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 Russian Reaction Blog / EconomicsTeasers

So the other day Mark Zuckerberg, who is all but officially campaining for the Presidency in 2020, came out in favor of basic income:

Every generation expands its definition of equality. Now it’s time for our generation to define a new social contract. We should have a society that measures progress not by economic metrics like GDP but by how many of us have a role we find meaningful. We should explore ideas like universal basic income to make sure everyone has a cushion to try new ideas.

I do support basic income.

Though who cares what I support. Two to three decades down the line, basic income will become all but inevitable if the oligarchs want mass consumer capitalism to survive under mass automation.

The only problem is that Mark “I Don’t Know Why They Trust Me, Dumb Fucks” Zuckerberg is just about the last person you’d trust to implement a basic income.

Don’t like his sister’s ideas on “whitewashing ancient statues”? That’s a 10% cut in your soypack purchasing power.

zuckerberg-basic-income

Mainstream Republicans and Democrats are corrupt retards who care naught beyond more tax cuts for the oligarchs and gibsmedats for the ghettoes, respectively. So its likely that it will be some political outsider President who ends up instituting basic income. In practice, given their wealth and high IQ, this in turn probably means some Silicon Valley plutocrat.

 
• Category: Economics • Tags: Facebook, Universal Basic Income 

In recent weeks I’ve had cause to look at Moscow property prices.

moscow-property-prices-2013

There are basically three major socio-economic regions in Moscow:

  • The center – Upper middle class, very high property prices (300-400,000R/sq m), cosmopolitan, tilted against Putin and towards liberal parties like Yabloko, full of cafes with Macbook toting hipsters, do not discriminate against immigrants when renting out their properties (presumably because its not like Central Asian Gastarbeiters can afford the prices there anyway).
  • The south-west and west – Middle class, moderately high property prices (200,000R/sq m), tilted against Putin and towards liberals and Communists. This region traditionally hosted a large percentage of Moscow’s academic/R&D institutions and hi-tech factories, so the locals tend to be engineers and technicians and their well-educated children.
  • The east, south and north – Lower class, low property prices (150,000R/sq m), tilted towards Putin and especially the nationalist LDPR, majority proles – though very few work in factories, with a significant contingent of lumpenproles (one woman in my flat died from a drug overdose a few weeks ago) with a growing immigrant presence.

Whereas you see many Central Asians in the center of Moscow, there they are almost inevitably doing street sweeping or construction work, whereas in the outskirts there many of them start appearing out of work uniform. Most of them actually live in the cheaper outskirts, and are increasingly buying up property there. This is accompanied by ethnic tensions. One such region, Biryulyovo – which has Moscow’s second lowest property prices – was the site of a small race war back in 2013 provoked by the murder of a Russian by an immigrant. That said, it’s (still) a long way from the yearly “fireworks” you have in Paris.

In the meantime, I also suspect that many of the more successful locals from the prole areas are making their way to more prestigious regions. In the USSR, you tended to live where you worked (your apartment was assigned to you). With a free market in real estate, the way is clear for the sort of “cognitive clustering” that you see throughout the US and Europe, where the brightest, richest, most successful (all inter-correlated) converge onto good neighborhoods close to the center, while the duller and less successful elements are left behind in the Biryulyovo banlieues.

(Incidentally, this cognitive stratification is a microcosm of Russia as a whole – the average IQ in Moscow is ~106, versus ~96 in the rest of the country).

Here is a graph that I think supports this interpretation (left: Rubles / sq m, right: USD / sq m).

moscow-property-prices-2000-2017

Vykhino and Zhulebino (blue, orange) are classic prole regions – at 120,000R per sq m, they are marginally more upscale than Biryulyovo, but only just. Sokol (red) is a solidly middle-class region, and contains two universities and an industrial museum within its boundaries. Its average property price is 200,000R per sq m. Tverskaya (green) is a super-elite central region that hosts many of Moscow’s tourist landmarks, including the Bolshoi Theater; property prices there are a cool 400,000R per sq m.

But the trend is even more interesting – note the steady stratification of property values of Sokol and Tverskaya relative to prolecore Vykhino-Zhulebino. Even as early as 2013, Sokol was only about 40% as expensive, whereas today it is more than 60% as expensive. The differential between Vykhino-Zhulebino and Tverskaya has increased from being twice as expensive a decade ago, to almost four times as expensive today.

(This isn’t due to any particularities of the chosen regions – the trend for the prole South-East as a whole relative to the middle-class South-West and the elite Center matches the specific example above).

london-house-price-map Nor do I think this is likely to change anytime soon. This differential in real estate prices is now approaching what you see in both Paris and London (see right), both of which are far more advanced on the diversity (and financialization/cognitive clustering) front than Moscow.

This isn’t great for me personally. For instance, while it was still possible to leverage my apartment, which is in one of the crappier regions, to jump into the center a decade ago and maybe 5 years ago, it’s no longer so realistic today. I suppose I should hurry up while regions like Sokol are still within reach.

I suspect these differentials will continue widening in the years ahead. Immigration will continue, and might intensify as the Russian economy emerges out of recession. Cognitive clustering has a momentum of its own and isn’t going to run out of steam anytime soon.

Finally, I suspect that the advent of driverless cars in one or two decades will produce another major uptick in housing prices in the central regions of the world’s metropolises. One of the few major downsides of life in big cities is that traffic congestion costs go up 34% with every doubling of the urban population. The much greater efficiency of driverless cars should largely nullify those costs, turbocharging property prices in big cities and especially the central, already very expensive cores of the big cities even further.

I am obviously not in the business of giving financial advice. That said, even all else equal, I suspect that in Russia as in most of the Western world, people who move to the big cities – especially the expensive, prestigious regions where high property prices form an effective wall against vibrant diversity – will do financially better than those who stay in the outskirts.

 
• Category: Economics • Tags: Moscow, Real Estate, Urbanization 

Here is a graph of monthly births in Russia since 2006 through to March 2017:

russia-births-2006-2017

It is pointless to make sweeping conclusions based on demographic data from the past one or two months.

That said, the three month moving average has been down relative to the same period in the previous year since the middle of 2016, and as of this year, has widened to 10%, an unprecedented figure in the past decade.

russia-births-change-2006-2017

Now to be sure, birth rates should – all else equal – be falling, because the diminished generation of the 1990s is now moving into its peak childbearing years. It shouldn’t be falling by 10% in any one year, however. If this new trend continues, Russia’s TFR for 2017 should fall to about 1.65 children per woman from the 1.76 in 2016.

OTOH mortality continued improving, falling by 1% in the first three months of 2017 relative to same period last year, which translates into a correspondingly greater improvement in life expectancy because of Russia’s ageing population (i.e. for the same reason that Russia’s fertility rate would increase if the number of births was to stay the same).

So I don’t want to imply all is doom and gloom after having covered Russia’s demographic turnaround for almost a decade.

However, it does perhaps warrant a reassessment of the weight we attach to different demographic projections.

For instance, the “Medium” scenario in my Russian demographic model – also the one which I long thought likeliest – involves the assumption that the TFR would converge to about 1.75 (where it has generally been since 2012), with steady convergence in life expectancy to developed world levels, and annual (official) immigrant inflows of 300,000. In this scenario, Russia’s population would actually increase to about 150 million in 2025 and 158 million by 2050 (that’s including Crimea, aka +2 million).

However, if the recent fertility decline is not a one-year blip, and were to instead to continue falling to about 1.50, then Russia’s population would stagnate (this is from before Crimea):

Low (TFR=1.5 from 2010)Population growth starts from 2011, going from 142mn to 143mn by 2023. Then it falls slowly to 138mn by 2050. The birth rate peaks at 12.5 in 2013, falls sharply to 7.8 by 2032, and then remains in the 8-9 range. The death rate troughs at 11.4 in 2032, then rises to 12.9 by 2050. Positive natural increase is never attained.

Not really the demographic apocalypse long promised by the Western media either, but a disappointing outcome nonetheless.

It’s also possible that this will further encourage the kremlins to intensify immigration from Central Asia.

 
• Category: Economics • Tags: Demographics, Russia 

Ernst & Young regularly carries out large-scale surveys of corporate employees across a range of countries on issues such as ethics and corruption in the workplace.

In the latest Global Fraud Survey (PDF), which took place at the end of 2016, 88% of Ukrainian employees thought that bribery and corrupt practices are widespread in business in this country.

Incidentally, this figure was 85% in the 2013 survey, the last year of “normalcy” before the Maidan. It was also at 80% in 2015. In short, overthrow of the “kleptocratic” Yanukovych made no difference to these figures. Zilch.

Now to be sure, the E&Y survey is more a measure of corruption perceptions than a measure of corruption itself, and the two are not necessarily the same. Still, there is definitely a correlation – according to Transparency International’s direct surveys of bribery incidence, the Ukraine consistently competes with Moldova for the status of Europe’s most corrupt nation, while the country with the lowest (best) ranking on the E&Y survey, Denmark, had 0% of respondents saying they had to pay a bribe in the past year when they were queried about it.

Overall, this is just one more piece of evidence to the effect that the Maidan has failed to solve the main problem that it set for itself.

In other news, Central Bank head Valeria Gontareva has offered up her resignation (after having disappeared from the limelight several weeks ago). In her three years of office under Poroshenko, she and her relatives appear to have done well for thmselves, like many bureaucrats throughout the post-Soviet world. Still, but many accounts, she has done a pretty good job; some 40% of financial institutions have been closed, including many offshoring funnels and pocket banks, while most of the rest have been forced to clarify their ownership structures. But with mounting uncertainties over the future of IMF credits piling up and an emerging crisis over fraud at Kolomoysky’s Privatbank before its nationalization, I suppose now is as good a time as any to part ways.

