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This is a (very preliminary) prologue to a sci-fi novel I’ve been thinking of writing for some time. It’s called 100 YEARS TO VICTORY, but obviously liable to change. My sole question is: Would you continue reading the rest of this book?

It’s been nearly a decade since I built my first cage.

It was an exceedingly small cage. Physically, and literally, it was about the size of a large computer, though its inhabitants were none the wiser to the fact. To them, it would have appeared as a world entire, a world of rolling plains and giant trees and gentle hummocks in which they could make their burrows. That world wasn’t particularly big either. It didn’t have to be. Not when it hosted consciousnesses that were conditioned by evolution to a home range of less than 50 meters in radius. As far as a rat was concerned, the neighboring hill might as well be a foreign country, and its denizens – instinctual enemies, to be exterminated so that its own clan could survive and propagate.

And so the years passed, passing into decades, and centuries. There evolved subtle differences between rats in different locales: The rats in the ice-bound north, for instance, developed white fur and epicanthic folds to protect against snowblind, while males in the torrid south acquired rich manes to attract females. Many thousands of rat generations appeared and disappeared in the blink of a human eye. Arbitrary eons of blood and breeding, and the profound indifference of a Mother Nature that canceled them out over any long enough period of time.

Then I said, “Let there be grain.” Stalks of wheat sprouted out at the bed of one valley. A moment-millennium later, rice appeared in a second valley, and was followed by flowerings of millet, maize, and sourghum in yet other places.

The rat clans flocked down to the new oases of abundance. Old social structures broke down, for it was no longer possible for the alpha rats to monopolize a given territory and its females; the population density was now too big to treat every interloper as a hostile intruder, to be confronted and chased away. New structures arose in place of the old, in the form of vastly more complex dominance hierarchies that mediated the distribution of mates and resources. The rat population exploded, and though their grain-based diet made them far frailer and more sickly than their ancestors, their numbers soon far eclipsed those of the remaining wild rats in the corners and remote places of the map. No plague born of the filth and crowds checked their numbers for long; no periodic violent shift in the power hierarchy made a noticeable dent in their teeming hordes.

An eye-blink later, and the population was a hundred, a thousand times what it had been at “t” equals zero. The burrows delved dozens of meters underground, and some rats even attempted to build earthen structures into the sky, with grain farms on top. Others took a clue from the squirrels and the otters, and began to settle in the trees and dam off streams and lakes. The zone of grain cultivation overspread the entire surface of the Ratlands, displacing roots, legumes, nuts, berries, and lower-yielding wild cereals. All but the smallest and more elusive insects were devoured into extinction, leaving more of the yearly grain crop for the dominant species. The cleverest rats even realized you could store calories from a surplus year by a skilful application of yeast and time. It would be nice to imagine that those inventors became very famous and snagged all the girls at the parties, but let’s not get too carried away here… they were, after all, just rats.

Despite these efforts, some rats began to grow hungry. Oh, there had always been rats at the margins, runts without muscle, mates, or money; nobody cared for those losers. To the contrary, their fellows of both sexes took pleasure in harassing them and biting at their backsides, as is the way of rats. They died as they lived: In the margins, forlorn and anonymous. But as the years clicked by in rapid succession, the numbers of these marginal rats multiplied, and now they were no longer all outcasts and weaklings. For the population had long outstripped the carrying capacity of the Ratlands, and most rats now lived at the edge of subsistence; crop yields declined, as hungry rats learned to dig into the ground to get at the seed grain. The dominant rats had to resort to increasingly brutal methods to maintain the social hierarchy and their own positions at the top of it. But their late-ditch attempts were to be in vain, for a couple of hard winters tipped the Ratlands over into all-out collapse.

Some of the marginal rats coalesced into all-male bands that began to wreck havoc all across the Ratlands. They would kill off the local dominant alpha rat, gang rape his harem, and scour his territory clean before moving on to ravage the next. Left to themselves, a few territories might have pulled through: Some rat broods had become good at planning ahead, storing grain as reserves, while other broods were resilient by virtue of having avoided overpopulation, or over-dependence on grain monoculture. But marauding bands and starving refugees from the worst affected areas spread outwards in concentric tsunamis of destruction, ensuring that what might have otherwise been a limited set of local collapses would turn into a truly global die off.

Zooming around the map as a spectator, I began to notice discarded rodent skins with bones strewn about them; the victims had been eaten inside out. Countless other rats met less gory but no less tortuous ends, expiring of hunger, disease, or infected wounds. Even as mortality spiked, the fertility rate collapsed, as the all-pervading famine and stress made many of the females unable to bear offspring.

An eyeblink later, the population of the Ratlands had collapsed to a tiny fraction of its peak level.

One might have thought that in the wake of so drastic a culling, rat society might begin to slowly, haltingly recover. This was not to be. For in the decades before the collapse, grains had become the dominant crop, and whatever flora and fauna had escaped earlier encroachments was now picked clean by starving rats in those last, desperate months. Long deprived of nutrients due to the inherent nature of monoculture cultivation, and lacking the deep roots of shrubbery to hold the soil in place, the earth dried up as soon as it was exposed to the sunlight. The few remaining grain stalks dessicated and withered away. The lush verdure that had preceded civilization was followed by the desert, and no insect chirps or avian tweets would ever disturb its eternal silent spring.

The remaining bands ran out of new territories to scour clean, and turned in on themselves in a war of all against all.

The last rat breathed his last.

A melancholy wind blew across the Ratlands, now as deserted as they had once teemed with hustle and bustle. It gusted into the empty warrens beneath the grassy hummocks, failing to dispel the stench of death within, and tipped the lake-waters over the earthen dams that rats had built. The floodwaters, at least, were more effective at cleansing the land, replacing the decay of a civilization no matter how primitive with an entirely more elemental and natural oblivion.

Just a few decades later, there was no indication that the Ratlands had ever hosted their namesake. There was nothing more to be learned, so I switched off the simulation. After all, they were just rats.

This was when I first heard the voice, whispering to me: “Would humans do any better? Are we really all that different from rats?”

(Republished from Sublime Oblivion by permission of author or representative)
• Tags: Anatoly Karlin, Literature 
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Black Sun Rising (Book 1 of the Coldfire Trilogy) by C.S. Friedman, published in 1991. Rating: 3/5.

The Coldfire Trilogy is sometimes described as a successful fusion of sci-fi, fantasy, and horror. So what better work to start reviewing on this site?

I will be forthright: By far the most wondrous and intriguing element of this series is the world Celia S. Friedman built. Not really in the details – names are generic, and cities have no character of their own – but in the metaphysics. This is a world where simply thinking about something can bring it into being. This is reminiscent of other fantasy worlds like Solaris, numerous Philip K. Dick creations, and The Wheel of Time’s Tel’aran’rhiod. If you’re the type who has a lot of nightmares, living there probably wouldn’t be your cup of tea: “Erna is a harsh mistress.”

The interrelations between the cognitive and physical realms are mediated by the fae. The fae are a sort of energy current that can be manipulated, or “Worked,” by conscious minds to produce what we might think of as magic. But don’t call it that! For as the main hero of the story points out, “The fae is as natural to this world as water and air were to our ancestors’ planet.” Nor is it all bad: It can reinforce buildings against earthquakes, and cure wounds (giving faith healing an altogether more literal meaning!). The natural world, as a result, is subject to Lamarckian evolution: “Here, if trees grow taller, the next gaffi calves are born with longer necks.”

As it is now more than a millennium since humans first settled the planet, the concept of a world without fae is hard to imagine. Even though Damien Vryce, the main protagonist, serves a Church that is committed to the extirpation of the fae, he himself reacts to a vision of such a world with terror:

Explosives fire like a sharp drumroll in the distance, the crack of a hundred pistols perfectly synchronized. He feels a sharp bite of fear at the sound, at the unnaturalness of it. What kind of Working must it take, to make it possible for so many guns to fire successfully, with such planned precision? … For the first time in his life, he knows the rank taste of terror. Not the quantifiable fear of assessed risk, but the unbounded horror of total immersion in the unknown. Guns fire once more in the distance, and for the first time since coming here he realizes why they can function with such regularity. Man’s will has no power here—not to kill and not to heal, not to alter the world and not to adapt to it. The whole of this world is dead to man, dead to his dreams, impassive to his needs and his pleas and even his fears. The concept is awesome, terrifying.

This vision was created by Gerald Tarrant, the anti-hero of the story, to evoke fear in Damien. He is a centuries-old sorcerer who escaped death by pledging himself to demonic forces, gaining immortality and great power over the dark fae in return for regularly engaging in murder and feeding off the fear and terror of his victims – hence, his psychological torture of Damien, which the latter agrees to. But Tarrant is also the original founder of Damien’s Church, even if he has long abandoned its ideals (albeit he says it’s not that simple). This makes for an uneasy and tension-filled relationship between the two that looks like it will evolve in interesting directions in the next two books. It is also the main reason that I will continue reading the series to its end.

So why the rather mediocre rating? Plot. Characters. Consistency. It is not entirely clear why Damien became so committed to Ciani in the course of a weeks-long fling that he would literally travel to the ends of human civilization to bring back her stolen memories. Nor do I even recall why she was singled out in particular. The Big Bad’s fortress is originally described as a massive, physically-impossible structure of “naked stone” that “rose up from the earth like a basalt column,” but soon afterwards it becomes a citadel that was like “a jewel, a prism, a multifaceted crystalline structure that divided up the night into a thousand glittering bits.”

The very title of the book is “Black Sun Rising,” but there is only one reference to a black sun that I can recall. And unless it’s a metaphor for Tarrant, I don’t see it leading anywhere:

In the far north, across the Serpent’s waist, a midnight sun is rising. Black sphere against ebony blackness, jet-pure; a thing that can only be Felt, not Seen. Into it all the light of the world is sucked, all the colors and textures that the fae contains: into the crystalline blackness, the Anti-Sun. He stares at it in adoration and horror and thinks: There, where all the power is concentrated, like matter in a black hole . . . there is the power we need for this quest. Power to shake the rakhlands and make our kill and move the earth besides!

Apart from the stolid Damien Vryce and the darkly seductive Gerald Tarrant, the other characters are quite wooden, Senzei in particular giving off the vibes of an expendable (and accurately so, it turned out). Despite or rather because of his inherent intrigue and dark mystery, Gerald Tarrant is – looking at it in another way – a quite banal product of the feminine erotic imagination. Like a fusion of Stephanie Meyer’s vampires, and the serial killers who get bags of love letters in the mail, as channeled through Ciani:

With consummate grace, Tarrant walked to where she stood, took her hand in his, and bowed gallantly. Gritting his teeth, Damien was forced to acknowledge the man’s charm. … With a sinking feeling Damien realized just how drawn she would be to the Hunter, and to the mystery that he represented. It would mean little to her that he tortured human women as a pasttime, save as one more fact for her to devour.

It’s all the same power to her. He’s just another adept. More interesting than most, perhaps—but that only makes him more desirable. The cost of it means . . . nothing.

Essentially, the sheer awesomeness of Gerald Tarrant paradoxically cheapens him as a character, especially when he decides to slum it with mere humans. But maybe I am missing something big that explains all this in a later book.

Finally, there is also an ecological and anthropological element to the story. There is “The Forest” that Gerald Tarrant had engineered into existence with the force of his will, his need, and his intellect; sunlight and its solar fae are deadly to a man of the dark like himself, so over the long centuries, he created an entire ecosystem that could thrive without sunlight. There are the rakhlands, home to the rakh, a cat-like species that – under the avalanche of human fears over a rival species – evolved intelligence. The humans tried to exterminate them out of existence, with the result that the rakh retreated to an isolated part of the continent and erected a barrier called the “Canopy” to protect themselves from humankind. In a world where thinking really is existing, the Canopy can be seen as an “extentsion of their communal protection [and of] their need for protection [against man].” We also meet the “Lost Ones,” subterranean-dwelling relatives of the rakh who eat creatures from the above – including their cousins – for sustenance. They are the Morlocks/Falmer of Erna.

