Sep 7, 2018 | Brazil, Education, Postdoc
Rafael Morais
Rafael Morais is a recent participant in the IIASA-CAPES Doctorate Sandwich Program, he spent nine months at IIASA working in the Energy program.
In 2016, the Brazilian Federal Agency for Support and Evaluation of Graduate Education (CAPES) partnered with IIASA on a new initiative offering support to doctoral and postdoctoral researchers interested in collaborating with established IIASA researchers. As part of this initiative, IIASA and CAPES annually offer up to three fellowships for Brazilian PhD students to spend three to twelve months at IIASA as part of the joint IIASA-CAPES Doctorate Sandwich Program, as well as up to four postdoc fellowships that enable Brazilian researchers to work at IIASA for up to 24 months.
Rafael Morais, a PhD candidate at the Energy Planning Program of the Federal University of Rio de Janeiro, was part of the first group of Brazilian PhD students funded by CAPES to participate in this program. He spent nine months with the Energy Program at IIASA in 2017. We recently caught up with him and asked him about his research and what the fellowship has meant to him:
What is your PhD research about?
My research involves modeling the contribution of renewable energy sources in electric systems. My doctorate thesis includes a case study on Brazil, where we have large potential for wind and solar power generation in various regions. My main objective is to investigate how total costs develop considering the number of wind and solar plants in the Brazilian electricity system.
Why did you choose IIASA for your doctorate program (over other places)?
I chose IIASA because it is a very reputable think tank for energy and model development. People are very capable and well prepared. They have been working on energy systems modeling for many years, and their experience motivated my decision to come to IIASA. I talked with some people that were at IIASA before me and they were all very grateful for the experience. Another important factor was that it is an international institute, where one can have contact with people from many different countries, and the main language is English.
Rafael Morais
How did your participation in the program benefit you?
I had the opportunity to get into contact with diverse approaches to my research questions, thus enriching my thesis. Unlike my home institution, IIASA does not have only energy experts, but also computer scientists, mathematicians, and physics experts, all working in the same group, and all contributing to a great modeling team. Being here was an excellent opportunity to collaborate with them. As my first experience abroad, it was also a chance for me to grow and develop other skills, both on a professional and a personal level.
Would you recommend that people apply for the IIASA-CAPES doctorate program?
Yes, I would definitely recommend it! IIASA is a very nice place to work. People really care about a harmonious work environment, and IIASA staff are always available to help you with any issue. Apart from that, the people that I worked with during my time here are very knowledgeable and kind. In short, it was a great experience being at IIASA for nine months during my PhD.
Applications for the 2019 IIASA-CAPES Doctorate Sandwich Program and Postdoctoral Fellowship Program opened on 1 September 2018 and will run until 15 October 2018. Candidates have to apply to both CAPES (on the CAPES website) and IIASA. Successful applicants will be informed of the selection results by mid-December 2018. Selected candidates are expected to take up their position at IIASA between March and October 2019.
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.
Aug 27, 2018 | Data and Methods, Ecosystems, Postdoc
by Melina Filzinger, IIASA Science Communication Fellow
Ecosystems worldwide are changed by the influence of humans, often leading to the extinction of species, for example due to climate change or loss of natural habitat. But it doesn’t stop there: as the different species in an ecosystem feed on each other and are thereby interconnected, the loss of one species might lead to the extinction of others, which can even destabilize the whole system. “In nature, everything is connected in a complex way, so at first glance you cannot be sure what will happen if one species disappears from an ecosystem,” says IIASA postdoc Mateusz Iskrzyński.
This is why the IIASA Evolution and Ecology (EEP) and Advanced Systems Analysis (ASA) programs are employing food-web modeling to find out which properties make ecosystems particularly vulnerable to species extinction. Food webs are stylized networks that represent the feeding relationships in an ecosystem. Their nodes are given by species or groups of species, and their links indicate how biomass cycles through the system by means of eating and being eaten. “This type of network analysis has a surprising power to uncover general patterns in complex relationships,” explains Iskrzyński.
Every one of these food webs is the result of years of intense research that involves both data collection to assess the abundance of species in an area, and reconstructing the links of the network from existing knowledge about the diets of different species. The largest of the currently available webs contain about 100 nodes and 1,000 weighted links. Here, “weighted” means that each link is characterized by the biomass flow between the nodes it connects.
Usually, food webs are published and considered individually, but recently efforts have been stepped up to collect them and analyze them together. Now, the ASA and EEP programs have collected 220 food webs from all over the world in the largest database assembled so far. This involved unifying the parametrization of the data and reconstructing missing links.