***

E&Y: Corruption perception by country

  • Question: Can you indicate whether you think it applies, or does not apply, to your country/industry or whether you don’t know?
  • Answer: Bribery/corrupt practices happen widely in business in this country.
Rank Country %
1 Ukraine 88
2 Cyprus 82
3 Greece 81
4 Slovakia 81
5 Croatia 79
6 Kenya 79
7 South Africa 79
8 Hungary 78
9 India 78
10 Egypt 75
11 Slovenia 74
12 Nigeria 73
13 Italy 71
14 Bulgaria 68
15 Turkey 67
16 Russia 66
17 Spain 64
18 Czech Republic 63
19 Portugal 60
20 Serbia 57
21 Jordan 53
. Average of all participants 51
22 Latvia 51
23 Ireland 47
24 Lithuania 47
25 Germany 43
26 Saudi Arabia 43
27 Poland 38
28 Belgium 36
29 Austria 32
30 Estonia 32
31 Romania 31
32 France 28
33 UAE 27
34 UK 25
35 Netherlands 23
36 Oman 19
37 Sweden 18
38 Switzerland 18
39 Finland 16
40 Norway 10
41 Denmark 6

.

 
• Category: Economics • Tags: Corruption, Ukraine 

In an infamous 2008 article, Alexander Dugin makes the distinction between “patriotic corruption” and “comprador corruption,” or “Eurasian corruption” and “Atlanticist corruption.”

Here are the main features of “Eurasian” (patriotic) corruption:

  • Doesn’t damage Russia’s national security;
  • Concentrates the proceeds of corruption on Russian territory, or that of allied or strategically important countries;
  • Doesn’t put the corruptioneers in a state of dependency on Russia’s enemies;
  • Do not try to legitimize themselves through political lobbying and establish themselves as social norms.

And the main features of “Atlanticist” (comprador) corruption:

  • Damages Russia’s national interests;
  • Concentrates the proceeds of corruption outside Russia, in offshore havens and in countries hostile to Russia;
  • Makes the corruptioneer susceptible to blackmail from the governments and intelligence agencies of foreign Powers;
  • Attempts to create and empower lobbying structures, such as NGOs and political parties, that could legitimize the positions of Atlanticist corruptioneers in society.

Now okay, this distinction between “patriotic” and “comprador” corruption is trivially fun to make fun of. It is almost self-parodying. It is easy to ridicule whoever is making this argument, regardless of whether or not he benefits from said corruption. Dugin was endlessly ridiculed for it (even though there are no end of other, far more legitimate ways to make fun of him, such as his opposition to Hawking’s physics). No doubt I will be ridiculed for this post.

But for all that, Dugin is not wrong.

If large-scale corruption has to exist – and we know that for most countries outside North/West Europe, it must – it is doubtless better for corruptioneers to invest in their own society, like the American robber barons did in the 19th century and which the Chinese elite mostly do today, than to stash it away abroad, as was typical for Russia in the “roving bandits” era of the 1990s, when Yeltsin’s “family” was ferrying away assets in London and Switzerland like there was no tomorrow.

And the recent revelations about the network of charitable fronts that sustain Medvedev’s property empire prove that at least Russia’s political elites have embraced “patriotic” corruption.

Consider the following:

1. Of Medvedev’s $1.2 billion empire, a good 90% of investments are in Russia itself. And the 10% that is abroad – the Tuscan villa and vineyard – is in Italy, a country that does not have any particular animus towards Russia, unlike the favorite bolthole of corrupt Russian elites, Londongrad. In the 1990s, these ratios would have likely been the inverse.

2. As “stationary bandits” with some degree of interest in preserving the value of their holdings, the Russian ruling clique has a common interest in regulating corruption. Those who overstep the bounds of what is permissible, e.g. by practicing “compador” corruption, such as United Russia MP Vladimir Pekhtin with his Florida waterfront condo; or who end up stealing far too much for their station, such as the former head of Russian Railways Vladimir Yakunin and former Defense Minister Anatoly Serdyukov, are quietly dismissed. The question of whether or not Medvedev overstepped his station is now on the cards, with the systemic opposition in the Duma, such Fair Russia’s Sergey Mironov, calling on Medvedev to answer the questions raised by Navalny’s investigation.

3. The properties in question do not directly belong to Medvedev, not even to his direct relatives, but to an opaque network of charitable foundations credited with interest free loans by Russian state banks. And since what is given can be withdrawn, and – most critically – not on the whims of Western lawmakers (who in practice only target corrupt Russians who do not serve Western geopolitical interests), but on that of the dozen or so security men around Putin who rule Russia. To be sure, those “silovarchs” like to enjoy la dolce vita themselves, but at least they are not compradors themselves, i.e. they are more loyal to Russian national interests than to foreign ones.

4. “Patriotic” corruption, relative to “comprador” corruption, is closer to how political corruption tends to operate even in Western countries such as the United States. It’s an open secret that the Clinton Foundation has very little to do with charity, and a lot more to do with currying favor with one of America’s most powerful political dynasties. One critical difference, of course, is that it is not American state banks (hence, taxpayers) providing the financing, but private actors, companies, and foreign governments that expect to get some return on their investments. Now on the one hand, personally financing the lavish lifestyle of your elites is more directly insulting. On the other hand, having the likes of George Soros and Saudi Arabia do it for you is perhaps not an altogether superior alternative.

5. To end on an especially whimsical note: Although Navalny in his video criticizes Medvedev for owning Russian vineyards while also pushing for lower excise taxes on wine, one cannot judge him too harshly for it, since it would be a great boon for public health in Russia for alcohol consumption to shift from vodka to wine. To be sure, Medvedev – or rather, the charitable funds who finance the properties and vineyards he occasionally stays at – monetarily benefits from that, but then so does the life expectancy of Russians. Perhaps former Finance Minister Alexey Kudrin, one of Putin’s few confidantes who still enjoy respectability in the West, is personally less corrupt than Medvedev, but he has also gone on record calling for Russians to smoke more to benefit the Treasury; his fiscally hard-headed lack of concern for the social good was one of the reasons why he fell out with, and was eventually sacked by, Medvedev. Which of these two would be the better choice as PM for the average Russian? It is not clear that it would be Kudrin.

Well, that’s my strained defense of Russia’s corrupt thieving elites out of the way. They should pay me for the PR, or something.

 
• Category: Economics • Tags: Corruption, Dmitry Medvedev, Russia 

On March 29, the High Court in London has decided that the sanctity of Eurobond debt trumps Ukraine’s special pleading to treat the Russian $3 billion loan to the late Yanukovych regime as odious debt and wave it away on account of Russia’s supposed “aggression” against it.

This is not the final judgment, which is still a few weeks away, but Ukraine’s chances of winning have now diminished to the purely theoretical.

Once that happens, Ukraine will be found to be in default on its loan to Russia, and since Russia belongs to the Paris Club of major creditor countries, the IMF will be prohibited from any further lending to Ukraine.

At that point, the IMF will have to decide whether it is willing to bend its own rules to continue to lend to Ukraine. On the one hand, Western countries – the United States, the EU countries, and Japan – hold a narrow majority of the voting power in the IMF, so perhaps a pro-Ukrainian decision could be lobbied through.

However, I agree with Alexander Mercouris that this is unlikely. The Ukraine has made zero to negligible progress on combatting corruption, and with the recent transport blockade of the Donbass and the nationalization of Ukrainian enterprises in the LDNR, a huge chunk of Ukraine’s foreign currency earnings are now going to go up in smoke. The IMF decision to forego a planned $1 billion tranche on March 20th cannot augur anything very good for the Ukraine.

At that point, the Ukraine could either comply with the court decision for IMF lending, or it could not.

The former will be politically risky, especially given that Poroshenko’s position now seems to be far more fragile than it was even a few months ago, with the Kolomoysky-Turchinov-Tymoshenko alliance flouting his authority with apparent impunity, from the Donbass blockade to the ejection of Russian banks from Ukraine. The alternative would be to live without the IMF, but could the Ukraine manage that?

The economy, at least until the Donbass blockade, showed signs of finally turning the corner, recently clocking up 4.7% growth by the end of the year (albeit from an extremely depressed base). The loss of the LDNR enterprises means will force the Ukraine to make deeper than planned cuts this year, and will sink its current account deep into the red just as the positive effects from its post-Maidan devaluation begin to wear off. Even in 2015, Ukraine’s government debt to GDP ratio was at 79% – anything over 60% is considered to be the danger zone for emerging economies (Russia defaulted at 75% in 1998) – and it will be worse today. Meanwhile, its war chest of $15 billion in foreign currency reserves, though a great improvement over its nadir at $5 billion in 2015, could drain away rapidly if shorn of IMF support.

The markets agree that the situation is fraught. 5 year credit default swaps for Ukraine are currently at 628 basis points, which implies that the default risk for Ukraine is higher than for any other major country bar Venezuela.

 
• Category: Economics • Tags: Economy, Ukraine 

Why is corruption so bad in Eastern Europe? And what can be done about it?

hbdchick-europe-corruption-2012-hajnal-line

First off, I don’t know to what extent it can be reduced. According to the hbdchick’s theories on the Hajnal Line, ceteris paribus, Southern and Eastern Europe will always be more corrupt than the countries of “core Europe” because they did not undergo its centuries of selection for beyond-kin altruism.

Despite decades of institutional convergence under the aegis of European integration, Italy and Greece remain considerably more corrupt than Germany, Britainn, and Sweden. Poland has improved greatly since the 1990s, but reached an asymptote at around Italy’s level; Romania, at Greece’s. From the outset, this implies that Eastern European countries should keep their ambitions realistic, regardless of the policies that they choose to pursue.

Still, political economic factors do play a large role.

The main concept that I would draw upon is Mancur Olson’s distinction between “roving bandits” and “stationary bandits.”

