Introduction & Contribution:

The social and economic costs of climate change are significant, including damage to infrastructure, loss of agriculture, and disruptions to education. Hurricanes and storms, such as Hurricane Katrina or Myanmar’s Cyclone Nargis, are particularly visible and destructive manifestations of climate change. The incidence of these storms varies across places, suggesting that migration from more- to less-exposed areas could be an important form of climate adaptation, alongside, e.g., building more resilient infrastructure. However, our knowledge of climate migration, particularly its causes and frequency, is limited.

In “Understanding the migratory responses to hurricanes and tropical storms in the USA,” A. Patrick Behrer and Valentin Bolotnyy show — perhaps contrary to expectations — that Americans’ migratory response to storms is limited. Most storms do not result in meaningful out-migration from impacted counties. Meanwhile, when people do migrate, they do not necessarily move to areas with less storm exposure. The paper draws on a range of data sources to highlight the deeply economic drivers of migration, which stem from the concentration of economic opportunity in storm-exposed areas.

The paper highlights tensions between two commonplace assumptions: first, that “rational” migration should reduce the risks of climate change, and second, that migration is driven by economic opportunity. These assumptions are in tension precisely because, as Behrer and Bolotnyy show, hurricane risk and economic opportunity are highly correlated in America. One policy implication is that local governments must invest in storm-resilient infrastructure to prevent the destruction of physical capital and the flight of human capital. In addition, permitting more remote work could reduce the economic appeal of productive but vulnerable migration hubs.

Prior Research:

Scholars have found evidence that hurricanes and storms both do and do not affect migration, which tends to vary based on the places studied and their levels of economic development. These contradictory findings would seem to call for a deeper investigation of the causal mechanisms underlying climate migration, but our understanding is also limited here. Do individuals and families migrate as a consequence of long-term factors (e.g., frequent, medium-intensity flooding) or short-term ones (e.g., a single severe flood)? Do they migrate on the basis of rational, cost-minimizing calculations, or are they influenced by cognitive biases that lead them to overestimate the true costs of one disaster? And what role do certain amenities (e.g., reliable infrastructure) or forms of protective insurance play in decreasing the incentives to migrate?

It is difficult to sustain a purely instrumental account of migration, which is largely driven by existing social networks and occurs over short distances. For example, many survivors of Hurricane Katrina moved to Houston, which is a similarly exposed city just over 300 miles away. Even long-distance migration tends to be driven by social networks and may offer little protection against storms. Finally, migration is costly, not only in terms of moving but because housing prices in less-exposed areas are often bid up for that very reason.

Data, Methods, and Results:

Behrer and Bolotnyy’s empirical analysis is guided by several questions. First, do we observe greater outmigration after storms? Second, do migrants move to less at-risk counties? And finally, has the overall population of high-risk areas declined over the last 25 years? To answer these questions, the authors utilize migration data from the Internal Revenue Service (IRS) as well as storm exposure data from the National Oceanic and Atmospheric Administration (NOAA), the National Hurricane Center, and the Federal Emergency Management Agency (FEMA). Their regression models estimate the extent of migratory change in storm years relative to non-storm years, including lagged models that estimate changes in the years following storms.
 

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Fig. 1C-F: c,d, Coefficients from a panel fixed-effects regression of outmigration (c) and net migration (d) on whether a county experienced a storm. The first bar plots the coefficient from a regression with only contemporaneous storms. The next six bars show coefficients from a separate regression that includes contemporaneous storms and five year lags (L1–L5). The final bar shows the sum of the coefficients from the lags regression. The light grey lines show the 95% CIs. The sample size for these regressions was 52,514 for the outmigration results and 52,448 for the net migration results. e, Migrant-receiving counties in our sample period and the average number of migrants received in non-storm years. f, The same as e but in storm years.
 

Their results indicate that American outmigration has not increased at statistically significant levels after storms. In addition, there is no evidence that migrants in storm years move to less exposed areas compared to migrants in non-storm years. The most damaging storms are indeed followed by increased outmigration, but there is no evidence that migrants move to low-risk areas. In fact, they often migrate to other high-risk areas and to places with high economic activity. This is because the majority of American GDP is generated in coastal areas where storms are more prevalent. The authors thus uncover a tradeoff, namely that places in the U.S. with more opportunity face more risk. GDP is substantially more predictive of migration than storm risk. The economic and social benefits of moving to high-risk areas appear to outweigh any incentives to reduce one’s storm exposure via relocation. Finally, the authors find that overall population exposure to storms has increased.
 