The researchers use this database to find out how different ecosystems react to the ongoing human-made species loss, and which ones are most at risk. This is done by removing a single node from a food web, which corresponds to the extinction of one group of species, and modeling how the populations of the remaining species change as a result. The main question is how these changes in the food web depend on its structural properties, like its size and the degree of connectedness between the nodes.
From the preliminary results obtained so far, it seems that small and highly connected food webs are particularly vulnerable to the indirect effects of species extinction. This means that in these webs the extinction of one species is especially likely to lead to large disruptive change affecting many other organisms. “Understanding the factors that cause such high vulnerability is crucial for the sustainable management and conservation of ecosystems,” says Iskrzyński. He hopes that this research will encourage more, and more precise, empirical ecosystems studies, as reliable data is still missing from many places in the world.
As a next step, the scientists in the two programs are planning to understand which factors determine the impact that the disappearance of a particular group of organisms has. They are going to make the software they use for their simulations publicly available, together with the database they developed.
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.
Jun 4, 2018 | Demography, Postdoc, Poverty & Equity, Women in Science
©Nandita Saikia
By Nandita Saikia, Postdoctoral Research Scholar at IIASA
Being an author of a research article on excess female deaths in India in Lancet Global Health, one of the world’s most prestigious and high impact factor public health journals, today I questioned myself: Did I dream of reaching here when I was a little school going girl in the early nineties in a remote village in North East India?
I am the fourth daughter of five. In a country like India, where the status of women is undoubtedly poorer than men even now, and newspapers are often filled with heinous crimes against women, you may be able to imagine what it meant being a fourth daughter. Out of five sisters, three of us were born because my parents wanted a son. My mother, who barely completed her school education, did not want more than two children irrespective of sex, but was pressurized by the extended family to go for a boy after a third daughter and six years of repeated abortions.
I was told in my childhood that I was the most unwanted child in the family. I was a daughter, terribly underweight until age 11, and had much darker skin than my elder sisters and most people from our area, who have fairer skin than average in India. At my birth, my father, a college dropout farmer, was away in a relative’s house and when he heard about the arrival of another girl, he postponed his return trip.
This is a real story, but just one of those still happening in India. The fact that the girls of India are unwanted was observed from the days of early 20th century when it was written in the 1901 census:
“There is no doubt that, as a rule, she [a girl] receives less attention than would be bestowed upon a son. She is less warmly clad, … She is probably not so well fed as a boy would be, and when ill, her parents are not likely to make the same strenuous efforts to ensure her recovery.”
Regrettably, our current study shows that negligence against “India’s daughter” continues to this day.
Discrimination against the girl child can be divided in two categories: before birth and after birth. Modern techniques now allow sex-selective abortion. Despite strong laws, more than 63 million women are estimated to be ‘missing’ in India and the discrimination occurs at all levels of society.
Our present study deals with gender discrimination after birth. We found that over 200,000 girls under the age of five died in 2005 in India as a result of negligence. We found that excess female mortality was present in more than 90% of districts, but the four largest states of North India (Uttar Pradesh, Bihar, Rajasthan, and Madhya Pradesh) accounted for two thirds of India’s total number.
I have to tell you that I was luckier than most girls. Although I was an unwanted child in our extended family, to my mother, this underweight, dark-skinned, little girl was as cute as the previous ones! She gave her best care to her daughter, and she named her “Rani” meaning “Queen” in Assamese. I am still called by this name in my family and in my village.
When I grew up, I asked her several times about her motive for calling me Rani. She always replied: “You were so ugly, the thinnest one with dark skin, I named you as “Rani” because I wanted everyone to have a positive image before seeing you! Also, it is the name of my favorite teacher in high school and she was also a very thin but bright lady!”
The positive conversations with my mother played a crucial role to my desire to have my own identity, and influenced greatly my positive image of myself and my belief that I could do something worthwhile with my life. Much later, when I started my PhD at International Institute for Population Sciences (IIPS), Mumbai, I was surprised to learn that in Maharashtra, one of the wealthiest states of India, second or third daughters are not even given a name, but instead are called ‘Nakusha’, meaning unwanted.
My parents were passionate about educating their daughters, even with their limited means. My father, who was disappointed at my birth, left no stone unturned for my education! By the time I completed secondary school, our village, as well as neighboring villages, congratulated me during the Bihu celebration (the biggest local gathering) for my good performance in school exams. My parents were proud of me by that time; yet, for some strange reason, they always felt themselves weaker than our neighbors who had sons.
