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The TIMSS 2015 results for math and science are out and the results are pretty predictable.

All the data can be conveniently downloaded from here: http://timss2015.org/download-center/. See also Steve Sailer’s post from yesterday.

Math (8th grade)

timss-2015-math

Science (8th grade)

timss-2015-science

An extension of Heiner Rindermann’s observation on the differences between the two major international standardized tests – namely, that PISA is more a test of general intelligence, while TIMSS loads more heavily on specific curricular knowledge (Rindermann 2015) – is that the difference between the two can be used as a rough proxy for the quality of school systems.

After all, raising general intelligence through special schooling methods is well nigh impossible, but it is possible to teach how to do fractions properly. As I pointed out back in 2013:

However, a second possibility is that the PISA-TIMSS/PIRLS gap is a proxy for differences in the quality of educational systems. It is more feasible to prepare for the TIMSS/PIRLS than it is for PISA, which is closer to an IQ test and is, as such, more difficult to improve through policy interventions. It is nowadays fashionable to lambast the ex-Soviet and East Asian school systems for “rote learning,” “stifling creativity,” and whatnot. However, the data shows that under these systems, pupils perform well above the levels they “should” as indicated by their underlying IQ levels. Meanwhile, in places where “creativity” and “self-expression” are given full bloom, where science lessons focus on the evils of plastic bags in between sermons on LGBT appreciation and the progressiveness of Islamic civilization, academic performance is somewhat less than what might expect based on the local students’ apparent IQ levels.

The ex-USSR countries do not have particularly high IQs by developed European country standards – Russia itself is at around 97 – but it is nonetheless the best performing non-East Asian country in the TIMSS math test, and second after Slovenia in science. Kazakhstan comes just after Russia in math, which is highly impressive given that ethnic Kazakhs have an average IQ of just 82 relative a British mean of 100 (Grigoriev & Lynn 2014).

The Scandis are the opposite in this respect – pretty respectable native general intelligence, but much poorer than expected scholastic results. In the last TIMSS, only around 15% (sic!) of Swedish and Finnish 8th graders were able to do basic fractions. Normally I would have a hard time believing this, but the source was impeccable, and the horror stories about Swedish schools I’ve heard from Swedish acquaintances makes me willing to give credence to such results.

The East Asians get the best of both worlds, and for all the criticism directed at the education system in both the US and England – especially the marked Finland worship you get after every round of PISA – they do pretty solidly as well.

As per usual, the results from Africa and the Arabs are hopeless. As an an Arab Gulf State bigwig once said, “My grandfather rode a Camel, my father rode a Camel, I drive a Mercedes, my son drives a Land Rover, his son will drive a Land Rover, but his son will ride a Camel.”

 
• Category: Race/Ethnicity • Tags: Education, Intelligence, TIMSS 
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Further to my post on the remarkable failure of Scandinavian education systems to develop their students to anywhere near the levels indicated by their IQ potentials, a professor of mathematics at a Wisconsin university sent me data on the percentage of respondents in the TIMSS who gave the correct answer to the following question:

Which shows a correct method for finding 1/3 – 1/4?

A (1 – 1)/ (4 – 3)
B 1/ (4 – 3)
C (3 – 4)/ (3*4)
D (4 – 3)/ (3*4)

Below are the results. Do bear in mind that these are 8th graders we are talking about.

A B C D
Korea 2.7 6.9 4.2 86
Singapore 4.8 5.5 6.5 83.1
Taipei 2.9 7.7 7 82
Hong Kong 4 8.7 10 77
Japan 15.4 11.1 8.2 65.3
Russia 12.3 18.8 4.8 62.8
Average 25.4 26 9.4 37.1
US 32.5 26.1 10.7 29.1
Finland 42.3 29.5 8.7 16.1
Sweden 14.4
Chile 11.7

Finally, an international ratings list on which those smarmy, goody-goody Scandinavians don’t come on top! They barely do better than Chile, a country that got 421 (equiv. IQ ~88) in the PISA 2009 survey. Here is what he has to say on the matter:

One interesting fact is that among the 42 countries which tested 8th grade students, Finland had the highest percent of students who picked answer A and the third lowest percent correct. Chile had 11.7 correct and Sweden had 14.4 percent correct. The Finnish result is likely a surprise to the people who have praised the Finnish school system for their results on another international test, PISA. However university and technical college mathematics faculty in Finland will not be surprised. See [this] article signed by over 200 of them.

Anybody who suggests the progressive/neoliberal education policies of the Scandinavian countries are worthy of emulation should be presented with these figures and laughed out of the room.

The results for individual American and Canadian states:

A B C D
Mass. 21.4 20.8 9.9 44.4
Calif. 28.2 21.6 11 38
Minn. 23.5 26.3 14 35.1
Quebec 27.3 23 13 33
Ontario 27.7 22.4 14 32.5
Conn. 21.8 25.8 17.7 31.3
Alberta 34.7 23.7 12.3 27.8
(Republished from AKarlin.com by permission of author or representative)
 
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I had been meaning to post about this for a long time. Better late than never, I suppose.

The TIMSS and PIRLS are international assessments of academic ability in math, science and literacy that are conducted once every four years. They are similar to the PISA tests, although the latter are less purely academically focused and more a test of pure IQ.

Here are the results of TIMSS/PIRLS (h/t North Asian). And here are the results of PISA from 2009 for comparison.

As can be expected, they are highly correlated (r > 0.8 to be precise). This however makes the few differences all the more interesting. The gap between the East Asian countries and European countries, though substantial in PISA, is significantly greater in TIMSS/PIRLS. And most strikingly, both Russia and Israel go from being laggards in the OECD group to being at the forefront of the class.

Math (PISA) Math (TIMSS)
Korea 539 613
Sweden 494 484
Russia 468 539
Israel 447 516

From performing more poorly than Turkey in the PISA reading test, Russia soars to take second global position in the PIRLS.

Reading (PISA) Reading (PIRLS)
HK 533 571
Sweden 497 542
Russia 459 568
Israel 474 541

Meanwhile, some European countries, especially Sweden and Norway, plummet quite substantially.

What explains all this?

There are two possibilities. First, the TIMSS/PIRLS tests may have poorer samples than the PISA. For instance, we know from the latter that Moscow has a 10-point IQ lead over the rest of the country. If Muscovite pupils are over-sampled, then it’s quite feasible for the consequent result to be closer to say Hong Kong or Korea than to Greece or Turkey.

However, a second possibility is that the PISA-TIMSS/PIRLS gap is a proxy for differences in the quality of educational systems. It is more feasible to prepare for the TIMSS/PIRLS than it is for PISA, which is closer to an IQ test and is, as such, more difficult to improve through policy interventions. It is nowadays fashionable to lambast the ex-Soviet and East Asian school systems for “rote learning,” “stifling creativity,” and whatnot. However, the data shows that under these systems, pupils perform well above the levels they “should” as indicated by their underlying IQ levels. Meanwhile, in places where “creativity” and “self-expression” are given full bloom, where science lessons focus on the evils of plastic bags in between sermons on LGBT appreciation and the progressiveness of Islamic civilization, academic performance is somewhat less than what might expect based on the local students’ apparent IQ levels.

This all makes sense, I suppose. To be truly “creative” you first have to acquire a ton of skills and knowledge via the old method of applied hard work. Without that, “creativity” simply boils down to a sea of PoMo-waffling curmudgeons and MacBook-toting hipsters. And whoever needs that?

(Republished from AKarlin.com by permission of author or representative)
 
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A few months ago I posted a table and map of Russian IQ’s as derived from regional PISA performance. Those figures are based on Jarkko Hautamäki’s slideshow comparing regional PISA performance in Finland and Russia.

That material is a bit inadequate because, as had been my custom up that point, I was only making IQ estimates based on the Math and Science components of the PISA tests, and avoiding Reading to maintain reverse compatibility with my (now disused, in favor of just IQ) Human Capital Index. In light of some realizations that verbal IQ is no less important than numerical, I have updated the figures to include the verbal component as well. This doesn’t create any radical changes – the overall IQ only drops by 0.3 points – so I reuse the same map.

(Note that the legend on the map isn’t converted to IQ. “PISA scores, mean 500, SD 100, have to be transformed into IQ values, mean 100, SD 15, by adding or subtracting the deviation from the mean in the relationship 100 : 15 = 6,67.”)

Commentary

There are any numbers of comments one can make, but I will confine myself to the most important ones:

(1) In some regions, margins of error are high, as samples were low. Nonetheless, it is still possible to identify some concrete patterns. The overall estimate is very accurate because the sample was N=5,308 and representatively distributed across the country.

(2) Moscow pupils performed very well, at the level of the highest scoring OECD countries like Finland, Taiwan, and Korea. This is especially impressive considering the significant numbers of immigrants in that city from the North Caucasus and Central Asia, who come from poorly-scoring countries and rarely have good Russian. This is surely the result of a century of attracting Russia’s (the USSR’s) cognitive elite.

