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There is a popular genre of commentary which wishes to show that bright people make as many errors as less bright people, perhaps as a consequence of divine retribution. “Einstein made an error in maths which was spotted by a bus conductor” lifts the hearts of some readers. Of course, bright people make errors. Do they do so at a higher, lower, or the same rate as everyone else?

Can we test this in a way that favours the average citizen? How about ignoring high finance and stock picking and just concentrating on basic aspects of household financial decision-making, the nitty gritty of so many of our lives? Can we also avoid the charge that some have levelled against the correlation of intelligence and earnings and wealth, that some people just don’t want to be rich? Let us restrict the focus to seeing whether people, whatever their income, can avoid costly financial mistakes. I assume that even those who don’t wish to pursue inordinate wealth, but instead want to live happily on an average income, still wish to handle their meagre emoluments in a sensible fashion, avoiding hare-brained incompetence and fiscal irresponsibility.

Agarwal and Mazumder think this matter is worth exploring.

Sumit Agarwal and Bhashkar Mazumder. Cognitive Abilities and Household Financial Decision Making. American Economic Journal: Applied Economics 2013, 5(1): 193–207

We analyze the effects of cognitive abilities on two examples of consumer financial decisions where suboptimal behavior is well defined. The first example features the optimal use of credit cards for convenience transactions after a balance transfer and the second involves a financial mistake on a home equity loan application. We find that consumers with higher overall test scores, and specifically those with higher math scores, are substantially less likely to make a financial mistake. These mistakes are generally not associated with non-math test scores.

A 1 standard deviation increase in the composite AFQT score is associated with a 24 percentage point increase in the probability that a consumer will discover the optimal balance transfer strategy and an 11 percentage point decrease in the likelihood of making a rate-changing mistake in the home loan application process. Interestingly, we find that verbal scores are not at all associated with balance transfer mistakes and are much less strongly associated with rate-changing mistakes.

This was based on military personnel on whom there were results available on the Armed Forces Qualifying Test, then linked to data from a credit card finance company, so these are real data, able to pick up sub-optimal choices, more commonly known as mistakes.

The “balance-transfer mistake” is to be fooled by a “teaser” low APR rate on a new card into using the new card rather than the old one during the transfer period. This is because while the old purchase balance is transferred at the new low rate, new purchases on the new card are at a new much higher rate. Sneaky. Some will learn from their mistake as the monthly bills come in with surprisingly high interest rates, and have a “eureka” moment. Others will take more time to learn their mistake.

Lower ability people get fooled more often, brighter people learn about their mistake more often, and the brightest (those above 70th percentile) never make the mistake in the first place, so there is a hierarchy of “eureka” moments.

The next issue the authors consider is the mistake of picking the wrong rate when requesting a loan based on a home valuation. This is another opportunity for the lender to crank up the interest rate, but in this case the rates are visible before the loan is taken out, so it is possible to turn down a poor offer, and try another lender.

Again, the mistake (which increases the cost of the loan by 2.7%) is made at lower ability levels, and not in those above the 70th percentile.

Interestingly, given that the 2008 financial crisis was sometimes portrayed as being particularly unfair to black borrowers, the race difference in this study is in the opposite direction, so long as one controls for intelligence.

Interestingly, we find that the effect on being black is actually positive conditional on AFQT scores and education. This finding is interesting in light of the theoretical model developed by Lang and Manove (2011) who argue that blacks of similar ability to whites may need to signal their productivity to employers by acquiring more education. They cite studies suggesting that blacks are not rewarded the same as whites in the labor market for equivalent AFQT scores. It is possible that the increased likelihood of discovering the optimal balance transfer strategy among blacks who have the same measured ability as whites, reflects their greater investments along other dimensions of human capital.

Being intelligent implies an ability to learn quickly, so it is interesting to plot out how long it takes people to recognize their financial errors, and move to an optimal strategy. High scorers avoid any errors (they can see the error in advance, and avoid it) while those of lower ability take 5 months to correct their mistakes.

To illustrate the effects of AFQT scores on the speed at which individuals learn, we plot in Figure 3 the unadjusted mean AFQT scores for borrowers based on how many months it took them to discover the optimal strategy. The chart shows that AFQT is monotonically decreasing in the number of months it takes borrowers to learn. We estimate that a 1 standard deviation increase in AFQT scores is associated with a 1.5 month reduction in the time it takes to achieve optimal behavior speed. This analysis suggests that cognitive skills also affect the “intensive” margin of optimal financial decision-making behavior.

These two real-life financial errors show the importance of cognitive ability, and may explain a wider range of bad choices regarding finance.

In any case, we think that our analysis likely only touches the tip of the iceberg in terms of the effects of poor financial decision making, due to low cognitive ability, on individual and social welfare. It is highly plausible that similar types of financial mistakes have played a role in explaining loan default, foreclosures, and bankruptcies. In a highly complementary paper to ours, Gerardi, Goette, and Meier (2010) find a strong association between numerical ability and mortgage delinquency and default during the recent financial crisis. Future research may shed more light on the quantitative importance of cognitive ability.

In summary, I think that there are plentiful studies showing that intelligence tests produce scores which are predictive of a wide variety of important real-life measures: earnings, savings and managing loans.

• Category: Science • Tags: IQ 
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  1. Educated, high IQ people seem far more likely to support mass immigration and left wing views generally than the less educated, lower IQ working classes do. At least that is the case in Anglo countries, and I would assume it’s the same in most white countries but I can only speak for the Anglosphere.

    In my experience the more stereotypically “intelligent” someone is the more likely they are to believe in naive, lefty open borders politics and other left wing agendas. Right wing common sense politics is largely the preserve of the working class and lower middle class.

  2. dearieme says:

    It is possible that the increased likelihood of discovering the optimal balance transfer strategy among blacks who have the same measured ability as whites …

    One simple explanation would be that blacks somehow underperform on IQ tests. That is to say, that US blacks may indeed be on average considerably less intelligent than US whites (and yellows, and …) but that the gap is effectively, for some reason, less than is measured.

    I suppose that if one suspects that racial differences are quite real and rather profound, it’s not daft to suspect that different races might respond to IQ tests in different ways that distort – by however modest an amount – the conclusions. In other words the discrepancy might just be another nature-dominated effect and nothing much to do with a nurture-dominated effect such as “acquiring more education”.

    I wonder how one might investigate that hypothesis. I wonder whether such distortions, if they exist, all point in the same direction? Do such distortions occur only for the white/black comparison? Neither seems likely.

    Anyway, this is all secondary to the main lesson of the post, which is that broad-brush measured IQs tell the story you’d expect if you’ve met many humans.

    • Replies: @res
    , @James Thompson
  3. @England patriot

    We wouldn’t have this problem if we could just shame the more intelligent individuals who betray their own people.

  4. res says:

    One simple explanation would be that blacks somehow underperform on IQ tests.

    That’s an interesting idea, especially since academic measures seem to indicate the opposite effect.