In unstable polities, the elites can be replaced at any time, often through unpredictable and lawless methods such as coups, or “people power” driven “color revolutions” if the new gang are more pro-Western. The elites know this. As such, they have an interest in maximizing their thievery in the here and now, with corresponding disincentives to large, capital-heavy investments that will only pay in the long-term. Most likely, they will not be around to enjoy the fruits of their labor a decade or two down the line. But a Mayfair apartment and British Virgin Islands cash stash won’t go anywhere.

This describes Ukraine, and Russia in the 1990s.

In polities where the system is more stable, “roving bandits” start to settle down – they become “stationary bandits.” There are relatively greater incentives for long-term investments – if you steal less today, your pie will be greater tomorrow. Although corruption still exists, and may even remain systemic, the more predictable nature of the tariffs levied by “stationary bandits” enables corporations to account for them in their business plans. It’s not even so much the degree of corruption that’s important as its predictability. Furthermore, the bandits at the very top have greater incentives to clamp down on their underlings, since if they get start getting too greedy it will bite into their own profit margins. This in turn can pave the way for the emergence of institutions that can upgrade the war on corruption from manual to semi-autonomous mode.

This describes countries such as Russia, Kazakhstan, and Belarus. (China would also fall into this category).

industrialized-transition These ex-Soviet countries, ruled by “stationary bandits,” have been far more successful at economic recovery (and growth) than Ukraine. For all the “Gabon with snow” jokes, Ukraine is still an industrialized country with a well educated population and a respectable average IQ of perhaps 95, with considerable natural resources, access to the sea, and Russian gas subsidies that have totalled approximately $200 billion since independence.

So the Ukrainian economy should be doing MUCH BETTER, given the huge gap between potential and reality (perhaps the biggest gap of any country in the world). But as of 2015, its inflated-adjusted GDP was a mere 60% of the UkSSR’s in 1990 (Russia: 110%; Belarus: 180%), and is now in a neck-and-neck race with Nigeria in terms of Internet penetration.

Telling example: One of the few genuinely bright spots in the Ukrainian economy has been the IT sector. In particular its presence on the video game scene is rather impressive in relative terms – Cossacks, Stalker, Metro 2033.

Why? Because that is what you get when you combine roving bandits with a high IQ population. Few people are willing to build anything substantial like a multi-billion dollar factory. Hence, so far as heavy industry goes, it just continues to coast on the ever depreciating Soviet legacy.

How much capital do you need to launch a middle-sized video game studio? Can’t imagine it’s much more than $100,000. Most of the value is in the brains, and you get some of the best cognitive bang per dollar in the Ukraine. You can sell your game on Steam, and should instability strike, you can just bugger off to someplace warmer and more civilized, like Cyprus or Malta (like 4A games, the creators of Metro 2033, did in 2014).

Incidentally one can see the same thing (if to a significantly smaller extent) in both Russia and Belarus.

How to solve – or at least mitigate – corruption follows naturally from the above observations.

(1) The roving bandits need to be settled down. (Replacing one gang with another under the cover of a color revolution doesn’t do anything – as Ukraine has already proven, TWICE).

In Ukraine’s case, that means it needs to put an end to its never-ending internecine struggles. Broadly speaking, both Novossiya supporters and Ukrainian nationalists have the right idea, even if they are otherwise diametrically opposed. (Nadia Sevchenko represents a curious convergence of these two streams: A Ukrainian nationalist to the core, she has negotiated with LDNR authorities in contravention of official Kiev policy while suggesting that Ukraine needs a period of dictatorship to get itself sorted out).

(2) East Asia furnishes many several examples of non-Hajnal societies that have successfully solved the corruption problem. One approach is greater criminal penalties for corruption (“kill the chicken to scare the monkey,” as the Chinese proverb goes); another is to richly compensate civil servants, so as to reduce the relatice incentive for additional thievery (Singapore government ministers are paid like the CEOs of big corporations, and in tandem with harsh punishments and wealth, this has helped Singapore become one of the world’s least corrupt societies, despite traditional China’s penchant for corruption).

In practice, neither of these is practical for Eastern Europe. European human rights regulations preclude the killing of chickens; and East Europeans themselves are far too populist and demotic to tolerate elitist-technocratic policies like CEO-scale salaries for bureaucrats (with the result that said bureaucrats will unofficially continue to compensate themselves at CEO levels anyway, but with huge markups).

(3) The removal of roving bandits will enable faster economic growth, and greater tax receipts allow you to pay more to develop institutions, while greater per capita wealth leads to money floating about for the development of an indigenous civil society. It also makes e-government, which makes far less demands on face-to-face interactions between citizens and bureaucrats, with all their associated potential for corruption, far more realizable.

(4) To be sure, it can be very frustrating to live in a country that is visibly and strikingly more corrupt than the fairylands of core Europe. It is understandable that people, especially young people without much life experience, want change, and they want it quick. More often than not, the result is a cargo cult approach to combatting corruption, which results in spectacles such as Anti-Corruption Forums to which the participants show up in Mercedes and Lexuses (a most apt metaphor for Euromaidan).

From this perspective, an understanding of the deep gene-cultural underpinnings of corruption might not lead you to forgive everything, but it will at least imbue you with a sense of realism as to what is and what is not possible. A slow, steady convergence over two or three decades to Italy’s or even France’s level of corruption – entirely possible, even likely. A new Sweden overnight through the power of mass lustrations and Lenin statue topplings? Nope.

Going ahead will only set you up for eventual disappointment, but in the meanwhile, you’d have wrecked your own country.

Finally, don’t worry. In the end, corruption just isn’t that important to economic growth! Just compare Chile and China: One by far the cleanest country in South Americat; the other one is far more corrupt, but a standard deviation higher in average IQ. Which of those two is the economic steamroller, and which one has nothing to write home about? Exactly. And corruption tends to diminish with increasing wealth, as the power of institutions and civil society increases. Just don’t smother your economy with regulations and central planning, don’t allow roving bandits to pick the place clean and stymie all long-term development, and the problems should ultimately resolve by itself without any particular further effort on your part.

PS. Daniel Chieh comments: “These days, modern China has moved significantly from executions to pressuring corrupt officials to commit suicide: possibly a return to honor suicides that was the norm in Asia and perhaps part of the entire initiative for Xi’s “return of traditional Chinese virtues.” Honor suicides just doesn’t seem to be a thing in East Europe, that I know of, anyway. Human rights law in Europe in theory wouldn’t stop all methods of “killing the chicken” as there are a number of other “greater criminal punishments” that don’t include capital punishment – which is rarely used these days, to be honest. Mass social shaming, prohibitions on future job-seeking, reduced status opportunities and unfavorable associations that spread even to the family all work just as well.The life of a pariah can be worse than death, imo.

 
• Category: Economics • Tags: Corruption, Russia, Ukraine 

The final figures for life expectancy and TFR in total and for the regions have been released today.

The Rosstat computations give an estimate of TFR = 1.76 children per woman and LE = 71.9 years for 2016, which are pretty close to my rough estimates a month ago.

The total population is estimated to be 146,804,372 at the end of the year.

Not really much extra to comment on than what I already have in February.

One thing of note is that Crimea has by now been fully integrated into the statistics so we can begin to analyze how its doing after liberation from the yoke of Ukrainian backwardness.

For instance, in terms of disposable income, Crimea remains well behind almost all majority ethnic Russian regions, including neighboring Krasnodar Krai (which became post-Soviet Russia’s main breachfront location). However, it is also converging quickly. Although Russia was in a recession during 2016, with only 0.7% growth in disposable incomes (-5.4% inflation), Crimea and Sevastopol both grew by more than 15% – the fastest rate of increase in Russia.

Ukraine was, of course, also in recession during this period.

The fertility rate in Crimea and Sevastopol has also increased since 2014, which you presumably wouldn’t expect of regions under brutal occupation.