(3) St.-Petersburg and Tyumen oblast performed above the OECD average, while a few other regions performed at or only slightly below the OECD average.

(4) Among ethnic Russian republics, Siberian regions performed well, while the Urals and southern regions performed badly.

(5) Performance in ethnic minority republics differs dramatically. Many of the Turkic and Finno-Ugric regions, such as Tatarstan, Komi, Chuvashia, and Karelia did well; however, Mari El is a big exception. The Buddhist peoples of Asia, such as Chita oblast (now merged into Zabaykalsky Krai) and the Sakha Republic, performed relatively poorly, as did the Muslim North Caucasus region of Dagestan. Chechnya and Ingushetia would probably score around very low – probably in the mid-80′s. We can be pretty confident about that because their unemployment rates are nearly 50% despite tons of federal transfers.

Bear these figures in mind when considering long-term investments into Russia alongside with their business climate, corruption levels, etc.

PISA-derived IQ of Russian regions

The results by each of the 44 Russian regions which participated in PISA are reproduced below:

IQ
Moscow 106.6
Saint-Petersburg 102.6
Tyumen oblast 100.6
Novosibirsk 100.0
Chelyabinsk oblast 99.7
Omsk oblast 99.3
Samara oblast 99.2
Vladimir oblast 98.9
Tula oblast 98.6
Karelia 98.1
Tatarstan 98.1
Komi 98.0
Tomsk oblast 97.9
Primorie krai 97.2
Krasnoyarsk 97.1
Chuvashia 97.0
Udmurtia 96.4
Sakhalin oblast 96.4
Saratov oblast 96.0
Tambov oblast 95.9
Moscow oblast 95.6
Volgograd oblast 95.5
Vologda oblast 95.3
Kemerovo oblast 95.3
Altai krai 94.9
Astrakhan oblast 94.8
Ryazan oblast 94.7
Kursk oblast 94.6
Khanty-Mansijsk 94.2
Bashkortostan 93.4
Krasnodar 93.3
Perm krai 93.3
Rostov oblast 93.3
Nizhnij Novgorod 93.1
Voronezh oblast 92.7
Orenburg oblast 92.7
Kaluga oblast 91.7
Sverdlovsk oblast 91.6
Ulyanovsk oblast 91.5
Adygea 91.2
Stavropol 91.0
Mari El 90.1
Dagestan 88.7
Chita oblast 88.5
Sakha (Yakutia) 87.7
RUSSIA 96.0

Correlation with economic development

Doing the same exercise as I once did with Italy, the exponential correlation between IQ and GDP per capita (adjusted to reflect local prices; 2008) turns out to be R2=0.5262, if we only take into account those regions whose economies aren’t skewed by substantial natural resource sectors.

This is not as good as Italy’s R2=0.7302, but the result is still an amazingly good one in social sciences. In fact in Russia’s case it’s all the more impressive because its economy was for the most part built up under central planning, which isn’t as good as markets at allocating resources efficiently.

Even under a command economy, the principle still holds: Higher average IQ, higher human capital, greater productivity, greater GDP pre capita.

Other data on the Russian average IQ

(1) The PISA-derived IQ is 96.0.

(2) Richard Lynn estimates Russia’s average IQ to be 96.6 in his 2012 book Intelligence: A Unifying Construct for the Social Sciences.

(3) Heiner Rinderman estimates it at 97.3 in a 2009 paper.

The two most comprehensive authorities on international IQ’s, as well as the most comprehensive international standardized test, are all in agreement that Russia’s current average IQ is in the 96-98 range.

Other data on Russian regional IQ

(1) Map of average Unified State Exam (USE) scores among Russians admitted to institutions of higher education in 2010.

This is a biased sample because it only measures those Russians who were admitted to a university in 2010. It is not indicative of average regional IQ.

Data from Межвузовское исследование «Успеваемость студентов первого курсавысших учебных заведений России».

(2) Here is the same data by Federal District. They are, in order: Volga; North-West; Siberia; Central; Urals; Far East; North Caucasus.

(3) The share of “Olympians” (basically students who did really well and get benefits) in the annual university cohort. By region from top to bottom: Northern Caucasus; South; Far East; Volga; Urals; Siberia; North-West; Central.

There is nothing surprising about this. The Central Federal District contains Moscow. The North-West Federal District contains Saint-Petersburg, and I also suspect that ethnic Russians from the North-West region also have the highest IQ potential of all Great Russians because of admixture with Finno-Ugrics. (Finns and ethnic Estonians both have very high PISA scores).

(4) Unfortunately, Russia does not release regional average USE scores. It does this on purpose to avoid inciting ethnic enmity. (Basically, some regions – most of them non-Russian ones – systematically cheat and inflate their USE scores).

(However, I do recall visiting a site showing the number of people from each region who scored a 100/100 on USE subjects such as the Russian language, math, etc. It is a very rigorous exam and getting full marks on a subject like math is exceedingly hard; only a few hundred manage to do it every year if memory serves right. As IQ distributions are bell curves, it should be theoretically possible to get some idea of regional IQ’s by looking at the perfect scorers per capita rate. To do this however I will need to locate that site.)

Other EE Nations

The Ukraine didn’t participate in PISA 2009, but extrapolating from its TIMSS scores, its IQ would be around 93.1. Belarus would probably be considerably higher, because (1) they are basically genetically identical to Great Russians and Poles, and (2) they have done economically better than Ukraine since the 1990′s despite keeping much of their economy state-owned.

This section will be updated with info on other countries in the near future.

Slavic Genetic IQ Ceiling

The Slavic genetic ceiling appears to be around 100 based on the Czechs and Poles. The average height of young Russian men is about 175cm compared to 179cm-180cm among the Central-Europeans (Poles, Czechs, Slovaks). This discrepancy likely arose from the fact that Russia’s (and Ukraine’s) post-Communist transitions were far more catastrophic than those of the Poles and Czechs, involving a major deterioration in quality of nutrition during the 1990′s when the PISA 2009 cohort was growing up.

Russia’s meat consumption per capita (kg).

Russian nutrition has already returned to First World levels however; for instance, meat , fish, fruit, etc. consumption is now basically the same as in Europe or the US. This means that in the next decade I expect the Flynn Effect to kick off in Russia’s favor, raising its average IQ levels to their theoretical peak of 100 by the 2020′s.

(Republished from AKarlin.com by permission of author or representative)
 
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Now that I’m done with the Necessary Caveats, it’s time we had a look at why exactly HBD/IQ theories are both valid, and relevant to the real world. As I see it, their main import (as interpreted by me) can be distilled into a few logically consecutive, falsifiable statements:

  1. IQ tests are a valid, culturally fair measure of cognitive ability.
  2. It is hereditary.
  3. Race is real.
  4. There are racial/ethnic differences in average IQ that cannot be explained merely by reference to socio-economic or cultural factors.
  5. The US is an excellent “laboratory” to ascertain the average genetic IQ ceiling of different races and ethnicities.
  6. Average IQ influences prosperity, and general living standards.
  7. Consequently, knowing the racial constraints on average IQ’s – i.e., the IQ ceilings – we can estimate the relative development potential of different countries and regions.

All of them have have acquired a great deal of supporting evidence, even though they – or in particular, their linkage – remains taboo for the media and wider public discussion. By the numbers:

1. There is typically a large degree of correlation between various IQ tests, and academic achievement scores (1, 2). Nobody has yet discovered a test which has a negative correlation with a battery of other tests. This implies that there is a common “g factor” behind all types of cognitive ability.

Obviously this allows for very big variations within a single person. But within a group, someone who does well in one test will most likely also do well in another.

The argument that IQ tests are culturally biased is frequently made on the basis that they show differences in performance between racial/ethnic groups. This is a fallacy. In any case, there are IQ tests designed to be culturally fair insofar as they eschew words and test pattern recognition, such as Cattell Culture Fair III and Raven’s Progressive Matrices. These tests have a high correlation with the battery of other tests, i.e. they are valid reflections of g.

2. The scientific literature converges on a range from 40%-80% for IQ heritability. (1, 2) The correlation in scores between twins reared apart is around 75%-80%.

3. Is race a social construct? The commonsense answer is no. Consider that beyond the “my lying eyes” stuff (e.g. skin color/melanin content; epicanthic folds, etc.), there is also evidence of genetic differences in: Physical abilities (west African sprinters; Kenyan marathoners); conformity (Asians); lactose tolerance (whites); alcohol intolerance (Asians); even average penis size (large – Africa; Latin America; small – East Asia). The latter example isn’t nearly as… flippant as it seems, since testosterone levels have a large effect on behavior. There are multiple genetic disorders that only affect certain races or ethnicities, and race specific drugs are now coming online.

But ultimately, this is one of those cases where a picture is worth a thousand words.

