 5667325 61.11 54.52
Dominican Republic 108.18 2.65 9952711 58.93 54.48
Barbados 42.75 1.53 255203 22.97 53.74
Costa Rica 66.9 1.96 4519126 35.47 53.02
Georgia 44.34 1.58 4307011 23.2 52.33
Romania 30.68 1.35 21513622 15.69 51.14
El Salvador 82.22 2.32 6133910 41.28 50.2
Puerto Rico 52.72 1.8 3954553 25.63 48.61
Chile 59.42 1.93 16803952 28.81 48.49
Venezuela 89.67 2.54 27935000 43.28 48.27
Mauritius 39.77 1.58 1268854 18.63 46.86
Uruguay 60.86 2.01 3334052 28.08 46.14
Top 15 absolute deviation below the trend line
Libya 3.11 2.7 6294181 -47.39 -1523.69
Oman 10.39 3.05 2785361 -45.54 -438.3
Israel 14.15 2.96 7308800 -41.07 -290.26
Djibouti 22.51 3.9 849245 -39.33 -174.7
Samoa 26.77 3.95 178869 -36.17 -135.12
Algeria 7.25 2.36 34373426 -34.7 -478.63
Malaysia 12.66 2.56 27014337 -34.25 -270.55
Uzbekistan 12.83 2.56 27313700 -34.08 -265.64
Micronesia 24.67 3.57 110414 -33.15 -134.39
Jordan 24.33 3.49 5812000 -33.11 -136.09
Saudi Arabia 25.81 3.12 24807000 -30.5 -118.18
Tajikistan 28.07 3.41 6836083 -29.1 -103.68
Qatar 15.81 2.41 1280862 -27.34 -172.93
Tunisia 6.88 2.06 10327800 -27.21 -395.56
France 6.76 2 62277432 -25.75 -380.91
Top 15 percentage deviation below the trend line
Country Teen births/1,000 TFR Population Deviation % Deviation
Libya 3.11 2.7 6294181 -47.39 -1523.69
Algeria 7.25 2.36 34373426 -34.7 -478.63
Oman 10.39 3.05 2785361 -45.54 -438.3
Denmark 5.92 1.89 5493621 -23.59 -398.55
Tunisia 6.88 2.06 10327800 -27.21 -395.56
France 6.76 2 62277432 -25.75 -380.91
Slovenia 4.84 1.53 2021316 -14.94 -308.59
Sweden 7.58 1.91 9219637 -22.48 -296.58
Israel 14.15 2.96 7308800 -41.07 -290.26
Norway 8.39 1.96 4768212 -23.04 -274.57
Malaysia 12.66 2.56 27014337 -34.25 -270.55
Uzbekistan 12.83 2.56 27313700 -34.08 -265.64
Belgium 7.6 1.82 10708433 -20.02 -263.45
Italy 4.8 1.41 59832179 -11.76 -245
Switzerland 5.44 1.48 7647675 -12.98 -238.69

To restate: my assertion is that nations with a high TFR despite low birth rates in the 15-19 age range indicate a realized preference for large families. This seems to be the class that Israel, Rwanda, and many Middle Eastern nations fall into. Some European nations, such as France, have a higher TFR in relation to what they’re teen birth rates would predict. This is just a function partly of very low teen birth rates. But in the case of France it is probably a function of moderate pro-natalism.

In the other class you have many Latin American nations, whose fertility is modest, but teen birth rates are very high. I think this is probably a symptom of demographic structure within the population. There’s a lot of inequality and variation in economics and cultures within the societies. I think this is why a very low TFR countries such as Romania shows up: the Roma minority has a high teen birth rate. They are not numerous enough to change the average TFR much, but have shifted the teen birth rates.

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Data, Data Analysis, Fertility 
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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:

China’s coercive policy is often held up as a great success of the power of government to change from on high. But did you see the world population growth correction in the early 1960s? That was China. If you don’t know what was going on in China then, read books (hint: if you don’t know much about the history of China, you don’t know much about the history of the world). My point is that China’s solution was in part a reaction to a pro-natalist drive encouraged by one of the most powerful crazy men in the history of the world. On pure pragmatic grounds one may say that China had to do something, but their actions in the early 1980s did not occur in a vacuum, and were a consequence of a sequence of earlier events particular to that nation.