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Fig. 4: GDP versus net migration and number of storms. a, Correlation between net migration and GDP. The Z-score of total net migration is the Z-score across all counties of the sum of net migration (in-migration minus outmigration) for each county across all years in the sample. The Z-score of GDP is based on county GDP in 2019, as measured by the Bureau of Economic Analysis. All points are shaded equally, with darker areas on the graph indicating a greater density of counties. We omitted three outliers with GDP Z-scores >10. We show a version of this figure that includes the outliers in Supplementary Fig. 3. b, Correlation between the number of storms and GDP. Total storms is the sum of storms hitting each county across all years in our sample. ln(2019 GDP) is the natural log of county GDP in 2019, as measured by the Bureau of Economic Analysis. All points are shaded equally, with darker areas on the graph indicating a greater density of counties. The x-axis units are log points.
 

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Fig. 3: Trend in population-weighted exposure and correlation between net migration and total storms. a, Trend in population-weighted exposure. We plotted the weighted average number of storms across all 2,387 counties in our sample. Weights are the county population in each year. The number of storms in each county is the sum over the sample and so remains constant across years. The change in the trend line is due to changes in where people live. The flat grey lines show the weighted average if populations had not changed from 1990 levels—that is, if no one had moved. The solid lines show all storms. The dashed lines show storms with at least US$10 million in damages according to FEMA. b, Correlation between net migration and total storms. The Z-score of total net migration is the Z-score across all counties of the sum of net migration (in-migration minus outmigration) in the county across all years in the sample. The Z-score of total storms is the Z-score across all counties of all storms over our sample period. All points are shaded equally; darker areas on the graph indicate a greater density of counties. The dashed line is the linear best fit line of the plotted data points.
 

The authors caution that these findings may be driven by (a) those Americans most impacted by storms being least able to move, this despite their preferences to do so, and (b) those with the means to insure themselves against climate risks having weaker preferences to move. In addition, migration within the same county — for example, moving from lower to higher sea level areas — may be a significant but hidden process that enables climate adaptation. The findings may also be less relevant to understanding migration dynamics in low- and middle-income countries, especially in places with less comprehensive insurance and less resilient infrastructure.

Behrer and Bolotnyy deepen our understanding of the importance and “stickiness” of geography. Indeed, many people do not or cannot move, even if they want to and even if staying in place puts them at risk. One wonders about how these processes interact with politics. For example, climate change has coincided with the powerful forces of climate change denial. Perhaps skepticism about storms as systemic phenomena is blunting migratory pressures, leading those affected to view them as one-off occurrences. Similarly, social scientists have coined the term “petro-masculinity” to describe an identity that views the climate change consensus as an attack on, e.g., driving large trucks or eating meat. It may be that when this identity is salient, people view climate migration as a form of weakness or betrayal.

*Brief prepared by Adam Fefer.

This essay was first published by Seoul National University's Institute for Future Strategy. You can also view the Korean version.

Technological hegemony surrounding artificial intelligence (AI) has emerged as a central facet of national economies and security. Global competition among countries and corporations to secure high-level talent has intensified into a matter of survival. Worldwide demand for AI talent now exceeds supply by more than threefold. In Silicon Valley, AI dominates the discussion, and competition among big tech firms to attract talent is escalating. Ultimately, the rivalry between the United States and China will be decided not only by capital or technology but by who succeeds in attracting and retaining global talent.

In South Korea, concerns over talent outflows from Korea are growing. Last year, Korea ranked fourth among the 38 OECD countries in terms of AI talent outflow. Compared to other advanced economies, Korea’s AI industrial ecosystem remains underdeveloped, while overseas firms offer better compensation and research environments. The recent phenomenon of 56 Seoul National University professors relocating abroad over the past four years, a “new brain drain,” must be understood in this broader structural context.