This is a genetic map of Europe, superimposed on a geographic map (remarkable how it works out almost perfectly). Note that although there is some degree of overlap between European ethnicities, there are still clear clusters and centers of gravity corresponding to particular nationalities.

Now look at this genetic map (click to enlarge). See that dark blue oval to the center-left? That is Europe. Recall that even within that tiny space there are distinct clusters, with virtually zero overlap between, say, Greeks and Germans. Now note the vast distance that separates Europe from East Asia (center-right), and the three African clusters (bottom).

So it’s really just a minor matter of semantics. Some people shy away from using the word “race”, instead speaking of “genetic clusters”, “population groups”, “groups of common geographic ancestry”, etc. “Race” is short and convenient.PI

4. There is a vast body of global IQ scores (e.g. Lynn). They follow a consistent pattern: East Asian countries tend to score 105, European and Euro-settler countries 100, and sub-Saharan African countries 65-80.

The internationalized standardized PISA tests display the same pattern (as expected, since they load on the same g).

(Internationally, I think the culture argument makes some interesting points. E.g., the Protestant work ethic – reflected even now in the fact that the world’s richest and highest-IQ white countries tend to be Protestant. But there are two problems. First, possible narrative fallacy, e.g. Confucianism, with its connotations of traditionalism and conservatism, was once used to explain why Asian countries lagged behind Europe; but with their success in the past generation, the respect for learning, rule of law, etc. that it supposedly instilled is now sometimes used to explain their success! Can’t have it both ways. Second, what applies in one period can wane in another. Yes, Protestantism fostered human capital development by emphasizing independent Bible reading (i.e. more literacy!), which in turn helped early industrial growth. But today this effect seems to have receded into the past – see the success of south Germany, north Italy, France, Ireland.)

5. The US is an excellent “laboratory” to estimate the average genetic IQ ceiling of different races and ethnicities by virtue of its diversity; standardized education system that produces results that, when broken down by race, are superior to almost every other country in the world; decent equality of educational opportunity; no nutritional deficit among any population group; and post-Flynn effect status.

Within the US, all tests of cognitive ability – IQ, PISA (1, 2), SAT – replicate the global pattern. Though there is variance from test to test, but as a rule, the intelligence hierarchy is as follows: Asian-Americans; whites; Hispanics; blacks. The gaps between Asian-Americans and whites are narrowed than internationally (because Asian-Americans also include medium-IQ peoples like Filipinos and Vietnamese); and the gaps between whites and blacks are narrowed (because, unlike African or Haitian blacks, African-Americans enjoy better nutrition and education.

It must also be noted that whereas most of these tests indicate that Asians closed gaps (in reading, writing) and overtook whites (in math) over the years, there has been no sign of any significant convergence for blacks.

Is it because schools in poorer areas (inner city, where NAM’s cluster) are badly funded? No, per student funding tends to be broadly similar for both inner city and suburban schools. Besides, education funding doesn’t play a major role in results. In Italy, there is no correlation between school funding and performance by province. China gets PISA and IQ results higher than America’s despite spending a tiny fraction of the resources that the US lavishes on each of its pupils. Indeed, it probably doesn’t matter much, as IQ tends to be fixed by the age of the 5.

Is it because blacks come from poorer families on average? IQ is a far more persuasive explanation for why people are poor in the first place. Refer to The Bell Curve (Murray & Herrnstein).

US blacks (85-90) get far better IQ scores than Africans (65-80). These two facts are highly important because in Africa, the IQ’s of many populations are currently constrained by poor nutrition and (in some cases) the different psychologies of pre-industrial and illiterate peoples. In practice, and discounting variation (Africa is the world’s most genetically diverse continent, so it is not impossible that there will be some relatively high-IQ subgroups among them), it seems likely that the average IQ ceiling for African blacks is similar to the actual IQ’s of US blacks. I.e., maybe 85 (lower than 85-90, because US blacks have 20% admixture with whites).

US Hispanics score better than Mexicans or Central Americans, displaying IQ’s (or IQ equivalents) in the low 90′s (Mexico: 88-90; Panama: 84-80). Whites are at around 100. Asian-Americans tend to be in the low to mid 100′s, but there is huge variance (East Asians – higher; South-East Asians – lower).

7. Refer to Education as the Elixir of Growth III. There is a 0.43 correlation between the GDP (PPP) per capita of a country with its PISA/TIMMS scores, which rises to a stunning 0.84 once countries with a post-Communist legacy (low outliers), resource windfalls (high outliers), or offshore financial industries that constitute the bulk of their GDP (high outliers) are removed from the same. (Any correlation of >0.5 is an excellent one in social science). This implies a fairly rigid glass ceiling on GDP per capita for any one country in relation to its IQ. It’s largely invisible, as few people appreciate the importance of human capital to growth, but it’s most certainly there.

At the micro level, the g factor tends to be by far the best indicator of job performance (above grades, interviews, references, etc) – not only in “cognitive elite” jobs such as lawyers or physicians, but also to a significant extent even among menial workers. There is a correlation of 0.9-0.95 between employees in a certain profession and prestige ratings of those professions by the general public. The correlation between IQ and income is around 0.4-0.5.

The importance of average genetic IQ ceilings

We have a fairly strong and convincing (to me anyway) theory that average IQ ceilings depends on race, and that IQ (g, PISA scores, etc) are remarkable closely correlated with economic prosperity. Furthermore, it is almost certain that the causation is largely one way, at least once basic nutritional and literacy problems are solved; otherwise, the Chinese and Koreans would not be outperforming US Hispanics or African-Americans.

Following from the graph of Human Capital Index and income above, there seems to be a point past 450 – about 92.5, in IQ terms – at which (market-based) economies transition from middle-income status, to high-income. If Mexico could raise its human capital to about the levels of their compatriots in the US, this would (going by correlations) enable a massive expansion in its productivity.

Unfortunately, the average genetic IQ ceiling for African blacks is 85, maybe 90 at most. Nonetheless, if Africa could consistently raise it to even the former figure, it would then have a degree of human capital equivalent to today’s Brazil. Though true convergence with developed countries is precluded, reaching Brazil’s levels would be a gargantuan improvement for the living standards of the average African.

In general, it should be possible to construct a “potential IQ” (and corresponding potential GDP per capita level) for each country. They would look something like this (PISA/IQ format):

  • US (500/100) – All racial groups are already performing very close to their genetic potential (Asian-Americans (NOT East Asians) – low 100′s, whites – 100, Hispanics – low 90′s, blacks – high 80′s). The challenge will be in maintaining it (due to Hispanic immigration).
  • China (550/108) – It currently has 103(PISA converted into IQ)-105(IQ), but may still eke out a few more points by totally eliminating malnutrition. Should have no problem in becoming as rich as Korea or Japan with one more generation.
  • India (450/92.5) – Very low (and puzzling) 75(PISA)-82. But also malnutrition is still extremely high, as are endemic diseases; the vegetarianism of a significant portion of the population may also have a negative effect (protein aids brain development). My estimate is that average Indian genetic IQ ceiling is similar to Hispanics, but with huge variance due to caste/ethnic diversity.
  • Russia (500/100) – Moderate score at 95(PISA)-97(IQ). Smaller than ethnically similar Poland (99/100), due to 2 possible factors: (1) Academic focus to exclusion of more general g (Russia does much better on TIMMS, PIRLS); (2) Possible effects of highly prevalent alcoholism on the current cohort being tested. Poland’s score may represent a more accurate “Slavic ceiling.” Natural GDP per capita level would seem to be in between the Germanic countries and the Med, but resource windfall would nudge it closer to the former.
  • Brazil (460/94) – Today at 87(PISA)-85(IQ). Capping off the BRIC’s, the potential is derived by taking the estimated genetic ceilings of US blacks (with adjustment for Brazilian blacks having more admixture) with Med Europe ceiling, and weighing by population ratios.
  • Germanic Europe (520/103) – based on current scores, but will face challenge in maintaining it (due to immigration policies).
  • Med Europe (490/99) – based on Spain, Portugal, Italy results. In a way, one can see the Euro crisis – which is mostly affecting the PIGS – as the invisible hand’s way of bumping down the Med countries to a level more in line with their lower human capital (relative to the Germanic countries).
  • Turkey (470/96) – now at 91(PISA)/93(IQ), but potential based on Greece’s current scores; Turks and Greeks genetically similar.
  • Japan (530/105) – as now, no significant change as immigration is low. But economic difficulties due to debt, negative population growth, ballooning elderly dependency ratios.
  • Israel (?) – is globally irrelevant but a really fascinating case study, complicated by the discrepancy between Ashkenazi Euro-Jewish IQ scores (c.115) and Israel’s mediocre performance of 95(IQ)/94(PISA) which is hard to explain as Ashkenazi Jews still make up more than half of Israel’s population. Also lots of demography has to be taken into account. Deserves a separate post.
  • Australia, Canada (520/103) – as now, but will NOT face difficulties maintaining them because of their Cognitive Elitist immigration policies; as they also enjoy resource windfalls, they will probably do economically better than the rest of the developed world.

