Introduction and Motivation:

Social scientists and philosophers have shown increased interest in the concept of descriptive representation. Indeed, the identities and life experiences of those doing the representing may be critical for enacting the preferences of those being represented. This is especially the case for historically marginalized groups — upper-class, educated men may simply fail to adequately represent lower-class, uneducated, or women voters. In addition to considerations of fairness, there is growing recognition that descriptive representation can improve policy outcomes, such as service delivery or trust in government.

However, the study of descriptive representation has been hampered by data availability. Identifying simple correlations across the world’s democracies — for example, between proportions of working-class legislators and levels of social welfare provision — has hitherto been impossible.

In “The Global Legislators Database,” Nicholas Carnes, Joshua Ferrer, Miriam Golden, Esme Lillywhite, Noam Lupu, and Eugenia Nazrullaeva introduce the largest dataset of biographic and demographic information on national legislators ever assembled. GLD will enable scholars to assess just how much voters elect those with life experiences resembling their own. The authors compile information on five descriptive variables across 97 democracies: legislators’ party affiliation, gender, age, highest level of education, and previous occupation (to assess their social class). By contrast, prior datasets have focused only on heads of state or cabinet members, or on only a selection of more developed democracies.

Some questions around descriptive representation would seem to have intuitive answers: Wouldn’t developed countries have more women representatives, or wouldn’t women legislators feature less prominently in right-wing parties? Scholars can now hope to do more than merely gesture at answers.

Characteristics, Validity Checks, and Applications:

GLD comprises countries that (a) have a population of over 300,000 and (b) meet the standard for what Freedom House calls “Electoral Democracy” — having some minimum of political rights and civil liberties. Excluding six cases of data availability constraints, this yields 97 countries, including India, the United States, Brazil, Mexico, Nigeria, and the Philippines. Scholars of Pakistan, Bangladesh, or Turkey — who would likely characterize these countries as authoritarian during the 2015-17 time period — will be pleased that the authors chose a more forgiving measure of democracy.

Biographic data is drawn from the national legislature in unicameral countries and the lower chamber in bicameral countries. (By contrast, upper chambers are sometimes indirectly appointed or hereditary, which sheds less light on whether voters choose descriptively similar representatives.) This yields over 19,000 individuals who held office during at least one legislative session in 2015, 2016, and 2017. GLD has remarkably complete data for the five variables mentioned above: age and education data are presented for over 90% of legislators in the dataset, for over 93% as regards occupation, and nearly 100% for gender.

In order to assess GLD’s validity, the authors compare select variables to those in comparable datasets. For example, the gender variable is compared with gender data from the Varieties of Democracy (V-Dem) project, which shows that the two measures are nearly identical. So too is the age data nearly identical to an index from 15 affluent democracies.
 

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Figure 1. Shares of women legislators in the GLD and V-Dem. Note: Bahamas, Belize, Fiji, and Kosovo are omitted because of missing data in the V-Dem.
 

For categories like education and prior occupation — where comparable data are unavailable — the authors conduct “face validity” tests: these draw on our intuitions that legislators are, for example, mostly educated and not working class. And indeed, these intuitions are borne out in the distributions of GLD data. In terms of total coverage, GLD includes information on more legislators than the comparable Global Leadership Project database for all but two countries, and in many cases, the differences are large.
 

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Figure 3. Distributions of legislator traits in the GLD. Note: Age is calculated at the time of election. Higher education includes levels beyond primary and secondary education (Bachelors, Masters, PhD, LLB, LLM, JD, MD, and short-cycle tertiary). Data on educational attainments for legislators is unavailable for Côte d’Ivoire.
 

The authors then use GLD in application to a number of questions for which scholars have lacked global data. First, some have hypothesized that in legislatures with more (a) uneducated, (b) female, and (c) working-class representatives, incumbency rates will be lower. This is because individuals from these three groups might have a harder time overcoming challenges relating to expertise, sexism, and fundraising, respectively. Correlating GLD data with a global reelection database, the authors find only evidence for (b), suggesting that women may face higher barriers to remaining in office. These are only correlations, but they point to fruitful areas for exploration: why might women face unique barriers, and what distinguishes countries with lower versus higher barriers?
 

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Figure 5. Re-election rates by years of education, gender, and occupational background. Note: The share of working-class legislators is zero for six countries that are dropped from the figure: Albania, Botswana, Cyprus, Estonia, Guatemala, and Mongolia.
 

