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      in Environment

      The power of economics to explain and shape the world

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      Nobel Prize-winning economist Esther Duflo sympathizes with students who have no interest in her field. She was such a student herself — until an undergraduate research post gave her the chance to learn first-hand that economists address many of the major issues facing human and planetary well-being.“Most people have a wrong view of what economics is. They just see economists on television discussing what’s going to happen to the stock market,” says Duflo, the Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics. “But what people do in the field is very broad. Economists grapple with the real world and with the complexity that goes with it.”

      That’s why this year Duflo has teamed up with Professor Abhijit Banerjee to offer 14.009 (Economics and Society’s Greatest Problems), a first-year discovery subject — a class type designed to give undergraduates a low-pressure, high-impact way to explore a field. In this case, they are exploring the range of issues that economists engage with every day: the economic dimensions of climate change, international trade, racism, justice, education, poverty, health care, social preferences, and economic growth are just a few of the topics the class covers.“We think it’s pretty important that the first exposure to economics is via issues,” Duflo says. “If you first get exposed to economics via models, these models necessarily have to be very simplified, and then students get the idea that economics is a simplistic view of the world that can’t explain much.”Arguably, Duflo and Banerjee have been disproving that view throughout their careers. In 2003, the pair founded MIT’s Abdul Latif Jameel Poverty Action Lab, a leading antipoverty research network that provides scientific evidence on what methods actually work to alleviate poverty — which enables governments and nongovernmental organizations to implement truly effective programs and social policies. And, in 2019 they won the Nobel Prize in economics (together with Michael Kremer of the University of Chicago) for their innovative work applying laboratory-style randomized, controlled trials to research a wide range of topics implicated in global poverty.“Super cool”

      First-year Jean Billa, one of the students in 14.009, says, “Economics isn’t just about how money flows, but about how people react to certain events. That was an interesting discovery for me.”

      It’s also precisely the lesson Banerjee and Duflo hoped students would take away from 14.009, a class that centers on weekly in-person discussions of the professors’ recorded lectures — many of which align with chapters in Banerjee and Duflo’s book “Good Economics for Hard Times” (Public Affairs, 2019).Classes typically start with a poll in which the roughly 100 enrolled students can register their views on that week’s topic. Then, students get to discuss the issue, says senior Dina Atia, teaching assistant for the class. Noting that she finds it “super cool” that Nobelists are teaching MIT’s first-year students, Atia points out that both Duflo and Banerjee have also made themselves available to chat with students after class. “They’re definitely extending themselves,” she says.“We want the students to get excited about economics so they want to know more,” says Banerjee, the Ford Foundation International Professor of Economics, “because this is a field that can help us address some of the biggest problems society faces.” Using natural experiments to test theories

      Early in the term, for example, the topic was migration. In the lecture, Duflo points out that migration policies are often impacted by the fear that unskilled migrants will overwhelm a region, taking jobs from residents and demanding social services. Yet, migrant flows in normal years represent just 3 percent of the world population. “There is no flood. There is no vast movement of migrants,” she says.Duflo then explains that economists were able to learn a lot about migration thanks to a “natural experiment,” the Mariel boat lift. This 1980 event brought roughly 125,000 unskilled Cubans to Florida over a matter a months, enabling economists to study the impacts of a sudden wave of migration. Duflo says a look at real wages before and after the migration showed no significant impacts.“It was interesting to see that most theories about immigrants were not justified,” Billa says. “That was a real-life situation, and the results showed that even a massive wave of immigration didn’t change work in the city [Miami].”

      Question assumptions, find the facts in dataSince this is a broad survey course, there is always more to unpack. The goal, faculty say, is simply to help students understand the power of economics to explain and shape the world. “We are going so fast from topic to topic, I don’t expect them to retain all the information,” Duflo says. Instead, students are expected to gain an appreciation for a way of thinking. “Economics is about questioning everything — questioning assumptions you don’t even know are assumptions and being sophisticated about looking at data to uncover the facts.”To add impact, Duflo says she and Banerjee tie lessons to current events and dive more deeply into a few economic studies. One class, for example, focused on the unequal burden the Covid-19 pandemic has placed on different demographic groups and referenced research by Harvard University professor Marcella Alsan, who won a MacArthur Fellowship this fall for her work studying the impact of racism on health disparities.

      Duflo also revealed that at the beginning of the pandemic, she suspected that mistrust of the health-care system could prevent Black Americans from taking certain measures to protect themselves from the virus. What she discovered when she researched the topic, however, was that political considerations outweighed racial influences as a predictor of behavior. “The lesson for you is, it’s good to question your assumptions,” she told the class.“Students should ideally understand, by the end of class, why it’s important to ask questions and what they can teach us about the effectiveness of policy and economic theory,” Banerjee says. “We want people to discover the range of economics and to understand how economists look at problems.”

      Story by MIT SHASS CommunicationsEditorial and design director: Emily HiestandSenior writer: Kathryn O’Neill More

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      in Energy

      The reasons behind lithium-ion batteries’ rapid cost decline

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      Lithium-ion batteries, those marvels of lightweight power that have made possible today’s age of handheld electronics and electric vehicles, have plunged in cost since their introduction three decades ago at a rate similar to the drop in solar panel prices, as documented by a study published last March. But what brought about such an astonishing cost decline, of about 97 percent?

