True globalization and free trade economy have been the top agenda of world economies for quite some time, but, however, practically achieving very little. Both globalization and global trade are being effectively mismanaged and thereby controlled by USA and Europe and to some extend by Russia and China to their advantages. Rest of the world has to bear the negative consequences of restricted globalization and refusal to enact global free trade.
G20, the world’s top economies, is the extended version of G8, the western top economies, incorporating medium/developing economies as well to debate and make decisions on the future goals of world economy. The 2016 G20 Hangzhou summit will be the eleventh G20 meeting. It is planned to be held on 4–5 September 2016 in the city of Hangzhou, Zhejiang. It is also the first ever G20 summit to be hosted in China and the second Asian country after 2010 G20 Seoul summit was hosted in South Korea.
Sandwiched between events like the Brexit vote and the US presidential election, leaders of G-20, the world’s major economies meet this weekend in China presumably to take stock of the Brexit impact on world economy. But the world economies at G20 need to mount a realistic defence of the free trade and globalization they have long championed. At stake is the post-World War Two concord on globalization that proponents say has helped lift so much of the world out of poverty. China, the host of the Group of 20 meeting, has itself been one of the biggest winners from free trade, becoming the world’s leading exporter.
Britain’s shock vote in June to leave the EU and the rise of protectionist Donald Trump in the USA has shaken that accord ahead of the G20 summit in Hangzhou that starts on Sunday.
Hangzhou in China
China as the Olympic host this year, has left no stone unturned, no wall unpainted and no sewer unsealed in getting ready Hangzhou for the G20 Summit, an annual gathering of the leaders of the world’s 20 leading economies. Public offices will close for a special seven-day holiday. Private businesses have been urged to do the same, even though the summit itself only runs for two days. Hangzhou residents will receive 10 billion yuan ($1.5 billion) in tourism vouchers to visit other cities in Zhejiang province (of which Hangzhou is the capital) during the G20. The mayor boasts that a 760,000-strong volunteer force stands ready to serve the G20. One persistent rumor is that the city is spending 160 billion yuan ($24 billion) on the G20. If true, this would be remarkable, eclipsing Rio’s $5 billion expenditure on the Olympics. Many public organizations, however, criticised the government for wasting money in the name of a summit and disrupting ordinary people’s lives against communist principles.
Just 40 minutes west of Shanghai by bullet train, it is one of China’s wealthiest cities. The misty waters of West Lake at its heart, fringed by rolling tea fields, have inspired poets for centuries. In recent years, it has become an entrepreneurial hub, most famously as the hometown of Alibaba, an e-commerce company.
The G20 summit, to be held on September 4th and 5th, will be the first in China in the eight-year history of such meetings and a hugely important diplomatic occasion for President Xi Jinping. He clearly hopes that the event will highlight how central China has become to solving the world’s problems
It came as a surprise when China announced that Hangzhou, a second tier city in the eastern province of Zhejiang, would host the 2016 G-20 leaders’ summit, the political equivalent of the Olympics or the World Cup.
Over the past decade, China has hosted a series of high-profile international events mainly in its first-tier cities, such as the 2008 Summer Olympics and the 2014 APEC in Beijing and the 2010 Expo in Shanghai, in order to showcase the break-neck pace of China’s economic developments since it adopted the Open Door in 1978. Hangzhou, the ancient capital of the Southern Song Dynasty (1127-1279), was traditionally hailed as one of the most beautiful cities in China. The city has been transformed into a home for many high profile tech firms such as e-commerce giant Ali Baba, setting an example of how China’s splendid and rich culture and history in the past can still live on in a modern city with an innovative economy.
China, the economic giant
It’s an image that China wants to promote this weekend to the world’s top leaders, breaking away from its image as the world’s cheap labor factory. For China, it is beginning to catch up with the rest of the world in spending every year on research and development. The percentage is about 2.4% of the GDP, right now. That is close to what the United States is spending. And also, it’s growing at a fast pace. To make that case, Hangzhou is an obvious choice as a G-20 summit venue.