This reality is also clearly reflected in the Global Talent Competitiveness Index, published annually by INSEAD. Korea ranked 31st this year, a position disproportionately low relative to its economic standing, and fell seven places compared to two years ago. In particular, Korea performed poorly in attracting and retaining talent, ranking 55th and 37th, respectively. These findings suggest that, beyond economic incentives, social, cultural, and environmental factors play a decisive role in talent mobility.

Korea’s talent outflow is especially alarming because it coincides with record-low fertility rates and rapid population aging. Before this convergence hardens into irreversible decline, Korea must establish a Ministry of Human Resources to oversee a comprehensive national talent strategy and devise systemic measures for talent development, attraction, and utilization.
 

Talent Portfolio Theory
 

In a recent book published by Stanford University Press, The Four Talent Giants, I proposed a framework titled “talent portfolio theory.” Just as financial investment strategies adopt a portfolio approach, national talent strategies should also be portfolio-based, emphasizing diversification to minimize risk and continuous adjustment (rebalancing). In other words, just as financial portfolios are composed of cash, stocks, real estate, and bonds, talent portfolios consist of four elements—the “4B's”: brain train, brain gain, brain circulation, and brain linkage.

Moreover, just as investors design different portfolios, each country’s talent portfolio varies depending on its economic needs as well as cultural and institutional contexts. Japan, Australia, China, and India (all discussed in the book) include all four B's but have constructed distinct portfolios that contributed to their respective economic development. A portfolio approach transcends the traditional binary of “brain drain versus brain gain” and offers a more comprehensive and flexible framework for understanding national talent strategy, one that is particularly relevant for Korea.

First, “brain train” refers to developing domestic human resources through education and training. It is a fundamental element of any portfolio. In Japan’s portfolio in particular, homegrown talent accounts for a large share. Japan has favored domestically educated and trained talent over foreign or overseas-trained individuals, making them the backbone of its economic development.

By contrast, Australia places greater emphasis on “brain gain.” Brain gain involves importing foreign labor, and approximately 30 percent of Australia’s workforce is foreign-born. Until the 1970s, Australia upheld the “White Australia” policy, but a major shift toward multiculturalism subsequently elevated brain gain to a central position in its portfolio. Brain gain pathways include the study-to-work route, where international students remain for employment, and the work-to-migration route, where individuals enter on work visas and later settle. Australia has effectively utilized both pathways.

“Brain circulation” involves bringing back nationals who were educated or employed abroad, and it has been critical to China’s portfolio. Following China’s opening in the 1980s, Chinese nationals came to represent the largest share of participants in the global talent market, including international students. Approximately 80 percent of them returned to China after the 2000s. Known as haigui (sea turtles), these returnees played prominent roles in China’s science, technology, education, and economy, supported by numerous central and local government programs designed to promote talent circulation.

“Brain linkage” refers to those who do not return home after studying or working abroad but instead serve as bridges between their host countries and their homeland. By leveraging their local networks, social capital, they support their home country from abroad, making this a key component of India’s portfolio. India refers to them as a “brain bank” or “brain deposit,” exemplified by leaders of Silicon Valley big tech firms such as Google CEO Sundar Pichai.

However, all talent portfolios carry inherent risks. When adjustment is delayed or fails, risks can escalate into crises with negative effects on the broader economy. The experiences of the four countries illustrate this point.

Japan has faced two major risks. A talent strategy centered on domestic talent weakened its global competitiveness, while demographic decline reduced its labor pool. Although Japan actively attracted foreign students to increase brain gain, its exclusive social and cultural environment limited their integration into the workforce after graduation. While there are many reasons behind Japan’s “lost 30 years” since the 1990s, one factor was its failure to adjust a portfolio overly concentrated on domestic talent in a timely manner.

Australia has confronted rising anti-immigration sentiment and tensions with China. Public concern grew over excessive immigration and perceived threats to national identity, prompting the government to tighten immigration policies. Amid conflict with China, Australia diversified its foreign talent sources from China to India and Southeast Asia. The pandemic, which restricted cross-border mobility, dealt a severe blow to Australia’s talent attraction efforts.

