How to achieve scientific excellence

W. Brian Arthur from the Santa Fe Institute (SFI), and a former IIASA researcher, talks about increasing returns and the magic formula to get really great science.

Recently, Brian stopped in at the Complexity Science Hub Vienna, of which IIASA is a member institution, and spoke to Verena Ahne about his work.

Brian Arthur (© Complexity Science Hub)

Brian Arthur (© Complexity Science Hub)

Brian, now 71, is one of the most influential early thinkers of the SFI, a place that without exaggeration could be called the cradle of complexity science.

Brian became famous with his theory of increasing returns. An idea that has been developed in Vienna, by the way, where Brian was part of a theoretical group at the IIASA in the early days of his career: from 1978 to 1982.

“I was very lucky,” he recalls. “I was allowed to work on what I wanted, so I worked on increasing returns.”

The paper he wrote at that time introduced the concept of positive feedbacks into economy.

The concept of “increasing returns”

Increasing returns are the tendency for that which is ahead to get further ahead, for that which loses advantage to lose further advantage. They are mechanisms of positive feedback that operate—within markets, businesses, and industries—to reinforce that which gains success or aggravate that which suffers loss. Increasing returns generate not equilibrium but instability: If a product or a company or a technology—one of many competing in a market—gets ahead by chance or clever strategy, increasing returns can magnify this advantage, and the product or company or technology can go on to lock in the market.”

(W Brian Arthur, Harvard Business Review 1996)

This was a slap in the face of orthodox theories which saw–and some still see–economy in a state of equilibrium. “Kind of like a spiders web,” Brian explains me in our short conversation last Friday, “each part of the economy holding the others in an equalization of forces.”

The answer to heresy in science is that it does not get published. Brian’s article was turned down for six years. Today it counts more than 10.000 citations.

At the latest it was the development and triumphant advance of Silicon Valley’s tech firms that proved the concept true. “In fact, that’s now the way how Silicon Valley runs,” Brian says.

The youngest man on a Stanford chair

William Brian Arthur is Irish. He was born and raised in Belfast and first studied in England. But soon he moved to the US. After the PhD and his five years in Vienna he returned to California where he became the youngest chair holder in Stanford with 37 years.

Five years later he changed again – to Santa Fe, to an institute that had been set up around 1983 but had been quite quiet so far.

Q: From one of the most prestigious universities in the world to an unknown little place in the desert. Why did you do that? 

A: In 1987 Kenneth Arrow, an economics Nobel Prize winner and mentor of mine, said to me at Stanford: We’re holding a small conference in September in a place in the Rockies, in Santa Fe, would you go?

When a Nobel Prize winner asks you such a question, you say yes of course. So I went to Santa Fe.

We were about ten scientists and ten economists at that conference, all chosen by Nobel Prize winners. We talked about the economy as an evolving complex system.

Veni, vidi, vici

Brian came – and stayed: The unorthodox ideas discussed at the meeting and the “wild” and free atmosphere of thinking at “the Institute”, as he calls the Santa Fe Institute (SFI), thrilled him right away.

In 1988 Brian dared to leave Stanford and started to set up the first research program at Santa Fe. Subject was the economy treated as a complex system.

Q: What was so special about SF?

A: The idea of complexity was quite new at that time. But people began to see certain patterns in all sorts of fields, whether it was chemistry or the economy or parts of physics, that interacting elements would together create these patterns…To investigate this in universities with their particular disciplines, with their fixed theories, fixed orthodoxies–where it is all fixed how to do things–turned out to be difficult.

Take the economy for example. Until then people thought it was in an equilibrium. And there we came and proved, no, economics is no equilibrium! The Stanford department would immediately say: You can’t do that! Don’t do that! Or they would consider you to be very eccentric…

So a bunch of senior fellows at Los Alamos in the 1980s thought it would be a good idea if there was an independent institute to research these common questions that came to be called complexity.

At Santa Fe you could talk about any science and any basic assumptions you wanted without anybody saying you couldn’t or shouldn’t do that.