The information economy, championed as a new driving force for economic development in the era of “new normal”, accounted for 23 percent of Hangzhou’s GDP, contributing to over 45 percent of GDP growth in 2015, according to Hangzhou city. It was only natural that questions were raised as to why this relatively obscure city was chosen to host the summit meeting of the world’s 20 largest economies, representing two-thirds of the global population and 85% of the global economy.
President Xi Jinping achieved one of the highest GDP growth rates in China during the period when he held the Communist Party’s top post in this Zhejiang province between 2002 and 2007. World especially the West is eager to know whether China is capable of tackling problems stemming from slowing economic growth and overcapacity, wants to keep the focus of this year’s G-20 summit on economic growth. The summit will look at ways to build “an innovative, invigorated, interconnected and inclusive world economy,” he said.
China remains the world’s major growth engine. Despite all the hand-wringing over the much vaunted China slowdown, the Chinese economy remains the single largest contributor to world gross domestic product growth. For a global economy limping along at stall speed – and most likely unable to withstand a significant shock without toppling into renewed recession – that contribution is all the more important.
The Chinese economy accounts for fully 18 percent of world output – more than double India’s 7.6 percent share. Excluding China, world GDP growth would be about 1.9 percent in 2016 – well below the 2.5 percent threshold commonly associated with global recessions. More broadly, China is expected to account for fully 73 percent of total growth of the so-called BRICS grouping of large developing economies. . Chinese growth would have a much greater effect on an otherwise weak global economy than would be the case if the world were growing at something closer to its longer-term trend of 3.6 percent.
If Chinese GDP growth reaches 6.7 percent in 2016 – in line with the government’s official target and only slightly above the International Monetary Fund’s latest prediction (6.6 percent) – China would account for 1.2 percentage points of world GDP growth. With the IMF currently expecting only 3.1 percent global growth this year, China would contribute nearly 39 percent of the total.
Despite all the hand-wringing over the much vaunted China slowdown, the Chinese economy remains the single largest contributor to world gross domestic product growth. For a global economy limping along at stall speed – and most likely unable to withstand a significant shock without toppling into renewed recession – that contribution is all the more important.
Chinese domestic demand has the potential to become an increasingly important source of export-led growth for China’s major trading partners – provided, of course, that other countries are granted free and open access to rapidly expanding Chinese markets. There are of course the global effects of a successful rebalancing of the Chinese economy. The world stands to benefit greatly if the components of China’s GDP continue to shift from manufacturing-led exports and investment to services and household consumption.
A successful Chinese rebalancing scenario has the potential to jump-start global demand with a new and important source of aggregate demand – a powerful antidote to an otherwise sluggish world. That possibility should not be ignored, as political pressures bear down on the global trade debate.
Unlike the major economies of the advanced world, where policy space is severely constrained, Chinese authorities have ample scope for accommodative moves that could shore up economic activity. And, unlike the major economies of the developed world, which constantly struggle with a trade-off between short-term cyclical pressures and longer-term structural reforms, China is perfectly capable of addressing both sets of challenges simultaneously.
This meeting should send a clear message that world leaders have heard people’s concerns about globalization and are taking steps to better understand and address them. The risk is that nothing much will be achieved. More platitudes about the benefits of global trade and investment will ring hollow.
While there have been recent concessions that not everyone wins out of globalization, the White House has also signaled a renewed push on the controversial Trans-Pacific Partnership (TPP) trade deal as President Barack Obama’s term winds down.
The G20 earned its spurs with a concerted reaction to the 2008 global financial crisis, but recently opposition to free trade seems to have gained purchase and a coherent defence has been lacking. Among the biggest sticking points is overcapacity in the global steel industry, a sore point for China as the world’s largest producer of the metal. Other concerns include barriers to foreign investment, and the risk of currency devaluations to protect export markets.