Now, people from our village are proud of me not just because I teach in India’s premier university, or that I take several overseas trips in a year, but because they realize that daughters can equally bring renown to their village; daughters can be married off without a dowry; daughters can equally provide old age care to their parents; daughters too can buy property! Due to this attitude and lower fertility levels, many couples now don’t prefer sons over daughters. In a village of 200 households, there are 33 couples that have either one or two daughters, yet did not keep trying for sons. In my own extended family, no one chooses to have more than two children irrespective of their sex. The situation has changed in my village, but not everywhere.
What is the solution of this deep-rooted social menace? We cannot expect a simple solution. However, my own story convinces me that education can be a game changer, but not necessarily academic degrees. I mean a system by which girls realize their own worth and their capability that they can be economically and socially empowered and can drive their own lives. With the help of education, I made myself from an “unwanted” to a wanted daughter!
The purpose of sharing my story is neither self-promotion nor to gain sympathy, rather to inspire millions of girls, who face numerous challenges in everyday life just because of their gender, and doubt their capability, just like I did in my school days. They can make a difference if they want! Nothing can stop them!
Jan 8, 2018 | Economics, Postdoc
By Isela-Elizabeth Tellez-Leon, IIASA-CONACYT postdoc in the Advanced Systems Analysis, Evolution and Ecology, and Risk and Resilience programs.
The rise of foreign investment in emerging economies after the global financial crisis of 2008-2009 has renewed interest in what drives such investment. My colleague at the Central Bank of Mexico and I examined the determinants of foreign investment, known as capital flows, into Mexico in 1995-2015, a period characterized by a free-floating exchange rate, that is, the authorities did not set an exchange rate.
Our research has useful findings for the design of economic policies because it provides measures that authorities can take to direct proper functioning of the economy. It also contributes to improved understanding of what influences capital flows into Mexico. We analyzed the determinants of each type of foreign investment separately, because different financial flows respond differently to the various external and internal factors. Mexico is an interesting case study because it experienced a large volume of capital investment after the commercial opening in the 1990s and more recently in the aftermath of the 2008-2009 financial crisis, as international investors were searching for high yields and security. In addition, the trading volume of Mexican government securities is one of the highest among emerging markets.
Capital flows are incorporated into financial accounts where foreign transactions are noted—including investments by foreign residents into Mexican public and private sector securities and by domestic residents in foreign securities. Mexico’s financial accounts (Figure 1) are composed of the following three components: portfolio investment (in terms of liquidity—i.e., the extent to which a market allows assets to be bought and sold at stable prices—this is a short-term investment, Figure 2), other investment (Figure 3), and foreign direct investment (in terms of liquidity this is a long-term investment, Figure 4).
The financial account is divided into three main areas: foreign direct investment (FDI), portfolio investment (PI) and other investment (OI). Figure 1 shows the net flows of foreign investment. Figure 2 displays portfolio investment (PI) and its components of domestic and foreign investors. Figure 3 and 4 show OI and FDI split into their different components. The figures show moving averages over 4 quarters adjusted for seasonality. Source: Elizabeth Tellez and the Central Bank of Mexico.
Portfolio and other investments tend to leave and enter a country quicker than foreign direct investment; thus, they are likely to respond faster to shocks. In particular, portfolio investment by foreign agents might have a different response compared to portfolio investment by domestic agents. For example, if foreign investors have timely information about the external economic conditions, they will likely respond faster to foreign shocks.
In general, foreign investment has an impact on developing economies in at least two ways. On the one hand, international borrowing allows a country to increase investment in the private sector, without sacrificing consumption. On the other hand, large foreign investment flows may be followed by increases in the prices of goods and services because of the strength of the exchange rate. In turn, this increases purchases of foreign products (imports), but exports decrease. In this way, a country’s foreign trade may become more vulnerable to external shocks and reversals of foreign investment.
Central Bank of Mexico © Elizabeth Tellez.
To analyze what determines capital flows in the short and medium term for Mexico, we used an econometric model known as Vector Autoregression. This model allows us to examine the impacts of different shocks on capital flows. We studied two sets of factors that can encourage investors to shift resources to emerging markets. The first set considers external shocks (push factors), which are beyond the control of developing countries, such as foreign interest rates or economic activity in advanced countries.
The push factors we examined were global risk, US liquidity, US GDP, and US interest rates. The second set of factors are the prevailing economic conditions in the emerging economy (pull factors). For these we considered Mexican GDP, interest rates, inflation, and exchange rates.