Have no illusions: This is not a landmark fantasy series. The characters are forgettable, with the partial exception of Damien Vryce and Gerald Tarrant (although the latter has his own issues). The plot meanders considerably, and is barely discernible in places, like the earth fae over the ocean. I think there are too many points of inconsistency for them all to have been a result of errors on my part as a reader (if so: Apologies. Maybe somebody was stealing my memories when I was reading the book?). There is also one character’s miraculous and unexpected survival at the end that, much like Sherlock Holmes’ faked death, strains the bounds of credulity. I wonder if the author will explain this sometime, or whether its a deus ex machina that will lie buried – unlike the unlikely survivor – to the end.

But it intrigued my just about enough to download the second book. I guess that means that aura of Erna can still draw you in even despite quite significant flaws in execution.

(Republished from Sublime Oblivion by permission of author or representative)
• Tags: Literature, Sci-Fi 
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Not like most people in Moscow live in palaces.

There is a certain Russian expression: “Москва — не Россия” (i.e. Moscow, isn’t Russia), to denote the idea that while the capital may be rich, at least by Russian standards, the rest of the country languishes in grinding poverty. This is a trope is frequently taken up by the Western media, which at times presents the Russia outside Moscow and St.-Petersburg as a wasteland languishing in Third World-style destitution. It is also commonly implied that Moscow is growing fast in prosperity, while the rest of the country lags behind.

And at first glance the statistics seem to confirm this, with salaries in Moscow for 2010 almost double the Russian average. Income disparities are even greater, the average income in Moscow being 2.5 greater than in Russia as a whole. It accounts for about 20% of Russian GDP while only representing 7% of its population. But as is usually the case, there is an important catch. As argued in an excellent article by Sergey Zhuravlev, there are several factors dragging down Moscow’s real level of prosperity.

First, prices for a fixed assortment of goods and services in Moscow are approximately equal to the OECD average, and higher than in the rest of Russia by a factor of about 1.4 (see Rosstat). This means that a ruble of consumption in Moscow only buys as much as 70 kopeks in the provinces.

As a result, the 2.5 differential in incomes – this figure, by the way, is down from its peak of 3.6 in 2000, so in reality Moscow has grown substantially slower than Russia as a whole – is reduced to about 1.8 as of 2009.

However, what’s more, Moscow’s level of inequality is the greatest in Russia (as one might expect of a city with so many billionaires). It’s Gini index of 52 is about 10 points above the Gini index for Russia as a whole. So the median resident of Moscow got only 36% as much income as the typical Russian in 2009 (albeit this figure would likely recover to its more typical level of about 50% after the recession). A disparity of this modest scale is fairly large but not completely atypical by developed country standards.

Two conclusions follow. First, headline figures of the gulf of the inequality between ordinary denizens of Moscow and the rest of Russia overestimate its real extent due to their omission of price differentials and intra-regional inequality (both of which favor Russia). Second, the gap has been slowly narrowing over the past decade, as both incomes and prices in the Russian interior slowly converge to Moscow/OECD levels.

This is not to say that Moscow is poor, far from it, most of its socio-economic and consumption indicators are at or near the top of the Russian regions (e.g. meat consumption, Internet penetration, etc). But for most people living standards are not cardinally different from what they’d experience in in any other Russian city.

(Republished from Sublime Oblivion by permission of author or representative)
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Really now?

Apart from direct falsifications, which were extensively discussed here, the other really big criticism of the Russian elections process is that it isn’t a level playing field. As said by an OSCE bureaucrat, “The point of elections is that the outcome should be uncertain. This was not the case in Russia.”

Well wait a second. First, uncertainty isn’t the point of an election at all; otherwise, why not make it into a lottery? It’s to get the person who most represents the people into power. Second, there is no country where each candidate gets equal airtime, ad money, debating invites, etc. Cases in point: Ron Paul, Nader, Marine Le Pen, generic Green Parties and Pirate Parties, etc. Perhaps one day we will live in Internet democracies where anyone can nominate oneself and debates are won and lost via webcasts on Facebook but for now level playing fields are a fiction everywhere.

One can write a whole article on comparisons, but why bother when the Russian political scientist Evgeny Minchenko has already done an excellent job of picking apart these questionable assertions about how elections in Russia are much less free and competitive than in the West in his article Seven Myths about the Russian Elections? I translate his effort below. H/t @lindsey_bn for the link via Twitter.

Seven Myths About The Russian Elections

Evgeny Minchenko

Myth 1 – A prolonged stay in power can be the basis for proclaiming the government illegitimate. Here we can look at the examples of Canadian PM Jean Chrétien – 20 years, Federal Chancellor of the FRG Helmut Kohl – 16 years. Ólafur Grímsson is the President of Iceland since 1996, and in 2000 his term of office was extended without elections as there was nobody willing to compete with him, he won the elections in 2004, he once again had his term extended in 2008 with no elections, and he does not exclude participating in the upcoming 2012 elections. There is a similar history with Chrétien and Kohl, although one has to note that it’s a slightly different state of affairs in parliamentary democracies.

Myth 2 – Elite collusion, in our context the Putin – Medvedev “castling”, can be a basis for proclaiming the government illegitimate. Unfortunately, politics is structured in such a way that elite collusion does happen. A striking example is the history of Tony Blair and Gordon Brown. When they were nominating a candidate for Prime Minister, they agreed that Blair would go first, and then Brown. Vladimir Putin gave this very example: When Tony Blair stepped down after a scandal, there were no elections. Gordon Brown carried on for another three years as Prime Minister, with no elections, even though when the British voted for New Labour at the polls they were voting for Tony Blair as Prime Minister. On the other hand, when they finally did hold elections, Labour was crushed. In my opinion, this demonstrates that the public does have the opportunity to express their attitudes towards this kind of collusion. Our reaction was Bolotnaya Square and Prospekt Sakharova.

Myth 3 – Harsh screening and disqualification of undesirable candidates in the Russian Federation. True, we have our Grigory Yavlinsky with his 1.5% rating who couldn’t take part in the elections, but I want to draw attention to what is now happening in the Presidential campaign in France. They have a very specific system in that the candidate must enlist the support of at least 500 mayors or elected local officials. Despite there being 50,000 such officials in France, Marine Le Pen – who has a 17% approval rating – has yet been unable to collect these signatures. And this isn’t Yavlinsky, with his 1.5%, this is a person, who has a real chance of reaching the second round. I hope that Marine Le Pen will be able to solve her problem, as did her father Jean-Marie Le Pen; the ruling authorities were forced to command signatures to be gathered on his behalf after public pressure. There are various technologies for filtering out undesirable candidates. A striking example is the impeachment of Rolandas Paksas in Lithuania: Only after he left did it emerge that the court had pronounced him innocent, but by then he could not return to the Presidency. Another example – the story of Strauss-Kahn, who had a leading position among the French Presidential candidates, but who for reasons unknown to us could not take part in the elections. Bidzina Ivanishvili lost his Georgian citizenship, and is not allowed into the Presidential election.

Myth 4 – The dominance of one party or one candidate in the mass media. I think this problem with access to media resources exists everywhere. It’s obvious that in the US candidates from the two key parties dominate over all others. On the other hand, it’s worth pointing out that the benefits which Mikhail Prokhorov enjoyed on Russian TV channels in the last elections were for a long time enjoyed by no other candidate.

Myth 5 – Vladimir Putin declined to participate in the debates, so the elections were illegitimate – the voters didn’t have an opportunity to assess him. Let’s take a look at other countries. There were 23 candidates in the last US elections. For instance, Ralph Nader was registered in 48 states out of 51, but the elected Obama debated exclusively with McCain. Having a minimum of 15% in opinion polls is a condition for participating in US debates. Or what about France, 2002 – Chirac vs. Le Pen. As a rule, there are no debates prior to the first round in France. The tradition of holding debates only applies to the period between the first round and the second round. Mikhail Saakashvili, who is frequently portrayed as a great democrat, has never debated anyone in his two Presidential elections.

Myth 6 (very common) – Russian legislation creates comfortable conditions for electoral falsifications. The suggested solution – rewrite the laws so that they match those of normal “democratic countries.” But the problems aren’t in the laws. As a matter of fact, ours are very stringent. They say, “Let’s abolish early voting!” But in the US, typically up to 30% of voters cast their ballots early. As for procedures on allowing observers into polling stations in other countries, in France you have to be a member of the Electoral Commission to observe the voting, and in the US observers are frequently denied access, especially foreign ones. In terms of observer access to polling stations, Russia is actually one of the world’s more liberal states.

Myth 7 – Big protest actions are a cause for a revision of the election results. One striking example – the attempted “Cactus Revolution” in Mexico in 2006. Compared to our modest turnouts, in Mexico up to a million people took to the streets. At the same time, there appeared the following phenomenon: “And I don’t know why this candidate was elected, none of my acquaintances voted for him.” The specific cause of this lay in López Obrador being Mayor of Mexico City, and dominant in the capital and the adjoining southern regions, where many people genuinely didn’t know anyone who voted for Calderón. Nonetheless, all those protests came to naught.

What is to be done?

For the elections to be more honest and transparent, we need to have an independent judiciary, and opposition representation in parliament and the regions. I think that if there were to be elections for governors, they would enable them to reallocate administrative resources between the various parties. Inter-elite conflicts, a stable tradition of political competition – which we still have to work out, as it unfortunately isn’t double within 20 years – independent media, true federalism, and so those proposals that were made by Medvedev are, in my opinion, adequate: The liberalization of political party registration, and the transition to direct elections of governors.

(Republished from Sublime Oblivion by permission of author or representative)
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This post is a follow-up to a similar one for the 2011 Duma elections. It contains an extensive list of blogger, pundit and “expert” opinions on the extent of fraud in the 2011 Duma elections. Interspersed among these opinions and analyses are results from federal opinion polls, election monitors, and other evidence.

In general, it seems we can identify three “theses” or “clubs.” The 0% Club holds the idea that falsifications were non-existent or minimal; it is advanced by Kremlin officials and supported by many opinion polls. Its polar opposite is the 15% Club, which is – unlike in the Duma elections – now only claimed by opposition forces and some liberal and Western media outlets. The 5% Club tends to arguee that Putin got a solid majority with some 56%-60% of the vote; almost all evidence converges to this figure. Most of the systemic opposition and arguably most Russians belong to this club.

The 0% Club (<2% fraud)

* PRE-ELECTIONS POLLS: Levada (66%), VCIOM (66%), and FOM (70%) all gave Putin more than its official result. However, because of the relative passivity of United Russia’s electorate – its supporters are less like to vote – raw (i.e. unadjusted) polling numbers almost certainly overstate Putin’s real electoral popularity.
* POST-ELECTIONS POLL: State pollster VCIOM reports 67% and Levada reports 60.7% responding they voted for Putin. Both figures are within their 3.4% margins of error.
* OFFICIAL RESULT: Putin has 63.60% according to the Central Elections Commission of the Russian Federation. This is more than 13% points above the 50% level that would have otherwise necessitated a runoff.
* CEC HEAD: Vladimir Churov said that “more honest elections than those in Russia will not be held in other countries in the near future, at least until they begin to adopt our technical experience” (refers to web cams at polling stations).
* PUTIN’s CAMPAIGN CHIEF: Stanislav Govorukhin said the election was the “cleanest in the history of Russia.”
* VLADIMIR PUTIN: The President-elect thinks that “there probably was some fraud, but it could only affect hundredths of one percent, well on 1% I can still imagine, but no more.”
* PRE-ELECTION PREDICTION: FOM gave Putin 61.7% on Feb 27-29, within 2% points of the official result, and Levada gave Putin 61.5% on Feb 24-Mar 1, within its 3.4% margin of error. Both couldn’t be legally published so close to election time. But p redictions may implicitly assume fraud. VCIOM gave Putin 58.6% on Feb 11-12 . But Putin’s popularity was rising during the next 3 weeks.
* EXPERT ANALYSIS: Sergey Zhuravlev estimates 1.7% fraud using statistical analysis. This approach has methodological flaws.