International Monetary Fund (IMF) Managing Director Christine Lagarde described the global economic outlook as “slightly declining growth, fragile, weak and certainly not fuelled by trade and said this week that G20 leaders need to do far more to spur demand, bolster the case for trade and globalization, and fight inequality. The Centre for Economic Policy Research estimates that in the first eight months of 2016 alone G20 governments implemented nearly 350 measures that harmed foreign interests. The jumps in G20 protectionism in 2015 and 2016 coincide ominously with the halt in the growth of global trade volumes.
The Washington-based U.S. Chamber of Commerce fired a broadside at what it saw as creeping protectionism in the information and communications technology sector, releasing a report citing aggressive new measures from China to Russia to the EU. National security was the reason given by Australia’s government when it rejected Chinese bids for an electricity grid last month, a decision that Beijing labeled as “protectionist”.
West is opposed to free trade with developing nations. When EU Commission President Jean-Claude Juncker and EU Council President Donald Tusk set out their priorities for the Hangzhou meeting this week, free trade was next to last. It was preceded by the refugee crisis, jobs growth, financial stability and tax transparency. While the challenge was recognised, no solutions were offered.
The G20 might discuss how to reverse the slowdown in the growth of trade and foreign investment and to communicate the benefits of trade to citizens while addressing their concerns. The critics argue the benefits of globalization are too often over-hyped by politicians, leading to public disappointment.
Obama has promoted the TPP deal as an engine of job creation yet it might add all of 0.5 percent to economic growth after 15 years. The 12-nation TPP is the number one legislative goal of Obama’s remaining term, yet is under assault at home and abroad. Both the main candidates in the November election, Republican Trump and Democrat Hillary, have come out against it, blaming past deals for destroying Americans jobs. If anything, the TPP highlights the divisions within the G20. It was sold as the economic pillar of Obama’s broader plan to shift U.S. foreign policy toward Asia and counter the rising might of the hosts of this very meeting, China.
As China, among other advancing economies are making big strides in capitalist development actions, the G7 leaders USA and EU have brought them also into what is now called the G-20. One of the reasons is to curb fast climate disorder with the help of these developing economies that are also responsible for rising sea levels, threatening the existence of island nations, like Sri Lanka, Maldives, etc.
An officially communist country, China heavily subsidizes capitalist economy of USA, finances the NATO imperialist wars, has been sympathetic to fascist aggression of Palestine by fanatic Israel, would not appreciate Kashmiri struggle for freedom from Indian yoke primarily because China also occupies a part of Kashmir, taken from Pakistan as a stolen gift.
The G20 needs to do better in communicating the benefits of free trade, while giving the political push that’s needed to unlock stalled multilateral trade liberalization. Delivering a successful G20 summit in Hangzhou means tackling big global challenges successfully through practical actions benefit the world.
Hopefully, the G20 would seriously consider global free trade mechanism so that all under developed nations also benefit from G-20. It is urgent the G20 nations evolve a strategy for a global free trade treaty.
Banks and Artificial Intelligence
“Artificial Intelligence” is a terminology specifically invented in 1956 by John McCarthy and concerns the ability to make appropriate generalizations quickly, but based on an inevitably limited set of data.
The wider the scope and the faster conclusions are drawn, and with minimal information, the smarter the machine’s behaviour can be defined.
Intelligence is the creative adaptation to quick changes in the environment. This is the now classic definition, but in this case, with machines, the speed and the increasingly narrow base of the starting data are also evaluated.
What if the starting data does not contain exactly the necessary information – which is possible? What if, again, the speed of the solution stems from the fact that the data collected is too homogeneous and does not contain the most interesting data?
Konrad Lorenz, the founder of animal ethology, was always very careful to maintain that between instinctive behaviour and learned behaviour, external environmental and genetic sources can be equally “intelligent”. The fact, however, is that greater flexibility of a behaviour – always within a reasonable time, but not as quickly as possible – generates greater intelligence of the animal.
As said by a great student of Lorenz, Nikko Tinbergen, human beings are “representational magpies”, which means that much of their genetic and informative history has no practical value.
When the collection of information becomes easy, the “adaptive” magpie has a very adaptive behaviour, but when the data collection is at the maximum, all data counts and we never know which, among this data, will really be put into action.