TFR

TFR 2013 2014 2015 2016
Russian Federation 1.707 1.750 1.777 1.762
Central Federal District 1.478 1.514 1.575 1.595
Belgorod Oblast 1.526 1.544 1.561 1.547
Bryansk Oblast 1.534 1.557 1.650 1.612
Vladimir Oblast 1.591 1.643 1.730 1.712
Voronezh Oblast 1.437 1.471 1.517 1.484
Ivanovo Oblast 1.554 1.572 1.629 1.595
Kaluga Oblast 1.644 1.689 1.836 1.785
Kostroma Oblast 1.852 1.866 1.890 1.880
Kursk Oblast 1.674 1.699 1.716 1.643
Lipetsk Oblast 1.601 1.657 1.700 1.687
Moscow Oblast 1.522 1.600 1.675 1.727
Orel Oblast 1.530 1.552 1.603 1.590
Ryazan Oblast 1.552 1.595 1.640 1.703
Smolensk Oblast 1.480 1.528 1.522 1.509
Tambov Oblast 1.423 1.493 1.512 1.503
Tver Oblast 1.639 1.663 1.696 1.709
Tula Oblast 1.424 1.466 1.568 1.547
Yaroslavl Oblast 1.635 1.640 1.695 1.710
Moscow 1.328 1.341 1.406 1.460
North-West Federal District 1.574 1.613 1.657 1.670
Republic of Karelia 1.648 1.744 1.766 1.763
Komi Republic 1.961 2.013 2.002 1.972
Arkhangelsk Oblast 1.803 1.835 1.847 1.833
of which:
_Nenets Autonomous Okrug 2.312 2.423 2.584 2.774
_Arkhangelsk Oblast 1.784 1.812 1.818 1.795
Vologda Oblast 1.852 1.856 1.922 1.897
Kaliningrad Oblast 1.644 1.699 1.745 1.728
Leningrad Oblast 1.227 1.282 1.286 1.318
Murmansk Oblast 1.623 1.649 1.714 1.653
Novgorod Oblast 1.700 1.749 1.776 1.776
Pskov Oblast 1.675 1.695 1.741 1.796
St. Petersburg 1.482 1.522 1.591 1.634
Southern Federal District 1.642 1,711 1 1,735 1 1.719
Republic of Adygea 1.684 1.730 1.724 1.681
Republic of Kalmykia 1.882 1.853 1.831 1.708
Krasnodar Krai 1.825 1.818 1.763
Republic of Crimea 1.724 1.805 1.840 1.829
Astrakhan Oblast 1.911 1.968 1.970 1.938
Volgograd Oblast 1.529 1.571 1.589 1.574
Rostov Oblast 1.522 1.605 1.627 1.596
Sevastopol 1.649 1.821 1.726
North Caucasus Federal District 1.987 2.034 1.979 1.936
Dagestan Republic 2.015 2.077 2.022 1.978
Republic of Ingushetia 2.231 2.278 1.971 1.752
Kabardino-Balkar Republic 1.803 1.831 1.753 1.724
Karachay–Cherkessia 1.673 1.650 1.541 1.518
Republic of North Ossetia – Alania 1.977 2.009 1.930 1.891
Chechen Republic 2.925 2.912 2.799 2.622
Stavropol Krai 1.548 1.617 1.644 1.678
Volga Federal District 1.750 1.789 1.818 1.788
Republic of Bashkortostan 1.887 1.948 1.939 1.860
Republic of Mari El 1.926 1.981 1.993 1.980
Republic of Mordovia 1.366 1.374 1.360 1.403
Republic of Tatarstan 1.832 1.844 1.863 1.855
Udmurt Republic 1.922 1.959 2.006 1.956
Chuvash Republic 1.851 1.878 1.909 1.869
Perm Krai 1.932 1.977 2.018 1.979
Kirov Oblast 1.868 1.885 1.913 1.943
Nizhny Novgorod Oblast 1.561 1.593 1.669 1.649
Orenburg Oblast 2.001 2.027 2.013 1.946
Penza Oblast 1.486 1.529 1.550 1.503
Samara Oblast 1.589 1.647 1.708 1.714
Saratov Oblast 1.536 1.574 1.601 1.550
Ulyanovsk Oblast 1.611 1.673 1.712 1.705
Ural Federal District 1.907 1.960 1.965 1.919
Kurgan Oblast 2.115 2.101 2.123 2.030
Sverdlovsk Oblast 1.871 1.921 1.945 1.911
Tyumen Oblast 2.004 2.073 2.072 2.009
of which:
_Khanty-Mansiysk Ugra-Autonomous Okrug 2.050 2.090 2.073 2.020
Yamalo-Nenets Autonomous Okrug 2.090 2.189 2.188 2.084
Tyumen Oblast 1.959 2.054 2.064 2.002
Chelyabinsk Oblast 1.802 1.855 1.843 1.809
Siberian Federal District 1.880 1.902 1.902 1.870
Altai Republic 2.815 2.883 2.677 2.634
Republic of Buryatia 2.205 2.260 2.280 2.237
Republic of Tuva 3.424 3.485 3.386 3.345
Republic of Khakassia 2.013 2.007 1.986 1.967
Altai Krai 1.830 1.841 1.811 1.777
Zabaykalsky Krai 2.014 2.078 2.057 1.979
Krasnoyarsk Krai 1.775 1.807 1.837 1.815
Irkutsk Oblast 1.978 1.966 2.012 1.989
Kemerovo Oblast 1.787 1.778 1.726 1.713
Novosibirsk Oblast 1.749 1.765 1.817 1.805
Omsk Oblast 1.867 1.951 1.911 1.808
Tomsk Oblast 1.591 1.593 1.600 1.581
Far Eastern Federal District 1.814 1.869 1.893 1.858
Republic of Sakha (Yakutia) 2.168 2.247 2.191 2.090
Kamchatka Krai 1.773 1.850 1.887 1.890
Primorsky Krai 1.685 1.732 1.761 1.736
Khabarovsk Krai 1.744 1.787 1.854 1.779
Amur Oblast 1.844 1.849 1.838 1.817
Magadan Oblast 1.693 1.659 1.664 1.596
Sakhalin Oblast 1.808 1.962 2.019 2.156
Jewish Autonomous Oblast 1.857 1.948 2.022 1.987
Chukotka Autonomous Okrug 1.906 2.041 2.097 2.112

Life Expectancy

Russian Federation 70.76 70.93 71.39 71.87
Central Federal District 71.93 72.10 72.72 73.07
Belgorod Oblast 72.16 72.25 72.61 72.87
Bryansk Oblast 69.75 69.42 70.36 70.92
Vladimir Oblast 69.13 69.25 69.82 70.28
Voronezh Oblast 70.89 70.82 71.67 72.08
Ivanovo Oblast 69.84 69.88 70.62 70.77
Kaluga Oblast 70.02 69.93 70.73 71.18
Kostroma Oblast 69.86 70.05 70.38 70.87
Kursk Oblast 70.14 70.11 70.80 70.94
Lipetsk Oblast 70.66 70.60 71.07 71.62
Moscow Oblast 70.78 70.94 72.26 72.50
Orel Oblast 70.22 69.88 70.38 70.73
Ryazan Oblast 70.74 70.80 71.46 71.87
Smolensk Oblast 68.90 69.44 69.74 69.98
Tambov Oblast 70.93 71.11 71.67 72.11
Tver Oblast 68.13 68.43 69.10 69.24
Tula Oblast 69.41 69.63 70.06 70.56
Yaroslavl Oblast 70.45 70.64 70.98 71.21
Moscow 76.37 76.70 76.77 77.09
North-West Federal District 71.25 71.42 71.70 72.16
Republic of Karelia 69.19 69.36 69.16 69.78
Komi Republic 69.27 69.05 69.40 69.45
Arkhangelsk Oblast 70.16 70.23 70.71 70.82
of which:
_Nenets Autonomous Okrug 65.76 70.65 71.00 71.08
_Arkhangelsk Oblast 70.27 70.20 70.70 70.80
Vologda Oblast 69.35 69.74 70.40 70.24
Kaliningrad Oblast 70.51 70.28 70.58 71.92
Leningrad Oblast 70.36 70.28 71.23 71.70
Murmansk Oblast 70.46 69.97 70.24 70.94
Novgorod Oblast 67.67 68.41 68.70 69.15
Pskov Oblast 67.82 68.07 68.48 69.25
St. Petersburg 74.22 74.57 74.42 74.90
Southern Federal District 71.76 71,74 1 72,13 1 72.29
Republic of Adygea 71.80 72.01 72.22 72.59
Republic of Kalmykia 71.35 72.03 72.15 73.35
Krasnodar Krai 70.74 70.52 70.74
Republic of Crimea 72.29 72.28 72.53 72.83
Astrakhan Oblast 71.34 70.76 71.36 72.20
Volgograd Oblast 71.42 71.62 71.98 72.49
Rostov Oblast 71.39 71.30 71.90 72.20
Sevastopol 72.28 70.67 71.64
North Caucasus Federal District 73.95 74.11 74.63 75.13
Dagestan Republic 75.63 75.83 76.39 77.23
Republic of Ingushetia 78.84 79.42 80.05 80.82
Kabardino-Balkar Republic 73.71 74.16 74.61 75.12
Karachay–Cherkessia 73.94 73.91 74.44 74.72
Republic of North Ossetia – Alania 73.94 73.82 74.20 75.05
Chechen Republic 73.20 73.06 73.45 74.20
Stavropol Krai 72.75 72.75 73.36 73.40
Volga Federal District 70.06 70.20 70.71 71.39
Republic of Bashkortostan 69.63 69.76 70.08 71.00
Republic of Mari El 69.30 69.42 69.80 70.75
Republic of Mordovia 70.56 71.38 72.06 72.25
Republic of Tatarstan 72.12 72.17 72.81 73.64
Udmurt Republic 69.92 70.03 70.46 70.86
Chuvash Republic 70.79 70.62 71.35 71.52
Perm Krai 68.75 69.04 69.09 69.74
Kirov Oblast 70.26 70.59 71.11 71.71
Nizhny Novgorod Oblast 69.42 69.53 70.17 70.75
Orenburg Oblast 68.90 68.73 69.63 70.57
Penza Oblast 71.54 71.63 72.12 72.53
Samara Oblast 69.40 69.63 70.35 71.08
Saratov Oblast 70.67 70.95 71.40 72.07
Ulyanovsk Oblast 70.50 70.37 70.46 70.97
Ural Federal District 70.06 70.20 70.38 70.82
Kurgan Oblast 68.27 68.75 69.03 69.43
Sverdlovsk Oblast 69.81 69.76 69.83 70.02
Tyumen Oblast 71.35 71.50 71.76 72.33
of which:
_Khanty-Mansiysk Ugra-Autonomous Okrug 72.23 72.27 72.58 73.50
Yamalo-Nenets Autonomous Okrug 71.23 71.92 71.70 72.13
Tyumen Oblast 70.14 70.32 70.58 71.03
Chelyabinsk Oblast 69.52 69.71 69.90 70.50
Siberian Federal District 68.63 68.85 69.31 69.81
Altai Republic 67.34 67.76 68.44 70.13
Republic of Buryatia 67.67 68.54 69.15 69.61
Republic of Tuva 61.79 61.79 63.13 64.21
Republic of Khakassia 68.57 68.83 68.68 69.33
Altai Krai 69.77 70.01 70.44 70.74
Zabaykalsky Krai 67.11 67.38 67.34 68.33
Krasnoyarsk Krai 69.06 69.23 69.69 70.01
Irkutsk Oblast 66.72 66.87 67.37 68.20
Kemerovo Oblast 67.72 67.80 68.31 68.72
Novosibirsk Oblast 70.19 70.28 70.86 71.20
Omsk Oblast 69.74 70.13 70.41 70.78
Tomsk Oblast 70.33 70.67 71.25 71.66
Far Eastern Federal District 67.81 68.21 68.68 69.22
Republic of Sakha (Yakutia) 69.13 69.81 70.29 70.84
Kamchatka Krai 67.98 68.06 68.56 68.66
Primorsky Krai 68.19 68.74 69.21 69.66
Khabarovsk Krai 67.92 68.01 68.72 69.13
Amur Oblast 66.38 67.00 67.27 68.28
Magadan Oblast 67.12 67.19 68.11 69.00
Sakhalin Oblast 67.70 67.89 67.99 68.66
Jewish Autonomous Oblast 64.94 65.20 65.04 65.88
Chukotka Autonomous Okrug 62.11 62.32 64.16 64.42
 
• Category: Economics • Tags: Demographics, Russia 

The reason I don’t write much about Russia’s demographics nowadays is that there isn’t much point to it.