A second application involves public financing of elections, which is thought to favor more working-class legislators who would have a harder time fundraising. Correlating V-Dem data on public financing with the GLD variable on prior occupation, however, the authors find limited evidence for this conjecture. Finally, some have proposed that countries with a stronger rule of law would favor a higher proportion of lawyers in the national legislature. Looking again at GLD prior occupation data alongside V-Dem rule of law data, the authors find limited evidence for this hypothesis.

These varied applications point to how the Global Legislators Database can serve as a valuable resource for scholars interested in the causes and consequences of descriptive representation. Although the GLD covers only a single point in time, it can serve as a bedrock for additional data-collection efforts. In addition to expanding its temporal coverage, scholars may also wish to gather data on upper chambers. Especially in ethnically diverse countries like Bosnia and Herzegovina, upper chambers are intended to mirror the descriptive composition of specific regions. However, it may be the case that ethnic representatives are still vastly more wealthy or educated than their constituents, thus impeding their ability to represent.

*Brief prepared by Adam Fefer.

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.

Overview and Contributions:

In “Profitable Misconduct, Corporate Governance, and Law Enforcement,” Anat R. Admati, Nathan Atkinson, and Paul Pfleiderer show how misconduct, managerial compensation, and enforcement policy are closely — and at times perniciously — related. Corporate misconduct can cause extensive harm, including death, physical and mental injury, and environmental destruction. Profit-maximizing corporations can also harm democracy and the rule of law by impacting both the language and the enforcement of the law. This paper focuses on a situation in which, as is often the case, law enforcement efforts to address corporate misconduct are ineffective. There are many reasons for this situation, including difficulties in monitoring opaque corporations and detecting misconduct, as well as the many ways corporations can limit their liabilities.

The authors show that when managerial compensation aims to motivate maximizing profits for shareholders, managers will generally engage in profitable misconduct and, importantly, that corporations can reduce or nullify the deterrence effects of fines and penalties that target either the corporation or managers directly might have, thus further weakening already insufficient enforcement. They also show that common enforcement policies, such as those that offer discounted fines when corporations self-report misconduct or implement compliance programs, can backfire and exacerbate harm by making misconduct more profitable. Understanding corporations' strategic responses to law enforcement is essential for designing more effective policies to deter misconduct.
 

Corporate Governance, Misconduct, and Law:

The authors begin by discussing why the policing of corporate misconduct is so difficult. One problem arises because corporations are collections of individuals, which renders responsibility diffuse and complicates the identification of perpetrators. Detecting misconduct often depends on highly visible, chance events such as plane crashes, whistle-blowing, or media investigations. When the profits gained from misconduct exceed the expected fines and other financial consequences, executives may view misconduct as a “cost of doing business.” Other problems are due to the difficulties encountered in estimating the extent of the harm and the limitations on the penalties that can be imposed. Even when misconduct is detected, fines often fall short of the corporation’s private gains from that misconduct. In notable cases, corporations can limit the consequences by declaring bankruptcy. It is also very rare for directors and executives to face meaningful criminal liability.

Governments have often been unsuccessful in prosecuting misconduct because of the high legal bar required to show personal intent to commit crimes and the reticence of prosecutors to pursue challenging cases due to career concerns and limited resources, especially relative to the resources corporations can access. As we saw in the financial crisis, authorities often worry about targeting “important” corporations and imposing significant fines and sanctions.
 

Argument and Implications:

The authors’ mathematical model captures some of the complexities involved in the interactions among corporations, managers, and governments. One of the values of a model is that it can show how well-intentioned and seemingly reasonable policies can be counterproductive once one accounts for various ways profit-maximizing actors will respond. The authors consider, for example, some policies that have been designed to increase the probability that misconduct will be detected in a timely way. These policies encourage corporations to implement “compliance” programs or to self-report misconduct by promising that any fines they must pay will be heavily discounted. Using their model to analyze the effectiveness of this approach, the authors find that these policies can make matters much worse. This is because the discounted fines can increase the profitability of misconduct while it is undetected or not self-reported. This can lead to firms engaging more aggressively in misconduct, knowing that this can be self-reported later, and the corporation will be subject to reduced fines. If corporations strategically take all this into account, the total harm may actually increase. The authors are not contending that these policies will always increase harm, but they are pointing out that these policies are quite likely to be inferior to others that don’t allow strategic responses that can make things worse.