In other words, machine data processing is a “competence without understanding”, unless machines are given all senses – which is currently possible.
Human intelligence is defined when we are at the extreme of physically possible data acquisition, i.e. when individuals learn adaptive-innovative behaviour from direct imitation of abstract rules.
Abstract rules, not random environmental signals.
If machines could reach this level, they would need such a degree of freedom of expression that, today, no machine can reach, not least because no one knows how to reach this level; and how this behaviour is subsequently coded.
What if it cannot be encoded in any way?
The standardization of “if-then” operations that could mimic instincts, and of finalized operations (which could appear as an acquired Lorenz-style imprinting) is only a quantitative expansion of what we call “intelligence”, but it does not change its nature, which always comes after the particular human link between instinct, intelligence and learning by doing.
Which always has an accidental, statistical and unpredictable basis. Which duck will be the first to call Konrad Lorenz “dad”, thus creating a conditioning for the others? No one can predict that.
If systematized, bio-imitation could be a way to produce – in the future – sentient machines that can create their own unique and unrepeatable intelligent way to react to the environment, thus creating a one and only intelligent behaviour. Will it be unique?
However, let us go back to Artificial Intelligence machines and how they work.
In the 1980s there was the first phase of large investment in AI, with the British Alvey Program; the U.S. DARPA Program spending a billion US dollars on its Strategic Computing Initiative alone; finally the Japanese Fifth Generation Computer Project, investing a similar amount of money.
At the time there was the booming of “expert systems”, i.e. symbolic mechanisms that solved problems, but in a previously defined area.
From the beginning, expert systems were used in financial trading.
There was the hand of the expert system in the fall of the Dow Jones Industrial Average by 508 points in 1987. In 1990, however, Artificial Intelligence also began to be used in the analysis of financial frauds, with an ad hoc program used by the Financial Crimes Enforcement Network (FinCEN), especially with the possibility to automatically review 200,000 transactions per week and to identify over 400 illegal transactions.
Machine learning, the model on which the most widely used AI financial technology relies, is based on a work by McCullogh and Pitts in 1943, in which it was discovered that the human brain produces signals that are both digital and binary.
A machine learning system is composed, in principle, by: 1) a problem; 2) a data source; 3) a model; 4) an optimization algorithm; 5) a validation and testing system.
In 2011, deep learning (DL) added to the other “expert” systems.
It is a way in which machines use algorithms operating at various separate levels, as happens in the real human brain. Hence deep learning is a statistical method to find acceptably stable paradigms in a very large data set, by imitating our brain and its structure in layers, areas and sectors.
As explained above, it is a mechanism that “mimics” the functioning of the human brain, without processing it.
DL could analyse for the first time non-linear events, such as market volatility, but its real problem was the verification of models: in 2004 Knight Capital lost 440 million US dollars in 45 minutes, because it put into action a DL and financial trading model that had not been tested before.
In 2013, during a computer block of only 13 minutes, Goldman Sachs flooded the U.S. financial market with purchase requests for 800,000 equities. The same week., again for a computer error, the Chinese Everbright Securities bought 4 billion of various shares on the Shanghai market, but without a precise reason.
Between 2012 and 2016, the United States invested 18.2 billion US dollars in Artificial Intelligence, while only 2.6 were invested by China and 850 million US dollars by the United Kingdom in the same period.
The Japanese Government Pension Savings Investment Fund, the world’s largest pension fund manager, thinks it can soon replace “human” managers with advanced Artificial Intelligence systems.
BlackRock has just organized an AILab.
In 2017, however, China overtook the United States in terms of AI startups, with 15.2 billion funding.
China now has 68% of AI startups throughout Asia, raising 1.345 billion US dollars on the markets for their take-off.
China has also overtaken the United States in terms of Artificial Intelligence patents over the last five years.
Nevertheless, considered together, the USA and China still account for over 50% of all AI patents worldwide.