    Less well known is what in the scholarly literature is called “the underperformance problem.” Once in college blacks with the same entering SAT scores as whites and Asians earn substantially lower grades over their college careers and wind up with substantially lower class rankings. This gap in grade performance, moreover, is not reduced by adding high school grades or socio-economic status to the criteria for matching students. Blacks equally matched with whites or Asians in terms of their entering scholastic credentials and socio-economic backgrounds simply do not perform as well as their Asian and white counterparts in college. And the degree of underperformance is often very substantial.

    Regarding the original point: It is possible that the increased likelihood of discovering the optimal balance transfer strategy among blacks who have the same measured ability as whites …

    My first thought for an explanation was that blacks tended to have more education than whites with the same IQ. But I’m not sure that is convincing, even to me.

    • Replies: @roberto1
  5. @dearieme

    Jensen 1980 wrote a whole book about this “Bias in Mental Testing”.
    He said that it would be possible to show that IQ tests were biased against black test takers if their real life achievements turned out to be better than predicted by the test. In fact, he found that the tests slightly over-predicted real life achievements.

  6. res says:

    This excerpt from the paper caught my eye:

    We also observe the FICO score as well as a proprietary (internal) credit “behavior” score.

    Does anyone have any idea what this “behavior score” is measuring? Because I think it is the big unexamined story of that paper.

    Table 1 has the regression models for “eureka” behavior, but unfortunately I don’t see much detail about the variables (e.g. are the various demographic variables Z-scored or the original numbers? this greatly impacts the meaning of the numerical coefficients) or their summary statistics and between variable correlations. (it seems to me that any regression model paper like this should include at minimum summary statistics and correlations for all variables–why is this not done?)

    It is hard to draw firm conclusions given the lack of details, but it looks to me like we have the AFQT score explaining about 26% of variance in Model 1 with the behavior score (quadratic model) adding most of the additional 16% seen in Model 2. Assuming those variables are at least somewhat correlated (and how much so is a VERY interesting question IMHO), I would not be surprised if behavior score was actually a better single variable predictor than AFQT score. On the other hand, the AFQT score coefficient did not change much (and actually increased) when behavior score was added to Model 2 so perhaps they aren’t that correlated?

    Notice that the FICO score variable is not even significant in any of the models! I find that stunning.

    My guess is that behavior score is measuring something like “tendency to be a sucker” (or less offensively, say “financial savvy” ; ) This seems extremely cynical, but does anyone have a better idea? It seems clear that savvy and payment are a useful pair of axes to evaluate credit card customers. Presumably someone who always pays but is not savvy is the ideal customer.

    P.S. This excerpt indicates all tests are Z scored. Not sure if that includes FICO/behavior/etc. demographic variables, but probably?

    In all of our estimations, we have standardized all the test score variables to have a mean of zero and a standard deviation of one.

  7. res says:

    There is an online appendix at the paper page:

    I think the Table 1 regression models in the paper use the Eureka Sample (N = 399) in Table A.3 (except Table 1 claims N = 480 observations, any idea what is going on here?)
    Given the number of different samples, I can see why they chose to put summary statistics in the appendix. Unfortunately, no correlations to be seen anywhere.

    The appendix also includes two additional analyses which might be of interest. There is text discussion, but these tables summarize the results:
    Table A5: Effects of AFQT on implied discount rates using NLSY
    Table A6: Effects of cognitive skills on financial and non‐financial outcomes using HRS

    One interesting wrinkle is how in Table A5 the Female and Log Earnings coefficients change greatly when Black and Hispanic race variables are included/excluded.

    They also teased me with a data set link which turned out to be basically a PDF saying “private.”

    • Replies: @James Thompson
  8. @res

    Thanks very much. Lots to work on.

  9. Realist says:
    @England patriot

    Educated, high IQ people seem far more likely to support mass immigration and left wing views generally than the less educated, lower IQ working classes do.

    What is the basis of your claim of Educated, high IQ people…? Because someone is a college graduate does not mean they are educated…or high IQ. Their course of study is important in determining that.

    • Replies: @neir
  10. Realist says:

    not true, engineers are notorious conservatives

    It appears you don’t know how to use this comment board. The block quote is the comment I am replying to. The comment below that is my reply. You are missing the value of the comments section if you don’t know how to use it.

    • Replies: @anon
  11. When it’s all said and one, the failure of the cognitive also-rans to make good decisions on their own behalf, is neither here nor there.

    Far more important, is the fact that they outnumber the cognitively-capable by 20-to-1 (at the very least, when considering matters of greater complexity – for example the average government policy), and their lack of cognitive grunt enables the political class to lead them by their retarded noses.

    TL;DR: I don’t give a fuck if they make systematic mistakes with their own money – but I take it personally that they get any say whatsoever on what happens with mine. Unless you can properly analyse a policy, and form a sensible estimate of the bounds around the future paths of benefits and costs… you should not be permitted to have a say in that decision.

    We don’t permit children – no matter how bright- to have input into political decision-making, even for policies that will affect the child’s near future economic prospects (because debt accrued by governments is underwritten by the kid’s futures taxes). Hell, we seldom permit children (again, no matter how bright) to have an equally-weighted say in how our households are run, or what clothes the kid can wear. We recognise that their relative lack of expertise, if permitted an equal weigh, could cause a dominant coalition that had suboptimal objectives.

    But we permit people less than 2sd above the mean IQ – who objectively are incapable of proper syncretic analysis[1] – to help the professional parasites to piss away everything they grift from us, and billions more… and to turn the screws on our rights … and these two processes (more grift and waste, fewer rights) proceeds monotonically, every year.

    [1] If you haven’t read a PIAAC study (or its precursors – LISS and ALSS), don’t be tempted to disagree with that high benchmark until you do. If you read a PIAAC study and come away thiking that an IQ of 130 suffices to properly understand complex information that is outside an individual’s specific domain… then your own domain of expertise doesn’t include statistics.

    • Replies: @James Thompson
  12. Gordo says:
    @England patriot

    Educated, high IQ people seem far more likely to support mass immigration and left wing views generally than the less educated, lower IQ working classes do.

    Somebody said stupid people believe X, clever people believe Y, very clever people believe X.

  13. dearieme says:

    What ho, doc! May I assume that you’ll be telling us about this sometime soon?

    • Replies: @James Thompson
  14. anon[383] • Disclaimer says:

    You make a great secretary, Realist, feminine perfectionism can always be harnessed and put to good use. Speaking of that, have you researched what the term “exothermic reaction” means yet?

  15. @dearieme

    Thanks, looks good, am reading it now.

  16. Factorize says:

    The left as intellectual class perhaps works best when considering nations that have already achieved a post-economic reality. Such nations often have marginal utility of incomes that are judged by the UN to be small. Yet, the right is right perspective seems highly applicable to the question: How can the economies of poor nations achieve prosperity? For these nations, economics is not a mere empty political debate as their marginal utility of income can be quite substantial. It would not be fair to say that the left has not played a productive role in the discussion about human development, however, capitalist style thinking has helped an enormous number of people out of poverty. After the collapse of communism this truth has become overwhelming self-apparent.