Based on the figures above, we can expect that the BRIC’s nations should in principle be able to converge to developed country levels. However, there are two major groups within the BRIC’s. China and Russia are already at a human capital level that enables convergence (China’s is significantly higher, but Russia is already richer, and also has the added bonus of a resource windfall). In contrast, Brazil and India are not currently at human capital levels that enable convergence; however, they do both have the potential to raise them to just the levels needed to break out of the “middle-income” trap and converge. But for that they have to develop their human capital to its full genetic potential. The quantity of the needed change is very significant and, even under rosy assumptions (e.g. +3 IQ points a decade until equalization with genetic potential), the process will take decades. Until they at least the low 90′s, they will remain stuck – especially Brazil, because it is already very rich for its human capital level – with fairly low long-term growth rates.

Whatever their average genetic IQ ceilings, it is highly advisable for all the poorer and low-IQ nations to: (1) improve childhood nutrition (e.g. free vitamin pills at schools seems especially low-cost/high-impact); (2) anti-vegetarian propaganda, where such applies; (3) study the experience of foreign countries, esp. the US which has had a lot of success with maximizing NAM scores, and Finland which (at least on PISA) manages to maximize white scores; (4) explore pharmaceutical and technological means of bridging their IQ gaps with the developed world (e.g. nootropics).

(Republished from AKarlin.com by permission of author or representative)
 
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Human capital (primarily education) is the single most important factor behind long-term productivity gains, and hence economic growth. The relatively high human capital of Russia and China, which is comparable to developed country levels, is the most important reason why I rate their future prospects much higher than those of the other two BRIC’s, Brazil and India.

But the internal distribution of human capital is also very important. For instance, in Italy there is an almost perfect correlation between regional PISA scores in Math and Science, and regional GDP’s. I have long wanted to find a similar data set for Russia, and I finally did so today in Jarkko Hautamäki’s slideshow comparing regional PISA performance in Finland and Russia. Based on the figures there I estimated the PISA scores (Math and Science) for Russia’s regions and compiled the map below.

russia-map-pisa-results-2009

The results by each of the 44 Russian regions which participated in PISA are reproduced below*:

Region PISA 2009
Moscow 546
Saint-Petersburg 519
Tyumen oblast 506
Novosibirsk 502
Chelyabinsk oblast 499
Omsk oblast 497
Samara oblast 496
Vladimir oblast 494
Tula oblast 492
Karelia 489
Tatarstan 489
Komi 488
Tomsk oblast 488
Primorsky krai 483
Krasnoyarsk 482
Chuvashia 482
Udmurtia 478
Sakhalin oblast 477
Saratov oblast 475
RUSSIA 475
Tambov oblast 474
Moscow oblast 472
Volgograd oblast 471
Vologda oblast 470
Kemerovo oblast 470
Altai krai 468
Astrakhan oblast 467
Ryazan oblast 466
Kursk oblast 465
Khanty-Mansiysk 463
Bashkortostan 458
Krasnodar 457
Perm krai 457
Rostov oblast 457
Nizhny Novgorod 456
Voronezh oblast 453
Orenburg oblast 453
Kaluga oblast 446
Sverdlovsk oblast 446
Ulyanovsk oblast 445
Adygea 443
Stavropol 441
Mari El 436
Dagestan 426
Chita oblast 425
Sakha (Yakutia) 419

There are any numbers of comments one can make, but I will confine myself to the most important ones:

(1) In some regions, margins of error are high, as samples were low. Nonetheless, it is still possible to identify concrete patterns.

(2) Moscow pupils performed very well, at the level of the highest scoring OECD countries like Finland, Taiwan, and Korea. This is especially impressive considering the significant numbers of immigrants in that city from the North Caucasus and Central Asia, who come from poorly-scoring countries and rarely have good Russian.

(3) St.-Petersburg and Tyumen oblast performed above the OECD average, while a few other regions performed at or only slightly below the OECD average.

(4) Among ethnic Russian republics, Siberian regions performed well, while the Urals and southern regions performed badly.

(5) Performance in ethnic minority republics differs dramatically. Many of the Turkic and Finno-Ugric regions, such as Tatarstan, Komi, Chuvashia, and Karelia did well; however, Mari El is a big exception. The Buddhist peoples of Asia, such as Chita oblast (now merged into Zabaykalsky Krai) and the Sakha Republic, performed relatively poorly, as did the Muslim North Caucasus region of Dagestan. Extrapolating from Dagestan, Chechnya would probably score around 400, i.e. like Brazil.

Bear these figures in mind when considering long-term investments into Russia alongside with their business climate, corruption levels, etc.

Finally, there is a table below comparing individual Russian regions with countries around the world. (The Ukraine didn’t participate in PISA 2009, but extrapolating from its TIMMS scores, its rating should be around 454. The OECD average is about 500.) I have bolded countries and Russian regions which are especially useful, in my opinion, for comparative purposes.

Region PISA 2009
China: Shanghai 588
Hong Kong 552
Singapore 552
Finland 548
Moscow 546
Korea 542
China 537
Japan 534
Chinese Taipei 532
Canada 528
Liechtenstein 528
New Zealand 526
Switzerland 526
Netherlands 524
Australia 521
Estonia 520
Saint-Petersburg 519
China: Macao 518
Germany 517
Belgium 511
Slovenia 507
Tyumen oblast 506
United Kingdom 503
Novosibirsk 502
Iceland 502
Poland 502
Denmark 501
Chelyabinsk oblast 499
Norway 499
France 498
Ireland 498
Omsk oblast 497
Czech Republic 497
Hungary 497
Samara oblast 496
Austria 495
Sweden 495
United States 495
Vladimir oblast 494
Slovak Republic 494
Tula oblast 492
Portugal 490
Karelia 489
Tatarstan 489
Komi 488
Latvia 488
Tomsk oblast 488
Luxembourg 487
Italy 486
Spain 486
Lithuania 484
Primorsky krai 483
Krasnoyarsk 482
Chuvashia 482
Udmurtia 478
Sakhalin oblast 477
Saratov oblast 475
Russia 475
Tambov oblast 474
Croatia 473
Moscow oblast 472
Volgograd oblast 471
Vologda oblast 470
Kemerovo oblast 470
Greece 468
Altai krai 468
Astrakhan oblast 467
Ryazan oblast 466
Kursk oblast 465
Khanty-Mansiysk 463
Malta 462
Bashkortostan 458
Krasnodar 457
Perm krai 457
Rostov oblast 457
Nizhny Novgorod 456
Voronezh oblast 453
Orenburg oblast 453
Israel 451
Turkey 450
Kaluga oblast 446
Sverdlovsk oblast 446
Ulyanovsk oblast 445
Adygea 443
Serbia 443
Stavropol 441
Mari El 436
Chile 434
Bulgaria 434
United Arab Emirates 430
Romania 428
Uruguay 427
Dagestan 426
Chita oblast 425
Thailand 422
Costa Rica 420
Sakha (Yakutia) 419
Mauritius 419
Mexico 418
Malaysia 413
Trinidad & Tobago 412
Venezuela 410
Moldova 405
Kazakhstan 403
Azerbaijan 402
Montenegro 402
Jordan 401
Brazil 396
Argentina 395
Colombia 392
Tunisia 386
Albania 384
Indonesia 377
Georgia 376
Qatar 374
Panama 368
Peru 367
India 341
Kyrgyzstan 331

* Methodological note: In reality, the figures given were for all three components of PISA (i.e., Reading, as well as Math and Science). I just assumed there is a perfect correlation in relative performance in Reading as compared to Math and Science (a valid one, I think, as the cross-national evidence indicates this relation is very close), and adjusted from Russia’s Math and Science score. The reason is for the Russian figures to have compatibility with my Human Capital Index, which is the average of PISA and/or TIMSS Math & Science scores.

(Republished from Da Russophile by permission of author or representative)
 
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Just in case you thought the correlation between human capital and economic development was an artifice of the post-socialist world, here is a similar graph (R2=0.4273) for all the world’s countries that have participated in the Math and Science portions of the PISA or TIMMS (8th grade) international standardized student assessments.

education-economy-global-1

The methodology is the same as described in the previous post. As you can see, the relation is every bit as strong at the global level. However, you may point to a few outliers. How to explain them?

Corruption, institutions and “governance”, “ease of business” indicators, etc. are all next to useless; in fact, it has even been found that some corruption is better for growth than no corrupt at all (though there is a critical point of extreme corruption at which it becomes deeply harmful).