The 5% Club (2%-10% fraud)

* Juha Savolainen thinks 3%-5%.
* THIS BLOG’S AUTHOR: Anatoly Karlin estimates that Putin got 59%-60%, and so the aggregate level of falsifications is about 4%.
* EXIT POLL: State pollster FOM gave Putin 59.3%, implying possible fraud of 4.3%. They covered 81 regions, 800 stations, and 80,000 voters.
* EXPERT ANALYSIS: Dmitry Kobak, a programmer, estimates 4.6% fraud using statistical analysis.
* EXIT POLL: State pollster VCIOM gave Putin 58.3%, implying possible fraud of 5.3%. They covered 81 regions, 800 stations, and 80,000 voters.
* OBSERVERS: Anatoly Karlin, i.e. this blogs author, estimated a possible fraud figure of <5.9% by adjusting figures from observer protocols to get rid of the Moscow bias. This method has methodological flaws as there were few observers in the Putin-supporting countryside.
* EXPERT OPINION: Aleksandr Kireev, a prominent Russia elections analyst, estimates 6% fraud.
* EXPERT ANALYSIS: Sergey Shpilkin, veteran Russia elections analyst, estimates 6% fraud using statistical analysis. But his key assumptions are questionable.
* The difference between machine ballots and the overall result for United Russia is 6.1% as calculated by Aleksandr Kireev. This approach has methodological flaws.
* EXPERT OPINION: Boris Ovchinnikov, a Russian blogger and mathematician, thinks that Putin got 55%-58%, translating into about 7% fraud.
* EXPERT OPINION: Aleksandr Shen’, a prominent Russia elections analyst, gives a range of 5%-10% fraud.
* OBSERVERS: Protocols from Golos election observers gave Putin 54.8%, implying fraud of 8.8%. This approach has methodological flaws.

The 15% Club (10%+ fraud)

* OBSERVERS: Protocols from all election observers gave Putin 50.2%, implying fraud of 13.4%. This approach has methodological flaws; nearly 50% of all observers were concentrated in Moscow, where Putin’s support is naturally lowest.
* LOSS OF LEGITIMACY: Once fraud approaches 14%, the case can be made that Putin’s victory is illegitimate as a result of less than 50% would have necessitated a second round.
* The Economist, a British publication which the eXile called the “world’s sleaziest magazine,” strongly implies 14% fraud.
* Oleg Kozlovsky, an opposition activist, claims 14% fraud, with Putin getting no more than 50%.

Fraud In Moscow

* OFFICIAL RESULT: Putin has 46.95% according to the Central Elections Commission of the Russian Federation.
* EXPERT OPINION: Dmitry Kobak thinks Putin got a 47%.
* OBSERVERS: Protocols from all election observers gave Putin 45.18%, implying fraud of 1.8%. This may have methodological flaws.
* Statistical evidence strongly indicates that the fraud in Moscow was present but at very low levels in these elections.

Fraud In St.-Petersburg

* OFFICIAL RESULT: Putin has 58.77% according to the Central Elections Commission of the Russian Federation.
* Statistical evidence strongly indicates that the level of fraud in St.-Petersburg was a lot greater than in Moscow.
* OBSERVERS: Protocols from all election observers gave Putin 50.35%, implying fraud of 8.4%. This may have methodological flaws.

The Moscow Protests

In post-elections Мeetings, the anti-Putin one at Novy Arbat on March 10 got 10,000 (police), 22,600 (RIA estimate), 26,000 (Nikolai Pomeshchenko), or 25,000-30,000 (organizers). The precise details probably don’t matter; what ALL estimates concur on is that turnout plummeted from the 60,000+ levels of the three major post-Duma elections Meetings.

Putin’s post-victory rally at Manezh Square on March 5 got 70,000-110,000 people.

Further Reading

My best articles on election fraud in Russia:

(Republished from Sublime Oblivion by permission of author or representative)
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Remember Sergey Shpilkin? He is the mathematician, blogging as [info]podmoskovnik, who estimated 16% fraud for the Duma elections (also the one whom the WSJ plagiarized off). He got this figure by assuming that in a fair election, the share of the vote for each candidate at each level of turnout had to be a constant factor.

This is, of course, a flawed assumption, as I argued extensively in Measuring Churov’s Beard. First, that would imply that elections in countries such as Israel, Germany, and the UK – where the share of the vote for right-wing parties rises with turnout – are also falsified. Second, it is further refuted by Russian opinion polling evidence: Rural Russians are both more more likely to vote than urban ones, and more of them would vote for Putin.

This influence of electoral sub-groups partially explains United Russia’s “fat tail” to the right of a turnout / share of the vote graph (although NOT the spikes at 80%, 85%, 90%, and 100%, or the general “bump” in that region). As such, we can say with confidence that the level of falsifications was significantly lower than 16%, i.e. around the 6% or 7% indicated by FOM’s exit poll.

Anyhow, Shpilkin repeated his exercise for the 2012 Presidential elections, and the fraud figure he got was much lower this time, at 6% (official result: 63.6%; result according to this method: 57.5%). Using the same method Kobak got 57%. Here is a graphical comparison of the two elections using Shpilkin’s graphs:

The bottom axis is turnout in the 2011 Duma election, and the vertical axis is percentage of the vote. The green line is the vote for non-UR parties, the blue line is the vote for UR, the cyan line is the vote for UR if it remained strictly proportional to the votes for the other parties on the right hand side of the graph as well as the left, and the purple line denotes the anomalous part of the votes for UR. The latter are 16% of all the votes, and are taken by Shpilkin to be synonymous with falsifications.

This graph shows the exact same for the 2012 Presidential elections, just replace UR above with Putin. The anomolous part of the graph is visibly much less, at 6% of the total votes.

Of course, as acknowledged by Shpilkin himself in discussions with another mathematician Dmitry Kobak (if not in the media), this method is flawed, and a more accurate approach would be to break down this analysis by region, with separate graphs for cities and villages. This approach, which is far more accurate, yields 59% for Putin, i.e. about 4% something falsifications. (I.e., almost exactly matching the results of the FOM exit poll, at 59.3%, and the VCIOM exit poll, at 58.3%).

One caveat is that the separation between “cities” and “rural” may still be too crude, even at regional levels; there are still significant differences between voting patterns in bigger towns and smaller towns, for instance, with the latter closer to the profile of villages (i.e. higher turnout, and more votes for Putin. This may trim down the fraud by half of to one percentage point.

(A similar exercise for the Duma elections yielded a result of 39% for United Russia. Since this way of estimating fraud gives plausible results for the Presidential elections, this has made me reevaluate my old estimate of 5%-7% fraud in the Duma elections, based off the results of the FOM exit poll, to perhaps 8%-9%.)

There are three further points I’d like to make then:

(1) The Presidential election, though still very sub-par, was not just modestly but A LOT cleaner than the Duma ones. The absolute lowest feasible “floor” on Putin’s real result is around 57% (note: confirmed by properly adjusted figures from observers). This is well above the critical 50% mark that the radical opposition and Western journalists claim that Putin actually got.

(2) I was predicting that Putin would get about a real result of 56%-57%, as in the forecasts of the major polling agencies, and about 2%-3% of fraud would raise it to 58%-60% (hence, I predicted 59%). In reality, his real result was probably 59%-60%, with still higher than what I expected fraud of 4% raising it to 63.6%.

(3) As the adjusted Shpilkin/Kobak statistical method appears to be reliable, the real level of fraud in the Duma elections may well have been closer to 10% than to 5%, which would begin raising real questions about its legitimacy.

(Republished from Sublime Oblivion by permission of author or representative)
• Tags: Elections, Politics 
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Yes, this WAS the cover to one Economist issue.

It’s all so predictable. In its main piece on the elections, The Economist wrote:

And by some estimates vote-rigging added at least ten percentage points to Mr Putin’s tally. The main victim was Mikhail Prokhorov, a business tycoon and the only fresh face in the election. Officially he got 8%. His real vote was probably nearly twice that, says the League of Voters, a group set up by civil activists after a rigged parliamentary election in December.

Note that the “at least” (my emphasis) part is supposed to give the impression that Putin’s result may well have been less than the 50% needed to avoid a second round, thus making him illegitimate.

They totally glide over the inconvenient fact that the League of Voters observers were concentrated in Moscow, where the results are naturally lowest. Even Dmitry Oreshkin, the head of the project, is forced to admit this even if he does do a lot of weaseling about in the process: “Most likely, our sample isn’t entirely adequate.” As I showed in this post this is a detail that CARDINALLY changes the picture.

Furthermore, note two more brazen lies. First, the Economist asserts, “middle-class Muscovites… mostly voted against Mr Putin.” No, they didn’t; even in the richest neighborhoods Putin got 10% points more than their beloved Prokhorov.

Second, they make out that Putin is “not recognised as a legitimate president by a large minority of Russians and by a majority in Moscow.” Note their unstated (but self-evident) assumption that Russians who didn’t vote for Putin are so partisan and contemptuous of the democratic process that they would all refuse to accept the majority’s choice. Perhaps this describes some of The Economist’s idols like Navalny or Yulia “Pinochet” Latynina or Chirikova (We must dissolve the Russian people and elect another!” – Alex Mercouris, by way of Bertolt Brecht) but I for one think that far from all Russians who didn’t vote for Putin hate democracy.

Needless to say, for every straight out lie and misrepresentation like the above there are about ten different smears and aspersions. But what else can one expect of The World’s Sleaziest Magazine?

(Republished from Sublime Oblivion by permission of author or representative)
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Vile, vile election fraudsters...

Did you know that elections in Britain and the US are marred by mass fraud? At least that would be the inescapable conclusion if they were to be subjected to the most popular methods to “prove” that Russian elections are rigged in favor of Putin and United Russia. Below I have a translated a delightful quiz by Mikhail Simkin, where you have to answer just one question: Did this happen in Russia or in a democratic country?

Some of the following weirdness happened in elections in Russia. They contradict the laws of mathematics and basic decency. They cannot be explained by anything other than mass falsifications. Some of the weirdness happened in democratic countries. They can be explained by natural causes. Can you identify which is which?

(1) The distribution of polling stations by the percentage of votes for the winning presidential candidate in their region.

Did this happen in (A) Russia or (B) in a democratic country?

(2) The dependence of the share of the vote for each of two parties on turnout. Each dot represents a region. Each region has a few dozen polling stations, and represents a few tens of thousands of voters. For some reason, the percentage of the vote for Party A grows in lockstep with the turnout whereas the percentage of the vote for Party B doesn’t change.

Did this happen in (A) Russia or (B) in a democratic country?

(3) In one city during the Presidential elections, more than 300,000 people voted. Of them some 97% voted for one candidate, who went on to win nationally (albeit with a score much less impressive than 97%). He got 100% of the vote in more than 15 of the six hundred precincts of the city in question. The biggest of the precincts where he got 100% had 580 voters.

Did this happen in (A) Russia or (B) in a democratic country?

(4) The distribution of polling stations by the percentage of votes for the winning party in their region.

Did this happen in (A) Russia or (B) in a democratic country?

(5) The dependence of the share of the vote for each of two parties on turnout. Each dot represents a region. Each region has a few dozen polling stations, and represents a few tens of thousands of voters. For some reason, the percentage of the vote for Party A grows with turnout, whereas the percentage of the vote for Party B decreases.

Did this happen in (A) Russia or (B) in a democratic country?

(6) The distribution of polling stations by the percentage of votes for the winning party in their region.

Did this happen in (A) Russia or (B) in a democratic country?

(7) In one region, in districts where turnout was less than 65%, party A got 30%, while party B got 39%. But in districts where turnout was higher than 65%, party A got 46%, while party B got only 31%.

Did this happen in (A) Russia or (B) in a democratic country?

(8) The distribution of polling stations by the percentage of votes for the winning presidential candidate in their region.

Did this happen in (A) Russia or (B) in a democratic country?

Turn the page for answers.

The answers are:

1) B
2) A
3) B
4) A
5) B
6) A
7) B
8) B

(1) The distribution of polling stations by the percentage of votes for Obama in the 2008 Presidential elections in the state of New York.

This happened in a democratic country.

(2) The dependence of the share of the vote for each of two parties on turnout in Moscow in the 2011 Duma elections. Each dot represents a region. Each region has a few dozen polling stations, and represents a few tens of thousands of voters. Part A is United Russia, Party B is the Communist Party.

This is almost the same graph as the one in Shpilkin’s [famous article about falsifications]. Only difference is that I grouped the data by region, so that it would be easier to compare with the graph for London in No.5, where there is no data at the level of individual polling stations.

This happened in Russia.

(3) In Detroit during the 2008 Presidential elections, more than 300,000 people voted. Of them some 97% voted for Obama, who went on to win nationally (albeit with a much lower score of 53%). Obama got 100% of the vote in more than 15 of the six hundred precincts of Detroit. The biggest of the precincts where he got 100% had 580 voters.