    It might not be widely appreciated, but capitalism has recently demonstrated an enormous ability to raise the human welfare of some of the poorest people on the planet, this is seen especially with the extreme success of the UN’s Millennium Development Goals, some of which were achieved 5 years ahead of schedule, and now the even more ambitious set of goals called the Sustainable Development Goals in which the 10 year target is to END poverty and have ZERO hunger. While
    there are grounds for reasonable criticism of this success, it would be wise not to reflexively assume that Western patterns of growth similar to the Industrial era working conditions chronicled by Dickens necessarily apply to nations such as China. In fact, it is plausible that many ordinarily Chinese firmly adhere to their new capitalistish social order as it has brought them so much prosperity in a very short time frame. Western Leftish style consciousness should thus not be assumed to be a universal outcome of the industrialization process. It is entirely possible that such thinking might not emerge in China as a direct response to their current development.

    This figure shows the high intelligence strategy of patience and waiting for social variables to be in place before launching a drive for development. England as it went through its industrial revolution
    actually had minimal annual economic growth for the 64 year period ending in 1820 (0.33%). During this time interval, the workers had 0.0% wage growth. 64 years without a raise? Yeah, I’d probably be on the picket line, too. The social variables were not set up for them for rapid growth, they had very high fertility rates etc, and no ready mass consumer export market to sell to; this is what happens when you are the lead train.

    As seen in the time series below, China has power drived to success in one nearly continuous motion. With England and other Western nations it was a bumpy ride. Yet, with the wealth generation machine of China, buying off the left becomes an obvious political strategy, simply keep the good times rolling and incomes surging. How could you have a communist counter-revolution with this amount of prosperity?

    This is income growth that has real economic relevance, not the hollow positional economies of modern nations with minimal marginal utilities. However, it should not be unexpected that China might soonish reimagine itself as an SJW positive nation. At these income levels it has nearly achieved such status. Ironically, it would indicate that they have truly entered modern reality. China is rapidly approaching the designation of a post-economic economy.\$state\$time\$value=2018;&marker\$axis_y\$which=gdp_per_capita_yearly_growth&domainMin:null&domainMax:null&zoomedMin:null&zoomedMax:null&spaceRef:null;;;&chart-type=bubbles

    This one shows growth versus income. China has had very steady growth patterns for many years.\$state\$time\$value=2018;&marker\$axis_y\$which=gdp_per_capita_yearly_growth&domainMin:null&domainMax:null&zoomedMin:null&zoomedMax:null&spaceRef:null;;;&chart-type=bubbles

    This is a very cool one: income versus TFR. IQ test item: High or low fertility? Answer was first arrived at by France, now there is a global rush for all nations to follow the lead. Notably, Russia was at the extreme high end at the start of the time series. IQ would plausibly correlate with how soon and how fast nations were able to make the deduction to choose low TFR. Surprising that nations never seemed to experiment with this variable in the past. Everyone kept doing the same thing within realizing that their behavior did not maximize their utility.\$state\$time\$value=2018;&marker\$axis_x\$which=children_per_woman_total_fertility&domainMin:null&domainMax:null&zoomedMin:null&zoomedMax:null&scaleType=linear&spaceRef:null;&axis_y\$which=income_per_person_gdppercapita_ppp_inflation_adjusted&domainMin:null&domainMax:null&zoomedMin:null&zoomedMax:null&scaleType=genericLog&spaceRef:null;;;&chart-type=bubbles

    This one dramatically illustrates the different paths to development taken by China and the UK (both with trails). The UK took a century to double income from ~ 1820 to ~1920. China turbocharged through these the same income interval in 10. These were the UK’s years of Dickensian conditions with wrenching social problems largely created by the economic transformation and a fertile soil for guilt socialism to grow. Trying to develop at TFR levels of ~5 seems almost futile, this is the hard way to economic success. With China you see this enormous sense of collective purpose starting around 1970 when the TFR moves steadily down to ~2 and then there is an overwhelming economic breakthrough, its first ever such sustained prosperity. The other variables such as urbanization %, education years etc. probably all follow similar conscious trajectories.

    UK’s development stalled out from ~1878 to ~1940. While China powered through the 8K to 16K income interval in 10 years; ~ 70 years for UK. It is isn’t always what you achieve in life that is important, but the strategic plan that allows you to reach your objectives in first class. China is now 40 years off UK’s development track and closing rapidly.

    16K is near an income level in which money no longer has economic importance- the great anomie begins. Selling copies of Das Kapitel in China today probably would not be easy, while Atlas Shrugged might be required reading.\$state\$time\$value=2018;&marker\[email protected]\$country=gbr&trailStartTime=1800;&\$country=chn&trailStartTime=1800;;&opacitySelectDim:1&axis_x\$domainMin:null&domainMax:null&zoomedMin:null&zoomedMax:null&scaleType=genericLog&spaceRef:null;&axis_y\$which=children_per_woman_total_fertility&domainMin:null&domainMax:null&zoomedMin:null&zoomedMax:null&spaceRef:null;;;&chart-type=bubbles

    These data visualizations at gapminder offer some extremely powerful tools to reconstruct the social and economic histories of the nations of the world. One can abstract away all the details of any particular nations past and see how important social drivers were involved in their development. I have almost no understanding of Chinese history, though you can almost feel the
    mind force that is at work to form their industrial strategy which then leads to astonishing wealth generation.

    • Replies: @James Thompson
  17. Factorize says:

    The time series at gapminder are fascinating! They reveal a great deal about the development path of nations purely from the stats. The UK took a difficult path; income stagnated for about a century at double subsistence. The society created would have been highly divided by marginal utilities at this per capita average, Orwell’s eternal boot becomes readily understandable. Basically, there appeared to be a nearly endless income stasis that prevented upward social mobility for many. Anyone with a conscience can see how a social duality could emerge from such an economic feature (yet such a duality will perhaps not be as obvious in Asian nations). While the US followed much the same route, the actual lived experience likely felt very different. With a near endless frontier, one would not even need to be aware of social differences that might exist thousands of miles away.

    Russia is another interesting example. The fertility rate was massive right into the 20th Century and then it plunged. This happened right near the time that motorized vehicles hit the market. Such technology would nearly eliminate the value of much of the labor force. With the large TFR a worker’s revolution does not, in retrospect, seem overly surprising. (With the UK, the relief valve was migration to the New Worlds.)