      Some of the researchers behind that earlier study have now analyzed what accounted for the extraordinary savings. They found that by far the biggest factor was work on research and development, particularly in chemistry and materials science. This outweighed the gains achieved through economies of scale, though that turned out to be the second-largest category of reductions.

      The new findings are being published today in the journal Energy and Environmental Science, in a paper by MIT postdoc Micah Ziegler, recent graduate student Juhyun Song PhD ’19, and Jessika Trancik, a professor in MIT’s Institute for Data, Systems and Society.

      The findings could be useful for policymakers and planners to help guide spending priorities in order to continue the pathway toward ever-lower costs for this and other crucial energy storage technologies, according to Trancik. Their work suggests that there is still considerable room for further improvement in electrochemical battery technologies, she says.

      The analysis required digging through a variety of sources, since much of the relevant information consists of closely held proprietary business data. “The data collection effort was extensive,” Ziegler says. “We looked at academic articles, industry and government reports, press releases, and specification sheets. We even looked at some legal filings that came out. We had to piece together data from many different sources to get a sense of what was happening.” He says they collected “about 15,000 qualitative and quantitative data points, across 1,000 individual records from approximately 280 references.”

      Data from the earliest times are hardest to access and can have the greatest uncertainties, Trancik says, but by comparing different data sources from the same period they have attempted to account for these uncertainties.

      Overall, she says, “we estimate that the majority of the cost decline, more than 50 percent, came from research-and-development-related activities.” That included both private sector and government-funded research and development, and “the vast majority” of that cost decline within that R&D category came from chemistry and materials research.

      That was an interesting finding, she says, because “there were so many variables that people were working on through very different kinds of efforts,” including the design of the battery cells themselves, their manufacturing systems, supply chains, and so on. “The cost improvement emerged from a diverse set of efforts and many people, and not from the work of only a few individuals.”

      The findings about the importance of investment in R&D were especially significant, Ziegler says, because much of this investment happened after lithium-ion battery technology was commercialized, a stage at which some analysts thought the research contribution would become less significant. Over roughly a 20-year period starting five years after the batteries’ introduction in the early 1990s, he says, “most of the cost reduction still came from R&D. The R&D contribution didn’t end when commercialization began. In fact, it was still the biggest contributor to cost reduction.”

      The study took advantage of an analytical approach that Trancik and her team initially developed to analyze the similarly precipitous drop in costs of silicon solar panels over the last few decades. They also applied the approach to understand the rising costs of nuclear energy. “This is really getting at the fundamental mechanisms of technological change,” she says. “And we can also develop these models looking forward in time, which allows us to uncover the levers that people could use to improve the technology in the future.”

      One advantage of the methodology Trancik and her colleagues have developed, she says, is that it helps to sort out the relative importance of different factors when many variables are changing all at once, which typically happens as a technology improves. “It’s not simply adding up the cost effects of these variables,” she says, “because many of these variables affect many different cost components. There’s this kind of intricate web of dependencies.” But the team’s methodology makes it possible to “look at how that overall cost change can be attributed to those variables, by essentially mapping out that network of dependencies,” she says.

      This can help provide guidance on public spending, private investments, and other incentives. “What are all the things that different decision makers could do?” she asks. “What decisions do they have agency over so that they could improve the technology, which is important in the case of low-carbon technologies, where we’re looking for solutions to climate change and we have limited time and limited resources? The new approach allows us to potentially be a bit more intentional about where we make those investments of time and money.”

      “This paper collects data available in a systematic way to determine changes in the cost components of lithium-ion batteries between 1990-1995 and 2010-2015,” says Laura Diaz Anadon, a professor of climate change policy at Cambridge University, who was not connected to this research. “This period was an important one in the history of the technology, and understanding the evolution of cost components lays the groundwork for future work on mechanisms and could help inform research efforts in other types of batteries.”

      The research was supported by the Alfred P. Sloan Foundation, the Environmental Defense Fund, and the MIT Technology and Policy Program. More

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      in Environment

      New “risk triage” platform pinpoints compounding threats to US infrastructure

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      Over a 36-hour period in August, Hurricane Henri delivered record rainfall in New York City, where an aging storm-sewer system was not built to handle the deluge, resulting in street flooding. Meanwhile, an ongoing drought in California continued to overburden aquifers and extend statewide water restrictions. As climate change amplifies the frequency and intensity of extreme events in the United States and around the world, and the populations and economies they threaten grow and change, there is a critical need to make infrastructure more resilient. But how can this be done in a timely, cost-effective way?

      An emerging discipline called multi-sector dynamics (MSD) offers a promising solution. MSD homes in on compounding risks and potential tipping points across interconnected natural and human systems. Tipping points occur when these systems can no longer sustain multiple, co-evolving stresses, such as extreme events, population growth, land degradation, drinkable water shortages, air pollution, aging infrastructure, and increased human demands. MSD researchers use observations and computer models to identify key precursory indicators of such tipping points, providing decision-makers with critical information that can be applied to mitigate risks and boost resilience in infrastructure and managed resources.