But these are minor technical discussions. As far as I can see, there are only three major factors that explain why some countries diverge from the close correlation (R2=0.8393) between human capital and economic development observed in normal countries with a long history of capitalist development: (1) Major exporters and mineral exporters, relative to their total GDP; (2) Countries with a legacy of socialism and central planning; and (3) Countries with small populations that are also major financial, tax haven, or tourism centers.

education-economy-global-3

As you can see from the graph below, the conventional countries would form a nice best fit exponential curve (R2=0.8393). So would the countries with socialist legacies (R2=0.4908), albeit with greater dispersion and at a systemically lower level than the normal capitalist ones – especially once you remove those among them with substantial resource endowments. The same in reverse applies considering those countries that have managed to occupy niches in tourism, providing tax havens, and above all in financial services (R2=0.6014) – they do systemically better than the normal capitalist countries. The only countries to defy this iron correlation between are those whose oil production enables their populations to live off the rents from it (R2=0.0002); but these Rich Oilmen countries are very few in number, and concentrated in the Gulf.

The Capitalist Normals

The Capitalist Normals (blue) have long histories of capitalist development, and while some – like Australia or Argentina – may have large primary resource endowments, they cannot be said to dominate the economy. They have a very close correlation (at least by social science standards) between levels of human capital and economic development. The developed countries in this band occupy the global technological frontier. As usual, the outliers tend to be exceptions that prove the rule, so I’ll focus on them.

Argentina does slightly better than its PISA scores might otherwise indicate, but here there may be a few explanations: (1) Older Argentinians are far better educated than their counterparts in most of the rest of Latin America; (2) Low school-leaver human capital may be in part compensated by having the continent’s highest tertiary enrollment ratio.

UPDATE: The Argentina outlier is solved. According to Steve Sailer, Argentina’s low score is thanks to the scrupulousness of its school administrators, who – unlike most other countries – took the effort to track down the truants and drop-outs, who constituted 39% of its school-age population. Without this effect, Argentina’s score would have been about 40 points higher, i.e. above Mexico, and similar to Chile and Bulgaria, that is to say right where it should be. Sailer also makes the observation that since truancy tends to be more prevalent in poorer countries – a factor that is only rare adjusted for in the PISA tests – the gap in the human capital of older schoolchildren between the high-scoring developed world and the low-scoring developing world are, if anything, even higher than recorded in these tests.

Syria and Jordan both do a bit worse than their potential. Perhaps the influx of poor Palestinian refugees depresses Jordanian per capita wealth, while Syria is hampered by an extremely statist economy.

Israel is a major positive outlier. One explanation is that there is a lot of math and scientific aptitude diversity within Israel, with Arabs and Sephardi Jews performing badly and Ashkenazi Jews doing much better and perhaps a great deal of variation within the higher-IQ Ashkenazi group in particular; however, this is not borne out in the statistics, with the standard deviation for Israeli scores no higher than in many other countries. So why is it richer than, say, Turkey? No idea. Maybe because of US financial help, which is not inconsiderable. Maybe because the entrepreneurial Jew stereotype is correct even if the clever Jew stereotype isn’t.

Greece is a minor positive outlier, but their debt crisis is cutting it down to where it should be; as with Ireland a few years ago (it used to be an outlier in 2007 but is no longer). I guess the invisible hand has a sense of justice.

The United States is the most significant positive outlier, getting almost $10,000 more GDP than would be warranted by its human capital levels, which are comparable to Sweden or Australia. One major factor is surely that Americans simply work much longer than Europeans; their productivity levels, output per hour worked is, in fact, virtually equal to that of Germans or Swedes. It also helps that it has plentiful land per capita with the world’s best natural riverine transport system – and useful land, not permafrost like in much of Russia or Canada – and controls the world’s reserve currency.

Korea is a major negative outlier, one of the world’s cleverest countries but one that hasn’t yet even fully caught up with Italy. However its case – as is, to a lesser extent, that of Finland and Taiwan – is explainable by the simple fact that for them, “convergence” isn’t a finished process; they continue to grow relatively rapidly by already-developed country standards, they do not have any debt or fiscal crises, and they can expect to continue moving in the direction of ultra-rich countries like Switzerland and Singapore in the next decades. That said, Japan – also a minor negative outlier – indicates there may be diminishing returns to ever more impressively educated populaces.

It is important to emphasize, also, which countries in this category are NOT outliers: Brazil, Mexico (despite a substantial oil endowment), Indonesia, India, and Turkey. Also South Africa, which is not in this database, but can be inferred to have very low human capital based on its still prevalent illiteracy and very low TIMMS (4th grade) results. Now Brazil and India are regarded in the Davos press as superior to Russia, and in the long-term superior to China also (by virtue, so their argue, of their democracy and “demographic dividends”); the other nations cited here have all at one time or another been suggested as replacements for Russia in the BRIC’s.

If we are however to regard human capital as the main determinant of the natural level of economic development, and the “potential gap” between the two to be the most reliable determinant of future growth prospects, then the best BRIC by far is China, followed by Russia; to the contrary, India and Brazil (and any prospective BRIC’s members) are unremarkable.

The Red Tigers

The Red Tigers (green) are countries with major legacies of socialism and often central planning. It is interesting to observe that countries where reforms started earlier (e.g. ex-Yugoslavia, East Central Europe) and where markets played a greater role under socialism are much closer to the “equilibrium level” indicated by their levels of human capital. That said, despite their relative affluence, their “potential gaps” are still substantial; for instance, the Czech Republic and Poland have human capital basically equivalent to that of Germany or the US, but are still up to twice as poor in terms of GDP (PPP) per capita. This implies that this group will continue converging to advanced developed countries in the years ahead.

Practically all outliers in this group are negative, and were already covered in the previous post. But to recap:

China is the mother of all outliers, and no doubt a very significant one – it has 1.3 billion people living at lower middle income levels (although a few provinces remain distinctly Third World) but their high-school students now outperform the US and most of the EU. In my opinion this is the result of a very special situation.

The Maoist state suppressed economic growth to a degree unprecedented in virtually any other state in the socialist camp; it also started from a very, very low base. But despite its ruinous economic views, its social policies – including basic education – were implemented far better than in almost any other low income country, and that on top of (a) their reverence for scholarship that only had its equivalent in the Protestant emphasis on literacy and (b) the observed high IQ of Chinese overseas communities which may have a genetic component. This means that when China introduced market reforms, the “potential gap” between its human capital and existing level of economic development was vast to a degree probably unprecedented anywhere else in the world and in all history. Hence thirty years’ worth of 10% GDP growth that shows no sign of stopping (in fact, China’s relative performance exceeds that of any other Asian tiger in their stage of rapid development). And barring a major and unexpected discontinuity is should NOT stop until China reaches the level of per capita wealth Korea, Taiwan, or even Switzerland.

One minor caveat is that rapid development means that this “potential gap”, while vast, may no longer be quite as vast as indicated by the graph. Note that according to some estimates, China’s PPP GDP is now larger than America’s, which would give a GDP (PPP) per capita of $10,000-$12,000 or so.

Armenia, and to a lesser extent Serbia and Bosnia-Herzegovina, are negative outliers. Their cases are clear; they suffered from destructive wars in the 1990′s, and in Armenia’s case it remains surrounded by neighbors from hell.

The ex-Soviet countries without oil, such as Ukraine and Moldova, tend to be deeply negative outliers. One reason is that they reformed slowly (while the Soviet-era system crumbled about them), and late; and have suffered from particularly incompetent and avaricious governance; as I argued in a prior post, Ukraine never left the period of “anarchic stasis” that characterized Russia in the 1990′s. However, Ukraine’s perspectives aren’t looking good, at least in the short-term. Perhaps it’s because corruption, etc. are still so high that – while they normally don’t have much of an effect – reach such critical levels that they significantly stymie growth; an alternate, and more benign, explanation is that Ukraine’s GDP (PPP) is underestimated – it was not adjusted upwards like Russia’s in the recent OECD and World Bank recalculation of relative prices – meaning that Ukrainians already live better than the statistics indicate, their “potential gap” is smaller, and thus understandably there is less room for fast GDP growth.

Azerbaijan, Kazakhstan, and Russia are curious creatures in that in their case, the resource windfall boon works against the socialist legacy curse. This means that, despite that they are ex-Soviet – i.e., the economy was more deeply distorted and reforms started later than in much of the rest of the socialist camp – they are nonetheless on the upper part of the human capital and economic development curve, along with countries like the Czech Republic or Romania, and are not outliers like Ukraine or even Latvia.

At this point I would also like to demolish the myth of Georgia as a shining beacon of unimpeded economic progress in the Caucasus. It will not transform into Switzerland or Singapore, or even Estonia, any time soon, i.e. the next few decades. Its human capital is very low and it is already fairly close to the maximum economic potential enabled by it; this may be an achievement on Saakashvili’s part, who massively – one might say recklessly – liberalized the Georgian economy, which caused (or accompanied) a big growth spurt in the mid to late 2000′s. But it is unsustainable, first because Georgia is now far nearer the limits imposed by its low level of human capital; second, because if anything human capital has declined under Saakashvili (e.g. tertiary enrollment has nearly halved as university fees exploded, making post-school study much less affordable for ordinary Georgians).