This happened in a democratic country.

(4) The distribution of polling stations by the percentage of votes for United Russia in Tatarstan in the 2011 Duma elections.

This happened in Russia.

(5) The dependence of the share of the vote on turnout in London during the 2010 Parliamentary elections. Each dot represents a region. Each regions represents a few tens of thousands of voters. Party A are the Conservatives, while Party B are Labour.

This correlation between party vote and turnout in the UK was discovered by Sergey Kuznetsov. I gave a simple explanation for this mysterious phenomenon in this article.

This happened in a democratic country.

(6) The distribution of polling stations by the percentage of votes for United Russia in the 2011 Duma elections in Dagestan.

This happened in Russia.

(7) In one region, in districts where turnout was less than 65%, the Conservatives got 30%, while Labour got 39%. But in districts where turnout was higher than 65%, the Conservatives got 46%, while Labour got only 31%.

This happened in a democratic country.

(8) The distribution of polling stations by the percentage of votes for Obama in the 2008 Presidential elections in Washington DC.

This happened in a democratic country.

Turn the page for conclusions.

This quiz does not, of course, prove that there’s no fraud in Russian election. However, it does caution us to take overly simple methods and bold conclusions with a pinch of salt.

In particular – due to the influence of populous sub-groups with their own particular voting patterns – a fair election need NOT have a Gaussian on a graph of turnout with voting share for a particular party. In the US, African-Americans overwhelmingly vote for the Democratic Party and its candidate; this explains the spikes Obama gets close to the 100% mark. The Detroit and Washington DC results are skewed in particular because they are predominantly African-American cities, plus the former hosts the automobile industries bailed out under the Obama administration.

Likewise, the share of votes for one party having a positive correlation with turnout is not indicative of fraud either. If that were the case, not only British elections would have to be considered rigged, but also those of Germany and Israel.

Now as blog readers will know from previous posts, I do think there is substantial election fraud in Russia: Around 5-7% in the 2011 Duma elections, and 3-4% in the recent Presidential ones. (This far more resembles someplace like Italy in the 1950′s than the US today where I very much doubt fraud is higher than 1%). However, the indicators I used to reach these figures are far more varied and nuanced than the flagrant statistical misuse that the far higher fraud figures like 10%+ are based on.

(Republished from Sublime Oblivion by permission of author or representative)
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Once again, a picture that’s worth a thousand words, courtesy of Alex Kireev: A map of how Russians abroad voted in the 2012 elections (see below).

Quantitatively, they split into three main groupings, each accounting for about a third of the votes from abroad: (1) Residents of Abkhazia, South Ossetia, and Pridnestrovie; (2) Other republics of the former USSR, or the “Near Abroad”; (3) the “Far Abroad”, which is basically the rest of the world. Each of these have specific electoral patterns.

1) Here support for Putin is overwhelming: 91.1% in Abkhazia, 90.4% in South Ossetia, and 87.2% in Moldova. Though very high, practically North Caucasus-like, I do not consider these figures suspicious. All of these states – most of the Moldova voters are from Pridnestrovie – owe their de facto independence to the Russian Army, and to the Kremlin’s foreign policy. Russian military, security, and diplomatic officials stationed in these areas would also be largely pro-Putin.

2) In the former USSR, Putin too has dominant support among Russians (more so than in Russia itself): 92.6% in Tajikistan, 90.7% in Kyrgyzstan, 88.5% in Armenia, 80.9% in Uzbekistan, 76.1% in Ukraine, 77.5% in Kazakhstan, and 66.4% in Belarus. It is ironic that his lowest score would be in Belarus, ostensibly the post-Soviet country with which Russia is closest integrated: Could it be an indirect protest vote against Lukashenko, or is that Belorussian TV’s propaganda campaign in 2010 against Putin as a thief has taken root? The Baltics follow the same pattern: 89.1% in Latvia, 85.4% in Estonia, and 75.7% in Lithuania. It is perhaps indicative that the more Russians are oppressed in a Baltic country, the greater their support for Putin.

Blue: Putin wins; Darker blue: Putin wins in first round; Darkest blue: Putin wins with more than 75%; Green: Prokhorov wins. [click to enlarge]

3) In the Far Abroad, there is a real contest, but not between Putin and Zyuganov – who is unpopular practically everywhere – but between Putin and Prokhorov. There are a few further subdivisions here.

(A) In countries where the Russian presence is dominated (in relative terms) by diplomatic and/or security staff, Putin is dominant. This describes much of Africa, Latin America, and the Middle East.

In the BIC’s countries, where there are also many business-types, there is more of a contest with Prokhorov but Putin still wins: China (VVP 40.7%, MDP 34.3%); Brazil (VVP 45.1%, MDP 28.4%); India (VVP 46.2%, MDP 24.5%). (India is also curious in that Mironov performs very well there, by his standards, getting 16.6%; I wonder if @FarEasterner was one of his voters there?).

In the South-East Asian emerging markets, where the non-official presence is probably dominated by businesspeople, it is a close race between Putin and Prokhorov: Indonesia (VVP 41.3%, MDP 39.4%); Malaysia (VVP 35.2%, MDP 32.6%); Thailand (VVP 38.3%, MDP 39.7%). However, Russians in Singapore almost give Prokhorov a first round victory with 48.8%. In most other emerging markets, however, Putin wins comfortable: 63.6% in Turkey, 55.8% in Argentina, 54.3% in Mexico, 53.5% in Egypt, 51.1% in Venezuela and Colombia, 43.8% in South Korea, 43.1% in South Africa.

Putin is dominant in Orthodox and Russia-friendly Greece (84.1%), Macedonia (81.6%), and Serbia (68.0%), but one of the most popular locations for Russian relocating abroad, Cyprus, gives a lower score, 56.8%.

(C) In the Western countries, Putin is either level-pegging with Prokhorov, as in much of post-socialist East Central Europe, the Med, Scandinavia, and the Germanic lands; or decisively behind him as in the Anglosphere.

In the following Western countries, Putin would have to fight a second round with Prokhorov: Hungary (VVP 49.9%, MDP 27.9%); Poland (VVP 48.5%, MDP 30.2%); Italy (VVP 48.3%, MDP 32.1%), Israel (VVP 48.1%, MDP 38.8%), Finland (VVP 44.0%, MDP 36.2%); Spain (VVP 40.8%, MDP 37.0%); Sweden (VVP 37.0%, MDP 36.5%).

In the Anglosphere, and a few other Western countries, Prokhorov leads Putin: Japan (VVP 38.2%, MDP 36.2%), France (MDP 41.2%, VVP 31.3%), Czech Republic (MDP 43.4%, VVP 36.0%), Australia (MDP 43.5%, VVP 33.1%), Canada (MDP 43.8%, VVP 36.2%), Switzerland (MDP 44.8%, VVP 32.0%), and the Netherlands (MDP 46.4%, VVP 27.8%).

In the two major Anglo-Saxon countries, Prokhorov would win the first round outright: The US (MDP 52.4%, VVP 30.0%), and Great Britain (MDP 58.0%, VVP 28.1%).

Looking at the map, there is a striking correlation – especially for the Far Abroad nations – between the level of Russophobia (especially in the media) and Putin’s result.

In a place like Germany, though the media is highly critical of Putin, coverage is however on the whole far more balanced and sophisticated than elsewhere in the West; that might be why Putin won. The French media is highly anti-Russian – on Runet discussions, the “глюк” is used as a unit of measurement for Russophobia, inspired by André Glucksmann – however, from the comments, my impression is that the French aren’t quite as taken in by the propaganda as the British or Americans. Broadly similar things may be said of Italy.

As for the UK, it hosts people like Zakayev, Berezovsky, and Chichvarkin (him on Putin voters: “Zombies, who wake up after drinking beer and vodka and switch on the first (state-controlled) TV channel. They don’t want to think, they don’t want to work, they don’t want to learn”). It is also the global center of the radical anti-Putin opposition, represented by people like Andrei Sidelnikov, who was along with Berezovsky’s PR man Alex Goldfarb the driving force behind the establishment of the anti-Putin campaign Strategy-31 Abroad. Practically all of its major newspapers without exception take a hysterically anti-Putin tone, and in the case of the Guardian actively censor people who argue otherwise (or who question their censorship for that matter). So no wonder that the UK Russians love the robber baron Prokhorov so much, the one who got a mere 6% in Norilsk, the Russian town where he is the major employer, and whose people presumably know him well – too well, perhaps. One can only hope that Prokhorov will leave for Britain to join his oligarch buddies there, to answer his true calling in life which is to be President of Londongrad.

Needless to say, the US media is also highly Russophobic, though perhaps not quite as vitriolic as the British press (for instance, the New York Times is certainly a lot better in that regard than any major British paper). No surprise then that Putin got the second least amount of votes in the US.

The results at the polling station of the San Francisco consulate (where I happened to vote) were 57.1% for Prokhorov and 26.7% for Putin, the biggest discrepancy in all the Russian polling stations in the US. My experience is that of the people from Berkeley, votes were split evenly between Prokhorov and Zyuganov (what do you expect? It’s a leftist place), with Putin taking up third place. However, in the wider Bay Area, the electorate is dominated by Silicon Valley types, who tend to be people who emigrated from Russia during the Soviet era and who associate it with backwardness, anti-Semitism, etc., and coupled with the libertarian / bourgeois nature of their views, Prokhorov is a perfect fit for them.

In the BIC’s nations, and most of the emerging markets, where the media environment is fairly neutral as far as Russia goes – as opposed to its highly Russophobic nature in the West – Putin ends up winning comfortably, including in countries that everyone accepts to be liberal democracies like India, Brazil, Turkey, etc. In fact they are very close to the results in Russia itself, especially when one adjusts for the types of people who are likely to be abroad (richer, well-educated) to their equivalents in Russia. This is evidence that whatever supposed pro-Putin bias the media may have in Russia (and I would say that on average it is now more negative than positive) it is far, far outweighed by the anti-Putin and Russophobic bias of the Western, and especially Anglo-Saxon, media, as testified to by the fact that Russian voters in the US and the UK would rather vote for a confirmed Yeltsin-era thief and oligarch than Putin.

(Republished from Sublime Oblivion by permission of author or representative)
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Sometimes a single picture is worth a thousand words. This is one.

Though Russia remains a highly dangerous country by developed country standards, it has improved immeasurably in the past decade. Fewer Russians today die from alcohol poisonings, homicides, suicides, and even – despite a near doubling of car ownership rates – transport accidents that they did in the 1990′s to early 2000′s. Indeed, most of these “non-natural deaths” indicators are back to the levels of the late 1980′s, coinciding with Gorbachev’s anti-alcohol campaign.

The importance of this decline shouldn’t be understated. Though they only account for a small proportion of total deaths, they tend to happen at earlier ages and thus have a significant impact on the workforce and overall life expectancy. Furthermore, the fact that the pace of improvements actually speeded up during the crisis indicates that Russia is becoming a “normal country” in the sense that health improvement trends have decoupled from economic fluctuations.

(Republished from Sublime Oblivion by permission of author or representative)
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Since yesterday, the following image from an article by liberal journalist Evgenya Albats has been making the rounds on the Internet. It shows that whereas Putin’s official tally was 65%, independent observers put it close to or below the 50% marker that would necessitate a second round, such as Golos’ 51% and Citizen Observer’s 45%. Predictably, these figures were seized upon by the liberals to condemn the legitimacy of the elections. As Putin ended up getting 63.6%, while the average of all observers was 50.2%, one could conclude that the level of fraud was 13% or more.

However, as pointed out by Kireev, this is a gross misuse of statistics for political ends, because of the severe sampling problems: Golos observers were concentrated in Moscow, St.-Petersburg, and a few other large cities where Putin is less popular, while Citizen Observer is almost entirely confined to the capital. The website collates the results from all the big Russian observer projects, and from the regional data, we can see that about half the election protocols compiled to create these figures were from Moscow; almost another quarter were from Moscow oblast and St.-Petersburg.

Nonetheless, while looking through the regional data, I realized that if it were to be adjusted for its pro-Moscow (anti-Putin) sampling bias, we could get a fairly a good estimate for the level of fraud in this election; or at least, an upper limit for it. And so that’s what I proceeded to do.