Our group as the first there set a lot of this wild style of research. There were lots of discussions, lots of open questions, without particular disciplines… In the beginning there were no students, there was no teaching. It was all very free.

This wild style became more or less the pattern that has been followed ever since. I think the Hub is following this model too.

The magic formula for excellence

Q: Was this just a lucky concurrence: the right people and atmosphere at the right time? Or is there a pattern behind it that possibly could be repeated?

A: I am sure: If you want to do interdisciplinary science – which complexity is: It is a different way of looking at things! – you need an atmosphere where people aren’t reinforced into all the assumptions of the different disciplines.

This freedom is crucial to excellent science altogether. It worked out not only for Santa Fe. Take the Rand Corporation for instance, that invented a lot of things including the architecture of the internet, or the Bell Labs in the Fifties that invented the transistor. The Cavendish Lab in Cambridge is another one, with the DNA or nuclear astronomy…

The magic formula seems to be this:

  • First get some first rate people. It must be absolutely top-notch people, maybe ten or twenty of them.
  • Make sure they interact a lot.
  • Allow them to do what they want – be confident that they will do something important.
  • And then when you protect them and see that they are well funded, you are off and running.

Probably in seven cases out of ten that will not produce much. But quite a few times you will get something spectacular – game changing things like quantum theory or the internet.

Don’t choose programs, choose people

Q: This does not seem to be the way officials are funding science…

A: Yes, in many places you have officials telling people what they need to research. Or where people insist on performance and indices… especially in Europe, I have the impression, you have a tradition of funding science by insisting on all these things like indices and performance and publications or citation numbers. But that’s not a very good formula.

Excellence is not measurable by performance indicators. In fact that’s the opposite of doing science.

I notice at places where everybody emphasize all this they are not on the forefront. Maybe it works for standard science; and to get out the really bad science. But it doesn’t work if you want to push boundaries.

Many officials don’t understand that.

In Singapore the authorities once asked me: How did you decide on the research projects in Santa Fe? I said, I didn’t decide on the research projects. They repeated their question. I said again, I did not decide on the research projects. I only decided on people. I got absolutely first rate people, we discussed vaguely the direction we wanted things to be in, and they decided on their research projects.

That answer did not compute with them. They are the civil service, they are extraordinarily bright, they’ve got a lot of money. So they think they should decide what needs to be researched.

I should have told them – I regret I didn’t: This is fine if you want to find solutions for certain things, like getting the traffic running or fixing the health care system. Surely with taxpayer’s money you have to figure such things out. But you will never get great science with that. All you get is mediocrity.

Of course now they asked, how do we decide which people should be funded? And I said: “You don’t! Just allow top people to bring in top people. Give them funding and the task of being daring.”

Any other way of managing top science doesn’t seem to work.

I think the Hub could be such a place – all the ingredients are here. Just make sure to attract some more absolutely first rate people. If they are well funded the Hub will put itself on the map very quickly.

This interview was originally published on https://www.csh.ac.at/brian-arthurs-magic-formula-for-excellence/

Emission reductions from fuel subsidy removal – the researchers respond to the debate

By Jessica Jewell, David McCollum, Johannes Emmerling, Christoph Bertram, David E.H.J. Gernaat, Volker Krey, Leonidas Paroussos, Loïc Berger, Kostas Fragkiadakis, Ilkka Keppo, Nawfal Saadi, Massimo Tavoni, Detlef van Vuuren, Vadim Vinichenko, Keywan Riahi

Our recent paper about our research on the effects of removing fossil fuel subsidies, published in Nature on February 8, 2018, generated a lot of comment and debate.

Here, we respond to three important themes raised in these comments. The first concerns the interpretation of our findings about the significance of subsidy removal for reducing CO2 emissions, the second concerns our approach to modeling and the data we used, and the third relates to policy options for more effective subsidy reform.

Nodding donkeys

© Shutterstock / huyangshu

What are fossil fuel subsidies and why are they interesting for climate?