The Oilmen

The Oilmen (red) are those very lucky countries with lots of oil and small populations. It is almost always oil; the sole exception in my sample is Botswana (diamonds and minerals).

Unlike either the Capitalist Normals or the Red Tigers, there is no correlation between levels of human capital and economic development among the Oil Guzzlers. That is because the oil production per capita effect, which relies on geological luck of the draw, overpowers all others. That said, they could be divided into a few distinct groupings.

(1) The Rich Oilmen. Qatar, Kuwait, and the UAE, and to a lesser extent Saudi Arabia, Bahrain, and Oman, are all fabulously rich thanks almost exclusively to their resource endowments. Their human capital is unimpressive and would not otherwise come anywhere near supporting their oil-enabled luxurious lifestyles. Their attempts at diversification are to be lauded, e.g. finance and tourism in Dubai, or journalism in Qatar, but these efforts are critically reliant on attracting foreign specialists with (oil) money so they are not sustainable.

(2) The Casual Oilmen. Norway and Russia benefit greatly from their oil windfalls; for a start, they largely rule out fiscal worries. Benefiting from uninterrupted capitalist development, Norway has transformed itself into one of the world’s wealthiest nations; even if it didn’t have oil, it would still be as rich as Sweden. Russia will probably never reach Norway’s level because the latter has far more oil per capita; nonetheless, it has a decent manufacturing base (e.g. capable of making stuff like GLONASS and advanced fighters) and a moderately growing economy that has no reason not to converge to Italy by 2020 and perhaps Sweden by 2025 or 2030. Tight supply and growing demand means that it is very unlikely that oil prices will fall and remain low in the foreseeable future, but even on the off chance that they do, Sergey Zhuravlev has calculated that the effects on Russia’s economy are going to be modest in the medium-term and negligible in the long-term.

(3) The Poor Oilmen. Oil is likewise of help for plugging budget holes to Algeria, Kazakhstan, Iran, Venezuela, Mexico, and Azerbaijan. However, unlike the case for the Rich Oilmen, their populations are too numerous to live off in sumptuous comfort off the rents; oil production per capita is too low. This means they can’t fly off into the stratosphere like the Rich Oilmen. They need non-oil based growth to become rich. But unlike the Casual Oilmen they are unlikely to achieve much of that because their human capital levels are very modest. If there is an oil crash, past experience – e.g., Venezuela in the 1980′s and 1990′s – suggests that they will be in for many years of stagnation and fiscal crises.

The Bankster Nations

The Bankster Nations (crosses) tend to be small countries which have managed to become major financial, tax haven, or tourism centers. Their GDP (PPP) per capita tends to be higher than the level suggested by their human capital, but not to anywhere near the same extent as the Rich Oilmen.

Liechtenstein is the biggest outlier in my database; its human capital is respectable, but its GDP (PPP) per capita at $141,000 is literally off the chart. No wonder when their population is a mere 30,000 souls. Luxembourg, Singapore, and Hong Kong have all carved themselves out very profitable niches as financial centers serving neighboring economies that are much bigger but also more regulated. Macao is Asia’s gambling center (and unofficial a conduit for Chinese money laundering). Cyprus serves a similar money laundering and reinvestment function for Russian nouveux riches, to the extent that the Russian government recently bailed out the island. Mauritius is a tax haven, and is also – along with Malta and Trinidad & Tobago – a popular vacation spot.

Switzerland is an entire nation that has devoted itself to financial services (including the more shady, secretive ones) as well as other very high added-value stuff like precision engineering and pharmaceuticals. And it has become extremely rich.

Without exception all these places are doing better or far better than the average Capitalist Normal country. That said, even here there is a definite correlation between human capital and GDP (PPP) per capita. These activities may require less hard work and scruples than is typical for other industries but they still require brains – especially for the high-end finance stuff. Not so surprising then that it is the highest human capital countries like Singapore, Hong Kong, and Switzerland that have become so prominent in it.

(Republished from Sublime Oblivion by permission of author or representative)
 
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That title sure caught you attention? Good. Now for the 1000-words-in-a-picture evidence.

gdp-human-capital-socialist-bloc-3

Human capital refers to educational attainment, as measured by the results of the PISA and TIMMS standardized tests*. As you can see, there is a very close correlation between human capital and GDP (PPP) per capita. The exceptions all confirm the rule. For now I have only done the post-socialist space, because of its sheer variety – different cultures, different rule-of-law and ease of business environments, difference resource endowments and political systems – which lets me illustrate just how irrelevant all those factors are compared to human capital. The same laws hold at the global level, and I intend to cover it in a consequent post, but that involves a lot more work so for now I’ll just settle for this.

The Near Developed nations have respectable GDP per capita (approaching the poorer members of the classical developed world, such as Portugal and Greece), and levels of human capital that are basically equivalent to those of the rich countries. They are close to converging with the developed world, so growth tends to be relatively slow by the standards of more dynamic (but much poorer) emerging markets, on the order of 3%-5%. Despite their low positions, neither Russia nor Latvia are outliers; more recent calculations by the World Bank give Russia a PPP GDP of $20,000 for 2010, wedging it in with Hungary, Poland, and Lithuania; while Latvia was very severely affected by the late recession. The Czech Republic is close to being a positive outlier: One reason may be its proximity to developed Germany, another the early start of its reforms.

The Red Train is, basically, China. Its searing growth rates aren’t because of its state capitalist system or the Confucian work ethic, but because its human capital is wildly out of line with its economic development. Its high school graduates are ready to operate complex machines and staff the most hi-tech enterprises, but the legacy of Maoist economics – which, hard as it is to believe, were even more inefficient and offered fewer incentives than under Soviet central planning – means that a significant share of the population still uses oxen-pulled plowshares for farming. So it is no wonder that, with its markets freed, the system is straining to catch up – at the pace of 10% per year – to its equilibrium place along with South Korea and Japan. Note also that according to some estimates, China’s PPP GDP is now larger than America’s, which would give a per capita level of $10,000 or so; significantly higher than the figure displayed on the graph.

The Slow Middle are countries with moderate levels of human capital, and they are significantly poorer than the Near Developed nations; for them, convergence to developed country levels is still far away. Their growth rates are modest because their economic development is only slightly, if at all, below the level natural for their degree of human capital. While Turkey and the Balkan countries don’t look that far away from the poorest Near Developed countries, it should be noted that all three are currently suffering from major disbalances that could well end up in Latvian-style crashes. To set themselves on a sustainable development path, they will have to raise their human capital levels by at least another notch. The two negative outliers are Ukraine and Armenia. Ukraine has just been horrendously mismanaged; as I argued in a prior post, it never left the period of “anarchic stasis” that characterized Russia in the 1990′s. That said, the Ukraine may not so much of an outlier; its prices are low, and salaries are comparable to Serbia’s, so its PPP GDP may well be substantially underestimated. Armenia is an even more glaring outlier, with human capital that is comparable to the weaker Near Developed members, but I suppose huge military spending and being blockaded on two sides, and bordering Georgia and Iran on the other two, isn’t conductive to prosperity.

The Doldrums consist of Georgia and Moldova. Georgia has had good management under Saakashvili (it is now far less corrupt than Russia, or its Caucasian neighbors, and Ease of Business is very good by global standards), and Moldova has had bad management; nonetheless, their differences in GDP per capita are modest. The problem is that their schools produce people who are, largely speaking, functionally innumerate; so no matter how hard Saakashvili wills it, Georgia isn’t becoming a Singapore of the Black Sea any time soon. Sustained convergence to developed country levels is out of sight; radical improvements in human capital will first have to be made, and they can’t happen in the space of a few years; they require decades. The Saved By Oil group include Kazakhstan and Azerbaijan. They are as wealthy as the Slow Middle, but as stupid as the Doldrums. But in a world of high oil prices they should be relatively well off.

Kyrgyzstan is in the Third World. Although its Soviet-era legacy has enabled it to provide universal primary schooling, the quality of the products of that schooling is comparable to India – at the very bottom of the global heap. It may achieve decent growth of perhaps 4% or 5%, but it will be from a very low base.

There are several conclusions to this. First, there are only really three important factors to economic development. First, above all, human capital, i.e. primarily, the quality of education. It makes sense on an intuitive level and there’s a ton of literature in support but the graph above makes it… graphically clear. Second, resource endowments, when highly concentrated per unit of non-resource extraction based GDP – as in Kazakhstan and Azerbaijan, but not quite in Russia – will hugely, and positively, influence the level of GDP (it does play a substantial positive role in Russia but it should be noted that Russia’s oil production per capita is less than Canada’s, and its oil production per unit of GDP is far less than Kazakhstan’s or Azerbaijan’s). Third, political management. Especially incompetent regimes such as the ones in Ukraine will hold it back from achieving the full potential enabled by its human capital; if its monstrously incompetent and repressive of growth, as in Maoist China, the resulting gap between reality and potential can develop to truly vast proportions; consequently, when the most egregious barriers are removed, as during the late 1970′s, growth takes off at truly prodigal rates.