    The high IQ Asian nations took a different path than other Western nations. Japan and South Korea chose to round out the curve starting near TFR 4 and 2000. This seems a fairly good point to chose as you really want to try and avoid becoming trapped in the Dickens development quadrant bounded by 4K-8K and 4 – ~ 6+. The track taken by both of these nations resulted in a good human development result. However, China’s strategy has worked out even better. Getting down to near replacement ~2 TFR at subsistence income levels meant that the corrosive effects of the class divide could be avoided and everyone could unite in moving economic growth ahead. China has provided a near textbook example of how development should be done. They demonstrate to us that criticisms against capitalism are not universally truths; only specific instances sub-optimal development paths followed by Western and other nations.

    My one wish is that they are able to avoid the growth without development that has occurred in the US and other nations over the last 20 years. Hopefully China will be able to see through the illusion of increasing per capita incomes having no particular marginal utility for the individual or the community and instead focus on measures that reflect actual gains in human welfare (e.g., improved environment, improved worker rights etc.)\$state\$time\$value=2018;&marker\[email protected]\$country=chn&trailStartTime=1800;&\$country=gbr&trailStartTime=1800;&\$country=usa&trailStartTime=1800;&\$country=rus&trailStartTime=1800;&\$country=jpn&trailStartTime=1800;&\$country=kor&trailStartTime=1800;&\$country=prk&trailStartTime=1800;&\$country=npl&trailStartTime=1800;&\$country=bgd&trailStartTime=1800;;&opacitySelectDim:1&axis_x\$domainMin:null&domainMax:null&zoomedMin:null&zoomedMax:null&scaleType=genericLog&spaceRef:null;&axis_y\$which=children_per_woman_total_fertility&domainMin:null&domainMax:null&zoomedMin:null&zoomedMax:null&spaceRef:null;;;&chart-type=bubbles

  18. @Factorize

    Thanks for this very illuminating piece. I had just closed my Gapminder tab, having played with it for various countries some days before, and now immediately have to open it again.

  19. Factorize says:

    Dr. Thompson, thank you very much for the article on the bubbles and your response to my comment. I needed a reference for “life is getting better and better” and remembered your earlier thread about this, then watched the TED talk and found the gapminder website. {Hans is a great guy; he is really passionate about his data.}

    I found that these data visualizations provided an experience of profound insight. How could someone go about trying to explain the economic and social histories of these nations without immersing oneself in the data at gapminder? Data should drive the analysis of social science. However, I am afraid that too often researchers become entangled in the epiphenomenon of “he said this, they did that” and develop no conceptual understanding of their subject matter.

    After spending hours viewing and reviewing the animations, they have started to make a great deal of sense to me, and I can now start to create narratives of the histories that seem highly plausible. It is the closest I have found to psychohistory. Considering how vitally important economic development is for human welfare, why hasn’t a machine learning algorithm crunched through the data on gapminder in order to find the optimal solution to the question of how to grow one’s economy and society?

    The figure that I find most fascinating is TFR vs. income, as fertility is so centrally important for a variety of social processes. (Copy and paste the entire url below as it will not visualize properly otherwise.)\$state\$time\$value=1819;&marker\[email protected]\$country=rus&trailStartTime=1800;&\$country=fra&trailStartTime=1800;&\$country=fin&trailStartTime=1800;&\$country=deu&trailStartTime=1800;&\$country=usa&trailStartTime=1800;&\$country=esp&trailStartTime=1800;&\$country=ita&trailStartTime=1800;&\$country=pol&trailStartTime=1800;&\$country=prt&trailStartTime=1800;&\$country=ukr&trailStartTime=1800;&\$country=chn&trailStartTime=1800;;&axis_y\$which=children_per_woman_total_fertility&domainMin:null&domainMax:null&zoomedMin:null&zoomedMax:null&spaceRef:null;;;&chart-type=bubbles

    What I see in this visualization is that the yellow dots (some green) (Western nations) had a generally very difficult transition to modernity. Russia’s dramatically high TFR in 1900 along with moderate income would have placed an overwhelming weight on the far end of the scale with their subsequent revolutionary experiences following almost by logical necessity. When you invert the axes (TFR on X and Income on Y) and look at year 1900, you will see that almost all of the nations (yellow dots) that would later become Soviet satellites had TFRs above 5.

    The first gas powered car was demonstrated in 1885. How could anyone continue to believe that extreme fertility would remain viable in the 20th Century? Babies were being born that had no chance of producing wealth on the farm or elsewhere. Extreme fluctuations in Russia’s TFR began a few years before their revolution and would be present for many years. China also witnessed similar TFR behavior. Interestingly the nominal Western democracies had much less of this turbulence; they adjusted their societies over many years, sometimes decades to a lower TFR lifestyle. With China and Russia in particular, you can imagine that they simply wanted their lives to remain as they ever had been without the intrusion of modern reality interfering (or perhaps certain interests in their community wanted this). In this light, communists can be re-imagined as the great romantics.

    The UK with its ready access to foreign markets such as the US was forced to adjust to capitalist pressures incrementally and eventually accepted the logic of comparative advantage and the wealth that this brought. One suspects that the logic of market capitalism was less applicable to Russia and China due to their locations and particular geographies. Notice how low the TFR of several European nations was during the war years. How could a nation engage in total warfare with below replacement fertility? Even Germany was under 2 TFR during WW2. The only explanation I can suggest for such an inexplicable finding is that population momentum can override such demographic features over substantial periods of time.

    While the yellow dots illustrate a grinding path to development, the red dots (Asia) demonstrate development done right. Japan was the lead Asian nation in this transformation and they appear to have had a very good understanding of patterns of growth analysis. Starting in the late 1940s, they moved their economy on a fixed curve to growth. South Korea followed not long after.

    China has refined and optimized the strategy and appears to have put in an Olympic Gold medal performance for Economic Development. They landed and then flared their economy on what appears to be a pre-specified regression equation. (I wonder if one might simply fit a spline and then find the correlations between expected and actual). I really like what I see with China’s path; they managed to entirely bypass the dismal area of development occupied by the yellow dots where you have high fertility and moderate income (the UK occupied this zone for centuries). Dividing your community into classes causes long term damage and is best avoided.

    Many other nations are now on similarly impressive growth trajectories including Bangladesh, Nepal. In a previous blog post Nepal was noted as having the world’s lowest national IQ. What is so remarkable to me is that Nepal’s development path has shown much greater adaptive behavior than the paths taken by many other nations with much higher reported IQs. European nations went through a development process that involved child labor, slow growth over long periods, violent socialist counter-revolutions, two rounds of total warfare, etc., while several Asian nations (some with low IQ) avoided such turmoil. This would seem to establish that wise strategy can overcome manifest advantage.

    India is a particularly interesting development example. Many of the other Asian nations that went on to spectacular economic growth success (e.g. China) first had to go through what appears from the data to be extreme social instability as they tried to cope with the forces of modernity. Yet India appears to have never been stressed about becoming modern. Somehow they were able to cope with the changes that needed to occur without losing their composure. This is a highly notable and impressive achievement.

    • Replies: @res
  20. Thanks very much. I have run the sequence with “children per woman” rather than “lifespan” and will look at some other variables later. “Mean years at school” is linear and upwards when compared with income.