Up until the early 2010s, the Western media was brimming with misinformation about the subject – what we now call #fakenews – so refuting it was both profitable and easy. Incredibly easy. You didn’t really have to do anything much more complicated than taking a few minutes to browse through Russia’s national statistics database, but apparently that was beyond the capabilities of most Russia journalists.

However, by now a critical number of Western pundits have apparently acquainted themselves with at least the Wikipedia article on Russia’s demographics. In the longterm, reality wins out, and so with a lag time of about a decade, references to Russia’s “plummeting population” and “sixth wave of emigration” have steadily petered out (the last major holdouts of Russia demographic doomerism was Barack Obama in this 2014 interview with The Economist, and Michael Rubin for Commentary in 2015,).

We can now finally say that the “Dying Bear” meme has fulfilled lived up to its own name.

***

Anyhow, preliminary demographic results for 2016 are in.

Births remained marginally ahead of deaths, both at around 12.9/1,000 people, though the usual ~300,000 annual net immigrants (almost half of them from Ukraine) will ensure that overall population growth remains decidedly positive.

russia-births-deaths-1946-2016

Births decreased by 2.6%. The full impact of the small 1990s cohort is now being felt, so this was always inevitable. Deaths also declined by 1.2%, despite the ongoing aging of the population. This pretty much completes what I termed The Russian Hexagon, the successor to the so-called “Russian Cross” in the early 1990s when the births and deaths graphs intersected; in the past decade, birth and death rates once again converged, but from the opposite direction, forming a sort of hexagon.

russia-tfr-1946-2016

The Total Fertility Rate seems to have stabilized at around 1.75 children per woman (inevitable question: How much without Muslims/ethnic minorities? Approximately 0.1 children less, based on completed fertility data from the 2010 Census).

This makes sense. As I pointed out almost a decade ago, Russian fertility preferences are similar to those of Scandinavians and the Anglosphere (~2.5 children per woman), and higher than that of Visegrad/The Med (~2.1 children) or the Teutonic world (1.7 children), so convergence to at least this level was always on the cards as soon as some semblance of economic stability and predictability was restored.

As I pointed out, this makes Russia’s fertility rates reasonably respectable by European standards; they are only noticeably higher in France, Ireland, the UK, and Sweden.

russia-life-expectancy-1946-2016

Life expectancy is now close to 72 years, which is the highest it has ever been in Russia’s history.

One way of looking at this is that mortality trends in Russia are basically tracking improvements in the ex-Soviet Baltics (and the City of Moscow) with a lag of ten years, so there is good reason to expect this trend will continue.

This is primarily linked to the big reduction in vodka bingeing during the past decade, which depressed Russian life expectancy by about a decade relative to what it “should be” based on its GDP per capita and healthcare system. This “alcoholization” began to soar from around 1965, and peaked in the 1990s and early 2000s. According to calculations by the demographer Alexander Nemtsov, something like a third of Russian mortality around 2005 could be attributed to it.


Blast from the Past

Incidentally, back in 2008, I created a demographic model for Russia, which enabled me to accurately predict a resumption in both total (2010) and natural (2013) population growth to the exact year.

In the scenario where TFR is set to a constant 1.75 children per woman, the “Medium” scenario of mortality improvements (which has best tracked Russia’s life expectancy trends to date), and about 300,000 annual immigrants, it predicted the following:

Medium (TFR=1.75 from 2010)The population grows from 2010, rising from 142mn to 148mn in 2025 and 156mn in 2050. The death rate troughs at 10.8 in 2034, before zooming in to 11.5 by 2050. The birth rate peaks at 13.6 by 2014, before plummeting to 9.7 in 2033, before recovering to 11.9 in 2046 and again falling, although less rapidly than before.

How does this stack up against reality? The birth rate reached a multi-year plateau at 13.3 children per woman during 2012-2015, when the decline in the numbers of women of childbearing age were exactly offset by rising total fertility rates. The mortality rate fell steadily throughout this period, just as predicted, though it is marginally higher as of 2016 (12.9/1,000) than in the Medium variant (12.6/1,000).

Overall, this is pretty close, and suggests that the model is fundamentally sound and thus so are its future population projections.

Of course it has to be adjusted upwards by 2.3 million to take into account Crimea, and any further (re)gatherings of rightful Russian clay.


 

As alcohol abuse fell, so did all of the other components of mortality, especially those most strongly associated with it, i.e. deaths from external causes:

russia-deaths-external-causes-1990-2016

… which includes homicides, suicides, deaths from transport accidents (despite soaring vehicle ownership), and, self-referentially, deaths from alcohol poisoning.

russia-mortality-alcohol-murder-suicide-1990-2016

Part of this reduction was due to cultural change, including the realities of life under capitalism (if you turn up to work drunk, you can be fired, unlike under socialism), part of it was due to economics (more diversity of choice), and part of it was thanks to specific Kremlin policies, such as steady increases in the excise tax on alcohol and restrictions on alcohol advertising.

Finally, the abortion rate continues to quietly decline. The ratio of abortions to births is now down to 40%, down from well more than 100% during the era from the post-Stalin legalization of abortion to the 1990s. This is still about 2-3x higher than in most of Western Europe and the US, but Russia is longer the absolute outlier it once was.

russia-abortion-rate-1957-2016

Just like the trends with fertility and mortality, this too can be considered a return to “demographic normality” after the Soviet aberration.

One important point: Conservative talking points to the contrary, there is no hard evidence that high abortion rates actually decrease fertility. Low abortion rates are good though for general health reasons and (depending on your religious views) for ethical ones but they have very little to do with demographic health per se.

Even though it completely bans abortions, Poland has one of Europe’s lowest fertility rates. For some reason Mark Steyn never did dwell on that…

 
• Category: Economics • Tags: Demographics, Russia 

transparency-cpi-2016

Has been released.

It is basically a composite index of about a dozen subjective corruption ratings given out by various development organizations and more political NGOs (e.g. Freedom House).

Although it generally reflects reality, as in it correlates well with other, more objective measures of corruption, there are two major caveats:

(1) It is not necessarily accurate for any one particular country. You would be better off looking at things like Transparency International’s own Global Corruption Barometer surveys of everyday bribery, the World Bank’s enterprise surveys, and expert assessments (preferably blind) of national legislation such as the Global Integrity Index, the Open Budget Index, and the Revenue Watch Index. (I tried to combine some of them here).

(2) The people actually doing the ratings are employed by outfits such as the World Bank and democracy promotion NGOs. This means their perspectives are going to be ideologically loaded in predictable directions.

For instance, it’s pretty likely that despite the Maidan’s promises, Ukraine is still considerably more corrupt than Russia. Although Ukraine and Russia score an equally bad 29/100 according to the CPI, there are differences in their component scores [XLSX]. The World Economic Forum Executive Opinion Survey, which queries businesspeople who are more concerned with profits than politics, gives Russia 38/100 to Ukraine’s 27/100. The “political” NGOs, however, rate Ukraine higher; Freedom House gives it 33/100 to Russia’s 25/100.

 
• Category: Economics • Tags: Corruption 

In international sociological comparisons of happiness Russia and the ex-USSR have become pretty much bywords for very low levels of happiness and life satisfaction.

Here is a not atypical graph showing Russia as one several extreme outliers.

russia-happiness-2000

However, polling evidence suggests this is an increasingly dated view, much as demographic data has already long invalidated the “dying Russia” trope.

russia-happiness-vciom-1990-2016

The above graph shows the results of VCIOM opinion polls on subjective happiness since 1990. The index represents the numbers of people saying they feel very or somewhat happy minus those saying they feel very or somewhat unhappy.

There was a peak at the height of the late 2000s boom, which went down during the recession. However, sentiments quickly recovered, and were impervious to the effects of the current (much milder) recession.

Moreover, the percentage of Russia now saying they are “very happy” – at 39% – is now almost twice as high as the 22% seen in 2008, to say nothing of the typical 5-10% figures during the 1990s.

 
• Category: Economics • Tags: Happiness, Russia 

Transparency International has released the Global Corruption Barometer 2016 for Europe:

transparency-international-gcb-2016-bribery-in-europe

The map above shows the answer to the most interesting question in the survey: “Did you or any member of your household make an unofficial payment or gift when using [a public service] over the past 12 months“?

In the last survey from 2013, at the height of the kleptocratic Yanukovych regime, that figure was 37% in Ukraine.

In this survey, it was 38% – the same as in Uganda.

In other words, more than three years after the beginning of the “Revolution of Dignity,” there has been absolutely no appreciable decline in corruption in Ukraine.

This is, incidentally, confirmed by other figures (earlier I posted a poll showing the bribery rate increasing from 37% to 40% between 2014 and 2015).

But what can one expect? What Westerners don’t get is that is that Maidanist Ukraine’s commitment to transparency is one big fat cargo cult. But what else can you expect in a country where “activists” turn up to “anti-corruption forums” in Lexuses and Mercedes? Where the physical symbol of the previous regime’s corruption, a golden loaf, went missing soon after the “revolution”? In a country that overthrew one kleptocrat and replaced him with a post-Soviet oligarch and one of the godfathers of Ukrainian clan politics?

To be sure, Russia with its 34% bribery rate (equivalent to Cote d’Ivoire), the joint-third worst in Europe after Moldova and Ukraine, has nothing to write home about either. It is a disturbing indication that there have been no improvements in everyday corruption during Putin’s time in power.