Fossil fuel subsidies are government interventions which decrease the price of fossil fuels below the market price. They can go to supporting the extraction of oil, gas, and coal (production subsidies) or making fuels cheaper for consumers (consumption subsidies) and amounted to over US$400 billion in 2015. There is a certain irony in that so many governments signed on to the Paris Agreement in 2015 yet in that same year many of those same governments spent so much money making fossil fuels cheaper.

How much would removing these subsidies help climate change mitigation efforts? How does it compare to what countries have already pledged to do for the climate under the Paris Agreement?

Comparing emission reductions from subsidy removal to key climate targets

Some commenters claim that it is already known that the effect of removing fossil fuel subsidies on emissions is limited. However, according to the authoritative Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5), subsidy reform “can achieve significant emission reductions”. This view also is evident in the political sphere as: the Friends of Fossil Fuel Subsidy Reform, a group of countries called fossil fuel subsidy reform “the missing piece of the puzzle in the fight against climate change”.

Our findings are that fossil fuel subsidy removal would lead to a 1-4% reduction in CO2 emissions in the energy sector by 2030 if oil prices stay low, and 1-5% if oil prices rise again, compared to the rise in emissions if subsidies are maintained, the baseline. It means that subsidy reform is a modest contribution to the global reductions required to achieve 2°C in a least-cost pathway, 27-57% by 2030.

More importantly, in our paper we compare emission reductions from subsidy removal not to this ideal goal, but to the actual targets pledged in the context of the Paris Agreement. Globally, Paris pledges would reduce emissions against the baseline in the energy sector by 9-13% in 2030 (under a moderate growth baseline) which is a larger reduction than fossil fuel subsidy removal would deliver. Under both the Paris climate pledges and fossil fuel subsidy phase-out global emissions would continue to rise whereas to achieve the 2°C target they should peak and eventually decline.

Identifying the regions with greatest impact

This global assessment is only part of our study. In addition, we show how the impacts of subsidy removal are different by region. In the major oil and gas exporting regions (Middle East and North Africa, Russia and its neighboring countries, and Latin America), removing fossil fuel subsidies lowers emissions by the same amount or more than these countries’ Paris pledges. Government revenues in these regions largely come from energy exports, which are squeezed by today’s low oil prices. Lowering government spending by removing subsidies is a real political opportunity to reduce emissions in these regions.

In other developing and emerging economies (India, China, the rest of Asia and Sub-Saharan Africa), removing fossil fuel subsidies has less of an effect on emissions than these countries’ Paris pledges. In addition, the number of people who might be affected by subsidy removal in these regions is higher, simply because there are many more people living below the poverty line, for whom subsidies make the most difference. Taken together, these two findings frame one of our main results: that subsidy removal would be most useful for the climate precisely in the regions where it would affect fewer people living below the poverty line.

Data on subsidies

The second theme we would like to address relates to our data and modeling. Some commenters claimed that we underestimate both production subsidies and the effect of their removal.

According to data from the IEA and OECD only about 4% of subsidies are production subsidies. The International Institute for Sustainable Development (IISD) and Overseas Development Institute (ODI) publish an independent estimate based on their own definition and approach. Extrapolating to the global level, production subsidies would be about 14% in 2013 under their approach. We ran a sensitivity analysis using this higher production subsidies estimate. This did not change our findings (discussed in the Supplementary Information to our article).

Some commenters claimed that our study does not consider electricity production subsidies. This is also not true. We use the IEA data where power generation subsidies are captured in electricity subsidies. The SI discusses how each model integrates electricity subsidies.

There are other, fragmented estimates for electricity generation subsidies in individual countries, which generally take a different view of subsidies. For example, the recent report from IISD on Chinese subsidies to coal-fired power plants indicates that in 2014 and 2015, between 89% and 97% of these subsidies went to incentivize air pollution control equipment or closing inefficient plants. According to the same report, these subsidies also dropped by half from 2014 to 2015. Few governments would consider this as an environmentally-harmful subsidy, and removing such support will increase, not decrease emissions.