After assembling the data, I came up with the following table. The first column are the different provinces. The second column is Putin’s vote according to the observer protocols for that region. The third column is Putin’s vote according to the Central Election Commission. The third column is the difference between the two. It may represent fraud, but it may also be (1) sampling bias – more on this later, (2) natural margins of error, which are especially high in regions where there were few observers. The fourth column is the total number of ballots (both real and spoiled) cast in this region.

ВВП (набл.) ВВП (ЦИК) Х бул.
Республика Адыгея (Адыгея) 59.72 64.07 4.35 220481
Республика Башкортостан 63.21 76.38 13.17 2300258
Республика Карелия 50.56 55.38 4.82 309439
Республика Коми 70.28 65.02 -5.26 525780
Республика Марий Эл 57.11 59.98 2.87 381148
Республика Татарстан (Татарстан) 72.21 82.70 10.49 2378904
Удмуртская Республика 62.50 65.75 3.25 784405
Чувашская Республика – Чувашия 59.01 62.32 3.31 702957
Алтайский край 50.90 57.35 6.45 1175430
Краснодарский край 59.96 63.72 3.76 2692090
Красноярский край 55.33 59.53 4.20 1303846
Приморский край 40.97 57.31 16.34 989669
Ставропольский край 66.80 64.47 -2.33 1195740
Хабаровский край 52.21 56.15 3.94 653997
Амурская область 59.35 62.84 3.49 399704
Архангельская область 54.83 57.97 3.14 575014
Астраханская область 60.46 68.76 8.30 432603
Белгородская область 49.22 59.30 10.08 899973
Брянская область 50.01 64.02 14.01 699848
Владимирская область 50.03 53.49 3.46 638010
Волгоградская область 58.91 63.41 4.50 1278416
Вологодская область 58.88 59.44 0.56 608595
Воронежская область 55.05 61.34 6.29 1304344
Ивановская область 60.33 61.85 1.52 519239
Иркутская область 50.49 55.45 4.96 1072723
Калининградская область 47.82 52.55 4.73 457483
Калужская область 54.18 59.02 4.84 506933
Кемеровская область 66.51 77.19 10.68 1642580
Курганская область 53.68 63.39 9.71 482391
Курская область 56.91 60.45 3.54 606717
Ленинградская область 55.86 61.90 6.04 810757
Липецкая область 54.70 61.00 6.30 626535
Московская область 52.71 56.85 4.14 3545368
Мурманская область 58.58 60.05 1.47 407311
Нижегородская область 53.58 63.90 10.32 1857953
Новгородская область 51.49 57.91 6.42 309970
Новосибирская область 52.15 56.34 4.19 1352726
Омская область 42.80 55.55 12.75 974829
Оренбургская область 50.91 56.89 5.98 1014937
Орловская область 45.22 52.84 7.62 450151
Пензенская область 53.43 64.27 10.84 765541
Пермский край 59.62 62.94 3.32 1170209
Ростовская область 58.15 62.66 4.51 2113180
Рязанская область 54.16 59.74 5.58 620967
Самарская область 52.98 58.56 5.58 1557667
Саратовская область 60.52 70.64 10.12 1323161
Сахалинская область 53.76 56.30 2.54 228350
Свердловская область 60.06 64.50 4.44 2073983
Тверская область 54.67 58.02 3.35 667496
Томская область 50.93 57.07 6.14 458311
Тульская область 58.16 67.77 9.61 867569
Тюменская область 73.19 73.10 -0.09 836179
Ульяновская область 53.99 58.18 4.19 666159
Челябинская область 60.76 65.02 4.26 1729399
Забайкальский край 60.94 65.69 4.75 498407
Ярославская область 48.58 54.53 5.95 670972
Город Москва 45.11 46.95 1.84 4247438
Город Санкт-Петербург 50.33 58.77 8.44 2388567
Ханты-Мансийский автономный округ 65.12 66.41 1.29 707504
Чукотский автономный округ 44.84 72.64 27.80 29337
Территория за пределами РФ 65.17 73.19 8.02 441931
Всего в регионах с наблюдателями 56.11 61.97 5.86 63151581
РОССИЯ 63.60 71701665

Sources: CEC regions data, Kommersant elections map, Golos’ SMS-ЦИК observer data aggregation project.

As you can see, the figures are more or less as what we can expect from analysis already published on this blog. In Moscow, fraud is minimal, the difference between observer protocols and the official result being less than 2%. We can be fairly certain about this: The protocols analyzed have data on over a million, i.e. some 1,021,810 votes, out of a total of 4,247,438 cast; at almost 25%, this is excellent coverage. Furthermore, the real fraud figure may be smaller than the 1.84% given above because the observers made sure to cover all the stations with the most suspicious 2011 results.

Coverage in St.-Petersburg is far smaller at 5%, but the fraud figure of 8.44% can still be treated as very reliable. It is backed up by other statistical evidence.

To get a figure for the regions in SMS-ЦИК dataset, which accounted for 88% of Russia’s total votes, I took the regional observer protocols’ figures for Putin and weighing them by the total number of ballots in that region. My final fraud figure using this method came out to 5.86%.

Five Caveats

This is not a conclusive fraud figure, of course, there still being at least five factors that would further influence it. Two of them are negative, one is probably neutral, and two are positive.

(1) This is a negative factor, but one that is very hard to quantify. The pro-Putin votes are weighted according to turnout, however, it is also the case that regions with greater turnout tend to have more fraud – this is because one of the most common methods of fraud is inflating turnout that almost invariably benefits Putin. But it is important stress that this relationship does not necessarily imply fraud, for it is also the case that there are subgroups of the Russian population – primarily, rural dwellers – among whom turnout is naturally higher. So we can expect turnout to be higher in some of the more rural provinces without fraud being responsible. Separating out the two is extremely tricky and is closely tied to a related problem – to what extent is fraud, or subgroups with specific voting patterns, responsible for Putin’s and United Russia’s long tails?

(2) The neutral factor (more or less) are the margins of error that come from only having a very limited numbers of observers in the more remote regions. For instance, it seems pretty unlikely there was 5% fraud AGAINST Putin in the Komi republic. ;) I am assuming that since there margins can either be positive or negative, they will largely cancel themselves out by the time we calculate the aggregate total.

(3) This is a negative factor. Some regions, accounting for 12% of the total votes, are missing from the SMS-ЦИК dataset: Altai Republic, Buryatia, Daghestan, Ingushetia, Kabardino-Balkaria, Kalmykia, Karachay-Cherkess, Mordovia, Sakha Republic, North Ossetia, Tyva, Khakassia, Chechnya, Kamchatka krai, Kirov oblast, Kostroma oblast, Magadan oblast, Smolensk oblast, Tambov oblast, Jewish autonomous oblast, Nenets autonomous oblast, Yamalo-Nenets autonomous oblast, and Baikonur (Kazakhstan).

The FOM exit poll data showed that even though the North Caucasus was the region most wracked by fraud, it also showed, at 68.4%, the highest genuine support for Putin. The election in Stavrapol krai appear to have been fair – the official figure there was actually higher than the observers’ – so let’s leave its result as is. Assuming that turnout in the ethnic minority republics of the North Caucasus was only 50% or so, as seems more likely based on anecdotal evidence rather than the 90%-like official turnout, then the real, average Putin vote across those areas would then be about 71% – still above the Russian national average, but only moderately so – as opposed to the official 89%. This would raise Putin’s real average score by a bit, but by less than he would lose from the large amount of fraud embodied in them.

Similar things can be said, albeit to a smaller extent, for the other ethnic republics (a few of which, like Buryatia, seem to be quiet fair; others, like Mordovia, which are as fraudulent as anything observed in the North Caucasus). The average Putin vote officially in all the non-North Caucasus, non-observed regions is 68%; of the ethnic Russian majority ones, only about 62%. These regions are already almost or entirely consistent with the national average, so they will have only the most insignificant impacts.

Including all the other regions will up the official score to 63.6% (by definition), but will also increase both the level of fraud and Putin’s real score. So perhaps Putin will go up to 57.0% (thanks to the genuine North Caucasus votes), but fraud will also increase to maybe 6.6%.

(4) Now this is already looking very bad, as bad as the 2011 elections, but fortunately there are two major mitigating factors. First, just as nationwide observers are biased towards Moscow, then logically at the regional level they would likewise be biased towards major urban areas. If a crew of observers volunteer in some Russian backwater province, after hearing Navalny’s call over the Internet, chances are they would hail from the big local urban center. And there are significant voting differences between town and city in Russia, with the rural voters consistently both turning out in greater numbers and giving the Kremlin candidate around 10% or even 15% more votes (e.g., in FOM’s last pre-elections poll, only 43% of Muscovites and 47% of people living in cities of more than one million said they’d vote for Putin, compared to 51% of small towners and 58% of rural folks).

Now some 25% of Russia’s population is rural, and another significant part lives in small towns; the observer presence there is all but minimal, in any one region. As such, the observer protocol figures would systemically understate Putin’s vote. To what extent? Crude back of the envelope calculation, but I think it’s valid: 25% of a subgroup that gives Putin 10% more would give him 2.5% more, and they are very much underrepresented in the poll; add another 0.5% for the small town people. Putin’s real score rises to 60.0%, while his fraud score is compressed to 3.6%; total remains, by definition, at 63.6%.

(5) It is also known that observers concentrated most on polling stations that had a legacy of suspicious results from the 2011 elections. Since it is likely that those stations are still more likely – relative to others – to be bad apples this time round, the focus on them means that the level of fraud may be further artificially skewed.


There are many ways one can interpret these results.

One can cite the 5.86% figure as the most precise one, but one that doesn’t take into account a number of complicating factors. Alternatively, one could argue for a significantly lower figure, like 3.6% – or even lower once you adjust for the last factor. Alternatively, one can argue that the positive factors cancel out the first factor, which is unknown in magnitude but surely significant, and so return to a fraud estimate of 4%-6%. This range would back the two most comprehensive exit polls, FOM which gives Putin 59.3% (possible fraud: 4.3%) and VCIOM, which gives him 58.3% (possible fraud: 5.3%).

Either way, one thing is absolutely clear: A proper analysis of the observer protocols statistics can in no way support the theory that Putin got less than 50%.

(Republished from Sublime Oblivion by permission of author or representative)
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Analysis of the election data is now trickling in, so I feel I can now make some real preliminary estimates of the degree of fraud (eventually, I will compile a list of estimates as I did for the 2011 elections). My assessment is that in these elections it was on the order of 3%-4%, which is lower than my estimated range of the 5%-7% fraud in the Duma elections, but still far too high by developed country standards. The geographical distribution of fraud has changed significantly: Moscow actually appears to be very clean this time wrong (in stark contrast to 2011, and 2009). However, there were little to no changes for the better in the ethnic minority republics, which is where the great bulk of the falsifications are now concentrated.

The most reliable evidence, in my opinion, is the FOM exit poll which gave Putin a vote of 59.3% in contrast to the 63.6% official tally – a difference of slightly more than 4%. (VCIOM gave him 58.3%, but I consider it slightly less reliable: It polled 63 regions, to FOM’s 81, and the missing regions included places like Ossetia and Daghestan where support for Putin is higher than average – even if so is the level of falsifications). Below is a table of regional falsifications, courtesy of Kireev. As you can see, the highest discrepancies between official and exit poll results – and the only ones exceeds the margin of error – are now in Federal Districts with many national ethnic minority republics: North Caucasus (Daghestan, Chechnya, etc), the Urals (Tatarstan, Bashkortostan), and the South (Kalmykia, Adygea). Across Russia as a whole, the discrepancy was 4.3%, relative to 6.3% in 2011.

FOM exit poll Official Difference
Central FD 53.8 56.6 2.8
Northwestern FD 56.3 59.1 2.8
Southern FD 59.0 63.8 4.8
North Caucasian FD 68.4 82.7 14.3
Volga FD 61.3 68.1 6.8
Urals FD 64.4 67.0 2.6
Siberian FD 61.0 62.1 1.1
Far East FD 60.3 59.9 -0.4
Russia 59.3 63.6 4.3

Moscow May Not Trust Tears But It Does Trust Gauss

Readers of the blog will know that my assessment is that Moscow was marred by extensive fraud in 2011, with United Russia getting 30%-35% as opposed to its claimed result of 46.6%. Now Putin is always 10%-15% more popular than United Russia, so the very fact that he got virtually the same score – 47.0%, to be precise – in Moscow as did United Russia three months later is damning of the capital’s 2011 elections by itself. But there is also stunning graphical evidence of this, courtesy of Maxim Pshenichnikov. The graphs below show the votes for turnout (horizontal) vs. the votes for UR/Putin (vertical), in the 2011 election (left) and the 2012 election (right). Observe the vast change from two clusters in 2011, with the bigger one around 55% representing stations where there was fraud, and the very tight, elegant cluster around 45% representing the vote for Putin in 2012.