Equally important is the fact that things commonly cited by Thomas Friedman, Davos Man, The Economist, The WSJ, The Financial Times, the respectable experts, etc. etc. as important for economic growth turn out to be largely irrelevant. Ukraine is more democratic than Russia and Kyrgyzstan is more democratic than China, but their growth profiles are much worse regardless. Russia is fairly corrupt – though not nearly to the extent implied by Transparency International’s Corruption Perceptions Index – and so is Hungary, and they both have much poorer Ease of Business indicators, but they are both much better off than cleaner and business-friendly Georgia. Latvia was part of the “clean” Baltics, but that didn’t stop it from tumbling to the bottom of the Near Developed pack in the wake of the global financial crash; is it too much of a coincidence that Estonia, which has a slightly edge in human capital, managed to hang in tight? The three biggest outliers by far in a best fit line on the graph – China, Kazakhstan, and Azerbaijan – are all patently explainable by a Maoist legacy and oil windfalls.

Suffice to say, most of the former socialist bloc – most of the world, in fact, but that’s for another post – is at precisely the economic development levels implied by their levels of human capital. There are exceptions, most especially China, but to a lesser extent also many of the poorer Near Developed countries, where the distortive legacy of central planning has resulted in lower current economic development levels than should otherwise have been the case had markets been allowed to function; nonetheless, they tend to compensate with respectable growth rates, as the reality – potential gap seeks closure. If you need to blame someone for why your country is poor, don’t bother trotting out the usual canards: State interference, authoritarianism, corruption, anti-Western policies, privatization and liberalization will solve everything! (liberal canards); neocolonialist exploitation (leftist canards); Russian exploitation (East European nationalist canards). More likely than not your countrymen are illiterate, innumerate slobbering buffoons and it’s as simple as that.

* Human capital was calculated by the average of PISA 2000 scores in Math and Science, and of TIMMS 2008 scores in Math and Science. Where data sets for both assessments existed for a particular country, the TIMMS score was – on average – around 7.7% higher than the PISA score, so I adjusted the former down by that amount. The human capital index was calculated by taking the average of the PISA and adjusted TIMMS scores where applicable, or either the PISA score or the adjusted TIMMS score where data for only one of them existed.

(Republished from Sublime Oblivion by permission of author or representative)
 
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What are the reasons behind the wealth and poverty of nations? Since this question has exercised the minds of thinkers from Adam Smith to David Landes, Jared Diamond and Richard Lynn, I decided to take a look at it myself. I came to the conclusion that while geography, macroeconomic policies, resource windfalls and the microeconomic environment do play important roles, by far the most important factor is the state of a country’s human capital – things like literacy rates, school life expectancy and performance on international student assessments.

This is not a new idea. A Goldman Sachs report, Dreaming with BRICs, noted that:

Many cross-country studies have found positive and statistically significant correlations between schooling and growth rates of per capita GDP—on the order of 0.3% faster annual growth over a 30-year period from an additional one year of schooling.

However, I think education is much more central to this. The problem with using years of schooling as a yardstick is that in many middle-income countries, like Argentina, Turkey or Brazil, the amount of schooling is converging to that of the developed world, but the quality isn’t. This is attested to by their performance on international student assessments like PISA. For instance, in the 2006 PISA Science assessment, only 15.2% of Brazilians were at Level 3 or higher (the threshold for moving beyond purely linear problem-solving), compared with 47.6% of Russian, 51.3% of American and 66.9% of Australian students. Is it really then surprising to discover that from 1997 to 2007 purchasing power GDP per capita in Brazil and Russia, both medium-income countries, has grown at 1.3% and 6.0%, respectively, i.e., that Russia is playing the game of economic catch-up much more successfully?

I collected educational statistics on 65 countries and used a formula to work out a Human Capital Index (HCI), relying on three main stats – the literacy rate, PISA/TIMSS/PIRLS performance and tertiary attainment. I then compared this with their purchasing power GDP per capita and its average growth rate for 1997-2007. The results are in the table below.

Source: CIA World Factbook for literacy rates, GDP per capita, 2007 GDP per capita growth; PISA 2006 executive summary for Maths, Science, Reading stats (note: China, India are guessed); eighth-grade Maths, Science performance from Highlights from TIMSS 2003; fourth-grade Reading from PIRLS 2006; tertiary enrolment, 1997-2006 GDP per capita growth from World Bank. M1 and M2 refer to the mean of a country’s scores across PISA and TIMSS/PIRLS, respectively, divided by average across all participating countries; if there’s a figure for both M1 and M2, then M3 = (M1+M2) / 2; if not, M3 = M1 or M2, as appropriate. HCI = literacy * M3 * tertiary enrolment ^ (1/3). Figures in italics are those for which I’ve had to use other sources.

The chart below shows how closely educational capital and wealth correlate in 2007. We see an inverse square relationship or possibly a kind of S-curve with two inflection points.

Let us note a few things:

1. Notice that out of the 30 countries with an HCI below 0.80, with the marginal exception of Saudi Arabia, not a single one had a GDP per capita exceeding 20,000 $. In fact, this chart understates the pattern, because the detailed educational stats produced by programs like PISA and TIMSS typically don’t include low-income countries, where human capital is going to be typically very low.

2. Practically all outliers can be explained by one of two things – resource windfalls and socialist legacies. Among all countries with HCI’s of less than 0.80, the top outliers are all big oil or minerals exporters. This artificially inflates their GDP’s, varying in extent from Iran, South Africa and Mexico (where oil and minerals production co-exists with a burgeoning manufacturing base) to Saudi Arabia and Botswana (which are dominated by hydrocarbons and diamonds, respectively). The latter are green and the former are cyan/green. The reason Norway is the world’s most affluent country also comes down to the oil boost (its human capital is unremarkable by average OECD standards).

3. Similarly, the vast majority of low outliers come from the former Communist bloc. East European former satellites are red, post-Soviet countries are dark red and Russia is black. Note how far off the vast majority of them are from where their HCI seems to indicate they should be (the exceptions being Azerbaijan, the Czech Republic, Slovakia and to a lesser extent Bulgaria and Romania). Poland, Hungary and the post-Soviet world are currently well below their potential. The explanation is that these countries have spent much of this century languishing under central planning with all its inefficiencies and contradictions and thereafter being subjected to a decade-long period of brutal restructuring, before normal economic growth could again resume towards the mid to late 1990′s. Meanwhile, the Communist emphasis on education payed off bigtime, as human capital is comparable to that of much richer countries. It is worth noting also that the gap between potential and actual is greatest in the former Soviet bloc, presumably because the socialist legacy was strongest there (no folk memory of pre-WW2 capitalism, no Visegrad-like experiments with creeping capitalism, etc). The big exception is Azerbaijan, which has an oil windfall; Russia, the other country in a similar position, doesn’t replicate this because its potential (based on human capital) is much higher – its socialist legacy outweighs its resource windfall.

Below is a table with three indicators for each country – their actual GDP, potential GDP based on average macroeconomic/microeconomic policies and potential GDP based on optimal policies.

Potential and Actual GDP per capita (2007 $)
Actual Mean Potential
Max Potential
Georgia 4,200 15,000
24,000
Latvia 17,700 38,000
48,000
Moldova 2,200 17,000
26,000
Poland 16,200 33,000
44,000
Russia 14,600 35,000 49,000

4. There are five other low outliers – Slovenia, Taiwan, New Zealand, Finland and South Korea, of which the latter two are particularly big. The explanations aren’t as clear-cut here, but I’ll throw a few around. Finland is a northern country covered in permafrost that inflates construction, energy and transport costs, while New Zealand has a small population (i.e. a small market) far removed from the arteries of world trade. Slovenia has a socialist legacy. Taiwan and Korea are very densely populated, which impacts negatively on the productivity of the retail and construction sectors. Singapore is a top outlier, much richer than warranted by its human capital – I suppose that’s because of its status as a major trade hub. Not as convincing? I kind of agree. The above explanations do not have the all-encompassing unity and simplicity of the socialist legacy or the resource windfall. Which is why it’s time for us to talk about economic growth rates.

Speaking of which – see below.

Countries are marked by GDP / capita growth rates from 1997 to 2007. The colors go as follows: white (1.0-1.9%); yellow (2.0-2.9%); orange (3.0-3.9%); red (4.0-5.9%); dark red (6.0%-7.9%) and black (8.0%-14.9%). Also, GDP per capita figures (on the y-axis) are for 1997 – this is because what we are interested in is the influence of education levels on future growth, which we know for the period from 1997 up until today. Unfortunately, educational stats for 1997 will be much less comprehensive (PISA and TIMMS embraced much fewer countries then), plus it would take a lot of time digging them up – hence I made a rough assumption that they were the same as for 2007. Actually, the HCI is based on a collation of different stats from the 2000-2005 period).