In China’s case, despite aggressive brain circulation policies, top-tier global talent has remained hesitant to return, as relinquishing careers built abroad is not easy. China accordingly shifted its focus toward brain linkage for these elite individuals. At the same time, brain circulation and linkage strategies became a source of friction with the United States, and rising anti-immigration and anti-China sentiment in the U.S. and Europe reduced opportunities for study and employment abroad. Recently, China has adjusted its portfolio to strengthen domestic talent development.

India, despite its strong brain linkage, remains vulnerable to brain drain. However, as economic opportunities expand domestically, return migration has increased, gradually reshaping its portfolio composition.
 

What Should Korea’s Talent Portfolio Strategy Be?

What, then, about Korea? Let us examine Korea’s situation by comparing it with the four countries through the lens of talent portfolio theory.

Brain train: Human resources have been critical to Korea’s economic development, with the government playing a central role. Key examples include preferential policies for technical and commercial high schools during the 1970s under the Park Chung Hee administration to support industrialization, and efforts to internationalize universities in the 1990s as part of globalization. While less dominant than in Japan, brain train has constituted a significant share of Korea’s talent portfolio.

Brain gain: Korea has imported low- and semi-skilled labor from China and Southeast Asia to fill so-called 3D jobs, but attraction of global high-level talent has remained limited. As in Japan, social exclusivity and cultural barriers continue to impede integration.

Brain circulation: Comparable to China, brain circulation has played a vital role in Korea’s economic development. Overseas education and experience have carried strong premiums, and China explicitly benchmarked Korea and Taiwan when designing its own policies.

Brain linkage: Compared to brain circulation, brain linkage has, until recently, occupied a relatively small share of Korea’s portfolio.

Facing the AI era, low fertility, and the crisis of a new brain drain, what strategy should Korea pursue in the global competition for talent? As noted above, rather than fragmented and ad hoc measures, Korea must comprehensively review and continuously adjust its talent strategy through a portfolio approach.

Brain train: Korea must cultivate talent for future industries, particularly in science and engineering. Training should be aligned with AI-related fields to better match university output with corporate demand. The excessive concentration of top students in medical schools must be corrected. Support mechanisms to retain domestic talent should be strengthened. A recent Bank of Korea survey of 1,916 science and engineering master’s and doctoral degree holders working domestically found that 42.9 percent of science and engineering master’s and doctoral graduates are considering overseas employment within three years—an alarming signal. While brain train will remain vital, its relative share is likely to decline.

Brain gain: As demographic crises intensify and the share of brain train diminishes, the necessity and importance of brain gain will grow. In particular, Korea must actively utilize the more than 300,000 foreign students currently in the country as human and social capital. At present, universities focus merely on filling enrollment quotas, and most foreign students either leave Korea immediately after graduation or remain employed only briefly. This, too, constitutes a form of brain drain. To increase the share of brain gain in the portfolio, foreign students must be managed holistically from selection to graduation and employment. While immigration is ultimately inevitable, it must be approached cautiously and deliberately, considering its impact on the domestic labor market and anti-immigration sentiment. Australia’s successful experience offers useful lessons.

Brain circulation: Although it occupies a relatively modest share of Korea’s portfolio, a certain level should be maintained. With declining numbers of students studying abroad and reduced inclination among overseas Koreans to return, care must be taken to prevent a sharp drop in this component. Otherwise, Korea risks losing global competitiveness, as Japan’s experience warns.

Brain linkage: Alongside brain gain, brain linkage is crucial to Korea’s portfolio adjustment. Key target groups include departing domestic talent (the new brain drain), foreign students, and the diaspora. Although their likelihood of reemployment in Korea is low, their potential for exchange and collaboration with Korea remains open. Like India, Korea should foster and support brain linkage by treating them as a “brain bank” or “brain deposit.”
 

Toward the Establishment of a Ministry of Human Resources

At the national level, a control tower is needed to design an optimal talent portfolio and make timely adjustments. Korea should establish a Ministry of Human Resources by consolidating functions currently dispersed across the Ministry of Education (universities and graduate schools), the Ministry of Science and ICT (R&D), and the Ministry of Employment and Labor (foreign employment support). It is worth recalling that Singapore, ranked first globally in talent competitiveness, established its Ministry of Manpower early on. Expanded and reorganized from the Ministry of Labor in 1998, it played a pivotal role in transforming Singapore into a talent powerhouse. Through education and development investments, Singapore strengthened domestic talent competitiveness while opening its doors to multinational talent, and it also implemented policies to promote talent circulation and linkage. From the perspective of talent portfolio theory, Singapore represents a successful case of diversification and continuous adjustment. In the increasingly fierce global competition for talent in the AI era, nations and firms that fall behind cannot secure their future. Korea is no exception.