One of our main findings is that investors are risk averse and prefer to invest abroad when foreign interest rates are higher. Portfolio investment (PI) and other investment (OI) seem more responsive to short-term shocks than foreign direct investment (FDI), possibly because they tend to be more liquid than FDI. We also found that domestic conditions play a role in explaining capital flows. For instance, we found that higher GDP growth leads to higher portfolio investment, while higher interest rates and lower inflation generate higher inflows of other investment. Our work underlines the benefits of separately analyzing the components of capital flows. For instance, a shock to the federal funds rate has important effects on portfolio investment in public-sector securities by foreign residents. This is because public securities are the closest substitutes to US government bonds found in the Mexican financial market.
Reference:
Raul IR & Tellez Leon E (2017). Are all types of capital flows driven by the same factors? Evidence from Mexico. Banco de Mexico, Mexico.
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.
Nov 7, 2017 | Data and Methods, Food, Postdoc, Water
By Valeria Javalera Rincón, IIASA CONACYT Postdoctoral Fellow in the Ecosystems Services and Management and Advanced Systems Analysis programs.
What is more important: water, energy, or food?
If you work in the water, energy or agriculture sector we can guess what your answer might be! But if you are a policy or decision maker trying to balance all three, then you know that it is getting more and more difficult to meet the growing demand for water, energy, and food with the natural resources available. The need for this balance was confirmed by the 17 Sustainable Development Goals, agreed by 193 countries, and the Paris climate agreement. But how to achieve it? Intelligent cooperation is the key.
The thing is that water, energy, and food are all related in such a way that are reliant on each other for production or distribution. This is the so-called Water-Energy-Food nexus. In many cases, you need water to produce energy, you need energy to pump water, and you need water and energy to produce, distribute, and conserve food.
Many scientists have tried to relate or to link models for water, agriculture, land, and energy to study these synergic relationships. In general, so far, there are two ways that this has been solved: One is integrating models with “hard linkages” like this:
© Daniel Javalera
In the picture there are six models (let’s say water, land use, hydro energy, gas, coal, food production models) that are then integrated into just one. The resulting integrated model then preserves the relationships but is complex, and in order to make it work with our current computer power you often have to sacrifice details.
Another way is to link them is using so-called “soft linkages” where the output of one model is the input of the next one, like this:
© Daniel Javalera
In the picture, each person is a model and the input is the amount of water left. These models all refer to a common resource (the water) and are connected using “soft linkages.” These linkages are based on sequential interaction, so there is no feedback, and no real synergy.
The intelligent linker agent
But what if we could have the relations and synergies between the models? It would mean much more accurate findings and helpful policy advice. Well, now we can. The secret is to link through an intelligent linker agent.
I developed a methodology in which an intelligent linker agent is used as a “negotiator” between models that can communicate with each other. This negotiator applies a machine-learning algorithm that gives it the capability to learn from the interactions with the models. Through these interactions, the intelligent linker can advise on globally optimal actions.
The knowledge of the intelligent linker is based on past experience and also on hypothetical future actions that are evaluated in a training process. This methodology has been used to link drinking water networks, such as Barcelona’s drinking water network.
When I came to IIASA, I was asked to apply this approach to optimize trading between cities in the Shanxi region of China. I used a set of previously development models which aimed to distribute water and land available for each city in order to produce food (eight types of crops) and coal for energy. The intelligent linker agent optimizes trading between cities in order to satisfy demand at the lowest cost for each city.
The purpose of this exercise was to compare the solutions with those from “hard linkages” – like those in the first picture. We found that the intelligent linker is flexible enough to find the optimal solution to questions such as: How much of each of these products should each city export/import to satisfy global demand at a global lower economic and ecological cost? What actions are optimal when the total production is insufficient to meet the total demand? Under what conditions is it preferable to stop imports/exports when production is insufficient to supply the demand of each city?
The answers to these questions can be calculated by the interaction with the models of each city just by the interfacing with the intelligent linker agent, this means that no major changes in the models of each city were needed. We also found that, under the same conditions, the solutions using the intelligent linker agent were in agreement with those found when hard linking was used.
My next challenge is to build a prototype of a “distributed computer platform,” which will allow us to link models on different computers in different parts of the world—so that we in Austria could link to a model built by colleagues in Brazil, for example. I also want to link models of different sectors and regions of the globe, in order to prove that intelligent cooperation is the key to improving global welfare.