Question to everyone who expressed skepticism that there was mass fraud in Moscow in 2011: How would you explain this difference?

The ironic thing, of course, is that the cleanness of the 2012 elections implicitly condemn the results of the 2011 elections in Moscow. Nonetheless, its still a huge boost for Putin’s legitimacy, first and foremost because Moscow is the focal point of the protests against his rule. The protesters, at least at their local level, will no longer have a leg to stand on; nor will they be able to be able to parade about with signs like the one below.

Moscow trusts in Gauss, so they will now have to trust Churov too as the two now agree with each other.

Fraud in St.-Petersburg

The picture was far worse in St.-Petersburg, with it seeing significant falsifications to the tune of perhaps 5%-6%.

There appears to be little difference between 2011 and 2012; if anything, this year there were quite a few stations with close to 100% turnout and 100% pro-Putin votes, as shown by the cluster to the top right. There is also a second cluster at a turnout of 60% and pro-Putin vote of 80%; there, too, are falsifications beyond doubt, as they are all concentrated in just two Territorial Electoral Commissions and 32 identifiable polling stations. Beyond those two patently false clusters, the spread too is very suspicious, contrasting as it does with Moscow’s elegant oval.

Graphs For All The Russias

Again from the same source, the 2011 and 2012 elections visually compared.

As I argued in my epic post on statistical methods for detecting fraud, a positive correlation between turnout and votes for Putin, or United Russia, is not necessarily indicative of fraud (First, different socio-economic subgroups are known to have different electoral patterns in Russia under fair elections, e.g. rural areas have higher turnouts, higher votes for incumbents, and bigger spreads; Second, if this correlation were proof of fraud, one must then also conclude elections in Israel, Germany, and the UK are falsified too).

Nonetheless, they are useful in the sense that they can be compared from one year to the next. And as we can see above, overall 2011 seems to have been substantially more fraudulent; in particular, the unnatural cluster near the 100%/100% mark is both bigger and darker (i.e. denser) in 2011 than in 2012.

Furthermore, the center of the huge circle in 2012 – largely representing results from the ethnic Russian urban areas – is unambiguously above the 50% mark, at about the 55% point, compared to the official result of 64.6% (difference: 10%), which means that Putin definitely got enough votes to avoid a second round. In contrast, the center of that big circle was at around 30% in 2011, compared to the official result of 49.3% (difference: 20%). Though one cannot glean direct figures from this – again, urban ethnic Russians vote more uniformly and less enthusiastically for the establishment candidates – one can get a sense of the relative scale of fraud, and this back of the envelope calculation implies that overall fraud perhaps nearly halved in 2012 compared to 2011. As fraud was 5%-7% in 2011, with an absolute reasonable upper limit of 10%, this constitutes further support for my estimate that it was close to 3%-4% this time round.

More graphs for Russia as a whole:

Number of votes vertically, result for each candidate horizontally. Putin is dark red, Zyuganov is red, Prokhorov is green.

Prokhorov has an interesting bimodal distribution, because of the influence of subgroups: The bulk of the Russian electorate (first peak), then the urban metropolises of Moscow and St.-Petersburg (second bump).

Part of the “long tail” of Putin’s and United Russia’s results are because of fraud, however part of them are also the innocent result of, again, subgroup voting patterns, namely that of rural voters among whom turnout and support for Putin are both higher than in the urban areas.

Number of votes vertically, level of turnout at which they got those votes horizontally. Putin is dark red, Zyuganov is red, Prokhorov is green.

The above shows the turnout (horizontal) vs. the median vote for each party or candidate at that level of turnout.

Anyway you look at it, all graphs would suggest aggregate falsification was less in 2012 than in 2011.

The North Caucasus: Is It Fraud, Or A Communal Voting Culture?

The most egregious discrepancies come from the Caucasus. Whereas the exit polling evidence does indicate that Putin has very high “true” support at 68.4% in the North Caucasus Federal District – when one discounts the ethnic Russian region of Krasnodar (where he got 65%) then perhaps as high as 75% for the Muslim republics, the official results – 90%+ in all the Muslim republics, including 99%+ in Chechnya – are nonetheless incredible.

Kireev has a very interesting post on the mechanics of voting in Daghestan, where officially there was 91% turnout and a 93% share of votes for Putin. An observer watched one polling station via the website, and as the station was equipped with a voting machine, it allowed him to calculate both the correct turnout and share of votes for Putin (i.e. by excluding the people throwing in more than one ballot). The results of those who voted fairly, with turnout at just 36.3% with Putin getting 60.3% and Zyuganov getting 28.1%, differed substantially from the official tally of 94.3% turnout with 84.7% votes for Putin and 10.8% for Zyuganov.

Of the non-standard voters, there were many people who turned up there with 2 or 3 bulletins, i.e. they were not “mass” ballot stuffers. The possibility exists that they were simply voting for absent family members, and as such that not all the “stuffed” votes in this category were for Putin. Then there were a few people who came in with big packs of bulletins, who really did fit the characteristic of ballot stuffers.

In their case however, my pet theory is that it may not be quite so much a case of nefarious fraud as a reflection of Daghestan’s and the North Caucasus ethnic republics’ voting cultures; namely, the practice of voting not by individuals but by teips, i.e. the clans that form the heart of Chechen, Ingush, and Daghestani society. The teip decides on a single candidate for the teip to support; Putin would get the nomination in almost every case (after all, the exit poll shows ordinary Daghestanis giving him twice as much support as the next nearest candidate, Zyuganov); and the headman would send a representative to vote for Putin on behalf of everyone in the teip.

The “non-stuffed” result in that station, with 36% turnout with 60% voting for Putin, may then represent the true “representative” feeling of urban Daghestani society, as expressed by its urban residents that are not closely affiliated to a teip. The other part of Daghestani society works on communal principles, that if you think about it actually – de facto if not de jure (because the practice is formally illegal under Russian law) – resemble the winner takes all “first past the post” system in the UK.

That said, I stress that this is a theory, an alternate way of looking at the voting in places like Daghestan, Ingushetia, Kabardino-Balkaria and Adygea that shines a slightly more positive light than the standard interpretation that their elections are marred by huge fraud; it is not fact. The possibility that communal voting is an accepted electoral practice in those regions is further supported by the presence of a similar phenomenon in local elections in Arab villages in Israel. The topic needs further research.

(Republished from Sublime Oblivion by permission of author or representative)
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András Tóth-Czifra, our heroic winner.

András Tóth-Czifra, our heroic winner.

Before the 2012 Russian Presidential elections, 23 particularly courageous (or foolhardy?) netizens and Russia watchers participated in a contest on this blog to predict its results for the chance of eternal glory and a free S/O T-Shirt.

The winner is the person with the least aggregate error, i.e. the sum of the absolute discrepancies between his or hers prediction and the official tally for each of the candidates, as well as the percentage of spoiled ballots. With 99%+ of the votes counted, it is now safe to announce the winners.

Ladies and gentlemen, please give it up for… András Tóth-Czifra!

Contestant Aggregate Error (%)
Andras Toth-Czifra 7.94
Mark Sleboda 9.84
PK 10.30
Juha Savolainen 10.54
Hunter 11.82
Moscow Exile 12.34
Mark Chapman 13.02
Gladstone 13.24
AK (i.e., me) 13.84
Andy Young 13.90
Tony 14.36
donyess 14.68
FyRuPolitics 15.23
Andor 15.90
NinaIvanovna 15.90
SH 15.90
Alex Mercouris 19.44
aap 22.48
Ernst Krenkel 25.16
Carl Thomson 27.46
Alexandre Latsa 29.54
Timothy Post 31.82
Alexey Sidorenko 39.16

Furthermore, not only did Andras have the best overall prediction, but he also called Putin’s result to within 0.5% points – also the best result. Hunter and Mark Sleboda were runners up.

AK 3.27 0.19 3.65 1.82 4.76 0.15 13.8
showdown_2012 1.77 0.19 1.35 3.22 0.56 0.85 7.9
Mark Sleboda 2.77 2.19 2.15 0.82 1.76 0.15 9.8
Alex Sidorenko 0.77 8.81 9.15 4.82 14.76 0.85 39.2
Juha Savolainen 2.27 1.19 2.65 0.32 3.76 0.35 10.5
PK 1.67 1.49 2.25 0.88 3.66 0.35 10.3
Moscow Exile 0.17 0.49 4.15 3.22 2.46 1.85 12.3
Gladstone 5.77 2.19 0.85 0.82 2.76 0.85 13.2
Hunter 4.17 4.59 0.65 1.32 0.84 0.25 11.8
Andor 4.77 1.19 0.15 0.18 6.76 2.85 15.9
Mark Chapman 3.47 2.01 1.55 0.48 4.96 0.55 13.0
Andy Young 2.77 1.19 2.15 1.18 5.76 0.85 13.9
Carl 6.77 4.81 2.15 5.82 7.76 0.15 27.5
donyess 2.77 7.19 0.15 2.18 2.24 0.15 14.7
Tony 3.17 2.01 1.35 1.62 5.56 0.65 14.4
NinaIvanovna 1.27 2.19 4.05 0.68 5.76 1.95 15.9
Ernst Krenkel 3.77 3.81 4.15 1.82 10.76 0.85 25.2
Alex Mercouris 4.66 0.36 5.06 1.88 7.32 0.16 19.4
FyRuPolitics 3.54 2.83 0.54 1.47 6.14 0.71 15.2
Alex Latsa 5.57 1.69 7.35 3.82 9.26 1.85 29.5
SH 4.77 2.19 2.15 0.58 5.76 0.45 15.9
Timothy Post 2.77 0.81 0.15 12.18 15.76 0.15 31.8
aap 1.73 7.19 4.15 2.32 6.34 0.75 22.5

As for the others… Zhirinovsky’s result was best predicted by Moscow Exile; Zyuganov’s result was jointly best predicted by Andras and myself; Mironov’s result was jointly best predicted by Andor, donyess, and Timothy Post; Prokhorov’s result was best predicted by Andor, followed by Juha Savolainen and Mark Chapman; and the percentage of spoiled votes was jointly best predicted by Mark Sleboda, Carl Thomson, donyess, Timothy Post, Alex Mercouris, and myself.

(Republished from Sublime Oblivion by permission of author or representative)
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Latest results are getting in that Putin got 63.8%. That a second round would be avoided was never really in serious doubt for the past month, nonetheless the election would still be important from several other perspectives, such as the level of falsifications (in particular, in comparison with 2011), and the relative performance of Zhirinovsky, Mironov, and Prokhorov.

I’m afraid there was still substantial fraud, greater than the 2%-3% I predicted (relative to 5%-7% in the Duma elections). The FOM exit poll gave Putin 59.3% (80,000 respondents, 81 regions), the VCIOM exit poll gave him 58.3% (159,000 respondents, 63 regions). That is a 5% point discrepancy that is too big to explain by their margins of error. In particular, the results from large parts of the North Caucasus remain as hopelessly ridiculous as ever.

That said, there were improvements, especially in Moscow. Putin got 48.7% there. This is close to, if still higher, than the 45.1% recorded in Golos observer protocols. The Citizen Observer initiative says he got 47%. (Recall that United Russia, which always lags Putin by 10%-15%, got 46.6% in Moscow in 2011, whereas Putin got only 2% points higher; this is further, if indirect, evidence of mass falsifications in 2011).

The Golos observer protocols gave Putin 54.7% nationwide. The average of observer protocols from all election monitoring organization gave Putin 50.7%, with some giving him less than 50% (one example is Navalny’s RosVybory project, which gave him a mere 49.0%). Overall, I trust the exit polls more. They are more accurate than observer protocols for sampling reasons. Exit polls try to cover the whole country, and FOM/VCIOM largely succeed. Observers are more concentrated in the more central, accessible areas, where Putin is less popular than average. Furthermore, observers in this election took special care to focus more on stations where there was evidence of fraud in 2011. As such, the effects of “bad apple” stations figure more prominently in their figures.