Introduction and Contribution:

Authoritarian regimes are often reluctant to let their citizens leave: 79% of autocracies restrict emigration compared to only 4% of democracies. This reluctance is understandable, as migration deprives rulers of talent, resources, and implied consent to the system. Yet autocracies do change their emigration laws. What are the consequences of these changes? 

In “A Little Lift in the Iron Curtain,” Hans Lueders examines how a 1983 emigration reform in socialist East Germany (German Democratic Republic, GDR) affected crime rates in the country. The reform permitted about 62,500 citizens to exit the GDR over a short period of time — mostly to reunite with their families in West Germany. Lueders asks how this emigration affected crime. This is a natural outcome to consider because the former GDR, like many autocracies, used the emigration system to filter out individuals seen as criminals or  “undesirables.” Unauthorized exit was criminalized, and some citizens committed crimes precisely to signal that they should be allowed to leave.
 

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Figure 1: Consequences of the 1983 Emigration Reform
Note. This figure reports the number of first-time exit visa applications per year (gray line [Eisenfeld 1995, 202]) and annual emigration from the former GDR (black line; data collected by the author). The period after the emigration reform is emphasized.
 

Lueders shows that the effects of emigration following the 1983 reform on criminal activity depended on the type of crime. Ordinary kinds of crime — those not committed for political motifs — declined after the reform. However, border-related crimes increased sharply. This is ostensibly because those “left behind” (i.e., unable to take advantage of the 1983 reforms) resumed lawbreaking in order to pressure the regime to let them out as well. An analysis of petitions submitted to the state supports the idea that emigration raised demand for emigration.

The paper makes important contributions to our knowledge of authoritarianism and migration. For one, it shows how policies enacted to temporarily satisfy domestic or international audiences can backfire, later increasing the state’s burden. Autocrats may behave strategically in the short run, yet their choices can have powerful, unanticipated consequences in the years ahead. Otherwise, “strong” and repressive autocracies like the former GDR may struggle to address migratory pressures and be too inflexible to switch course after negative consequences become apparent. 

Safety Valves and Reform in East Germany:

Social scientists have argued that emigration policy under authoritarianism can serve as a “safety valve,” allowing or forcing the exit of those who threaten the stability of the regime. In addition, requiring citizens to apply for exit visas acts as a “screening mechanism” because applying is politically costly; those who keep applying reveal themselves to be potential troublemakers whose exit ought to be permitted. Lueders provides evidence that the costs of applying for exit visas were indeed high in the former GDR: applicants (and sometimes their families) were intimidated and harassed by secret police, expelled from universities, and demoted or fired. The state also tried to “win over” prospective emigrants, showing them reports about the allegedly dismal living conditions in West Germany or letters from East German refugees begging authorities to return to the GDR.

Importantly, officials considered how emigration would influence the GDR’s stability, looking for those who opposed the country and its socialist vision. Many applicants realized this and thus sought to publicly challenge the regime, for example, by leaving socialist mass organizations or abstaining from voting. Committing crimes thus raised one’s chances of successfully emigrating. East Germans watched peers and family members break the law to force their exit, learning that the system encouraged and rewarded criminality. 

After Germany’s division into two, many East Germans preferred the economic and political freedoms found in democratic West Germany. The government thus grew concerned: most émigrés were young and educated, and their exit undermined the GDR’s claims that it was popular and that socialism was the superior politico-economic system. Accordingly, emigration was criminalized in 1952, and the GDR began erecting physical barriers, culminating in the construction of the Berlin Wall in 1961. Emigration plummeted to between 25,000 and 40,000 per year thereafter.

Emigration remained severely limited until the early 1980s, when international pressure — from both West Germany and the Soviet Union — to reform its emigration system began to build. Ultimately, in September 1983, the GDR conceded and recognized the right of all citizens with family abroad to apply for an exit visa. 

