Even so, Mr Xi’s authority remains hemmed in. True, his position at the highest level looks secure. But among the next layer of the elite, he has surprisingly few backers. Victor Shih of the University of California, San Diego, has tracked the various job-related and personal connections between the 205 full members of the party’s Central Committee, which embodies the broader elite. The body rubber-stamps Mr Xi’s decisions (there have been no recent rumours of open dissent within it). But the president needs enthusiastic support, as well as just a show of hands, to get his policies—such as badly needed economic reforms—implemented. According to Mr Shih, the president’s faction accounts for just 6% of the group. That does not help.
Admittedly, this number should not be taken too literally: it is difficult to assign affiliations to many of the committee’s members. Doubtless, too, many members who are not in Mr Xi’s network support the president out of ambition or fear. Still, Mr Xi can rely on remarkably few loyal supporters in the Central Committee because he did not choose its members. They were selected at the same time he was chosen as party leader in 2012, a process overseen by the dominant figures of that period, Mr Hu and the long-retired Mr Jiang.
Most people who laud China’s autocratic success conveniently choose to ignore two important facts:
That China’s rulers, at least since the late 1970s, have not been totally unaccountable. The country is a dictatorship by committee. And a large committee at that. It is not a personalist one man show.
The the Chinese party-state works tirelessly to reduce the cost of compliance among its citizens — through conscious state building, coercion, and public services.
What this means is that in order to replicate China’s autocratic success, would be little Chinas must invest in both state capacity and intra-elite accountability (perhaps by building strong, institutionalized parties).
Absent this, what you are likely to get are mediocre petty tyrants running disorganized non-states with infant mortality rates straight out of the 16th century.
China today boasts roughly five workers for every retiree. By 2040, this highly desirable ratio will have collapsed to about 1.6 to 1. From the start of this century to its midway point, the median age in China will go from under 30 to about 46, making China one of the older societies in the world. At the same time, the number of Chinese older than 65 is expected to rise from roughly 100 million in 2005 to more than 329 million in 2050—more than the combined populations of Germany, Japan, France, and Britain.
And here is a summary of global population projections for perspective:
Who gets the Lion’s share of the Dragon’s loans? Angola received 25% of all Chinese loans to Africa between 2000 and 2015, almost all of them backed by Angolan oil.
Bloomberg and Fitch, take note: Did China Eximbank really lend more than the World Bank in Africa? SAIS-CARI data shows cumulative 2001 to 2010 China Eximbank loan to Africa amount to only US$27.2 billion, not your figure of US$67.2 billion. The World Bank is still a larger lender than China Eximbank.
What do Chinese loans pay for in Africa? Transportation. Between 2000 and 2014, transportation received the largest share: US$23.6 billion worth.
What are the biggest Chinese loan-financed infrastructure projects in Africa? No. 1: Kenya’s Mombasa-Nairobi Standard Gauge Railway Phase I, funded by US$3.6 billion worth of Chinese loans; No.2: Ethiopia’s Addis-Djibouti Railway, funded at US$2.5 billion. Both were signed in 2013.
….. Shanghai has a particular problem: last year, says China Daily, it became the first city in China to pass the crippling 30 per cent mark for population aged over 60. That’s nearly twice the 15.5 per cent for over 60 population nationally in 2014, the last year for which national figures are available.
GOVERNMENT statisticians shun the limelight, which only ever finds them when things go awry. So it is with India’s national bean counters, who are struggling to convince the world that an economy with idle factories, sagging exports and ailing banks grew by 7.5% in 2015, as their models purport to show. Ever since a new methodology for calculating GDP was adopted last year, India has appeared to be the world’s fastest-growing big economy, outpacing China. But scepticism about the data is growing even faster.
… Investors, at any rate, roundly disbelieve India’s growth figures. Nevsky Capital, a hedge fund, cited dodgy data from India, among other places, as a reason to shut up shop at the start of the year. Even the government’s own chief economic adviser has admitted he is sometimes flummoxed by the data. A cottage industry has sprung up to cater to the sceptics, blending various indicators of economic activity to produce new gauges of growth.
Such home-brewed statistics have been common in China for some time: Li Keqiang, now the country’s premier, admitted as a provincial governor that he all but ignored “man-made” economic statistics in favour of hard-to-fiddle data such as railway-cargo volumes, electricity consumption and loans made by banks. The Economist began publishing a “Keqiang Index” when his habits became known in 2010.