I prefer exit polls, post-elections polls, and statistical evidence. Grainy videos on YouTube where it’s impossible to work out what is happening, photos of lines of buses or big groups of “carousels” going about stuffing for Putin, etc are next to worthless. Speaking of those carousels, note that Moscow is a city of about 12 million. 75% are eligible to vote, and there was 60% turnout. This means there were about 5 million voters on March 4, 2012. You need tens of thousands of carousel workers and hundreds of buses (50,000 people, 1,000 packed buses = 1% for Putin) just to make the slightest uptick in the figures in support of Putin who has an unchallenged lead anyway.

In the courts, its been shown that whereas witness testimony is the type of evidence that is most frequently believed in by jurors, it is also the least objectively reliable. Same for these anecdotes about carousels and coerced voting. I view all evidence on these lines with great skepticism and recommend readers do the same.

Prokhorov did far better, getting more than 7%, than I expected, in significant part thanks to Moscow where even beat Zyuganov with almost 20%. Far more tellingly, perhaps, he only got 6% in Norilsk, where he is well-known as the owner of the nickel combine and main employer. Perhaps too well-known.

I was disappointed to see Mironov flopping, not even eking out 4%. Also a bit surprised, as I though he did very well in the TV debates. I guess most Russians disagree.

Overall, Western coverage hasn’t been quite as hysterical as in 2011, though if past experience is any guide things can change quickly for the worse (best example: First day coverage of the Ossetian war was actually fairly objective, only later becoming a propaganda fest in support of Saakashvili’s aggression).

Other things of note:

  • Putin crying
  • FEMEN booby protest. PS. A documentary on them.
  • Ballot stuffing in progress in Daghestan. The results at that station were annulled, but the 91% turnout and 93% Putin vote in that region indicates this was far from a isolated case.
  • Komsomolskaya Pravda: Караул! Лови фальсификаторов! An account of how the liberals have portrayed several things as falsifications (with “video evidence”) but which in fact were nothing of the sort. E.g., supposed “ballot stuffer” in Vladivostok was testing the machines before the start of the voting as required by regulation.
  • Georgia TV blasts Russia for fraud. Because Saakashvili is such a great democratist.
  • In case anyone was wondering why the Guardian censors users who support Putin and criticize its journalists, Luke Harding has the answer: “Many thanks for your comments! For those wondering why some have been deleted here’s Miriam Elder’s piece on Kremlin internet trolls.”
  • Mark Galeotti tweets: “Disgraceful! None of polling stations I’ve yet visited feature wheelbarrows of fake ballots, etc. Can’t they put on a show for a guest?”
  • On Mark Chapman’s blog, kievite calculates that US funds Russian opposition movement to tune of $500 million a year.
  • Alex Mercouris notes that the web cams were a genial idea.
  • The Wall Street Journalist (let me remind you, a plagiarist institution) resorts to outright, mendacious LYING to support its anti-Putin agenda: “Supporters were bused into Moscow to boost Mr. Putin’s vote in the capital, where his support has been below 20% in polls.” This is completely, utterly wrong. VCIOM predicted Putin 43.7% there; FOM, 45.0%. The real result was 47.0%, within the margins of error of both polls. Say one thing for the WSJ, though, they don’t censor my opinion there (unlike The Guardian).
  • CNN: “”The point of an election is that the outcome should be uncertain. This was not the case in Russia,” said Tonino Picula, the head of an observer mission from the Organization for Security and Cooperation in Europe (OSCE).” – Erm, that’s not the point of an election at all, Mr. Picula.
  • Eminently satisfying to see Russia Today give Luke Harding, Miriam Elder, and Shawn Walker well-deserved drubbings for their smearing, lying ways.
  • Also courtesy of Moscow Exile I found this old post by Vadim Nikitin about Luke Harding’s plagiarism, which apparently extended well beyond riffing off the eXile and Kevin O’Flynn.
(Republished from Sublime Oblivion by permission of author or representative)
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Here it is: Reading the Russian election.

Please comment at their site, rather than here, if possible.

(Republished from Sublime Oblivion by permission of author or representative)
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One of the key criticisms of my last post on the tight connections between (educational) human capital and economic performance is that correlation need not imply causation. An alternate (and PC-compliant) explanation is that “you get the education system you could afford, and the level of human capital in the kids is mostly determined by the efficiency of the schooling system.” Is there any evidence to support this argument?


As a country with a long history of normal capitalist development, and with no regions enjoying particularly lucrative resource windfalls, it is not a surprise to see a close exponential correlation between my Human Capital Index (see methodology here) and Italy’s GDP (PPP, in US dollars) per capita (R2=0.7302).


Furthermore, when we note that one of the major outliers hosts the Italian capital, and remove it, the correlation becomes even more impressive (R2=0.8221), equaling that of the Capitalist Normal countries as a group. Removing the other major outlier, Apulia, and the Germanic South Tyrol, makes the correlation almost perfect (R2=0.9461).

Is there anything like that kind of correlation between public expenditure per pupil (which according to Italian statistics has an almost perfectly linear relationship to numbers of teachers per pupil, which is one of the best proxies we have for school quality) and academic results? Not at all. (R2=0.0544, linear)


This does not strictly prove anything, but it is a good argument for the relative lack of importance of funding levels towards academic success. There appear to be hard limits to the human capital money can buy. After all, Italy’s education system is highly centralized, with a difference of a mere 20% between the highest and lowest spending provinces on education (it is also well known that it is socio-culturally variegated to a much greater extent than your typical European country, which makes it a good laboratory for social science experiments). Nonetheless, they produce a wide range of outcomes; for instance, whereas the best-performing provinces like Trentino and Friuli-Venezia Giulia get results similar to that of the Netherlands, the worst-performing ones like Calabria and Sicily have countries like Turkey and Bulgaria for company.

(A quick note about the outliers. The South Tyrol is a minor positive outlier; perhaps it can be explained by its Germanic background with its special discipline and technical skills culture. The big positive outlier, Lazio, isn’t a mystery; it hosts the capital Rome, and these regions always tend to have their GDP’s artificially boosted by the massive state presence in them. But most curious is Apulia, a massively negative outlier, which hugely outperforms all its Southern neighbors but remains one of the three poorest Italian provinces, its GDP (PPP) per capita comparable to Poland’s. Anyone have theories on why that is the case?)

Education is very important, being intricately connected with potential for productivity growth and increasing prosperity; it deserves a lot of funding, and optimizing reforms. But as Italy glaringly demonstrates, the potential for developing human capital is constrained by some combination of social, cultural, and ethnic factors; factors that can be partially mitigated but not overcome by throwing money at them. There are plenty of other examples to back this up. For instance, inner city schools in the US get a lot more in the way of funding than suburban ones – let alone average Chinese schools, which have been de-emphasized in the reform era. Nonetheless, the human capital generated in the latter two institutions far exceed that generated in the US inner city schools.

Next in this series: How to reconcile Israeli idiocy (as measured by the HCI) with Jewish intelligence (as measured by IQ tests, Nobel Prize winners, etc) – any preliminary theories?, and perhaps on how they also challenge some stereotypes about Georgians.

(Republished from Sublime Oblivion by permission of author or representative)
• Tags: Education, IQ, Italy, PISA, Psychometrics 
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Inspired by Kireev’s similar posts in Russian, I’m asking S/O readers to predict (1) The official results of the elections, and (2) The actual, i.e. non-falsified, results. Please give them to one decimal point, and include all the five candidates as well as the share of invalid votes. They will be displayed in the table below.

The winner will be the one, the sum of whose predicted results differ least from the official results. In the (very unlikely) case that there emerge two winners, i.e. they were wrong by the same amount, the one who responded earlier will be considered the winner. The reward will be ample praise on this blog and a free S/O T-Shirt. (Which reminds me, I still owe one to Alex Mercouris. Will get to work on that…)

Separately, feel free to also predict the real, i.e. non-falsified, results, or the scale of falsifications you expect in these elections. I expect 2%-3% falsifications, lower than the 5%-7% I believe happened in 2011, but not rooted out entirely.

AK 9.5 17.0 7.5 6.0 59.0 1.0
showdown_2012 8.0 17.0 5.2 4.6 63.2 2.0
Mark Sleboda 9.0 15.0 6.0 7.0 62.0 1.0
Alex Sidorenko 7.0 26.0 13.0 3.0 49.0 2.0
Alex Latsa 11.8 15.5 11.2 4.0 54.5 3.0
Juha Savolainen 8.5 16.0 6.5 7.5 60.0 1.5
PK 7.9 15.7 6.1 8.7 60.1 1.5
Moscow Exile 6.4 16.7 8.0 4.6 61.3 3.0
Gladstone 12.0 15.0 3.0 7.0 61.0 2.0
Hunter 10.4 12.6 4.5 6.5 64.6 1.4
Andor 11.0 16.0 4.0 8.0 57.0 4.0
Mark Chapman 9.7 19.2 2.3 8.3 58.8 1.7
Andy Young 9.0 16.0 6.0 9.0 58.0 2.0
Carl 13.0 22.0 6.0 2.0 56.0 1.0
donyess 9.0 10.0 4.0 10.0 66.0 1.0
Tony 9.4 19.2 5.2 6.2 58.2 1.8
NinaIvanovna 7.5 15.0 7.9 8.5 58.0 3.1
Ernst Krenkel 10.0 21.0 8.0 6.0 53.0 2.0
Alex Mercouris 10.9 16.8 8.9 5.9 56.4 1.0
FyRuPolitics 9.8 20.0 4.4 6.3 57.6 1.9
SH 11.0 15.0 6.0 8.4 58.0 1.6
Timothy Post 9.0 18.0 4.0 20.0 48.0 1.0
aap 4.5 10.0 8.0 5.5 70.1 1.9
RESULTS 0 0 0 0 0 0

Predictions will be accepted until evening March 3, Moscow time. And now they are closed, thanks to the 23 people who participated!!

As soon as we get the official results, I will compile a list of our competitors by the accuracy of their predictions.

(Republished from Sublime Oblivion 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.


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.


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.


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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Sergey Zhuravlev is a Russian economist who runs a wonky but eminently readable and very useful, interesting blog and writes for Expert (author profile), which I may add is an excellent publication. You have met him previously on my blog as the inventor of a clever – if, in my opinion, flawed – argument that the 2011 Duma elections were marred by 5%-6% fraud, but were clean in Moscow; and if you read the Russia blogs, you may also have come across Mark Adomanis’ translation of one his articles about Russian regional inequality. Now I am presenting a translation of his Feb 13 article on what I called as the end of Russia’s demographic crisis: The Reversal of the Russian Cross. In my opinion, it has a few weaknesses; in particular, he is too cavalier about dismissing the “alcohol hypothesis” about post-Soviet Russia’s “supermortality”. But overall it is a brilliant and deeply informative survey of the origins of the Russian Cross – the crossover of the births and deaths graphs in 1992 – as well as of its recent reversal, to the extent that natural population decline is now almost stabilized and the overall population is able to grow due to net migrants.

The Reversal Of The Russian Cross

Last year our country’s population increased, for the first time in 20 years. Although positive growth in aggregate was only enabled by immigration from the Near Abroad, existing trends in rising fertility and falling mortality were maintained.

If we are to go by Rosstat’s figures, in the past year Russia’s population – for the first time in virtually the entire twenty years of Russia’s existence as a sovereign state – increased, exceeding 143 million people. The maximum population size was reached in 1992, at 148.56 millions, and has since decreased at a practically monotone rate. That said, it should be added that small population growth was previously observed in 1994 and 2009, and that the population fall in 2010 was, most likely, explained by cumulative errors over the period since the 2002 Census, and by the abnormal mortality during that summer’s heatwave [AK: There were c.56,000 excess deaths during the anomalous 2010 heatwave, which is basically equivalent to population decline of 48,300. Furthermore, the 2010 Census showed there to be 143.9 million Russians, which was one million higher than projections based on the 2002 Census; this implied that during the period, net immigration was underestimated by more than 100,000 per year. So its likely that even despite the heatwave, Russia's population still eked out an increase in 2010].