After the reform, exit visa applications and departures surged, the largest wave since the Berlin Wall’s construction. Emigration patterns evidenced a clear demographic shift: émigrés were less likely to be retired or to have formerly served in prison, while working-age East Germans made up 75% of emigrants, up from 49%. The state viewed this emigration wave as a welcome opportunity to get rid of criminals and political enemies. However, it underestimated the long-term consequences of offering some citizens a way out.
 

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Table 1: Comparison of Emigrants in 1983 and 1984 (January to June of each year)
 

Data and Findings:

To measure the effects of the 1983 policy on crime, Lueders presents crime data from 1976 to 89. He divides crime into “ordinary,” e.g., against state property or persons, and “political” crimes, e.g., the use of force against state officials, treason, and, importantly, illegal border crossings. Two of Lueders’ key hypotheses for our purposes are that emigration reform led to (1) a decline in ordinary crime, because the GDR effectively removed so-called troublemakers (the safety valve mechanism), and (2) a rise in border crimes, because those left behind were willing to break the law in order to exit (the demand mechanism).

The statistical analysis — consisting of comparing places with varying emigration rates — is consistent with both hypotheses. For the most part, ordinary crime declined after 1983. By contrast, border crime also initially declined, but this pattern dramatically reversed within two years. By 1987, border crimes began to rise significantly in places that had experienced a lot of emigration in the initial wave. Lueders thus provides evidence that in the short run, emigration indeed functioned as a safety valve (i.e., criminals were successfully identified). But thereafter, emigration had severe repercussions: rather than alleviating pressure on the regime, it created even greater demand for emigration — and thus more criminal activity.

A final piece of evidence comes from detailed data on petitions. The GDR encouraged citizens to communicate a range of demands and grievances to state officials, including the desire to emigrate. Lueders shows that in 1984, over 16,000 petitions were written specifically about emigration, which constituted nearly 28% of the total number of exit visa applications. And these petitions for exit visas increased substantially more in areas with above-average emigration during the initial emigration wave, suggesting that greater emigration in one period was associated with greater demand for it in subsequent periods. An understanding of East Germany illustrates how autocrats face a delicate balance between permitting migration and managing its consequences.

*Research-in-Brief prepared by Adam Fefer.

The "Meet Our Researchers" series showcases the incredible scholars at Stanford’s Center on Democracy, Development and the Rule of Law (CDDRL). Through engaging interviews conducted by our undergraduate research assistants, we explore the journeys, passions, and insights of CDDRL’s faculty and researchers.

How can empathy and perspective-taking be implemented on a larger scale, and how can they be used to address the challenges we see in the world today? 

Well, this isn’t something you can legislate. You can’t tell politicians to force people to imagine someone else’s life. The real audience for this work is advocacy organizations like the United Nations High Commissioner for Refugees (UNHCR) or the International Rescue Committee (IRC), because they’re already doing it. They use storytelling and humanizing narratives in their campaigns all the time. 

It’s really hard, though, because we’re living in what people call the attention economy, which is driven by social media. Everything is about visibility, clicks, and headlines, and there’s always a new crisis. It becomes difficult for people to hold on to empathy for more than a moment because the focus is constantly shifting from one story to another. Even if a big influencer were to advocate for refugees or displaced communities, another could just as easily come along and dehumanize them or spread misinformation that undermines this. So it becomes this constant tug-of-war between empathy and fear, between humanizing and othering. 

With that being said, I think social media can also be used as a really powerful tool for sharing stories and reaching people who might not otherwise engage with these issues. It gives us a space to humanize experiences and make them visible at a scale that wasn’t possible before. The challenge is figuring out how to use these platforms not just to get attention for a moment, but to actually build connection and understanding that last beyond a single news cycle.

How does this translate into policy? 

Ultimately, I do think that public opinion matters for policy. The way people feel about migration or refugees — whether they see them as part of the community or as outsiders — shapes which policies are politically possible. And today, public opinion is shaped more than ever by social media. It’s not just voters who are influenced by online narratives; policymakers and donors are too. That’s why empathy and communication are central to policymaking, as social media now plays such a major role in shaping how both the public and those in power think and respond.