One reason that the fines imposed directly on corporations are often inadequate to deter misconduct is that authorities are reluctant to levy sufficiently large fines because they fear this will lead to “collateral damage” suffered by innocent stakeholders like employees and customers. These concerns are allayed if, instead of corporate-level fines, large fines are imposed on managers. The authors’ model shows that it can be very expensive for shareholders to offset the potential deterrence effects of managerial fines if the only way shareholders can do this is by increasing the manager’s stock-based compensation to make misconduct more rewarding relative to the level of fines. Because it is so expensive for the corporation and shareholders to respond in this way, relying more on managerial fines might be a good policy. Unfortunately, shareholders have much less expensive ways to offset fines on managers — they can indemnify the manager or provide insurance that pays for fines. Essentially, they can simply offset the fines with cash, which is much cheaper. As the authors point out, this suggests that, to strengthen enforcement and deterrence, limitations on corporations' ability to indemnify and insure managers are likely a good way forward.
 

One of the main lessons of the authors’ analysis is that internal governance practices set by the corporation and its shareholders can profoundly influence the effectiveness of external governance designed to limit the harm created when corporations and their managers engage in profitable misconduct. Further study of these interactions and their implications for effective enforcement policies is clearly warranted.

*Research-in-Brief prepared by Adam Fefer.

Overview & Contribution:

Salvadoran President Nayib Bukele calls himself the “world’s coolest dictator,” which may be an apt title given his social media savviness, backwards baseball caps, and concerted efforts to undermine democracy. While Bukele has enjoyed widespread popularity for his success in crushing El Salvador’s gangs, this has come at a high cost. Thousands of innocent Salvadorans have been imprisoned without due process as Salvadoran streets become ever more militarized. The “Bukele model” has been emulated by a number of Latin American leaders with authoritarian ambitions, which will likely complicate international efforts to isolate the Salvadoran government. Can Bukele continue to consolidate his personal power and popular support? 

In “Does the Bukele Model Have a Future?” Beatriz Magaloni and Alberto Díaz-Cayeros argue that the Salvadoran state’s apparent strength sits atop an extremely fragile foundation: Bukele’s crime policy has successfully improved physical security for some while failing to deliver social and economic gains for El Salvador’s increasingly vulnerable citizenry. As the country’s economic situation worsens, Bukele’s support will decline, likely increasing his reliance on repression. The article is informed by original interview data, which illustrates how dire the situation for ordinary Salvadorans has become both inside and outside of the country’s notorious prisons. 

The reader comes away somewhat optimistic that Bukele’s authoritarianism cannot remain popular indefinitely. And although El Salvador has largely evaded international pressure, this could change, for example, after the United States’ 2028 elections. At the same time, domestic efforts to push back against Bukele and his anti-democratic legacy will surely be difficult. The authors predict that Bukele will alternate between moments of popularity, episodes of repression, and external challenges.

The Bukele Model and Its Pitfalls:

Bukele is perhaps best known for his war on crime, which followed his unsuccessful attempts to negotiate with and make concessions to gang leaders. Although Bukele took office at a time when homicide rates had declined considerably, crime has sharply declined during his tenure. Yet El Salvador now enjoys the world’s highest incarceration rate by more than double the next highest country. Bukele has consolidated significant executive power, firing Supreme Court justices and pressuring his opponents via armed military and police incursions into the legislature.

The authors conducted interviews with formerly incarcerated Salvadoreans to better understand how the Bukele model has been experienced both inside and outside of prison. Interviewees report that ordinary people are incentivized to provide information (whether true or false) that leads to arrests because of the cash rewards offered. As the country’s economy worsens, these practices have led to a mushrooming of innocent arrests. Although international observers have tended to focus on human rights abuses in El Salvador’s CECOT prison, the conditions in more peripheral prisons are even more harrowing. As the authors report,

Upon entry, detainees are frequently subjected to a violent initiation ritual involving beatings by multiple prison guards…leav[ing] many prisoners with severe physical injuries…once confined…basic human needs such as rest, sanitation, breathable air, food, and water were denied. Some people…reported guards throwing tear gas into their cells and banging repeatedly on cell bars throughout the night…[they] described cells as so overcrowded that they were often forced to sleep in rotations: one half lying on the floors, with their neighbors’ feet pressed against their faces, while the remainder stood waiting for their turn.

A worrying consequence of Bukele’s rise is the diffusion and emulation of his “model” across the hemisphere. For example, Honduras and Ecuador have implemented states of emergency and deployed the military against domestic gangs, citing Bukele as inspiration. Javier Milei’s cabinet has used Bukele’s alleged success as a justification for undermining judicial autonomy in Argentina. Even Costa Rica — one of Latin America’s most stable democracies — built a CECOT-inspired prison and has witnessed growing support for strongman rule as it faces its highest homicide rates on record.