    Have you thought of writing up your comments, perhaps with more detail, as a separate post of yours for some other setting? It seems to strike at the puzzle of fertility being both a leading and trailing indicator of prosperity, depending on the level of understanding, or strategy as you put it.

    • Replies: @Factorize
  21. res says:

    India is a particularly interesting development example. Many of the other Asian nations that went on to spectacular economic growth success (e.g. China) first had to go through what appears from the data to be extreme social instability as they tried to cope with the forces of modernity. Yet India appears to have never been stressed about becoming modern. Somehow they were able to cope with the changes that needed to occur without losing their composure. This is a highly notable and impressive achievement.

    How much of that do you think is due to the British Raj introducing aspects of modernity? Colonialism had both good and bad aspects.

    At the end of the day though, the Indians were the ones who did it and should get the credit.

    P.S. Lots of food for thought in the rest of your comment. Thanks.

    • Replies: @Factorize
  22. Factorize says:
    @James Thompson

    Watching China’s “babies per woman” with a trail is very exciting. Starting in the 1970s a coherent policy of TFR reduction begins, then in the 1980’s economic growth materializes, and then in the 1990’s China locks into the below replacement TFR zone and the economy launches.

    With “Mean years of School”, I am also seeing a great set-up by China in the 1970s, with a mean of primary school completion by the early 1980s, and junior high school completion by the 1990s. The economic development community does not seem overly impressed with prolonged educations in the context of these often poor developing nations. They don’t appear accepting of the idea that it can take a few years for students to get it together (at least in Western nations). Instead their target is to have at least on average a primary school education which gives the economy a maximal return on investment. The efficiency of Asian educational resource allocation was highlighted by a Lorenz curve that showed an East Asian nation with a Gini = ~ 0.2 (i.e. relatively low educational inequality). India, however, had a great deal of inequality Gini =0.69. Indeed, half the Indian population received ZERO education which the text cited as being highly inefficient. Thus, the averages need to considered carefully.

    Regarding writing this up, I am working away on my sociology course and I am greatly enjoying it, though every time I make some progress I am thrown a curve ball. The gap minder site would be a great resource to base my final course assignment on, yet I am very interested in discussing the sociological implications of the approaching Cognitive Singularity Event.

    Yes, TFR in China and other nations on the visualizations show some focused social planning. You can almost feel the ahas as nations (such as China in 1970s) put together the functional consequences of lower fertility on financial and human (e.g. in education) capital formation, the knock-on effects for urbanization etc.. Fertility seems to me to be the central hub of the development process, though I have watched other visulizations and the basic human development factor can be perceived in many of them. Would be neat if they could do a PCA analysis and find the HD factor (Human Development). It is exactly when the whole force of human development can is stage managed and setup before the growth begins that you start to see this nearly magical economic liftoffs. Reasonably, we are now seeing a positive feedback effect in which other nations of whatever suspected IQ realize what they need to do to make their lives better and this is occurring in the context in which many nations (notably China and India) are now available as large consumer/commodity markets. This surge of capitalism appears to have been initiated in some nations with the end of communism in the 1990s.

    I also greatly enjoy changing the dot size (on the right of the gapminder tool) to represent one of the 3 levels of extreme poverty. When you put the trail on China with the first level extreme poverty as dot size, you see that the dot has almost disappeared in the last data point of the time series. It is like watching an ice cube of poverty melt away. The other levels of severity of poverty are also highly revealing. Changing the y-axis to the third level % of extreme poverty is another one of interest. In 2015, 27.2% of Chinese fell below this threshold. What I think is important to consider is that conditional upon being in the higher income subgroup, per capita incomes would be \$5000 per year higher than stated. So, income should drift upwards merely by bringing those people who are yet in extreme poverty into the economy.

    The big headline for me is the emergence of global super-capitalism. I had not been aware that this was underway until I looked at gapminder. When you set the tool to TFR on Y, income on X, what I find surprising is that there is now a clear pattern in which even some of the world’s poorest nations appear to be with the program. I can see the tell-tale growth signature of lower TFR and at least some economic growth happening in many African nations such as Ethiopia, Rwanda and several others. It is especially impressive that all three of these nations are “on the curve” and have been for many years. None of these nations have ever experienced such prolonged economic growth in their entire recorded histories. My impression, as informed by the Bottom Billion, had been that many of these nations were essentially undevelopable over the long-term. The numerous complex and interlocking negative forces at play made development seem almost impossible. If this is in fact shown to be in error, then over the next decade the SDG goals of ZERO hunger and No poverty might truly be realized; a very large victory for humanity.
    If we could get all the nations of the world to row the boat, then we could be heading for an age of universal prosperity.

  23. Factorize says:

    Hmm, actually my first hunch was this might be related to India as master of consciousness: Mind over Matter. However, setting up an economic development department possibly during British rule could have been extremely useful to them in their subsequent duties as economic managers. The British likely had a very detailed understanding of the ideas I have suggested as they had insight into the development patterns of so many of their other colonies. This knowledge could have been transferred to their Indian successors.

    Yet, I want to stay away as much as possible from such cognitive explanations. In a state of consciousness embracing behaviorism and the denial of mental events, I will port this philosophy over to the gapminder dataset: There are no cognitive events to analyze, only data points. I think this point of view would be helpful for others as I notice in my EcoDev text that without being compelled to stick to the data points, one can start simply making up your own narratives that do not fit the facts. Returning to
    the India data set, one thing that I notice is that India really was not that poor; \$1,000 annual income is poor though above frank starvation. With China, in various years between the 1940s and 1960s, they were at dangerously low income levels in which basic survival might have become tenuous. At such a narrow margin of survival one could easily imagine that a variety of delusions, economic cults and pyramids scams might displace sound economic planning. A 19th Century style Romanticism in which people try to overturn reality through the force of their own delusions does seem to be at play in the development histories of both Russia and China. One could well imagine that if one fine day a boat docked in port loaded with a million of tonnes of rice capable of possibly making redundant a billion Chinese rice farmers, then the sense of panic would have been overwhelming.The main difference with capitalist economies is that such adjustments are obstructed for decades but occur on a nearly continuous basis on market exchanges.

    Yes, India does deserve a great deal of credit. Their development path, when including the pre-growth phase, is possibly even more impressive than China’s.

  24. Factorize says:

    World Prosperity has arrived.

    The Gapminder visualizations conclusively demonstrate that the world has already transitioned into a state of near universal prosperity, and that those nations that remain near subsistence levels could easily be assisted by the world community in time of need. One of the best ways to see this is TFR vs. Income with the bubble size representing the size of each nation’s Total GDP PPP. In the year 1800, almost all nations had high fertility and low incomes; today, only a few do and all of these have relatively small economies. The UN’s SDGs of Zero hunger and No poverty planned to be achieved by 2030 could clearly already be guaranteed today by the world community as such a commitment would be supported by nearly the entire global economy with only a small number of nations (with small economies) who would qualify for assistance. Even these poorest nations can be seen in the visualization to be rushing to lower fertility and higher income (i.e., even the poorest nations are become wealthier). As the provision of such basic economic security for all is so easily achievable with the current global economy, the stretch goal could perhaps be to guarantee level 1 economic security and comfort for all. That this is even conceivable dramatically highlights the ubiquitous economic growth over the last 2 centuries, as only 2 nations in the world were above level 1 in 1800: the UK and the Netherlands.