For our main analysis, we relied on IEA and OECD data for both production and consumption subsidies because these inventories are aligned with governments’ own estimates which are prepared as part of the G20 pledge to remove subsidies from 2009 reaffirmed in 2016. By using the same input data as governments and international organizations who are pledging or considering fossil fuel subsidy removal, we ensure the policy relevance of our results for these actors. 

Estimating the effects of production subsidy removal

There were several comparisons of our results with those reported in a recent paper by Erickson et.al. in Nature Energy, which found that under the currently low oil prices, removing production subsidies in the US would make several oil fields unprofitable and eventually result in their closure. We find contrasting these two papers misleading as they ask very different research questions. Our study does not investigate how many oil fields in the US or elsewhere will become unprofitable after subsidy removal, but looks at the global effect of subsidy removal on emissions by taking into account trade in fossil fuels, the demand response and potential substitution of fuels and technologies. Erickson and his colleagues do not ask how much emissions will change as a result of closed oil fields. These are two very different questions.

Erickson and his colleagues compare the amount of carbon embedded in the oil reserves that may become unprofitable due to subsidy removal, to how much carbon the US would be allowed to emit under a stringent climate target. This creates an impression that they investigate the impact of removing oil production subsidies on US emissions. However, calculating the emission impact from removing oil production subsidies requires not only calculating the emissions embedded in foregone oil production, but also the possible emissions resulting from replacing this lost oil with other fuels, or changes in demand, for example if Americans choose to drive less if wells are closed, or if the US imports oil instead. We use these types of feedbacks in our models to calculate the emissions effects of subsidy removal (both consumption and production).

Redirecting subsidy funds

The third theme raised in the comments to our article was why we did not model redirecting subsidies to supporting renewable energy. While this is a very tempting question to ask from a climate perspective, and certainly one which we could do in our models, we did not consider it a realistic policy to be prioritized in our scenarios. In most countries fuel subsidies were introduced to support those on low incomes, although it is an inefficient way to do so. A state budget deficit and today’s low oil prices can often prompt successful subsidy reform. Indonesia for example recently expanded spending on infrastructure and programs to reduce poverty, while India introduced vouchers for cooking fuels. Iran, meanwhile introduced universal health coverage.

Fossil fuel subsidies do need reform

We would like to express our agreement with two comments, one from Ian Parry who wrote a commentary to our paper in Nature, and another from David Victor in his statement to Scientific American, that there are many reasons to reform fossil fuel subsidies other than emissions reductions. Our article does not cover these reasons and should not be interpreted as a comprehensive assessment of all aspects of subsidy removal.

We do however hope that our transparent and rigorous assessment of the effects of subsidy removal on CO2 emissions and energy use will support realistic and effective subsidy removal policies, and help in understanding the relative importance of a range of emission-reduction measures needed for achieving the ambitious long-term targets of the Paris Agreement.

As some commenters pointed out, we need all tools in the box to combat the enormous challenge of climate change. We fully agree. At the same time, we also believe in the need to understand how much each tool can do and where it can be most effective. This is exactly what our study answers.

Reference

Jewell J, McCollum, D Emmerling J, Bertram C, Gernaat DEHJ, Krey V, Paroussos L, Berger L, Fragkiadakis K, Keppo I, Saadi, N, Tavoni M, van Vuuren D, Vinichenko V, Riahi K (2018) Limited emission reductions from fuel subsidy removal except in energy exporting regions. Nature DOI: 10.1038/nature25467

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

Using Twitter data for demographic research

By Dilek Yildiz, Wittgenstein Center for Demography and Global Human Capital (IIASA, VID/ÖAW and WU), Vienna Institute of Demography, Austrian Academy of Sciences, International Institute for Applied Systems Analysis

Social media offers a promising source of data for social science research that could provide insights into attitudes, behavior, social linkages and interactions between individuals. As of the third quarter of 2017, Twitter alone had on average 330 million active users per month. The magnitude and the richness of this data attract social scientists working in many different fields with topics studied ranging from extracting quantitative measures such as migration and unemployment, to more qualitative work such as looking at the footprint of second demographic transition (i.e., the shift from high to low fertility) and gender revolution. Although, the use of social media data for scientific research has increased rapidly in recent years, several questions remain unanswered. In a recent publication with Jo Munson, Agnese Vitali and Ramine Tinati from the University of Southampton, and Jennifer Holland from Erasmus University, Rotterdam, we investigated to what extent findings obtained with social media data are generalizable to broader populations, and what constitutes best practice for estimating demographic information from Twitter data.