Contrast China with South Korea, a culturally similar nation, which went through decades of authoritarian rule, but never imposed coercive family planning policies of the sort common in the People’s Republic. Like Japan and Taiwan South Korea’s fertility and population growth rates declined naturally through economic development. With abundant human capital (high literacy) to start out with these nations replicated, and in some ways exceeded, the trajectory of the European demographic transition concomitant with an increase in economic productivity and urbanization. In fact, their fertility rates are lower than that of China, probably because they’re economically more advanced. If it wasn’t for China’s three decade long dance with crazy Communism the coercive policies in relation to reproduction may never have been necessary.

Economic development isn’t the only way to staunch population growth. Iran has taken a different, and less optimal, but still not grossly coercive, path. Because of the lack of economic opportunity in Iran’s society there was an understanding at both the commanding heights and the grassroots that large families were simply not sustainable, at least not using the quality of life which people had become used to in the 1970s as a reference point.

As I noted yesterday, the problem within India is that there is a wide region-to-region variation. The southern cone of India is already verging toward sub-replacement fertility. A major difference I see between China and India though is that the economically and socially most backward area is the cultural heart of the latter. There may be vague analogies to Italy, where Rome is a government town in the center, while northern Italy is the economic motive force, and southern Italy serves as a vote-bank which reliably backs the party which makes the biggest cash transfer promise. A big difference between Italy and India: the backward region is numerically dominant in India, while it is not in Italy.

Here are two bubble plots which show the divide in India. The size of the bubbles are proportion to the population size of the state. The two ones to the top left are Uttar Pradesh and Bihar.

[nggallery id=4]

The fact is that South Asia is low on the human capital scale:

800px-World_literacy_map_UN

The only long term solution is to leverage the fact that other parts of the world are higher up on the human capital ladder, and still producing innovation and generating new ways to increase productivity. Matt Yglesias has a post up about Japan, from which I got this chart:

TFPjapan-1

Because Japan’s population is shrinking its economy will decline over time. Additionally, because of the unfavorable demographics, with more older people than young workers, it will go through some decline in quality of life. But the average Japanese still consumes at a very high level, it’s not dystopia. Ultimately the Japanese are relying on innovation to buoy their economy. And that’s the real long term solution: without innovation we’re f**ked. Period. Demographic adjustments are really epiphenomena on the margins. That’s why the media can report on both sides of the ledger as if they are both positive and negative. It’s about quality of human capital and the innovation they’re producing, not the quantity of humans.

Image Credit: Wikimedia

(Republished from Discover/GNXP by permission of author or representative)
 
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I’ve been poking around the Census data sets for a few days now. I want to merge them with the longevity stuff soon, but while was at it I decided to check to see how variation in geography related to variation in fertility. You can go to the GSS and see all sorts of national trends, but I thought a county-by-county view would be of interest. Click the images for bigger versions. The fertility is defined as “women with births in the past 12 months; rate per 1,000 women.” Coming out of the American Community Survey. All the data are for Non-Hispanic white women.

(Republished from GNXP.com by permission of author or representative)
 
• Category: Science • Tags: Census, Fertility 
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A reader pointed me to the Population Reference Bureau which has total fertility rates for women broken down by economic fifths. Unfortunately these data are limited to developing countries, but reader might be interested in any case. In no case do the women of the richest fifth have a higher fertility than the women in the poorest fifth.

Poorest Fifth Middle Fifth Richest Fifth
Armenia 2.5 1.4 1.6
Bangladesh 4.6 3.3 2.2
Benin 7.2 6.5 3.5
Bolivia 7.4 4.4 2.1
Brazil 4.8 2.1 0.7
Burkina Faso 7.2 6.8 4.5
Cambodia 4.7 3.9 2.2
Cameroon 5.9 5 3.6
Central African Republic 5.1 4.8 4.9
Chad 7.1 6.2 6.2
Colombia 4.4 2.4 1.8
Comoros 6.4 4.5 3
Cote d’Ivoire 6.4 5.7 3.7
Domican Republic 5.1 3.3 2.1
Egypt 4 3.3 2.9
Eritrea 8 6.4 3.7
Ethiopia 6.3 5.9 3.6
Gabon 6.3 4.1 3
Ghana 6.3 5 2.4
Guatemala 7.6 5.1 2.9
Guinea 5.8 6.3 4
Haiti 6.8 5 2.7
India 3.4 2.6 1.8
Indonesia 3.3 2.6 2
Jordan 5.2 4.3 3.1
Kazakhstan 3.4 2.1 1.2
Kenya 6.5 4.7 3
Kyrgyzstan 4.6 3.6 2
Madagascar 8.1 6.8 3.4
Malawi 7.1 6.4 4.8
Mali SDNUM="1033;">7.3 7.3 5.3
Mauritania 5.4 4.9 3.5
Morocco 6.7 4.2 2.3
Mozambique 5.2 5.4 4.4
Namibia 6 4.6 2.7
Nepal 5.3 4.7 2.3
Nicaragua 5.6 3.1 2.1
Niger 8.4 7.8 5.7
Peru 5.5 2.6 1.6
Philippines 6.5 3.6 2.1
Rwanda 6 5.9 5.4
Senegal 7.4 6.2 3.6
South Africa 4.8 2.7 1.9
Tanzania 7.8 6.1 3.4
Togo 7.8 6 2.9
Turkey 3.9 2.7 1.7
Turkmenistan 3.4 3 2.1
Uganda 8.5 7.5 4.1
Uzbekistan 4.4 3.2 2.2
Vietnam 2.2 1.8 1.4
Yemen 7.3 7.3 4.7
Zambia 7.3 6.8 3.6
Zimbabwe 4.9 4.5 2.5