But at least Russia didn’t wage a war against its own people in the name of Poroshenko’s frescoes, oops, I meant “European values.”

But anyway – commenting on the map in general, the results are very much as expected based on country stereotypes and other subjective rankings like the CPI. That said, it’s worth nothing that Greece has made significant progress – whereas in 2013, 22% of Greeks had paid bribes, this year only 10% did.

 
• Category: Economics • Tags: Corruption, Russia, Ukraine 

Nothing illustrates China’s meteoric rise as some well chosen numbers.

By the end of the 1990s, China had come to dominate the mainstays of geopolitical power in the 20th century – coal and steel production. As a consequence, it leapt to the top of the Compositive Index of National Capability, which uses military expenditure, military personnel, energy consumption, iron and steel production, urban population, and total population as a proxy of national power. Still, one could legitimately argue that all of these factors are hardly relevant today. While Germany’s fourfold preponderance in steel production over Russia may have been a critical number in 1914, China’s eightfold advantage in steel production over the US by 2014 is all but meaningless in any relevant comparison of national power. The world has moved on.

By the end of the 2000s, like Victorian Britain in the mid-19th century, China became the workshop of the world, overtaking the US in both manufacturing and coming very close to it in terms of PPP-adjusted GDP. As a consequence, this was when China also overtook the US on a wide range of consumer welfare and ecological impact indicators, such as exports, CO2 emissions, Internet users, energy consumption, car sales, car production, and number of patents issued. Still, its presence in the hi-tech sector was still pretty modest, and innovation was low. This was not yet an economy that could furnish first-class armaments, or inspire far off peoples to carry out color revolutions in its name.

But as of this year, China is hurtling past yet another set of inflection points – the hi-tech component of its economy, roughly comparable to any of the major European Powers a mere decade ago, is now about to converge and then hurtle past that of the US by the end of the 2010s (even if in per capita terms it remains considerably behind, like South Korea 20 years ago).

This process can be proxied by three indicators: Number of scientific articles published, operational stock of industrial robots, and number of supercomputers.

Science Articles

The SJR maintains a database of scientific publications by country and subject for the past 20 years.

In 1996, China published a mere 29,000 papers, well behind Japan, the UK, Germany, and France (50,000-90,000) not to mention the US with 333,000. As of 2015, however, China had surged to 416,000 published papers, still modestly behind the US with its 567,000 papers but far ahead of everyone else.

science-plagiarism-map Now to be sure, Chinese papers are still considerably less cited than those of the developed world. And yes, this reflects the fact that, on average, the quality of Chinese scientific output remains inferior – less innovative, more derivative – than that of the US. This extends to outright plagiarism; the negative stereotypes about Chinese academia are somewhat borne out by a study that showed that 7-8% of Chinese articles on arXiv.org were flagged for text overlaps, compared to less than 4% for the US and the UK.

Nonetheless, in the “hard”/STEM spheres that arguably matter more for technological progress – and which have much less in the way of a replicability crisis – China is already ahead of the US in terms of total publications: 34,000 to 28,000 in mathematics; 67,000 to 52,000 in physics and astronomy; 63,000 to 36,000 in chemistry; 120,000 to 67,000 in engineering; 49,000 to 41,000 in computer science. The only major spheres here in which the US remains considerably ahead are the more biologically orientated sciences, such as: 196,000 to 69,000 in medicine, 83,000 to 59,000 in biochemistry/genetics, 23,000 to 7,000 in neuroscience, and 18,000 to 14,000 in pharmacology. Otherwise, the US retains clear dominance only in the the softer spheres of social science and the arts: 54,000 to 7,000 in the social sciences, 10,000 to 2,000 in economics, 23,000 to 2,000 in psychology, and 27,000 to 2,000 in the arts and humanities. In one subcomponent that is arguably outright negative value added, that of Gender Studies, the US published 1,456 documents to China’s 23.

The overall trends cannot be denied – Chinese scientific output is rapidly approaching American levels and will probably outright overtake, at least in absolute numbers, by around 2020.

Robots

Until recently, the general consensus was that automation would be an issue mainly for developed countries with high labor costs. China, then still seen as a country of boundless, cheap, and disciplined if unskilled labor, was not expected to be deeply affected by those developments (except perhaps to the extent that it would be challenged by renewed competition with First World manufacturing “reshoring” back to the American rustbelts).

This was, until recently, a logical enough viewpoint. Traditionally, the world’s operational stock of industrial robots was concentrated in the most advanced manufacturing economies, with the highest per capita rates seen in Japan (which accounted for a third to half of all industrial robots during the 1980s and 1990s), Germany and the Germanic lands, Northern Italy, and more recently, South Korea. In contrast, until the early 2000s, the publicly available databases generally didn’t even bother to estimate the numbers of industrial robots in Chinese factories so small and insignificant were their numbers.

But from the late 2000s, the robotization of Chinese industry began to explode.

industrial-robots-by-country

China went from having 32,000 industrial robots in 2008 (~Spain), to 189,000 by 2014 (~Germany) and approximately 263,000 robots by 2015, which puts it ahead of the 259,000 robots in all of North America and just behind Japan’s 297,000. It is therefore safe to assume that China took first place this year. By 2018, China is projected to have 614,000 industrial robots, equal to that of Japan and North America combined.

It is also worth noting that China dominates the global machine tool production industry, having overtaken the two leading countries in that sphere – Germany and Japan – around 2010. As of 2014, China accounted for 30% of the world’s yearly production of machine tools. This is of special interest not only because of this industry’s inherent technological sophistication, but also because of its strategic importance as the only part of the industrial economy that actually reproduces itself and makes everything else possible.

Supercomputers

A third excellent proxy for a country’s technological sophistication is its stock of supercomputers, which enable detailed simulations of phenomena as disparate as global climate, protein folding, and nuclear weapons reliability.

China emerged on the supercomputing scene in force during the early 2010s, when it became the world’s (distant) second to the US. However, within the space of the past year, it has surged ahead. According to the June 2016 list of the world’s top 500 supercomputers, China is now marginally ahead of the US in terms of total number of systems, with 168 top systems relative to America’s 165, and well ahead in terms of performance share, with 211 petaflops total to America’s 173 petaflops.

top500-supercomputers-country-share

China also hosts the world’s most powerful single supercomputer, the Sunway TaihuLight, which is nearly three times as powerful as the world’s second best (also Chinese) and five times as powerful as the top US supercomputer. Remarkably, it is based entirely on Chinese processors, the US having banned the export of Intel chips used in previous Chinese supercomputers for national security reasons in 2015. Evidently, this has had negligible effects on Chinese technological progress, because China has no dearth of native human capital and a state-backed program to reduce reliance on foreign technologies.

***

Forget the war against terror, forget the Syrian conflict, forget Ukraine – when historians look back on this period, they will identify China’s emergence as a technologically capable continental economy (soon to far overtake the US in absolute size) that is less and less reliant on the West for its technological convergence is by far the most important geopolitical trend of the century.

As this process unfolds, China is likely to start being more assertive on the international stage. We are already seeing this in the South China Sea, and its recent aquisition of its first foreign military base in Djibouti and plans to multiply its (as yet meager) power projection capabilities by building over 1,000 heavy strategic aircraft – that’s far more than what the US and Russia have combined. (Note that my standing projection is for China to overtake the US in total military power by 2030 and in naval power by around 2040).

It will also come to assume a much bigger presence in science, culture, and soft power generally, though this will take some time to recognize given the long lag times between invention and recognition.

Its also worth emphasizing that this technological emergence is quite specific to China, not to the BRICS in general. South Africa is basically an affirmative action BRIC and not worth mentioning further, while Brazil is the country of the future – and always will be, as per De Gaulle’s witticism. Despite strong recent economic growth, India’s presence in all the aforementioned spheres – published papers, supercomputers, industrial robot stock – is comparable to that of a typical middle-sized European country, its huge population being nullified by underdevelopment and an average national IQ in the low 80s.

As for Russia, while general economic output has recovered and exceeded Soviet era levels, its scientific and technological superstructure remains depressed: Russia’s share of global science papers as of 2015 is now 1.9% of the world’s total relative to 7.6% in 1986 (a drop made all the more remarkable by the USSR’s absence of a “publish or perish” scientific culture); its respectable Soviet-era stock of ~60,000 industrial robots has now almost entirely depreciated without getting replaced; and the quantity of Russian supercomputers in the top 500 in any given year has stabilized at around 5-10 since the late 2000s (i.e., comparable to Sweden). This is a consequence of the post-Soviet degradation of Russia’s human capital, especially its more elite elements, due to the 1990s brain drain; the ultimately lackadaisical approach to industrial and technological policy under Putin; and the intrinsic limitations of a ~97 average national IQ (in comparison, China, Germany, Japan, and the advanced parts of the US and Italy are in the low 100s).

 
• Category: Economics • Tags: Automation, China, Technology 

At his blog Greg Cochran raises the issue of the Great Stagnation.

decline-in-growth

Basically, GDP per capita growth rates throughout the developed world have plummeted relative to the levels of 1950-1973 (the years of the miracle economy, Wirtschaftswunder, trentes glorieuses, etc).

They are however more or less typical of growth rates earlier in the century, substantially higher than in the 19th century, and still cardinally different from the Malthusian stasis that characterized most of human history (when technology increases led to bigger populations but no improvements in individual wellbeing, at least in nutritional terms).

So the question could also be put as: What made the third quarter of the 20th century so special?

(1) Long-term GDP per capita growth is ultimately a function of growth in total factor productivity, or the “A” part of the Cobb-Douglas production function (where GDP = A*Capital^0.3*Labor^0.7).

(2) Total factor productivity is itself, for the most part, a function of technology, including social technology (otherwise known as institutions); and of aggregate cognitive power, which determines the efficiency with which said technology can be utilized.