China also dominates the market of patents on AI technology vision systems, while deep learning data processing systems are now prey to the big global companies in the sector, namely Microsoft, Google and IBM. Similar Chinese networks are rapidly processing their new “intelligent” data collection systems, also favoured by the fact that the Chinese population is about twice as much as the US population and hence the mass of starting data is huge.
The Chinese intelligence industry zone near Tianjin is already active.
In the end, however, how does Artificial Intelligence change the financial sector?
AI operates above all in the trading of securities and currencies in various fields: algorithmic trading; the composition and optimization of portfolios; validation of investment models; verification of key operations; robo-advising, namely robotic consultancy; the analysis of impact on the markets; the effectiveness of regulations and finally the standard banking evaluations and the analysis of competitors’ trading.
Algorithmic trading is a real automatic transaction system – a Machine Learning program that learns the structure of transaction data and then tries to predict what will happen.
Nowadays computers already generate 70% of transactions in financial markets, 65% of transactions in futures markets and 52% of transactions in the public debt securities market.
The issue lies in making transactions at the best possible price, with a very low probability of making mistakes and with the possibility of checking different market conditions simultaneously, as well as avoiding psychological errors or personal inclinations.
In particular, algorithmic trading concerns hedge funds operations and the operations of the most important clients of a bank or Fund.
There are other AI mathematical mechanisms that come into play here.
There is, in fact, signal processing, which operates by filtering data to eliminate disturbing elements and observe the development trends of a market.
There is also market sentiment.
The computer is left completely unaware of the operations in progress, until the specific algorithm is put to work – hence the machine immediately perceives the behaviour of supply and demand.
There is also the news reader, a program that learns to interpret the main social and political phenomena, as well as pattern recognition, an algorithm teaching the machine to learn and react when the markets show characteristics allowing immediate gains.
Another algorithm is available, developed by a private computer company in the USA, which processes millions of “data points” to discover investment models or spontaneous market trends and operates on trillions of financial scenarios, from which it processes the scenarios deemed real.
Here, in fact, 1,800 days of physical trading are reduced to seven minutes.
However, the algorithms developed from evidence work much better than human operators in predicting the future.
Artificial Intelligence works as a prediction generator even in the oldest financial market, namely real estate.
Today, for example, there is an algorithm, developed by a German company, that automatically “extracts” the most important data from the documents usually used to evaluate real estate transactions.
In Singapore, Artificial Intelligence is used to calculate the value of real estate property, with a mix of algorithms and comparative market analysis. Man is not involved at all.
As to corporate governance, there are AI programs that select executives based on their performance, which is analysed very carefully.
What is certainly at work here is the scientist and naive myth of excluding subjectivity, always seen as negative. The program, however, is extremely analytical and full of variables.
Artificial Intelligence is also used in the market of loans and mortgages, where algorithms can be processed from an infinity of data concerning clients (age, work, gender, recurrent diseases, lifestyles, etc.) and are linked to operations – always through an algorithm – which are ordered, without knowing it, from one’s own mobile phone or computer.
So far we have focused on Artificial Intelligence algorithms.
But there is also quantum computing (QC), which is currently very active already. Its speed cannot be reached by today’s “traditional” computers.
It is a more suitable technology than the others to solve problems and make financial forecasts, because QC operates with really random variables, while the old algorithms simply simulate random variables.
Quantum computing can process several procedures simultaneously, and these “coexistence states” are defined as qubits.
In a scenario analysis, QC can evaluate a potentially infinite set of solutions and results that have been randomly generated.
An extremely powerful machine which, however, cannot determine exactly – as it also happens to slower machines – whether the scenario processed corresponds to human interests (but only to the initial ones known by the machine) or whether the procedure does not change during operations.