Ambit Capital, a broker based in Mumbai, now computes its own “Keqiang Index” for India, which implies a real growth rate of 5.4%. Economists at HSBC, a bank, think 5.9-6% is closer to the truth.
Akinwumi Adesina, who took over as president of Africa’s lead development lender in September, has said that his flagship project aims to raise $55bn of investment to close the energy deficit in the next decade.
He says the bank will take a leadership role, coordinating with existing multinational initiatives and pushing member states to move faster to privatise and liberalise their energy sectors.
China has experienced a spectacular economic growth in recent decades. Its economy grew more than 48 times from 1980 to 2013. How are the other countries reacting to China’s rise? Do they see it as an economic opportunity or a security threat? In this paper, we answer this question by analyzing online news reports about China published in Australia, France, Germany, Japan, Russia, South Korea, the UK and the US. More specifically, we first analyze the frequency with which China has appeared in news headlines, which is a measure of China’s influence in the world. Second, we build a Naive Bayes classifier to study the evolving nature of the news reports, i.e., whether they are economic or political. We then evaluate the friendliness of the news coverage based on sentiment analysis. Empirical results indicate that there has been increasing news coverage of China in all the countries under study. We also find that the emphasis of the reports is generally shifting towards China’s economy. Here Japan and South Korea are exceptions: they are reporting more on Chinese politics. In terms of global sentiment, the picture is quite gloomy. With the exception of Australia and, to some extent, France, all the other countries under examination are becoming less positive towards China.
That’s Yuan, Wang and Luo writing in a neat paper that analyzes news coverage of China in different countries.
It is interesting that across the globe young people, on average, have a more positive view of China’s rise than older people. Younger people probably associate China more with glitzy gadgets in their pockets; and less with cultural revolutions and famine-inducing autocracy.
He also makes an interesting observation on the fluctuations in mortality rates in the 19th century:
A second interesting characteristic that is immediately noticeable is that the series are very ‘spikey’ in the 19th century and are then much smoother in the 20th century. This is partly because the data quality is improving over time but it also shows how frequent crises were in pre-modern times. The decline of crises is an important aspect of improving ‘living standards’. In the ‘Our World in Data’ entry on food price volatility you find a long-run series of food price volatility in Pisa by Cormac O Grada that shows how frequent food crises were.
This is an important observation. One of the key differences between wealthy and relatively poorer countries is the variance in their growth rates. Most advanced economies grow (and have historically grown) at a steady rate (Tyler Cowen for example notes that Denmark never had a “growth miracle”). Developing countries on the other hand experience relatively greater levels of both longitudinal and cross-sectional variation in growth rates. The boom-burst cycles often make it hard for meaningful accumulation of wealth and steady growth of per capita income.
Last year the French company Danone (maker of Activia yogurt) bought a 40% stake in the Kenyan dairy firm Brookside, a sign of the growing importance of the dairy market in the wider eastern Africa region. But the story doesn’t end with the big household names. Smallholder farmers are also getting a piece of the dairy bonanza in Kenya:
On a related note, here is how a company in China is helping industrialize the country’s dairy sector:
A milk scandal erupted in China in 2008 when the industrial chemical melamine was found in dairy products nationwide. While many Chinese dairy companies faced huge losses or bankruptcy as a result, one small firm, Dairy United, accelerated its development. Dairy United is one of the fastest-growing and most innovative Chinese dairy producers, one that features an unusual organizational structure and business model. Unlike most corporate and cooperative dairies that purchase cows on the market, Dairy United leases dairy cows from local farmers, giving it access to its primary asset without a large up-front investment, and letting the firm grow its dairy herds with newborn heifers. In return, farmers receive fixed payments biannually, but relinquish control rights and residual claims to the firm. Thus, Dairy United’s leasing is helping transform Chinese milk production from a backyard, labor-intensive activity to a more industrialized mode of farming. The case is particularly interesting for understanding applications of agency theory in agribusiness.
3. Dark Leviathan: How even the deep web, in desperate need to signal credibility, cannot escape the need for the “law merchant” (and eventually the state, or some generalizable norms a la Avner Greif).