A key issue when using this data source is that a sample selected from a social media platform differs from a sample used in standard statistical analysis. Usually, a sample is randomly selected according to a survey design so that information gathered from this sample can be used to make inferences about a general population (e.g., people living in Austria). However, despite the huge number of users, the information gathered from Twitter and the estimates produced are subject to bias due to its non-random, non-representative nature. Consistent with previous research conducted in the United States, we found that Twitter users are more likely than the general population to be young and male, and that Twitter penetration is highest in urban areas. In addition, the demographic characteristics of users, such as age and gender, are not always readily available. Consequently, despite its potential, deriving the demographic characteristics of social media users and dealing with the non-random, non-representative populations from which they are drawn represent challenges for social scientists.

Although previous research has explored methods for conducting demographic research using non-representative internet data, few studies mention or account for the bias and measurement error inherent in social media data. To fill this gap, we investigated best practice for estimating demographic information from Twitter users, and then attempted to reduce selection bias by calibrating the non-representative sample of Twitter users with a more reliable source.

Exemplar of CrowdFlower task © Jo Munson.

We gathered information from 979,992 geo-located Tweets sent by 22,356 unique users in South-East England and estimated their demographic characteristics using the crowd-sourcing platform CrowdFlower and the image-recognition software Face++. Our results show that CrowdFlower estimates age more accurately than Face++, while both tools are highly reliable for estimating the sex of Twitter users.

To evaluate and reduce the selection bias, we ran a series of models and calibrated the non-representative sample of Twitter users with mid-year population estimates for South-East England from the UK Office of National Statistics. We then corrected the bias in age-, sex-, and location-specific population counts. This bias correction exercise shows promise for unbiased inference when using social media data and can be used to further reduce selection bias by including other sociodemographic variables of social media users such as ethnicity.  By extending the modeling framework slightly to include an additional variable, which is only available through social media data, it is also possible to make unbiased inferences for broader populations by, for example, extracting the variable of interest from Tweets via text mining. Lastly, our methodology lends itself for use in the calculation of sample weights for Twitter users or Tweets. This means that a Twitter sample can be treated as an individual-level dataset for micro-level analysis (e.g., for measuring associations between variables obtained from Twitter data).

Reference:

Yildiz, D., Munson, J., Vitali, A., Tinati, R. and Holland, J.A. (2017). Using Twitter data for demographic research, Demographic Research, 37 (46): 1477-1514. doi: 10.4054/DemRes.2017.37.46

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

Parched: The war for water in Mexico City

By Parul Tewari, IIASA Science Communication Fellow 2017

Mexico City has been experiencing a major water crisis in the last few decades and it is only getting worse. To keep the water flowing, the city imports large amounts of water from as far as 150 kilometers.

Not only is this energy-intensive and expensive, it creates conflict with the indigenous communities in the donor basins. Over the last decade, a growing number of these communities have been protesting to reclaim their rights to water resources.

The ancient city of Tenochtitlan as depicted in a mural by Diego Rivera
(cc) Wikimedia Commons

As part of the 2017 Young Scientists Summer Program at IIASA, Francine van den Brandeler studied the struggle that Mexico City is facing as it tries to provide water to its growing population and expanding economy. Local aquifers have been over-exploited, so water needs to be imported from distant sources, with high economic, social, and environmental impacts. Van den Brandeler’s study assesses the effectiveness of water use rights in promoting sustainable water use and reducing groundwater exploitation in the city.

“A few centuries back, Tenochtitlan, the place where Mexico City stands today, was known as the lake city,” says Van den Brandeler. The Aztecs had developed a sophisticated system of dikes and canals to manage water and mitigate floods. However, that changed quickly with the arrival of the Spaniards, who transformed the natural hydrology of the valley. As the population continued to grow over the next centuries, providing drinking water became an increasing challenge, along with controlling floods. As the lake dried up, people pumped water from the ground and built increasingly large infrastructure to bring water from other areas.