    The world has achieved remarkably prosperity. Those wanting to stay current need to appreciate this. The Gapminder visualizations are great tools to explore our world of wealth.

  25. Factorize says:

    After continuing to process the global development database at Gapminder, it occurred to me that one highly useful way to understand the visualizations is simply as dots that do not represent any specific nations. Moving away from direct emotional connections with the movements of dots as nations allows one to be more objective.

    Further, one could think of the visualization with Income vs TFR as a game in which the objective is to maximize the human development of the globe at any particular point in time. Once securing my own basic welfare, maximizing this objective function on a global level is in my best self-interest and presumably would be understood by others to also be in their best self-interest. Optimizing human development in its truest sense means that people are engaged in activities that produce the maximum total utility given their innate ability level. From this maximum product, I then have the widest range of possible goods and services that I could consume and enjoy.

    From this starting point I will describe what I see with the dots in Income vs TFR. Starting with the yellow dots, I notice that for almost the entire 19th Century, there is little over all trend. On casual inspection, the yellow dots appear to be engaged in Brownian motion (for those without physics preparation, take this to mean random motion). While it is true that incomes increase and fertilities decrease through these decades; at the end of the 19th Century, TFR is still mostly above 5 and Income is typically below \$4000. The yellow dots have the highest incomes and generally lowest TFRs. During the first half of the 20th century, the yellow dots fall to replacement TFR and then over the next half century largely move in an uninterpreted push of growth.

    Next the red dots. For the entire 19th Century these dots are largely stationary; they become active in the first part of the 20th Century and in the second part their TFRs move down and their incomes increase. In comparison to the yellow dots, the red dots were able to transition through the various income levels in a decade or two instead of 2 centuries or more. It is also notable that the red dots reduced their fertility faster in the development cycle and then enjoyed a rapid growth phase (more of an L on the figure). One can perceive that the yellow dots might be attracting the red dots forward, and also that the red dots (especially the bigger two) are now also pulling forward other red dots and blue dots.

    Last of all are the blue dots. While starting intermixed with the yellow and blue dots, they remained largely with high TFR though some of these dots increased their incomes through much of the 20th Century and only began an en masse descent from high TFR and ascent from often low income in the 1980s and have been following a SSE trajectory since then. The blue dots might require another 20 years before hitting into sub-replacement TFR and then turbo-charging their economic performance in this growth zone.

    I think that it was worthwhile to go through this descriptive exercise as so often others will simply write up histories or social science commentaries (e.g., in economic development) without actual reference to the facts on hand. It becomes a story without the constraint of empirical evidence allowing the narratives to be more fictional than factual. Personal sentiments and ideology are inserted and obscure what the data reveal. It would be fascinating to have an economic development course in which there was no course textbook, just Gap minder, with the full course mark devoted to responding to the statement: “Explain and provide a development model of the economic history of the world over the last 2 centuries using the Gap minder datasets and visualizations.”

    As the thread is focused on psychometrics, it is notable that national IQ appears to decouple from
    the actual track of economic development taken. The reportedly high IQ yellow dots took a high fertility slowish growth route to mature development. The red dots which supposedly include a wide range of IQ took a similar track of lowish fertility first and then a growth spurt. I along probably with others on forum struggle with the concept of national IQ. With the red dots we see several nations with considerably disadvantaged IQs compared to the yellow dots, outperforming them in terms of their path to development. Economic development is perhaps one of the most fundamentally important g loaded test that a nation must solve, and yet here we see a clear outperformance by lower than higher IQ. It put stress on the belief in the national IQ concept. If all one needs to do in life to appear smart is to observe the smart people and duplicate their behavior, then it calls into question the fixedness of g. Economic development probably can be reduced more or less to about 10 important variables (of central importance is probably TFR, possibly a some minimum educational attainment (junior high?), functioning institutions, urbanization ….). If you can move many of these into a good growth zone, then you probably have almost assured a launch.
    Yet, if the formula is this simple, then the correlations that we have seen between economic development and national IQs might be somewhat hollow: If all that is needed for national success is to merely imitate the successful, then perhaps a similar strategy of imitating the successful at a personal level would also allow for a similar smoothing of the differences. It would be like allowing me to upgrade my intelligence simply by looking out into the world finding the smart people and becoming smart simply through my observing and reenacting their behavior. If this is correct then possibly psychometrics is not such a dismal science after all.

  26. Factorize says:

    Hopefully, those on forum will find these comments to be of some value. One probably should simply let the visualizations speak for themselves as they do provide profound insight into how the global economy and society has evolved through time. However, making simple observations can help flush out patterns that are present in the data and serve as the basis for possible generation of testable hypotheses. Yet, simply describing what is happening in the visualizations does not seem overly helpful as one could always make such observations oneself. The problem, of course, is that it is all too easy to merely glance over datasets without ever paying sufficient attention (i.e., not doing one’s homework). This deliberate SLOW thinking in my above posts is intended to move the chaotic dot patterns into higher order word patterns.

    Back to the dots. The yellow dots appear to have begun a coordinated growth pattern ~1950, the red dots ~1970, and the blue dots ~2000 (especially seen with a diagonal trajectory to the bottom right; would be helpful if there were a tool on Gap minder that would allow a set of dots in a quadrant etc. to be chosen and then see the growth trajectory through time of this set.) Now is the time of the blue dots, as their marginal utilities of income are higher than those for any others on the visualizations. Within the last 10 years there appears to have been a focused effort by the totality of the blue dots to coordinate a cohesive growth push. This truly might be the time in which the last high fertility low income nations transition to an economic state beyond absolute poverty.

    The power of these visualizations to illustrate the economic growth path of all of humanity is extremely impressive. Collectively the dots represent tens of trillions of dollars of annual output of the global economy; if one could tweak the behavior of these dots even slightly to a more optimal state, then the value creation would be in the billions of dollar per year possibly in perpetuity. By carefully observing the behavior of the dots and how this has changed through time, it seems clear from our current omniscient perspective with Gap minder that a better growth trajectory could have been taken by the dots and probably could be taken if only the dots displayed more a sense of self-consciousness than the zombie like motions that can be seen. Anyone so inclined wanting to reward me for these insights, Treasury bearer bonds would be entirely acceptable.