Caucasian Mountains only bested by Urals Mountains

The aggregate growth in our country’s permanent population was 165,000 for the past year [AK: This was a preliminary estimate that seems to have discounted December's migration stats; the final figure is population growth of 189,000]. Although overall positive growth is only enabled by migrants – net immigration is estimated at 296,000 for this year – the rate of natural population decrease continued to decline at a fast pace. Whereas in 2005 there were 828,000 more deaths than there were births, this past year it declined to 131,000.

Russia’s population is substantially affected by the effects of migration from the former Soviet Union. In the 22 years after 1990 – the year when ethnic problems in the former USSR exploded – some 7 million people have moved to Russia for permanent residency. This figure is in net terms, accounting for reverse flows from Russia, and discounting temporary labor migrants. Although net population outflow from Russia into countries of the Far Abroad constituted 80,000 annually throughout the 1990′s – in total, 1,050,000 Russians have officially moved into countries of the Far Abroad for permanent residency since 1990 – it has practically ceased from 2006 [AK: The Far Abroad is the world outside the former USSR, minus the Baltics and (recently) Georgia. Note also that Russia's "brain drain" came to a dripping halt at precisely the time when hacks in the Western media began to propagandize it].

Russia hosts the world’s second largest migrant population, after the US; it slightly exceeds Germany in this respect, and doubly so the next five largest migrant centers: Saudi Arabia, Canada, Great Britain, Spain, and France. A third of Russia’s migrant inflow from 1990 to 2010 from the former Soviet bloc accrued to Kazakhstan. But in the noughties Kazakhstan ceded leadership as a source of migrants to Uzbekistan, and after the Orange Revolution Ukraine caught up with them, and Kyrgyzstan after the Tulip Revolution [AK: Zhuravlev has a separate blog post noting that emigration waves typically accompany revolutions in the former Soviet space. I guess its something to look forwards to if the White Ribbon crowd seizes power.]

The only former Soviet republic with which Russia has had a negative migration balance these past 21 years – in which more people left than came in – is Belarus. That said, it should be noted that starting from 2005 the migration balance with Belarus too has turned positive, albeit it remains modest (net immigration from Belarus constitutes less than 8,000 people over the past six years). It is unclear why more people left for Belarus before this date; perhaps because the Russian provinces neighboring Belarus, such as Belarus, aren’t exactly the richest ones. Maybe it was tied to family reunification – parents returning to their children, or Belorussians returning to their homeland, for instance from Komsomol construction projects. Perhaps for this same reason Russia had a net outflow of migrants into Ukraine in the very early 1990′s.

As regards internal migration, the statistics do not reveal any special revelations that could refute or even complement intuition. There are three main destinations for internal migrants: The city of Moscow and Moscow oblast (in the past year the entire agglomeration absorbed 125,000 people, or three quarters of Russia’s population growth), and St.-Petersburg (33,000 migrants in the past year). There is also substantial migration into the Southern Federal District (in significant part from the neighboring North Caucasus) and into the Urals Federal District.

An important caveat is that in the two latter cases, population growth carries an exclusively point-like character. In the Urals Federal District, it is almost entirely concentrated around Tyumen oblast, the richest province in Russia today. Due to the high levels of social support in Tyumen oblast, fertility is also high: Young families get generous housing benefits, there are special programs for families with children. On its part the situation is similar for the Southern Federal District, which grows entirely thanks to Krasnodar krai, which is also understandable: Sochi.

It is clear that Russia’s demographic situation has improved in substantial part on account of the Northern Caucasus, where a strengthening baby boom started from about 2005. The other more or less demographically balanced Russian region, experiencing positive natural population growth, is the Urals Federal District thanks in turn to Tyumen. But contrary, perhaps, to popular belief, the Northern Caucasus isn’t the main source of migrants to the Central Federal District. In 2010, the most recent year for which internal migration data is available, only 16,000 people from the North Caucasus got permanent residence in the Center. This is but a drop in the ocean to the 19 million population of the Moscow region.

The biggest “donors” to the Moscow agglomeration are the Center itself and the Volga Federal District. These two regions, which constitute the primordial Russia as it developed in the 16th-17th centuries, experience not only the maximum natural population decrease in Russia but also the maximum mechanical loss of population, which in its turn is getting fairly intensively replaced by migrants from Central Asia (and in Siberia, apparently, from China [AK: Here I disagree with Zhuravlev. While there are significant numbers of Chinese labor migrants and shuttle traders in the Far East, very few of them choose to stay. This is not the case for Central Asians.])

Wartime Losses in Peacetime

Russia’s natural population decrease has declined as a result of a significant improvement in mortality, as well as a modest increase in fertility. The fall in mortality, just as its rise earlier in the 1990′s and early 2000′s, for the most part affected men, and substantially affected their expected life expectancy. From a remarkably low level for a civilized country of 58.9 years six years ago (the minimum was 57.4 years in 1994) it has now improved to 63.6 years. This is still far from a result to write home about, but at least it is now almost equal to the best Soviet-era indicators in the early 1960′s and late 1980′s. As for mortality among under 40′s, which has always been the scourge of Russian men, the current curves are even better than the Soviet ones (granted, the share of men living to 35-40 years is now higher mostly thanks to significantly lower infant and child mortality rates).

The phenomenon of “supermortality” from 1991 to 2009 – the 6.24 million excess deaths in the past 19 years, of which 3.2 million accrue to the 1990′s, that would not have occurred had age-specific mortality rates remained fixed at 1990 levels – has yet, in my opinion, to be endowed with a rational explanation [AK: This is the weakest point of Zhuravlev's essay. Yes, there is a rational and very convincing reason: Alcohol. There is a very close correlation between alcohol consumption and mortality since the late Soviet period, when an anti-alcohol campaign reduced consumption and improved life expectancy, to local peaks in consumption - and mortality - around 1994 and the early 2000's, to the past few years, when mortality reductions have occurred in lockstep with less boozing. There are similar correlations between alcohol consumption and mortality by geography, sex, and socio-economic sex; see the evidence here.]

Despite the hugeness of the number itself. It is equal to or even exceeds the “supermortality” caused by collectivization, is almost an order of magnitude greater than the number of victims of the Great Terror, and has the same order of magnitude as the rear losses of the USSR during the Great Patriotic War.

Falling living standards? This fit the maximum in 1994, but not the second local maximum in 2003, when normality was returning. And on the whole, while living standards fell during the transition period and reattained Soviet levels only in 2003-2005, the depth of the fall was nowhere near deep enough to explain this “supermortality” as during the war years with reasons such as malnutrition, poor sanitation, and the unbearable conditions of mobilized labor. The “supermortality” of the past twenty years carried some war front characteristics: Excess mortality among males from 25 to 44 years of age in percentage terms relative to Soviet norms was maximal, at 57%. As if Russia had a war.

To this day another very popular explanation is the “alcohol hypothesis.” Booze became more accessible, people got more free time on their hands, and parasitism was no longer a jailing offense. It is probable that more accessible spirits, and especially drugs – which were little known in the USSR – played their role. However, during the period, people didn’t start to buy fewer spirits; it remained at a constant 9-10 liters of ethanol per capita annually (the contribution of homemade moonshine is purely evaluative, often they add on about 10 liters of ethanol per capital, but who’s doing the counting?).

Be that as it may, the reduction in external (“non-natural”) causes of death in the past few years was very significant and was visibly faster than the reduction in mortality from all other causes. For instance, if aggregate mortality declined by 2.9% in 2011, for non-natural causes – homicides, suicides, alcohol poisoning – it fell by 9%-17%. Albeit, mortality from traffic accidents did increase by 1.3%.

The causes for this reduction in “non-natural” mortality should probably not be sought for beyond rising living standards. Especially revealing in this context is a comparison between large megapolises, especially Moscow, with the rest of Russia. In the capital, the numbers of murders and suicides, not to even mention alcohol poisonings by counterfeit vodka, are many times lower – by up to five to ten times lower – than in the rest of the country.

In aggregate drunkenness, banditry, the increasing number of auto accidents, and the war in Chechnya explain much less than 100,000 of the annual number of abnormal deaths, which in some years have reached up to 600,000 in the past decade. Furthermore the rise in mortality also affected women, albeit to a lesser extent, for whom the chances of meeting one of the deaths described above are much less characteristic.

The melancholy arising from a career loss is surely an important factor, especially when it comes to people near the end of it. But then its unclear why mortality increases afflicted 25 year old youths; there are cases of suicide even among party and Komsomol activists of this age, even though they fit perfectly into the new capitalist economy.

The mere fact of the demise of the state of “Kuzmich” could hardly have caused such an overpowering depression, as to invoke the desire to end it lethally [AK: Кузьмичи refers to a person who grew up on Soviet kitsch and later became disillusioned by it, but was forced to continue living the lie to retain his power. This cynicism and obscurantism described the Soviet nomenklatura by the 1970's-80's.] To be honest, it was sooner the other way round: They had annoyed everyone by then. One final consideration: We may be dealing with a statistical artifact from Soviet times. It’s well known that to a Soviet economic statistics were just rubbish to a significant extent. Is it possible that similar techniques were applies to mortality statistics, even though its more difficult? [AK: I very much doubt it, not only because falsifying demographic stats is more difficult but because the picture they reveal is damning nonetheless: Stagnant life expectancy (an overall decline for men) and an infant mortality rate that actually, unique among industrialized countries in peacetime, that actually increased under the late Brezhnev period.]

Girls, Ask your Girl Friends

The shifts taking place in fertility were no less interesting. In the 1990′s, the quantity of children per woman younger than 25 years nearly halved. This decrease barely affected older women; however, because it was specifically “youth fertility” that was high in the USSR, the aggregate result was dramatic. The total fertility rate (TFR) – the number of children a woman can expect to have in her lifetime – fell from 1.89 children in 1990 to 1.16 (!) in 1999, which is, of course, very far from level required to assure population replacement. Although the noughties observed an increasing TFR on account of more births among older women – in 2009, the TFR reached 1.54 children – the total “shortfall” of births from the reduction in “youth fertility” during the 1991 to 2009 period consisted of 11.292 people.

Up until 2007, the influence of these changes on the crude birth rate – the numbers of births per 1000 people – was slightly offset by the increase in the numbers of women in their childbearing age.

In the graph below, it is clear that in this indicator, adjusted for changes in age-specific mortality, was actually growing in the 1990′s and the first half of the 2000′s. This is not surprising, as fertility was mostly formulated on account of women born in 1975 or younger, when we had a repeat demographic spurt (an echo of the baby boom of the 1950′s). After 2007, the crude birth rate is starting to be affected by the echo of its own collapse in the 1990′s and by population aging. That is why the birth rate has remained almost flat since that year, despite the number of children per woman markedly increasing. This “echo effect” is going to influence fertility in the coming decade, since women from the small 1990′s cohort will be reaching child-bearing age.

It is difficult to say with certainty what caused this fertility shift towards women of greater age. In the Soviet period, a significant contributory factor to early childbearing was that it was figured as a condition for registration for the provision of housing. Apparently, postponed childbearing was enabled by growing income inequality (as a result of which, women began to take more care in choosing a mate, with economic factors playing a significant role in the process), new opportunities for international migration, or something else.

It’s clear that under the Soviet Union, the presence of kindergartens, schools, the Constitution’s guarantee – which was more or less followed in practice – of free housing constituted significant social supports, which enabled high fertility rates. One can also add that many Soviet cities – maybe, all of them – were developed like a “company town”, with social and housing infrastructures closely tied to the town-forming enterprise. When markets were introduced, and it became clear that nobody wanted so many tractors or so many tanks and the revenues of these enterprises dried up, all this infrastructure were left hanging in thin air. There was nothing left to finance the kindergartens and nurseries, no funds to build housing. And the destruction and uncertainty, of course, also influenced decisions on having children.

The economic stabilization of the 2000′s, and especially the new social support measures introduced in 2006-2007 – maternity capital, credit programs, etc. – launched a “delayed fertility” effect, a shift of births towards older women. In general fertility has matured, albeit one shouldn’t exclude the possibility that further concerted efforts to provide social support for families and children will return TFR back to Soviet levels. In any case, more than half of the movement back is already behind us.

(Republished from Sublime Oblivion by permission of author or representative)
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.