The Reckoning: Debt, Democracy and the Future of American Power- Book Review
Authors: Junaid R.Soomro and Nadia Shaheen
The chapter is written by Michael Moran in which he discussed about the relations between the economic institutions with the other institutions of the state. A state is a combination of many institutions that work together as a single body to make the state run accordingly. Political and economic institutions are two major components of the state. Politics and economy somehow depend on each other from a very long time. The both concepts are old and influenced by each other. The major changes occurred after the industrial revolution that gave birth to new tactics and opportunities to the economy. Earliest, before the French Revolution the economy was controlled by the elites that were the political identities. This is the example that how those bourgeois controlled the economic structure of the state and how they shape or influence the economical aspect of the society. These involvements of both disciplines gave birth to a new subject that is known as the political economy of the states, that how political and economic policies influence each other because it is not possible for any institution to work separately. The economic institutions shape the economic structure of the state and it is controlled by many aspects, including the political institutions, the economic regulations, the political structure of the state that somehow effects the economic institution of the state.
The chapter tells us that how economic institution and other institutions are interconnected.
Firstly, the focus is on the political institutions. The recognitions of an economic institution as a political act. The “politics” and “market” are somehow interconnected. It’s not because the political institutions shape the fate of economy, but the economy shapes it as well. From the start of the history these two aspects are there and depend on each other. We can see it through the examination of the history that how the political elites dominated the society because they were also superior financially. The political institutions somehow legitimize the economic institutions. According to “Godin” different preoccupations drive inquiry in different disciplines: for instance, choice in economy and the power in the politics.
Secondly the focus is the connection between institutionalism and the economic institutions.
The institutions are constructs of human mind, we cannot see or feel them. The regulations and the market grew up together. The current world politics is an example that how the regulations affect the economy and shape it as different stats can be taken as a model who are following the regulations. The institutions determine the opportunities of the society and in result the organizations are made in order or take benefit of those opportunities. There are several parallels that shape the behavior of the institutions that later affects the other institutions including the economic institution.
Thirdly, the connection between the economic institutions and the regulations.
The regulations are made to control the behavior of the institutions. This faced major change after the industrial revolution when many regulations were made that were supposed to control the outcomes of the institutions. We cannot run from globalization, this is the reason that the concept is not the same as it was in the past, but it came up with the new characteristics. Mainly the evolution in the middle of the twentieth century created a paradigmatic shift in the relationship of economic and political institutions. There are agencies with in the states that regulates the working on an institution and on the international level there are multinational corporations. This gives us two basic concepts. The first is uncertainty about the boundaries between the politics and economy, and the second is the importance of the agencies that fills the space and regulates the institutions.
Fourthly, the connection between the economic institutions and the capitalism.
Capitalism and the economy are directly connected with each other because the industrial revolution triggered the economy. Industries were made after the revolution and the world faced a new era of progress and economic change. The modern organizations are the basics that can be taken as the source of understanding the modern political economy. Industries were made after the industrial revolution that mainly works on the productivity, the more the productions are the more it will benefit. This era was a game changer for the economic aspect of the society and later it the economic institutions modified themselves.
Fifthly, the economic institutions and the democratic government.
The connection between democratic political institutions and the economic institution is complex. It depends that how far democratic government can try to constrain the operations of the economic institutions or how far the economic institutions can try the constrain the operation of the democratic government. the basic aspect of the relation is the relationship between the democracy and the market order. The control of the trade union and the control of the business. There are several problems such as the tussle between the capitalist institution and the democratic institution. There are several measures that can make both sides work together. The democratic governments usually believe on large economic interests and they also shape it according to their interests. There come the institutional regulations that regulates the behavior of these institutions in the particular manner.
State is made of many institutions. All the institutions work together this is the reason they depend on each other to work properly. The economic institution is the important institution of the state that makes it stand on its own. Today the examples are in front of us, those states th at has the best economic structures are now ruling the world. USA is the major power but with the passage of time new economic powers are competing with each other. The institutions regulate the behaviors but there are negative aspects when people use the institutions for their benefits. After the industrial revolutions there were merits and demerits. It depends on how one regulates the authority. If the institutions work properly the whole structure can be run perfectly but the interference that affects the institutions negatively can damage the structure. Today in the world where the concept of politics and economy is so dominant it is very important to regulate the bodies properly.
