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archived Ian Welsh and Norbert Haring, semiologists 2018 Parliament blocks SWIFT. 2010 Diversity is the key to economic and political evolution.
Now, compare it with currencies that are gaining against the US dollar: the Ukrainian hryvnia, the Georgian lari and the Colombian peso. Not exactly G20 heavyweights - and all of them also inside Washington's influence.
archived [IMF IMPERIAL BASKET EUR, USD, JPY] + RMB - GBP Diversity is the key to economic and political evolution.
"It is a total mess because the African countries do not agree among themselves on the need of the ACP group," underscores Jean Bossuyt.
Later, at the start of the Forum on China-Africa Cooperation (FOCAC), Xi announced $60 billion in funds for eight initiatives over the next three years, in areas ranging from industrial promotion, infrastructure construction and scholarships for young Africans. He added that Africa's least developed, heavily indebted and poor countries will be exempt from debt they have incurred in the form of interest-free Chinese loans due to mature by the end of 2018.
He added that Africa's least developed, heavily indebted and poor countries will be exempt from debt they have incurred in the form of interest-free Chinese loans due to mature by the end of 2018.
A study by the Center for Global Development, a US think-tank, found "serious concerns" about the sustainability of sovereign debt in eight Asian, European and African countries receiving Belt and Road funds. But South African President Cyril Ramaphosa defended China's involvement on the continent, saying FOCAC "refutes the view that a new colonialism is taking hold in Africa as our detractors would have us believe." During a visit to China last month, Malaysian prime minister Mahathir Mohamed warned against "a new version of colonialism", as he cancelled a series of Chinese-backed infrastructure projects worth $22 billion.
But South African President Cyril Ramaphosa defended China's involvement on the continent, saying FOCAC "refutes the view that a new colonialism is taking hold in Africa as our detractors would have us believe."
During a visit to China last month, Malaysian prime minister Mahathir Mohamed warned against "a new version of colonialism", as he cancelled a series of Chinese-backed infrastructure projects worth $22 billion.
Djibouti has become heavily dependent on Chinese financing after China opened its first overseas military base in the Horn of Africa country last year, a powerful signal of the continent's strategic importance to Beijing.
PHOTO OP:People hold Chinese and Djiboutian national flags as they wait for Djibouti's President before the opening of a 1,000-unit housing construction project in Djibouti on July 4, 2018. The project was financially supported by a Chinese company. Photo: AFP/Yasuyoshi Chiba
"serious concerns" about the sustainability of sovereign debt
is definitely worth a hearty laugh. She believed in nothing; only her skepticism kept her from being an atheist. -- Jean-Paul Sartre
Bounded rationality is a paradigmatic example. Early criticisms of rationality from people like Herbert Simon were broad ranging criticisms of the idea that people could even begin to behave in the way depicted by the standard utility-maximising model given that they had neither the information, the capacity to process that information, nor the ability to act upon it that would be required. Thus they would use rules of thumb, `satisfice' instead of `optimise', and and so forth.
`Imperfect information' in mainstream economics is another example: in a sense individuals have more information than under perfect information, since they know all the probabilities and possible states of the world instead of just one of the latter. And as I have previously argued, this point applies even to the name of macroeconomic models -- which claim to be Dynamic, Stochastic, General and Equilibrium, but are not really the first 3 in any meaningful sense. Critics would like to see their issue at the core of theories instead of bolted on at the end.
Today several branches of applied science assist the firm to achieve procedural rationality. 3 One of them is operations research (OR); another is artificial intelligence (AI). OR provides alogrithms [RULES] for handling difficult multivariate decision problems, sometimes involving uncertainty. Linear programming, integer programming, queuing theory [eg FIFO], and linear decisions rules are examples of widely used OR procedures. To permit computers to find optimal solutions with reasonable expenditures of effort when there are hundreds or thousands of variables, the powerful [RULES] associated with OR imposes a strong mathematical structure on the decision problem. Their power is bought at the cost [EXPENDITURE] of shaping and squeezing the real-world problem to fit their computational requirements: for example, replacing the real-world criterion function and constratins with linear approximations so that linear programming can be used. Of course the decision that is optimal for the simplified approximation will rarely be optimal in the real world, but experience shows that it will often be satisfactory. The alternative methods provided by AI, most often in the form of heuristic search (selective search using rules of thumb) [BIAS, PREJUDICE], find decisions that are "good enough," that satisfice. The AI models, like OR models, also only approximate the real world, but usually with much more accuracy and detail than the OR models can admit. They can do this because heuristic search can be carried out in more complex and less well structured problem space than is required by OR maximizing tools. The price paid [EXPENDITURE] for working with the more realistic but less regular models is that the methods generally find only satisfactory solutions, not optima. We must trade off satisficing in a nearly-realistic model (AI) against optimizing in a greatly simplified model (OR). Sometimes one will be preferred, sometimes the other.
To permit computers to find optimal solutions with reasonable expenditures of effort when there are hundreds or thousands of variables, the powerful [RULES] associated with OR imposes a strong mathematical structure on the decision problem. Their power is bought at the cost [EXPENDITURE] of shaping and squeezing the real-world problem to fit their computational requirements: for example, replacing the real-world criterion function and constratins with linear approximations so that linear programming can be used. Of course the decision that is optimal for the simplified approximation will rarely be optimal in the real world, but experience shows that it will often be satisfactory.
The alternative methods provided by AI, most often in the form of heuristic search (selective search using rules of thumb) [BIAS, PREJUDICE], find decisions that are "good enough," that satisfice. The AI models, like OR models, also only approximate the real world, but usually with much more accuracy and detail than the OR models can admit. They can do this because heuristic search can be carried out in more complex and less well structured problem space than is required by OR maximizing tools. The price paid [EXPENDITURE] for working with the more realistic but less regular models is that the methods generally find only satisfactory solutions, not optima. We must trade off satisficing in a nearly-realistic model (AI) against optimizing in a greatly simplified model (OR). Sometimes one will be preferred, sometimes the other.
Costs to Yield Curve Manipulation The Mitchell post explains why the government can set the entire yield curve. I will instead focus on the potential risks to such a posture. Losing the ability to influence the economy via setting interest rates. The political cost of changing bond prices. The loss of market information. Political cost of interest expense. I will cover these in turn.
Losing the ability to influence the economy via setting interest rates. The political cost of changing bond prices. The loss of market information. Political cost of interest expense.
I will cover these in turn.
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