Communities from lower-income groups, living in informal settlements on the outskirts of the metropolitan region are more vulnerable to this scarcity. Many live on just few liters of water every day, and do not have access to the main water supply network, instead relying on water trucks which charge several times the price of water from the public utility.

“In wealthier areas people consume much more than the average European does every day. It is a question of power and politics,” says van den Brandeler. “The voices of marginalized communities go unheard.”

Many people rely on delivery service for drinking water.
© Angela Ostafichuk | Shutterstock

The more one learns about the situation, the more complicated it becomes. The import of water started in the 1940’s. But with a massive increase in population in the last couple of decades, the deficits have become much worse.

The government’s approach has been to find more water rather than rehabilitating or reusing local surface and groundwater sources, or increasing water use efficiency, says van den Brandeler. Therefore wells are being drilled deeper and deeper—as much as 2000 meters into the ground—as the water runs out.

Some people have started initiatives to harvest rainwater, but it is not considered a viable solution by those in charge. “A lot of it has to do with their worldview and general paradigm. The people working at the National Water Commission and the Water Utility of Mexico City have been trained as engineers to make large dams and put pipes in the ground. They don’t believe in small-scale solutions. In their opinion when millions of people are concerned, such solutions cannot work,” says van den Brandeler.
Although the city gets plenty of rain during the rainy season, it goes directly into the drainage system which is linked to the sewage system. This contaminates the water, making it unusable. At the same time, almost 40% of the water in Mexico City’s piped networks is lost due to leakages.

Policy procedures and institutional functioning also remain top-down and opaque, van den Brandeler has found. One of the policy tools for curbing excess water use are water permits for bulk use, for agriculture, industry, or public utilities supplying water. Introduced in the 1940s, lack of proper enforcement has created misuse and conflicts.
For example, while farmers also require a permit that specifies the volume of water they may use each year, they do not pay for their water usage. However, it is difficult to monitor if farmers are extracting water according to the conditions in the permit. Since they do not pay a usage fee, there is also less incentive for the National Water Commission to monitor them. As a result, a huge black market has cropped up in the city where property owners and commercial developers pay exorbitant prices to buy water permits from those who have a license. Since the government allows the exchange of permits between two willing parties, they make it appear above-board. However, it has contributed to the inequalities in water distribution in the city.

With the water crisis worsening every year, Mexico City needs to find a solution before it runs out of water completely. Van den Brandeler is hopeful for a better future as she studies the contributing factors to the problem. She hopes that the water use permits are better enforced and users are given stronger incentives to respect their allocated water quotas. Further, if greater efforts are made within the metropolis to repair decaying infrastructure and scale up alternatives such as rainwater harvesting and wastewater reuse, the city won’t have to look at expensive solutions if adopted in a decentralized manner.

About the Researcher

Francine van den Brandeler is a third year PhD student at the University of Amsterdam in Netherlands. Her research is on the spatial mismatches between integrated river basin management and metropolitan water governance – the incompatibility of institutions and biophysical systems-, which can lead to fragmented water policy outcomes. Fragmented decision-making cannot adequately address the issues of sustainability and social inclusion faced by megacities in the Global South. She aims to assess the effectiveness of policy instruments to overcome this mismatch and suggest recommendations for policy (re)design. At IIASA she was part of the Water Program and worked under the supervision of Sylvia Tramberend and Water Program Director Simon Langan.