Related: Differences in fertility by class internationally.

(Republished from GNXP.com by permission of author or representative)
 
• Category: Science • Tags: Fertility 
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This chart shows the proportion of white men and women age 50 and over who have 0, 1, 2, etc. children, up to 7. I got this from the GSS via CHILDS. I dropped 8 or more since that’s unbounded, but very few had that many (on the order of 1%). Red is female, and navy male.

(Republished from GNXP.com by permission of author or representative)
 
• Category: Science • Tags: Fertility, GSS 
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Walker’s World: French births soar:

The second development to note is that INED, France’s National Institute of Demographic Studies, has done some detailed research and concluded that France’s immigrant population is responsible for only 5 percent of the rise in the birthrate and that France’s population would be rising anyway even without the immigrant population.

In fact in France, like everywhere else in Europe, the birthrate among immigrant mothers drops quickly toward the local norm in less than two generations. The measure most commonly used in international statistics is the Total Fertility Rate, which seeks to measure the number of children born to the average woman in her fertile years…

In France, the TFR has risen from 1.66 in 1993 to 2.0 in 2003 and 2.1 last year. If maintained, that means the population of France will rise from 60.7 million today to 70 million sometime before 2050.

The birthrates of Muslim women in Europe have been falling significantly for some time. In the Netherlands, for example, the TFR among Dutch-born women rose between 1990 and 2005 from 1.6 to 1.7. In the same period for Moroccan-born women in Holland it fell from 4.9 to 2.9, and for Turkish-born women in Holland from 3.2 to 1.9.

In Austria, the TFR of Muslim women fell from 3.1 to 2.3 from 1981 to 2001. In 1970 Turkish-born women in Germany had on average two children more than German-born women. By 1996 the difference had fallen to one child and has now dropped to 0.5….

A few points. First, even if there is convergence differentials still do matter. One thing I noted when surveying data on Mormon fertility is that though it has converged with non-Mormon fertility, the “floor” still usually remains higher than that of local non-Mormons. I’m not worried about a Mormon future of course because it is also a religion with a relatively high defection rate, but long term persistence of small differences do matter. Second, projecting to the year 2100 as many do today is very problematic. In the late 19th century some bureaucrats in the Ottoman government were relieved as the Christian Balkan provinces fell away through independence or assimilation into the Austro-Hungarian monarchy. The reason being the fact that Christians had higher fertility than Muslims; something most Muslims and Christians today would find a very peculiar worry. In After Tamerlane there is a reference to a racial triumphalist demographer writing in 1900 about the “fact” that in the year 2000 there will be 1.5 billion whites and only 400 million Han Chinese. Finally, variance matters. Note:

Germany is something of an oddity in this. In most countries with low fertility, young women have their first child late, and stop at one. In Germany, women with children often have two or three. But many have none at all.

Italy and Germany might both have low expectations in regards to the number of children a woman may have in her lifetime, but the shape of the distribution may matter a great deal if fertility is heritable to any extent (straight out of Genetical Theory here). Heritability need not be physiological; rather, it might be cultural and psychological propensities transmitted to the next generation. But if the data above hold one might expect German fertility to bounce back faster than Italian because a subset of the German population exhibit pro-natalist sentiments.

(H/T Talk Islam)

(Republished from GNXP.com by permission of author or representative)
 
• Category: Science • Tags: Demographics, Fertility 
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Razib Khan
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