  27. Factorize says:

    Why did Russia maintain such high TFR into the 20th Century? I am very unclear about this. All the other nations of Western Europe had gradually brought down their fertility rates through time, though for whatever reason Russia maintained a total fertility rate of ~7 right to ~2014. {One possibility is that it believed that it was in a fertility race with Germany or other European nations. Once a wave of industrialization based upon automobiles began, it is possible that Russia then realized that high fertility were no longer a strategic asset. Also, perhaps it’s relative geographic isolation was a factor.}

    The Russian Revolution in this light might be considered more of a push to modernism through planned state intervention than as a counter-modernist uprising. Indeed even the recognition that the means of production (i.e., capital) is the driving economic force indicates a modernist perspective, as clearly with such high TFRs one would expect that there would have been substantial capital shortages. Communism and capitalism, thus, could both be seen as an advance over the pre-capital stage of economic development, with the only contentious issue of determining who would own the capital left open to argumentation.

    The erratic swings of the TFR from ~2014 – ~2045 demonstrate the difficulty in attempting to socially engineer reproductive behavior. One might suspect that strong conservative sentiments would be awakened as people attempted to cling to their centuries old way of life. This feature of wild instability of social life under communism is best avoided. Evolution not revolution. Incremental change allows one to go on a journey and hardly realize that one is in motion. Yet, with chaotic revolutionary change resistance can begin.

  28. Factorize says:

    I wish that when I was at school studying “A Tale of Two Cities” someone had directed me to the economic history of the UK to have a better insight into how difficult the “best of times – worst of times” had actually been. For without this context, it can simply read be as a novel from the past without gaining the insight that 19th Century England was very much as Dickens presented it. When you watch the animation below from Gapminder with trails on the UK and China, you see the dramatic lack of economic growth in the UK decade after decade during the 19th Century (the 18th Century had not been much better, probably even worse), while China has recently managed to power through all of this dismal development misery in the space of only a few years. In fact, A Tale of Two Cities, was written during some of the best of times, as the UK had seen 30 years of economic growth to 1859, though one suspects that much of this wealth did not actually reach average citizens.

    It is startling to watch as the first 35 years of the animation shows a decline in TFR with no increase in income. The Factory Act of 1833 tries to establish some sense of labor standards by limiting the work week for those under 18 to no more than 69 hours. 40 years of economic growth ensued while maintaining a constant TFR. One can imagine that with such high TFRs many in the population would perceive little improvement in their standard of living, and thus, Marx could only look on from his well-chosen perch from a London library and see capitalism at its worst. Yet, possibly this was still not even the worst as from ~1880s to ~1940s there was a 60 year period in which, while TFR steadily declined, there was little change in income, though there would be 2 brutal total wars fought during this time interval. In the post-war era, there was a baby boom that brought TFR up to ~3 that possibly perhaps added social instability, though once the TFR went sub-replacement ~1980, the most impressive economic in English history began and has continued to the present.

    By considering this visualization, one can certainly appreciate the concerns that Dickens expressed. It would also be difficult to dispute the similar sentiments expressed by Marx. Marx was not in London by chance; he must have realized that England was the textbook example of economic development done wrong. Without other nations to model its behavior upon, and without markets to consume its products and to supply it with products made to global economy of scale of specs, winning the race to development was more of a winner’s curse than blessing for the UK.

    The take home message for me is that the form of capitalism that Marx saw in 19th Century England was as abysmal as he described it. However, the form of capitalism that we now see in the 21st Century in places such as China and many others is quite different. Many of these nations are demonstrating very rapid growth and appear to have a very good awareness of what they need to do (e.g. to TFR, education etc) to create the conditions necessary for an economic launch. Given this, Marx’s analysis could be considered correct for the 19th, but not the 21st Centuries.\$state\$time\$value=2018;&marker\[email protected]\$country=gbr&trailStartTime=1800;&\$country=chn&trailStartTime=1800;;&axis_y\$which=children_per_woman_total_fertility&domainMin:null&domainMax:null&zoomedMin:null&zoomedMax:null&spaceRef:null;;;&chart-type=bubbles

    • Replies: @James Thompson
  29. Factorize says:

    Sorry for all the typos in my posts everyone! It is cringe worthy, though with the edit blocking on this forum, somewhat difficult to avoid. I greatly wish that these posts on Gapminder have caught the attention of others and encourage them to think about what drives the development process. Most notably more effective paths to development often become decoupled from national IQ.

    This might be best illustrated by an analogy. I spent months solving various sizes and dimensions of Rubik style puzzles; it has been one of my more memorable intellectual adventures. However, for much of the time, I had no clue whatsoever of what I was doing. I made hundreds and hundreds of mistakes and sometimes might even have appeared to making random moves. I knew what my goal was, though I was just very unclear how to arrive at the solution.

    This description reasonably could also be applied to the earliest pioneers in economic development such as the UK during the 19th Century. They had very little idea of what they were doing, though they kept plugging away nonetheless. My previous post demonstrated that it was an enormous struggle, though eventually, through trial and error, an ability to mechanistically manipulate their economy can be seen to emerge.

    My hunch is that highly intelligent people/nations will often display this seemingly incompetent behavior, as they will be drawn to solve difficult problems lacking cook book solutions. Indeed, I could probably transfer all of my knowledge about Rubiks gained from months of exertion in a few minutes. Right out of the box such a person would demonstrate high level twisting proficiency, while lacking any underlying understanding of how the solution had been found. If they were then asked to solve a slightly different twisty problem they would likely be entirely lost. Thus, they would superficially appear to have cube IQ, yet it would be almost entirely hollow.

    In terms of economic development, “solving” how to generate growth is difficult, applying a pre-solved program might be as automatic as applying an algorithm to solve twisty puzzles. If life,then, is an open book intelligence test, then perhaps IQ could be forked. Launch a nation into massive economic growth- see recipe 1; personal financial independence- always spend less than you earn, etc. The dismal logic of psychometrics might be overridden very easily.

  30. @Factorize

    If you slow down the pace of the years, then it is clear that the Great Leap Forward of 1958-1962 was no such thing.

  31. Factorize says:

    Dr. Thompson, thank you again for your article on Hans which lead me to Gapminder and the visualization tools. Oftentimes, if one can be put in the right ballpark, then that is all that is needed to get to the next step. The Gapminder tools have been close to a religous experience for me. After watching the animations run a few hundred times, you begin to sense the underlying logic that drives the development process.

    Yes, the period from the late 1950s into the early 1960s was a highly unstable time for China, while I am trying on the first run through to avoid the social/culture aspects and concentrate only on how the bubbles are moving around, it is difficult to entirely ignore the widely known history of that era. Profound socioeconomic instability seems to be a recurring feature of command style economies (it was noted earlier for Russia ~1914- ~1940), though is largely absent from the Western nations which is quite ironic as the inherent instability of capitalism was thought by Marx to be a flaw that would inevitably lead to the collapse of capitalism.