Can you tell me more about your work at the Immigration Policy Lab? 

I just joined as Faculty Co-Director and am currently leading two key projects focused on migration and development, particularly in the Global South. 

One major area is climate migration, understanding how environmental shocks affect migration decisions. The people most vulnerable to climate change are often the poorest. We’re trying to understand how they perceive risk, what strategies they use to survive, and when migration becomes an option. We’re currently raising funds to collect data in places like Colombia and rural Guatemala.

Another big project focuses on return migration, looking at people who have been expelled or deported, as well as those who self-deport. We’re building partnerships with organizations like Mercy Corps and the IRC to study how they reintegrate, what challenges they face, and whether existing programs are actually helping.

What have been some of the most challenging aspects of conducting research in this field, and how did you overcome them?

I would say interest and funding. Studying migrant integration is not popular these days; it feels like everyone is obsessed with AI or how technology can solve problems. That also creates challenges with funding and resources, especially from federal sources, because projects like ours require long-term fieldwork and collaboration, which are expensive and time-intensive. 

That said, I’ve been really fortunate to find a strong community and support system here at Stanford and at CDDRL. Being part of this environment has enabled me to connect with others who care about these issues and to find the resources needed to keep the work going.
 

What gaps still need to be addressed in this research, and what do you hope to study in the future?

I think a big gap that hasn’t been studied enough is who actually engages with empathy-based initiatives in the first place. We know that when people are asked to imagine themselves in someone else’s shoes, they become more open and inclusive. But who is voluntarily clicking on those websites or reading those stories? Probably people who already care. That’s a limitation, because it means we might just be reinforcing empathy among those who already have it.

What I’d love to study next is how to reach people who don’t. People who avoid these stories or who hold more exclusionary views. What kinds of messages or media could reach them? Could framing, visuals, or certain messengers make a difference? Understanding that is crucial for figuring out how to scale empathy beyond its existing audiences.

If you had to give one piece of advice to students who want to get involved in this kind of research, what would it be?

Take my class next quarter! We talk about all sorts of issues related to migration and inclusion. But seriously, get involved early. Try to work as a research assistant, even on small projects. That’s how I got started, by working under a professor who brought me into areas and questions I didn’t think I’d be interested in. Those experiences can completely change your perspective and open doors you didn’t even know existed.

Lastly, what book would you recommend for students interested in a research career in your field?

I’ve heard very good things about The Truth About Immigration by Zeke Hernandez, which is more from an economist’s perspective, and I love Rafaela Dancygier’s Dilemmas of Inclusion, which looks at the challenges left-wing parties face in Europe. They’re the parties of inclusion, but they also have to navigate tensions when the groups they’re including hold more conservative social values. It’s a really interesting read for understanding how inclusion plays out in democratic politics.

Adida’s work highlights how understanding the human side of migration through empathy and perspective-taking can lead to more inclusive policies and stronger communities worldwide.

We are pleased to share the publication of a new volume, Cold War Refugees: Connected Histories of Displacement and Migration across Postcolonial Asia, edited by the Korea Program's Yumi Moon, associate professor in Stanford's Department of History.

The book, now available from Stanford University Press, revisits Cold War history by examining the identities, cultures, and agendas of the many refugees forced to flee their homes across East, Southeast, and South Asia due to the great power conflict between the US and the USSR. Moon's book draws on multilingual archival sources and presents these displaced peoples as historical actors in their own right, not mere subjects of government actions. Exploring the local, regional, and global contexts of displacement through five cases —Taiwan, Vietnam, Korea, Afghanistan, and Pakistan — this volume sheds new light on understudied aspects of Cold War history.

The book's chapters — written by Phi-Vân Nguyen, Dominic Meng-Hsuan Yang, Yumi Moon, Ijlal Muzaffar, Robert D. Crews, Sabauon Nasseri, and Aishwary Kumar — explore Vietnam's 1954 partition, refugees displaced from Zhejiang to Taiwan, North Korean refugees in South Korea from 1945–50, the Cold War legacy in Karachi, and Afghan refugees.

Purchase Cold War Refugees at www.sup.org and receive 20% off with the code MOON20.