Possible Scenarios:

The authors identify three routes that might characterize El Salvador’s politics in the coming years, none of which are mutually exclusive. A first scenario would involve support for Bukele continuing or increasing. However, given El Salvador’s economic situation, this situation is very unlikely. In places like Singapore and Kuwait, autocrats have enjoyed steady popularity because they have been able to deliver economic prosperity. Yet Bukele lacks foreign investment and world-class infrastructure, as in Singapore, and it lacks the Gulf oil monies that have been showered on Kuwaiti citizens to buy their acquiescence.

A second scenario, which the authors see as more likely, is that Bukele’s popularity declines, leading him to default to more repression and authoritarianism. This parallels Venezuela under Nicholas Maduro, where the collapse of oil prices — which had previously boosted Hugo Chávez’s popularity — coincided with growing corruption and economic precarity. As the country experienced hyperinflation, Maduro clamped down on his opponents and the media while rigging elections.

A third scenario would involve international pressure from democratic countries, such as the US and Brazil. This could at least strengthen Salvadoran opposition forces, but would not likely restore the country’s democracy to pre-Bukele levels. For the time being, much of the international community has minimized or ignored Bukele’s transgressions. For example, Bukele maintains a strong relationship with Donald Trump, and a recent U.S. State Department report downplayed Bukele’s human rights violations. Magaloni and Díaz-Cayeros show how El Salvador exemplifies the tension between genuine public approval — driven by unprecedented reductions in gang violence — and mounting authoritarianism that inspires other Latin American leaders.

*Research-in-Brief prepared by Adam Fefer.

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.

Motivation & Overview:

Black Americans have long and overwhelmingly supported the Democratic Party, though Donald Trump modestly increased his share of the Black vote in 2024 (15%, up from 8% in 2020). Given this enduring partisan loyalty — and the fact that Democrats generally take more liberal policy positions than Republicans — we might expect a strong overlap between Black Americans’ partisanship and their ideological self-identification. Yet, according to national surveys, up to 50 percent of Black Americans describe themselves as conservative, a pattern many social scientists have treated as paradoxical. 

In “The curious case of Black ‘conservatives’,” Hakeem Jefferson shows that the terms ‘liberal’ and ‘conservative’ are unfamiliar to many Black Americans. Constructing a “Liberal-Conservative Familiarity Scale,” Jefferson finds that Black Americans who are familiar with these ideological labels overwhelmingly identify as liberal Democrats. As such, the canonical liberal-conservative measure — used not only in the American National Election Studies (ANES) but also throughout the social sciences — may be ill-suited to understanding Black political behavior. Jefferson calls on researchers to describe ideological concepts more carefully to respondents and to develop new measures that better capture Black Americans’ political worldviews. 

Prior Research & Jefferson’s Intervention:

Political scientists and other researchers and practitioners have long accepted that the “mismatch” between Black voting behavior (or partisanship) and ideology is real. Some explain this by pointing to the strength of Black racial identity or consciousness: Black conservatives, they argue, are indeed conservative but support Democrats because of a shared commitment to racial progress. Others suggest that Black conservatives who might otherwise support Republicans refrain from doing so because of social costs within their communities. And indeed, experimental research has shown that Black participants are less likely to donate to Republican campaigns if they believe that members of their community will learn of such contributions. Still others emphasize that many Black Americans hold conservative views on social or moral issues, such that their identification as conservative on surveys may reflect those views, which do not necessarily inform their Democratic partisanship and thus help explain the partisanship-ideology mismatch. 

Jefferson acknowledges that there are indeed Black conservatives and that Black Americans who wish to ‘defect’ to the Republican Party may fear the social consequences of doing so. However, he argues that these explanations fall short of accounting for the long-standing mismatch between partisanship and ideology among Black Americans, and that the prevalence of Black conservative Democrats has been dramatically overstated. His argument begins with a striking observation: in 2012, 30 percent rated Barack Obama as conservative and 9 percent said they did not know where to place him ideologically. Conversely, 29 percent rated Mitt Romney as liberal, while 12 percent said they did not know. These patterns suggest that many Black respondents may have less familiarity with ideological concepts than is often assumed. Political scientists, dating back to the 1960s, have cautioned that few Americans, across racial groups, think about politics in abstract ideological terms. That the liberal-conservative measure remains so central to research on public opinion suggests that these early warnings have largely gone unheeded. 