    While it is true that much of the time, capitalism does appear somewhat unstable, this instability actually leads to continuous adjustments to find the optimal state on the production frontier. Yet, with command style economies incremental change is largely absent, it is always steady as she goes, until there needs to be a course correction and then the entire economy enters into collapse as no sociopolitical mechanism exists to make such changes. An entire society becomes captivated by an ideology that can no longer solve their problems, though rejecting the ideology is not even in the playbook for such a circumstance. Forums (such as are of such importance to keep open
    dialogues that can imagine other potentials even when such potentials can be disturbing to some.

    I am not sure to what extent Western conservative ideologues were able to sway the move to capitalism in Asia during the 1970s and 1980s, though I would not want to jump in my time machine and replace today’s Western media messages with those that were present then. There were powerful voices which clearly enunciated pro-market sentiments that probably had at least some influence in how events unfolded. It is no small feat that possibly through these ideas that billions of people on this planet have been removed from extreme poverty.

    Ironically with China, their growth path from the 1980s actually does indicate a strong hint of command style capitalism (Asian nations call this industrial policy). The big question for me is how will China adapt once its growth trend goes off the flight path. China is rapidly transitioning to be like almost any other nation which is near its growth frontier and it is not completely obvious what the next move should be. You can only watch the animations of almost any other nation over the last 2 centuries on Gapminder to see an at times nearly random walk as nations struggle to find appropriate responses to their challenges: a near endless squabbling in democratic society then results. Thus, there is often a well-deserved apprehension that the leadership in Western societies are not entirely sure what needs to be done to solve various problems. What will happen when this idea becomes transparently clear in China in the not distant future? Participatory democracy might be a way to channel such energy as China moves away from a economic needs based economy.

    The topic of the psychometrics of IQ/scarcity also occurred to me as I thought of Gapminder. I realized that the high IQ groups that we often speak of on this blog are known to have binding constraints related to resources. When such constraints are present high IQ groups emerge through time, though without such constraints even reasonably closely related groups do not evolve towards higher IQ. What I find especially interesting about this likely commonly recognized observation is
    that if the binding constraint were then to be lifted due to a lack of scarcity, then one might wonder whether high IQ might then lead to maladaptive behaviors. For instance, consider a population that evolved under a caloric restraint due to the agricultural environment which then resulted in an enhancement of intelligence. Some time later the economy shifted and food was no longer binding.
    Yet, this people continued to behave as their ancestors by symbolically storing up resources for a rainy day. One wonders whether the psychology of IQ then might be thought of as somewhat maladaptive.

    Considering how inspiring I have found the visualizations on Gap minder, I think that it would be a great idea if they were to directly offer students courses through their organization. Hans’ videos show such a positive energy and excitement that I am sure many would want someone like that for their teacher than whoever might be assigned by a scheduling computer. We could be moving to a global educational marketplace in which those who are the most passionate, most dedicated and most truly interested in their topic will attract students for all over the world. The idea of a course of Economic Development with a focus on Gapminder would be very appealing to me. We have now migrated to a highly standardized educational model in which a small number of highly similar textbooks are taught to millions of students in each subject. If competition were introduced and new conceptions of topics could be made available it could greatly awaken student interests in their studies. I studied economic development carefully for months, though the Gap minder visualizations were able to provide deeper insight than could be provided by a textbook. In fact, I would love it if the entire school curriculum could be remixed so that it had a data/math flavor.

    Data Economic Development, English for Data Scientists, Psychohistory … . In the past such an idea might be casually dismissed as outlandish and ridiculous, though with the nature of our virtual world I am not so sure. Gapminder does have an educational outreach program, though perhaps it would be even better if they became an educational provider themselves as they are the ones with the excitement and passion for data. Offloading their datasets to teachers who might have very little enthusiasm would not be a great advance. Funnily enough, I am now preparing for a course in psychometrics, though instead of the more mathematical treatment that I would be most interested, this course will be word heavy with lengthy discussions of the ethics of IQ, the history of IQ, epistemology of IQ, though only scant and tangential mentions of the actual mathematics of IQ. Restructuring education so that the learning leanings of students were incorporated would have to increase student engagement; I would guess that such a change would increase my course interest by 1-2 SD. I do not ever remember being as mesmerized about ecodev when studying it in my course as I was when I ran the Gapminder visualizations countless times.

  32. Factorize says:

    Switch the y-axis to show yearly economic growth, x-axis to show time, use the zoom tool on the right, put trails on the UK and China, use the hand tool on the right to drag the years forward and back. This figure highlights the wide growth swings experienced by the UK (especially during the 19th Century) versus China. For instance, during midish- 1800s, the UK sometimes had a majority of years in decades that had negative growth. This is an amazingly erratic pattern of economic growth. In the modern era if there is a pair of consecutive negative growth is about as bad as it gets over a decade or two, even this can induce protests.

    Keynesian economic interventions are uncomfortable for me, though if government intervention can smooth out growth patterns, then perhaps this is for the good. A (muted) hurray for Keynesianism. UK did not merely have sluggish growth post-industrial revolution, but the growth that existed was highly erratic.\$state\$time\$value=2013;&marker\[email protected]\$country=chn&trailStartTime=1801;&\$country=gbr&trailStartTime=1801;;&axis_x\$which=time&domainMin:null&domainMax:null&zoomedMin=1960&zoomedMax=2013&scaleType=time&spaceRef:null;&axis_y\$which=gdp_total_yearly_growth&domainMin:null&domainMax:null&zoomedMin:-66.52&zoomedMax:189.7&spaceRef:null;;;&chart-type=bubbles

    The World in Data has some great figures that also speak to the greatly increased economic stability that emerged in the 20th Century. Integrated global markets when they are allowed to operate can produce amazing results. Here is Sweden’s real wages as it entered into this age of stability. (possibly it is not so much Keynesianism after all?).

    Here’s another nice one showing the stabilizing effect of trade on wheat prices. Starting ~1880s, America exports massive quantities of wheat to the UK and it crushes the price gap. In the 1910s, about 70 mega cwts almost eliminates the price gap. If 70 meg can’t do, what would? Strangely, into the 1990s a widening price gap reemerged. Possibly related to the Eurozone?

    One of the more surprising findings from gapminder should be reiterated: the blue dots appear to have gained a sense of consciousness of what they need to do to achieve economic success. It is remarkable when watching the animation roll forward (TFR versus Income) and watching this collective recognition by the world’s poorest nations that they need to get with the program ~1995: i.e., lower fertility, and a long list of other interventions. This is a truly remarkable achievement and one that I had been very unaware of. The UN’s 2030 target for a global end to poverty (operationized here as beyond Level 1 income) seems more or less doable. Importantly, with the apparently determined effort by the poorest nations to make the tough choices needed for a better life, it might no longer be a truism that helping them can often make their lives worse.

  33. roberto1 says:

    Perhaps the blacks who have equivalent SAT scores as high school seniors have reached their peak intelligence at that age while whites and asians continue to develop and get smarter. Many blacks certainly reach their physical peak sooner than whites. Maybe their mental peak as well.

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