This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

Not a heron: the Eurasian Economic Union should ‘stand on two legs’

By Evgeny Vinokurov, Director of the Centre for Integration Studies at the Eurasian Development Bank, member of the IIASA-led project, Challenges and Opportunities of Economic Integration within a Wider European and Eurasian Space

An Italian nursery riddle goes: “Why does the heron stand on one leg? Because if it takes away the second leg, it will fall down!” An ornithologist will tell you that herons have incredibly strong legs. The EAEU, consisting of Armenia, Belarus, Kazakhstan, Kyrgyzstan, and Russia is not a heron – it does need to stand firmly on two legs. In this case, one leg is the European Union, and the other leg is the People’s Republic of China. An economist will tell you that the strength of “economic legs” underpinning the countries which make up the Eurasian Economic Union (EAEU) can be described, at best, as fair to middling: the heavy reliance on oil and gas is not particularly wholesome. That is why Russia and its EAEU partners need to establish close economic ties with both the EU and China.

© Galushko Sergey | Shutterstock

Both partners are critically important for the EAEU. The EU remains its largest trade partner: in 2016 it accounted for 50% of total exports from, and 41% of total imports to the Eurasian Union. EAEU member states are interested in expanding the inflow of European investment capital, transfer of EU technologies, and stable EU demand for energy. The EAEU, in turn, is the third largest EU trade partner (after the US and China); accordingly, the EU may be interested in liberalization of trade with the EAEU (establishment of a free trade agreement), reduction of non-tariff barriers in EAEU member states (with a view to increase EU exports), and stability of EAEU power supplies.

At the same time, the EAEU’s “turn to the East” is slowly gaining momentum: Asia-Pacific Economic Cooperation (APEC) countries,first and foremost, China and Association of Southeast Asian Nations  (ASEAN) countries, are beginning to overtake the EU. By the end of 2016, the Eurasian Union had imported 1.5% more goods from APEC countries (42.3% of total imports, mostly from China, Korea, and ASEAN countries) than it did from EU countries. It is also important for EU investors to understand that they are exposed to an ever-increasing risk of losing EAEU markets due to the inflow of capital from the leading Asian economies.

These matters have been subjected to rigorous applied analysis in Challenges and Opportunities of Economic Integration within a Wider European and Eurasian Space, a project initiated by IIASA in 2014. It advanced an independent dialogue platform to facilitate interaction between representatives of supranational bodies, expert and business communities of the two unions. The project is designed to help its European and Eurasian participants find common ground with respect to a possible inter-union trade and economic agreement.

According to project publications , it is advisable to reach a comprehensive agreement covering a much broader range of partnership domains than that associated with a standard free trade area. According to the latest calculations by European and Russian experts, an EU-EAEU free trade agreement would produce a positive impact. However, experts from the Information and Forschung (IFO) institute in Munich point out that EAEU agriculture and automotive industry may suffer heavy losses. This demonstrates that it is necessary to work out a quite structurally complex solution offering asymmetric advantages to the two sides.

Relations with China display completely different patterns. Two following “tracks” are especially important.

The first relates to the ongoing negotiations on a non-preferential agreement on trade and economic cooperation between the EAEU and China, envisaging reciprocal minimization of barriers in customs regulations and the financial sector, and intensification of investment cooperation. Talks have already been underway for one year, and are expected to continue for another year or two.

The second track deals with realization of the One Belt One Road  initiative. It involves implementation of large-scale joint infrastructure projects, primarily in transportation.  EAEU’s participation in the One Belt One Road initiative is very promising for its member states, especially for Russia and Kazakhstan, which need to remove infrastructural limitations inhibiting railroad carriage of containerized cargoes.  The EAEU continues to face the issue of insufficient investment capital allocation to container logistical hubs. Kazakhstan will also need to eliminate bottlenecks in its transportation and logistics infrastructure, primarily by building modern container terminals. These are but several of the numerous problems facing the EAEU.

We are looking at One Belt One Road in the broad Greater Eurasia context. Higher efficiency of Greater Eurasian land transportation corridors could enhance trade and generate numerous industrial opportunities. This is particularly relevant for landlocked countries and regions (all Central Asian countries, Russian Urals and Western Siberia).

Russia and its EAEU partners need to establish close economic cooperation ties with both the European Union and China. The EAEU will have to learn to balance between those two poles, making ample use of economic vistas presented by the tripartite cooperation setup, and “capitalize on contradictions.” If the EAEU manages to reach this overarching goal, its foreign economic policy would be successful.

This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.