      At MIT, the Joint Program on the Science and Policy of Global Change has since 2018 been developing MSD expertise and modeling tools and using them to explore compounding risks and potential tipping points in selected regions of the United States. In a two-hour webinar on Sept. 15, MIT Joint Program researchers presented an overview of the program’s MSD research tool set and its applications.  

      MSD and the risk triage platform

      “Multi-sector dynamics explores interactions and interdependencies among human and natural systems, and how these systems may adapt, interact, and co-evolve in response to short-term shocks and long-term influences and stresses,” says MIT Joint Program Deputy Director C. Adam Schlosser, noting that such analysis can reveal and quantify potential risks that would likely evade detection in siloed investigations. “These systems can experience cascading effects or failures after crossing tipping points. The real question is not just where these tipping points are in each system, but how they manifest and interact across all systems.”

      To address that question, the program’s MSD researchers have developed the MIT Socio-Environmental Triage (MST) platform, now publicly available for the first time. Focused on the continental United States, the first version of the platform analyzes present-day risks related to water, land, climate, the economy, energy, demographics, health, and infrastructure, and where these compound to create risk hot spots. It’s essentially a screening-level visualization tool that allows users to examine risks, identify hot spots when combining risks, and make decisions about how to deploy more in-depth analysis to solve complex problems at regional and local levels. For example, MST can identify hot spots for combined flood and poverty risks in the lower Mississippi River basin, and thereby alert decision-makers as to where more concentrated flood-control resources are needed.

      Successive versions of the platform will incorporate projections based on the MIT Joint Program’s Integrated Global System Modeling (IGSM) framework of how different systems and stressors may co-evolve into the future and thereby change the risk landscape. This enhanced capability could help uncover cost-effective pathways for mitigating and adapting to a wide range of environmental and economic risks.  

      MSD applications

      Five webinar presentations explored how MIT Joint Program researchers are applying the program’s risk triage platform and other MSD modeling tools to identify potential tipping points and risks in five key domains: water quality, land use, economics and energy, health, and infrastructure. 

      Joint Program Principal Research Scientist Xiang Gao described her efforts to apply a high-resolution U.S. water-quality model to calculate a location-specific, water-quality index over more than 2,000 river basins in the country. By accounting for interactions among climate, agriculture, and socioeconomic systems, various water-quality measures can be obtained ranging from nitrate and phosphate levels to phytoplankton concentrations. This modeling approach advances a unique capability to identify potential water-quality risk hot spots for freshwater resources.

      Joint Program Research Scientist Angelo Gurgel discussed his MSD-based analysis of how climate change, population growth, changing diets, crop-yield improvements and other forces that drive land-use change at the global level may ultimately impact how land is used in the United States. Drawing upon national observational data and the IGSM framework, the analysis shows that while current U.S. land-use trends are projected to persist or intensify between now and 2050, there is no evidence of any concerning tipping points arising throughout this period.  

      MIT Joint Program Research Scientist Jennifer Morris presented several examples of how the risk triage platform can be used to combine existing U.S. datasets and the IGSM framework to assess energy and economic risks at the regional level. For example, by aggregating separate data streams on fossil-fuel employment and poverty, one can target selected counties for clean energy job training programs as the nation moves toward a low-carbon future. 

      “Our modeling and risk triage frameworks can provide pictures of current and projected future economic and energy landscapes,” says Morris. “They can also highlight interactions among different human, built, and natural systems, including compounding risks that occur in the same location.”  

      MIT Joint Program research affiliate Sebastian Eastham, a research scientist at the MIT Laboratory for Aviation and the Environment, described an MSD approach to the study of air pollution and public health. Linking the IGSM with an atmospheric chemistry model, Eastham ultimately aims to better understand where the greatest health risks are in the United States and how they may compound throughout this century under different policy scenarios. Using the risk triage tool to combine current risk metrics for air quality and poverty in a selected county based on current population and air-quality data, he showed how one can rapidly identify cardiovascular and other air-pollution-induced disease risk hot spots.

      Finally, MIT Joint Program research affiliate Alyssa McCluskey, a lecturer at the University of Colorado at Boulder, showed how the risk triage tool can be used to pinpoint potential risks to roadways, waterways, and power distribution lines from flooding, extreme temperatures, population growth, and other stressors. In addition, McCluskey described how transportation and energy infrastructure development and expansion can threaten critical wildlife habitats.

      Enabling comprehensive, location-specific analyses of risks and hot spots within and among multiple domains, the Joint Program’s MSD modeling tools can be used to inform policymaking and investment from the municipal to the global level.

      “MSD takes on the challenge of linking human, natural, and infrastructure systems in order to inform risk analysis and decision-making,” says Schlosser. “Through our risk triage platform and other MSD models, we plan to assess important interactions and tipping points, and to provide foresight that supports action toward a sustainable, resilient, and prosperous world.”

      This research is funded by the U.S. Department of Energy’s Office of Science as an ongoing project. More