One thing that immediately stands out is how countries that are below their potential tend to have much higher growth rates than those on or above their potential. In other words, excluding chaotic and cyclical trends, economies tend to a steady state depending on the level of their human capital. Thus, the blue and cyan groups above tend to have equal growth in GDP per capita (although since the population grows in most cyan countries, absolute GDP growth will be larger), meaning that the cyan countries aren’t converging and should not converge economically, no matter their degree of openness or transparency.

The most glaring exceptions are typically due to oil booms and the like, which not only increase GDP in of themselves but also fuel consumption splurges. The purple group is the most interesting, which mainly encompasses relatively well-educated post-Communist countries. Unshackled from the chains of socialism, they are now growing very quickly due to the huge ‘potential gap’ that exists between their human capital and development level. (Picture this as a question of heat diffusion – the greater the difference, the greater the pressure to close it). The green countries must massively increase their investment into education if they want to join the development bandwagon.

Now for some questions and answers:

What does this mean for development strategies?

Policy-makers must realize that education is the elixir of economic growth. Individual incomes grow due to the introduction of new technologies, which increase total factor productivity. (Granted, it is possible to increase labor participation rates and increase savings – but only up to a point. There are only so many people in any workforce, while investment is subject to diminishing returns. The only long-term development model is continuous technological adaptation, which is recognized by the exogenous growth model). However, a country’s ability to take advantage of technology diffusion is governed by its educational levels (e.g., the illiterate will have little need for a computer).

It is not enough, however, to enroll every annual cohort, give them ten years of public schooling and consider the task done, as is the pattern in much of the developing world today. School life expectancy in much of Latin America, the Middle East, South Asia and China might be drawing close to Western standards – the same cannot be said, however, for its quality, as these international student assessments reveal. Secondly, tertiary enrollment there (15-30%) remains far below Western and post-Communist standards (50-80%). To bridge the gap into society-wide participation in the ongoing technological revolutions, developing countries must make efforts to remedy the two above problems. Massive labor and capital infusions will only take you so far. Once a country achieves a GDP per capita of around 5,000 – 10,000$, growth becomes a matter of increasing productivity in the services and higher-tech manufacturing sectors. This requires annual cohorts of well-educated workers.

I am not denying that there are many other conditions that have to be fulfilled for economic convergence to happen. Goldman Sachs, for instance, has compiled a Growth Environment Index that takes into account thirteen factors: inflation, government deficits, external debt, investment, openness, years of schooling, life expectancy, political stability, rule of law, corruption and Internet, PC and telephone penetration levels. I think this approach misses the central point of development, however. An honest and well-run state simply reduces barriers to an economy reaching its maximum potential level of development; if the human resources are lacking, it will not converge to Western levels.

To illustrate this, let’s take a few middle-income countries, say, Chile and Estonia – both have solid macro-economics and perform respectably in rankings such as economic freedom, ease of doing business and corruption perceptions. Nonetheless, Chile’s per capita growth rate for the past ten years has been a sluggish 2.6%, compared to Estonia’s tigerish 7.7%. Why? I suspect it has something to do with Chile scoring 0.69 and Estonia 1.00 in my Human Capital Index. Russia, rarely cited as a paragon of economic freedom but with a good HCI of 0.94, outperformed Chile with growth of 6.0%. I suspect that the 1-2% difference from Estonia is due to the greater barriers to technology/productivity diffusion in Russia. (Incidentally, the reason the late USSR grew slowly was because its human capital was immensely burdened by the planned economy).

The same goes for the arguments of geographic determinism. Yes, being landlocked and frozen, or suffering the scourges of endemic debilitating diseases in tropical climes, tends to negatively affect development. I don’t see, however, how these disadvantages are different in quality from factors like macroeconomic incompetence or failing institutions.

How will this affect the world’s future?

In my previous Core Article Towards a New Russian Century?, I identified economic convergence, doubly exponential growth in IT and climate change as key drivers of world geopolitics in the decades ahead. On the topic of the former, I wrote:

Of course, it’s not sufficient merely to be behind to catch up. One must also have the human capital and physical infrastructure in place. One of the best proxies for human capital is education. Now as we can see from the info above, Russia’s (and eastern Europe’s) educational profile is of a First World character. Hence it is likely that the region’s impressive post-millennial growth will be sustained, resulting in convergence with west European countries by a 2020-30 time frame.

I stand by this prediction. According to the data, Latin America, the Middle East and South Asia all have educational systems that leave much to be desired, and little sign of fundamental change can be observed (there is no discernable improvement in Mexico’s and Brazil’s PISA scores from 2000 to 2006; tertiary enrolments in the above regions are increasing at a glacial pace).

India is still plagued by illiteracy and as late as 2005 a tenth of the youth cohort didn’t receive primary education, 43% didn’t receive secondary and only 11% received a higher-level education (an unimpressive over 6% in 1991), according to the World Bank. India will be a Great Power, but its few economic/technological centres will remain islands of prosperity amidst a sea of backwardness.

China has a decent school life expectancy, literacy rate and enrollment rates (universal primary and 74% secondary), but its tertiary enrollment ratio is low at 20% in 2005. (Nonetheless, it has increased very rapidly, from 3% in 1991, and if the experience of other countries is anything to go by, a concerted effort could see their rates rise to developed-country standards within the next twenty years). I have no idea how average Chinese students would score on the PISA tests (comparing them to Hong Kong or Macau is a pointless exercise, because of the vast disparity in development), so I guessed 420. If so, then China’s current 10% growth rates should soon moderate to around 5% – as my second graph shows, it is a) fast approaching its potential and b) it’s hampered by bureaucracy and corruption. Today most Chinese growth, unlike in east-central Europe, comes from infusions of labor and capital rather than productivity improvements – growth which could experience a severe and protracted slowdown once the surplus labor pool in the countryside is expended and investment rates are hit by a financial crisis, as happened with the other east Asian tigers after 1997.

In conclusion, China seems set to do considerably better than other developing regions of the world (Latin America, Middle East, South Asia and Africa), but will still be very far from converging to advanced industrial levels in 2025. Meanwhile, eastern Europe will converge with western Europe, while Finland, Korea and Estonia may become some of the richest countries in the world.

How did you work out the Human Capital Index?

Explained beneath the big table. Basically, literacy rate * international student assessment scores mean average * tertiary enrollment ^ (1/3). The reasoning is that a) you must be literate, at a minimum, to participate in a modern economy, b) international student assessments give a clue as to the quality of those who are educated (better than school life expectancy) and c) tertiary education improves human capital further, though not to the same absolute extent as elementary schooling – hence we take the cube root of that figure.

I am aware that in an ideal situation, we would make a sample representing everyone in the country take a skills test to gauge human capital; since we don’t have that luxury, we must rely on available statistics, two of which (test scores and tertiary enrolment) apply mostly to the newest cohorts entering those countries’ labor forces.

What has this got to do with Russia?

When I say things like “Russia will have a GDP per capita of 30,000$ by 2020″, I work by a set of assumptions and beliefs that may not be entirely clear to the casual reader of this blog, particularly the Russophobe variety which believes Russia’s economy is an oil bubble about to pop like a balloon. Which is understandable, given that the Western MSM’s discourse on Russia’s prospects is mostly negative.

Nonetheless, some facts must be acknowledged. The government since 1998 has handled the economy well, balancing inflation and ruble depreciation by maintaining fiscal discipline. Since 2006, they have embarked on large-scale basic (agriculture, housing, health and education) and strategic (nanotechnology, venture capital) investment programs. Yes, the bureaucracy is unwieldy, corruption is a problem and life is hard for small businesses, but as the last few years have showed, these problems are not fatal – at worst, they have shaved off 1-2% of annual GDP growth, and in any case the Baltics are the exception rather than the rule in the post-Soviet space. Most importantly, Russia’s human capital is of First World standards – and as we’ve argued here, this is the key component of development.

If anything, it would be exceptional if Russia didn’t converge to west European levels of development by the 2020′s.

(Republished from Sublime Oblivion by permission of author or representative)
 
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Anatoly Karlin
About Anatoly Karlin

I am a blogger, thinker, and businessman in the SF Bay Area. I’m originally from Russia, spent many years in Britain, and studied at U.C. Berkeley.

One of my tenets is that ideologies tend to suck. As such, I hesitate about attaching labels to myself. That said, if it’s really necessary, I suppose “liberal-conservative neoreactionary” would be close enough.

Though I consider myself part of the Orthodox Church, my philosophy and spiritual views are more influenced by digital physics, Gnosticism, and Russian cosmism than anything specifically Judeo-Christian.