References
Xu X, Gao J, Cao G-Y, Ermoliev Y, Ermolieva T, Kryazhimskiy AV, & Rovenskaya E (2015). Modeling water-energy-food nexus for planning energy and agriculture developments: case study of coal mining industry in Shanxi province, China. IIASA Interim Report. IIASA, Laxenburg, Austria: IR-15-020
Javalera V, Morcego B, & Puig V, Negotiation and Learning in distributed MPC of Large Scale Systems, Proceedings of the 2010 American Control Conference, Baltimore, MD, 2010, pp. 3168-3173. doi: 10.1109/ACC.2010.5530986
Valeria J, Morcego B, & Puig V, Distributed MPC for Large Scale Systems using Agent-based Reinforcement Learning, In IFAC Proceedings Volumes, Volume 43, Issue 8, 2010, Pages 597-602, ISSN 1474-6670, ISBN 9783902661913, https://doi.org/10.3182/20100712-3-FR-2020.00097.
Morcego B, Javalera V, Puig V, & Vito R (2014). Distributed MPC Using Reinforcement Learning Based Negotiation: Application to Large Scale Systems. In: Maestre J., Negenborn R. (eds) Distributed Model Predictive Control Made Easy. Intelligent Systems, Control and automation: Science and Engineering, vol 69. Springer, Dordrecht
Javalera Rincón V, Distributed large scale systems: a multi-agent RL-MPC architecture, Universitat Politècnica de Catalunya. Institut d’Organització i Control de Sistemes Industrials,Doctoral thesis. 2016. http://upcommons.upc.edu/handle/2117/96332
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.
Aug 22, 2017 | Climate Change, Environment, Postdoc
By Katya Perez Guzman, IIASA CONACYT postdoctoral fellow in the Advanced Systems Analysis Program
Extractivism, a mode of economic growth currently practiced by many developing countries, is the phenomenon of extracting natural resources from the Earth to sell as raw materials on the world market. It is a central cause of many environmental problems, such as deforestation, loss of habitat and biodiversity, water, soil, and air pollution. Any study of these topics is therefore incomplete if it does not take this model of development into account.
Climate change is no exception, and it is my goal at IIASA to investigate the links between extractivism and climate change mitigation policies for Mexico. To start this search, it is relevant to ask whether the drivers of CO2 emissions might be different in countries that practice extractivism to those that do not. During my PhD, which examined the basic drivers of CO2 emissions in Mexico as a fossil fuel producer and exporter, I suggested that the answer is yes.
Even when there are as many causes of CO2 emissions as there are economic activities, CO2 emissions can be linked to four main drivers: population, GDP per person, the energy use per unit of GDP, and the CO2 emitted by each unit of energy consumed. The greater the value of these variables, and the faster their growth, the more CO2 emissions (all other things being equal). These four factors can then be incorporated into a model known as the Kaya identity, which aims to explain CO2 emissions at a global level.
Deforestation in Malaysia. © Rich Carey | Shutterstock
For fossil fuel producers and exporters, these four elements of the Kaya identity may vary in idiosyncratic patterns across various periods, for example during booms and busts. There is a possible positive relationship between oil abundance and increased population growth, namely because of increased migration to oil production sites. For GDP per capita, a phenomenon known as the natural resource curse describes how production and export of fossil fuels can harm economic growth in the long term, although this debate is still not settled. Alongside this, various analyses have linked fossil fuel production with higher energy consumption, especially during boom times.
Lastly, a proposed carbon curse relates higher abundance of fossil fuels to higher “carbon intensity”—the amount of CO2 emissions per unit of GDP. The carbon curse may be a result of four mechanisms. First, the predominance of a fossil fuel production sector which emits a lot of CO2 itself. Second, crowding out effects in the energy generation sector, forming a barrier to newer renewable energy sources. Third, crowding out effects in other sectors of the economy—a phenomenon known as the “Dutch Disease” because when the Netherlands discovered its Groningen gas field in 1959 the economic boom that followed the gas exports resulted in a decline in manufacturing and agriculture. Finally, less investment in energy efficiency technologies and more subsidies for national fossil fuel consumption can also bring on the carbon curse.
It is therefore crucial to account for the links between extractivism and climate change related topics: for mitigation, but just as importantly for vulnerability and adaptation. If the past can be used to shape the future, a measure of the carbon curse could help national and international policymakers to determine how close an oil-extractive economy can get to being a low carbon economy.
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.
You must be logged in to post a comment.