Now let us look at each of the above in turn:

(a) Social technology – In general, in most places – within the OECD, at least, as a criterion of inclusion – the best mix of institutions for maximizing economic output has already been found and implemented. There are, to be sure, substantial differences in ease of business and hours worked between, say, Italy and the US; but said differences are marginal, not cardinal, such as those between North Korea and the US.

Incidentally, the idea that in most areas of the world improving institutions further has entered the realm of decreasing marginal returns is hardly a fringe view in economics (e.g. Glaeser 2004).

(b) Cognitive power – Literacy was closing in on 100% by 1900 in the US and “core” Europe. At that same time, the Flynn effect took off in earnest, continuing to around 1970-2000 but tapering off or even going into decline by the turn of the millennium. So aggregate elite cognitive power is now increasing at much more modest rates than before.

(c) Technology – As per Apollo’s Ascent Theory, there is an equilibrium technology level for every level of aggregate cognitive power, with the rate of growth of technology being proportional to the gap between the current and equilibrium state. However, since the equilibrium level of technology is now seeing only very minor gains (relative to the trend for most of the 20th century), technological growth has also become more subdued.

(3) The decline in technological growth leads to a decline in the rate of GDP per capita growth in the advanced countries, which are close to the technological frontier.

(4) Why is China growing very fast? Because its growth is based on mere convergence to the developed world, which it can effect by dint of its First World-quality human capital. At a stroke, the reforms of the 1980s involved a quantum leap in social technology (i.e. abandonment of Maoist economics, an aberration that made Soviet-style central planning look rational) and the removal of barriers to technological diffusion from the developed world.

(5) Why was the 1950-1973 period that of the miracle economy?

The conventional explanation is that the world hit a sweet spot in which many interrelated productivity improvements linked to advances in electro-mechanics, decision theory, etc. in prior recent decades that had been marred by war and instability could now all be implemented at the same time. Another important factor is that back then industry accounted for a larger share of GDP than today, which enabled faster growth because productivity improvements in manufacturing are easier to implement than in services.

However, surely another major factor was that the Flynn Effect and improvements in cognitive technology, or what you could view as technology-to-make-technology (e.g. much better “cognitive sorting,” as described by Charles Murray and Richard Herrnstein in The Bell Curve) was advancing at a very rapid pace during that period.

Also, both Europe and Japan had been wrecked by the war, so they were very much below potential; and Japan especially still had ample scope for pure convergence growth, conveniently protected under the American security umbrella. Hence why most of Europe and especially Japan grew even faster than the US during that period.

There is also a “thermoeconomics” school (e.g. Ayres 2002) which argues that the Great Stagnation is explainable on account of energy conversion efficiency ratios beginning to hit plateaus from the 1970s.

ayres-us-gdp-forecasts1

Potentially, this could even lead to a decline in the level of equilibrium GDP, if technological growth slows down past the point at which it no longer fully counteracts increasing resource depletion.

That said, I don’t know to what extent I buy this thesis, and especially the impicit assumption that GDP must be quite tightly linked to material output.

 
• Category: Economics • Tags: Apollo's Ascent, Economic History 

ea-global-bio

 

Online version with hyperlinks: http://www.unz.com/akarlin/ea-and-intelligence-theory/

I am a blogger and independent researcher who is interested in the intersections of intelligence theory, futurism, economics, and geopolitics.

Here is a summary of my ideas relevant to Effective Altruism:

Intelligence is central to explaining the wealth and poverty of nations, so a good understanding of it is central to formulating good EA-based policies.

  • Near universal agreement amongst psychologists on validity of general factor of intelligence (Gottfredson 1994; Jensen 1998). No replication crisis in psychometrics unlike the rest of psychology!
  • Solid positive correlations with incomes, job prestige, and virtually all measures of worldly success.
  • Excellent correlation between national IQ and GDP per capita (0.9!!) once you adjust for resource windfalls and Communist legacy (Karlin 2012). The economist Garett Jones calls this the “hive mind” thesis, and has shown that the causation is mostly from the former to the latter (Jones 2015). There is an approximately 3x increase in GDP per capita for every S.D. gain in average national IQ.
  • Despite popular but usually mistaken anecdotes, such as that of Feynman’s mediocre IQ, the elite scientists who drive scientific and technological progress are around 4 S.D. above the Western population mean (Roe 1952).
  • There is a case to be made – what I call the Apollo’s Ascent theory – that rising intelligence is indispensable for scientific and technological progress, since problems tend to get harder over time (Karlin 2015).

Important implications for EA follow from this, some obvious – some less so, and some outright controversial.

Obvious: The necessity of IQ-ameliorating interventions, especially in the developing world. There have already been resounding successes on this front historically (salt iodization). Work on micronutrient supplementation and deworming is extremely effective and should continue, as the EA community has long recognized.

Less Obvious: Improving IQ in the developed world, since it is so strongly associated with greater prosperity and performance across all metrics of civilization (which also results in less need for charity in the first place). Unfortunately, all schooling interventions tried to date have been shown to be inefficacious, so we need to be more ambitious. We need to throw more money and brainpower at the genetics of IQ; CRISPR/Cas9 and other gene editing techniques; and more speculatively, neural augs. There are many “intersectionalities” between EA and machine intelligence safety research; more intelligent humans will find it easier to understand the case for caution and help decrease the likelihood of a malevolent “breakout.”

Controversial: It is time to look more critically at the Open Borders orthodoxy within the EA community (Karlin 2015):

  • Hive Mind: Unfiltered immigrants from the developing world almost inevitably have lower average IQs than the recipient country (Rindermann 2014). Nor is there any evidence of long-term convergence. As such, the quality of the “hive mind” decreases, resulting in long-term decrease of the “equilibrium” level of GDP per capita relative to what it would otherwise be.
  • Cognitive Colonialism: You can have a “cognitively elitist” immigration policy, like Singapore or Australia, but it imposes a heavy burden upon the developing world by scouring it of the “smart fractions” they need for their own development (Karlin 2015).
  • Skills misallocations: The First World has no shortage of specialists. A doctor from Syria or D.R. Congo is more likely to end up as a taxi driver (or Uber now?) as to make relevant use of whatever professional qualifications he might have.
  • Loss of global arbitrage opportunities: George Soros, an outspoken proponent of open borders, has called the EU to spend almost $20,000 per immigrant during just their first year. But $1 of spending in Africa goes a lot further than $1 in Austria or America. For instance, a Syrian refugee doctor and his family can buy an oceanfront suite for $2,500 in the capital of Tanzania (a poor country which gets a useful specialist and economic investment at a fraction of the cost of hosting said doctor in Europe).
  • Other costs: Cultural incompatibility, decrease in social cohesion, and rise in xenophobic sentiments (cross out as per your ideological tilt).

Did you find any of this interesting, intriguing, or at least not completely bonkers?

If so please feel free to check out my blog (http://www.unz.com/akarlin/) and website (http://akarlin.com/).

 
• Category: Economics • Tags: Effective Altruism, Futurism, Immigration 

I have often remarked that a convenient way to think about East Asian comparative economic development is to view its three biggest players – China, Japan, and South Korea – as being separated by twenty year “chunks” of development, with Japan being on its leading edge and China being its laggard.

For instance, here is a graph of their respective per capita GDP growth rates from 1950 for Japan, 1970 for Korea, and 1990 for China – the years when all three passed the $2,000 mark (in terms of 1990 Geary-Khamis dollars, the standard unit of measurement used by what is probably the world’s most accessible comprehensive economic history database compiled by Angus Maddison).

east-asia-comparative-economic-development

This argument has recently been advanced by Jingyi Jiang (via Brian Wang), who likewise noticed the similarity of Japan’s, Korea’s, and now China’s “miracle economy” growth experiences – although his explanation of this might be a bit lacking:

Third, South Korea, Japan and China are geographically close. They trade a great deal with each other, and both South Korea and Japan invest directly in China. These close economic ties suggest that their growth experiences could be similar.

Alternatively, it could have something – just a little – to do with the fact that all three of these countries have First World average national IQs, which have been shown time and time again both on this blog and increasingly in academia to be the best predictors of economic potential around. I know, crazy thought, that.

Jingyi Jiang predicts China’s ultimate steady state level of GDP per capita at around half of the American level. The basis on which he does this is pretty weak: “No country in the world has been able to sustain growth rates of 7 percent or higher for more than four decades.” But this does not have to apply to China, since its level of economic development had been artificially suppressed by Maoist economic lunacy prior to the 1980s. Since China’s average national IQ and hence human capital potential is comparable to that of Japan (which has settled at 75% of the US level) and that of South Korea (at 65% of the US level, but continues eking out small gains), an ultimate limit of 50% seems to be unduly pessimistic.

Of course in population terms China is Japan x10 or Korea x25, so even half the US level of GDP per capita translates to a Chinese economy that is more than twice as large as the US in aggregate and at least as large in terms of military spending even if the share of GDP devoted to it remains 2% and 4% for China and the US, respectively. This is why all the numerous pundits who have argued that the (actually largely non-existent) China hype is all fake by smugly pointing out similar trends with respect to Japan in the 1980s are either idiots or knowing peddlers of nonsense.

 
• Category: Economics • Tags: China, Development 

The most well known index of corruption is Transparency International’s Corruption Perceptions Index. However, as I have frequently pointed out, it has a lot of problems. The biggest one lies in its very name – perceptions are not necessarily equal to reality, even – or especially – if they come from a narrow class of self-appointed political and economic “experts” whom Transparency International queries when compiling the CPI.

In an attempt to remedy this, back in 2011 I compiled the Corruption Realities Index 2010 on the basis of objective measures of corruption such as the percentage of people who said they had paid a bribe in the past year, the results of blind reviews of national laws and regulations on corruption, and measures of budget transparency. Some countries, such as Italy (more corrupt than Saudi Arabia according to the CPI) and Russia (more corrupt than Zimbabwe according to the CPI) considerably improved their standings in the CRI relative to the CPI.