About the Author
Michael E. Moran (born May 1962 in Kearny, New Jersey) is an American author and analyst of international affairs he is also a digital documentarian who has held senior positions at a host of media, financial services, and consulting organizations. A foreign policy journalist and former partner at the global consultancy Control Risks, he is author of The Reckoning: Debt, Democracy and the Future of American Power, published in 2012 by Palgrave Macmillan. He is co-author of ‘The Fastest Billion: The Story Behind Africa’s Economic Revolution’. Moran served as Editor – in-Chief at the investment bank Renaissance Capital and has been a collaborator of renowned economist Nouriel Roubini as well commentator for Slate, the BBC and NBC News. He is also an adjunct professor of journalism at Bard College, a Visiting Fellow in Peace and Security at the Carnegie Corporation of New York, and conceived of and served as executive producer of the award-winning Crisis Guides documentary series for the Council on Foreign Relations.
China Development Bank could be a climate bank
Development Bank (CDB) has an opportunity to become the world’s most important
climate bank, driving the transition to the low-carbon economy.
CDB supports Chinese investments globally, often in heavily emitting sectors. Some 70% of global CO2 emissions come from the buildings, transport and energy sectors, which are all strongly linked to infrastructure investment. The rules applied by development finance institutions like CBD when making funding decisions on infrastructure projects can therefore set the framework for cutting carbon emissions.
CDB is a major financer of China’s Belt and Road Initiative, the world’s most ambitious infrastructure scheme. It is the biggest policy bank in the world with approximately US$2.3 trillion in assets – more than the $1.5 trillion of all the other development banks combined.
Partly as a consequence of its size, CDB is also the biggest green project financer of the major development banks, deploying US$137.2 billion in climate finance in 2017; almost ten times more than the World Bank.
This huge investment in climate-friendly projects is overshadowed by the bank’s continued investment in coal. In 2016 and 2017, it invested about three times more in coal projects than in clean energy.
scale makes its promotion of green projects particularly significant. Moreover,
it has committed to align with the Paris Agreement as part of the International Development Finance
Club. It is also
part of the initiative developing Green Investment Principles along the BRI.
This progress is laudable but CDB must act quickly if it is to meet the Chinese government’s official vision of a sustainable BRI and align itself with the Paris target of limiting global average temperature rise to 2C.
What does best practice look like?
In its latest report, the climate change think-tank E3G has identified several areas where CDB could improve, with transparency high on the list.
The report assesses the alignment of six Asian development finance institutions with the Paris Agreement. Some are shifting away from fossil fuels. The ADB (Asian Development Bank) has excluded development finance for oil exploration and has not financed a coal project since 2013, while the AIIB (Asian Infrastructure Investment Bank) has stated it has no coal projects in its direct finance pipeline. The World Bank has excluded all upstream oil and gas financing.
In contrast, CDB’s policies on financing fossil fuel projects remain opaque. A commitment to end all coal finance would signal the bank is taking steps to align its financing activities with President Xi Jinping’s high-profile pledge that the BRI would be “open, green and clean”, made at the second Belt and Road Forum in Beijing in April 2019.
CDB should also detail how its “green growth” vision will translate into operational decisions. Producing a climate-change strategy would set out how the bank’s sectoral strategies will align with its core value of green growth.
CDB already accounts for emissions from projects financed by green bonds. It should extend this practice to all financing activities. The major development banks have already developed a harmonised approach to account for greenhouse gas emissions, which could be a starting point for CDB.
Lastly, CDB should integrate climate risks into lending activities and country risk analysis.
One of the key functions of development finance institutions is to mobilise private finance. CDB has been successful in this respect, for example providing long-term capital to develop the domestic solar industry. This was one of the main drivers lowering solar costs by 80% between 2009-2015.
However, the extent to which CDB has been successful in mobilising capital outside China has been more limited; in 2017, almost 98% of net loans were on the Chinese mainland. If CDB can repeat its success in mobilising capital into green industries in BRI countries, it will play a key role in driving the zero-carbon and resilient transition.
From our partner chinadialogue.net
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