Now along comes a new index of corruption, or more precisely, of “a society’s capacity to control corruption and ensure that public resources are spent without corrupt practices.”

The iPi is based on the following six factors:

  • Judicial Independence
  • Budget Transparency
  • Administrative Burden
  • Trade Openness
  • E-Citizenship
  • Freedom of the Press

The first two factors seem to be the two that have the most to do directly with corruption. The second two are more incidental, though it is true that fewer regulations c eteris paribus results in lower corruption. Although one can see how e-citizenship is an extension of deregulation, in practice the particular measures used for it – such as the number of Facebook users as a percentage of the population (!) – is actually of highly questionable value. What are you going to do, report corruption on Facebook? And what if you use Twitter or Vkontakte instead? Although in principle Freedom of the Press should be a powerful tool in the battle of corruption, ratings are drawn from Freedom House which is just as subjective as the CPI (i.e., completely) and even more politicized, which makes this particular subcomponent totally useless.

The need for a truly objective measure of corruption realities remains.

Here is how this Index of Public Integrity (iPi) tallies up versus the CPI as of 2015 in terms of country percentile rankings:

cpi-ipi-2016

That said, the iPi, unlike the CPI, is based on significantly more objective/data-based measures, and unsurprisingly, both Italy and Russia (as I intuited) are some of the biggest relative improvers. This goes to support my longstanding arguments that in terms of corruption although Russia is an underperformer within Europe it is also not particularly bad at a global level, being around the average for middle-income countries, transition countries, and fellow BRICS countries, and nowhere near the “Zaire with Snow” outlier it is frequently portrayed as in the Western media.

China does considerably worse here on the iPi than the CPI. As an authoritarian country with a lot of economic regulations and telephone justice that stands to reason, though one might think that having the death penalty on the books constitutes a considerably greater “capacity to control corruption” than the absence of Facebook. The incidence of bribery polls indicate that low-level corruption in China is now actually quite rare for a country at its developmental level.

 
• Category: Economics • Tags: Corruption, Russia 

Tiny Iceland once astounded the world by being the only county to send its banksters to jail and repudiating the debts taken on by the citizenry they hoodwinked.

As a result, there were no significant drops in living standards, whereas Greece, which adopted the opposite policies, got stuck in a grinding depression that continues to this date.

Days after USAID/Soros- oh sorry I meant “people power” essentially mounted a coup against the Icelandic government… they free all the banksters!!

And then, minutes later, the Panama Papers were disclosed by the ICIJ, which had a clear target: to “expose” the “circle of friends close to Putin”, and of course, to reveal the dirty laundry of the Iceland Prime Minister, who resigned just two days after his shady offshore tax dealing were revealed to the world.

There was some “conspiratorial” speculation whether the explicit hit on ex-PM Sigmundur David Gunnlaugsson was precisely due to Iceland’s crackdown on the country’s criminal bankers. As a reminder, Iceland is the only nation that sent bankers found guilty of crimes resulting from the financial crisis, to prison.

It turns out there may have been something valid in said speculation, because moments ago, Iceland Monitor reported that three bankers from the defunct Iceland bank Kaupthing are to be released from jail today – after serving just one year of their 5-year sentences.

Magnús Guðmundsson, Ólafur Ólafsson and Sigurður Einarsson were one of four men jailed in 2015 in the so-called ‘Al-Thani case’ on charges of breach of trust and market abuse.

Sigurður Einarsson, former chairman at Kaupþing, received a sentence of four years, while Magnús Guðmundsson, former CEO of Kaupthing Luxembourg, and Ólafur Ólafsson, who was the bank’s second largest shareholder at the time, both received a sentence of four and a half years.

LOLOLZ!!

Long live people power! Heil Soros!

Conspiratards were right as usual.

putin-laughing-sarcastic

 
• Category: Economics • Tags: Conspiracy Theories, Iceland, Panama Papers 

And make no doubt about it – a collapse is exactly what it is, and it afflicts way more of the country than just the war-wracked Donbass. Ukraine now vies with Moldova for the country with the lowest average wages in Europe.

Gabon with snow? Saakashvili is hopelessly optimistic. That would actually be a big improvement!

GDP is at 60% of its 1990 Level

ukraine-gdp-1990-2015

As of this year, the country with the most pro-Western revolutions is also the poorest performing post-Soviet economy bar none. This is a not unimpressive achievement considering outcomes here have tended to disappoint rather than elate. Russia itself, current GDP at about 110% of its 1990 level, has nothing to write home about (though “statist” Belarus, defying neoliberal conventional wisdom, at a very respectable 200% does have something to boast about).

Back in 2010, although by far the worst performing heavily industrialized Soviet economy, Ukraine was still performing better relative to its position in 1990 than Moldova, Tajikistan, and Georgia. In the intervening 5 years – with a 7% GDP decline in 2014 which has widened to a projected 9% in 2015 – Ukraine has managed to slip to rock bottom.

How does this look like on a more human level?

Housing Construction is Similar to That of 5 Million Population Russian Provinces

housing-construction-russia-ukraine-in-2014

With a quarter of its population, Belarus is constructing as much new accomodation as is Ukraine. 16 million strong Kazakhstan is building more. Russia – more than ten times as much, even though it has less than four times as many people.

The seaside Russian province of Krasnodar Krai, which hosted the Sochi Winter Olympics, with its 5 million inhabitants, is still constructing more than half as much housing as all of Ukraine. No wonder the Crimeans were so eager to leave.

New Vehicle Sales Collapse to 1960s Levels

 

ukraine-automobile-sales

The USSR might have famously concentrated on guns over butter, yet even so, even in terms of an item as infamously difficult to acquire as cars under socialism, Ukrainian consumers were better off during the 1970-1990 period than today. Now Ukrainians are buying as few new cars as they were doing in the catastrophic 1990s, and fewer even than during the depth of the 2009 recession.

And even so many Maidanists continue to giggle at “sovoks” and “vatniks.” Well, at least they now make up for having even less butter than before with the Azovets “innovative tank.” Armatas are quaking in fear looking at that thing.

Debt to GDP Ratio at Critical Levels

ukraine-debt-to-gdp-ratio

And this figure would have risen further to around 100% this year.

Note that 60% is usually considered to be the critical danger zone for emerging market economies. This is the approximate level at which both Russia and Argentina fell into their respective sovereign debt crises.

To be fair, the IMF has indicated it will be partial to flouting its own rules to keep Ukraine afloat, which is not too surprising since it is ultimately a tool of Western geopolitical influence. And if as projected the Ukrainian economy begins to recover this year, then there is a fair chance that crisis will ultimately be averted.

But it will be a close shave, and so long as the “meet the new boss, same as the old boss” oligarchs who rule Ukraine continue siphoning off money by the billions to their offshore accounts with impunity, nothing can be ruled out.

Resumption of Demographic Collapse

ukraine-crude-birth-rate-1988-2015

Much like the rest of the post-Soviet Slavic world, Russia had a disastrous 1990s in demographic terms, when mortality rates soared and birth rates plummeted. But like Russia – if to a lesser extent – it has since staged a modest recovery, incidentally with the help of a Russian-style “maternal capital” program. In 2008, it reached a plateau in birth rates, which was not significantly uninterrupted by the 2009 recession.

Since then, however, they have plummeted – exactly nine months after the February 2014 coup. The discreteness with which this happened together with the fact that the revolt in the Donbass took a further couple of months to get going after the coup proper implies that this fertility decline was likely a direct reaction to the Maidan and what it portended for the future.

This collapse is very noticeable even after you completely remove all traces of Crimea, Donetsk, and Lugansk oblasts which might otherwise muddy the waters (naturally, the demographic crisis in all its aspects has been much worse in the region that bore the brunt of Maidanist chiliastic fervor). Here are the Ukrstat figures for births and deaths in the first ten months of 2013, 2014, and 2015:

Births Deaths
2013 350658 441331
2014 354622 445236
2015 329308 450763

Furthermore, this period has seen a huge wave of emigration. Figures can only be guesstimated, but it is safe to say they are well over a million to both Russia and the EU.

The effects of this will continue to be felt long after any semblance of normalcy returns to Ukraine.

 
• Category: Economics • Tags: Crisis, Finance, Ukraine 

Hungary is opting for the latter:

The scheme—designed to boost the Hungarian birthrate—was announced at a recent government press conference in the Hungarian Parliament building attended by the Minister heading the Prime Minister’s Office, János Lázár.

The scheme will see the state grant a non-repayable aid package of 10 million Hungarian Forints (HUF) to all couples agreeing to have three children within ten years.

According to the Global Property Guide, the average detached house price in Hungary is HUF 9.3 million.

Minister Lázár said that the grant was part of the extension of the government’s “family first home benefit.”

10 million forints is about $35,000.

hungary-birth-death-rates-historical

You may recall that this is the exact same sum that George Soros is demanding that the EU pay each immigrant during just their first two years there. No wonder he and his minions hate Orban so much.

Seems that supporting natality is much cheaper than supporting immigration and will result in a great deal less racism and Islamophobia besides. Everybody wins.

Besides, its something that Hungary needs regardless. It is a real demographiz disaster zone. As seen in the chart right, deaths started outnumbered births there since 1981, a full decade ahead of trends in most of the rest of East-Central Europe.

A reminder that Russia managed to reverse an analogous state of affairs with not inconsiderable help from “maternal capital” – about $10,000 worth of housing aid for each child above one – implemented from the mid-2000s. The total fertility rate (TFR) went from 1.3 children per woman then to about 1.8 now. This flew in the face of demographic conventional wisdom, which tended to dismiss the efficacy of such pro-natality schemes. Hungary currently has a TFR of 1.4 children per woman. It would be interesting to see if it turns out to be another counter-example.

 
• Category: Economics • Tags: Demographics, George Soros, Hungary 
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.