Data & Methods:

Jefferson begins by examining the relationship between partisanship and ideological self-identification over time and across racial groups. From 1972 to 2016, the average correlation between these two measures was .44 for White Americans, compared to just .12 for Black Americans. In 2016, the correlations were .73 and .001, respectively! In other words, among Black Americans, partisanship and ideology were almost wholly unrelated.. 

As shown below, the correlation between partisanship and ideology among White Americans has increased sharply over the past five decades, reflecting the broader ideological sorting of the major parties since the 1960s. By contrast, among Black Americans, the relationship has remained weak and, if anything, has slightly declined over time.
 

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Figure 1. Correlation between ideology and partisanship over time, by race, ANES 1972–2016. Figure 1 displays the correlation coefficient (r) between ideology and partisanship in the ANES over time. The red open dots indicate the r for Black Americans. The black closed dots indicate that for whites. LOESS lines are overlaid in black for white Americans and dashed red for Black Americans.
 

In addition, Jefferson notes that in 2012, 41 percent of Black respondents who were asked to identify their political ideology answered “don’t know,” while 18 percent placed themselves at the midpoint. In total, roughly 60 percent of Black respondents declined to take a clear ideological position. By contrast, only 19 percent of White respondents said “don’t know,” and 24 percent identified as moderate.

To further explore these patterns, Jefferson constructs a five-item Liberal-Conservative (L-C) Familiarity Scale based on whether respondents correctly identified Democrats and Democratic presidential nominees as liberal, Republicans and Republican nominees as conservative, and the Republican Party as the more conservative political party. Respondents who answered all items correctly, demonstrating perfect ideological familiarity. Jefferson finds that the scale exhibits high internal consistency.

The L-C Familiarity Scale serves as Jefferson’s key independent variable, which he theorizes influences how strongly people’s ideological self-placement aligns with their partisan identification. Consistent with this expectation, Black respondents with greater ideological familiarity are more likely to exhibit coherent alignments between ideology and partisanship. As the figure below shows, among Black respondents, higher liberal-conservative familiarity is associated with a lower likelihood of identifying as conservative. In other words, Black respondents who more accurately recognize which parties and candidates are liberal or conservative tend to place themselves further to the left on the ideological scale, where we would expect them to be, given their longstanding support for the Democratic Party. Conversely, Black respondents who identify as conservative and who have a clearer grasp of ideological terms are more likely to identify as Republicans, suggesting that ideological familiarity helps resolve the apparent paradox that has long puzzled political scientists and other researchers.
 

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Figure 3. Liberal-conservative familiarity scores predict ideological identification for Black Americans (top plot), but not white Americans (bottom plot). X-axis presents liberal-conservative familiarity score and the corresponding 95th percent confidence interval. Y-axis indicates the model for predicting ideology (conservative), faceted by race. Model 1 includes controls for age, income, education, gender, economic policy attitudes, social policy attitudes, religiosity, and moral traditionalism. Model 2 includes all of model 1’s variables and feeling thermometers toward Black Americans, white Americans, big business, unions, Hispanics, middle class, and gays and lesbians. Model 3 includes all of model 2’s variables and four averaged questions for office recognition. Model 4 includes all of model 2’s variables and three averaged questions for office recognition. Model 1 includes years 1992, 1994, 1996, 2004, 2008, 2012, and 2016; Model 2 includes 2004, 2008, 2012, and 2016; Model 3 includes 2012; Model 4 includes 2004, 2008, 2012, and 2016. Models 1, 2, and 4 include year-fixed effects. Standard errors are robust SE (HC1) and clustered by year when applicable.
 

White respondents demonstrate much greater familiarity with ideological concepts, yet this familiarity does not predict their ideological self-identification, as it does for Black respondents. Instead, White ideological self-placement is more closely tied to public policy and symbolic issues, such as government involvement in the economy or attitudes toward demographic change.

These results hold even after Jefferson controls for social conservatism (e.g., religiosity), which some have argued helps explain the partisanship-ideology mismatch among Black Americans. They also persist when he controls for the interviewer’s race, addressing the alternative explanation that Black respondents may understate their Republican partisanship to avoid social sanction within their communities.

Findings & Mechanisms:

Jefferson concludes by offering several possibilities for why Black Americans exhibit lower levels of liberal-conservative familiarity. One possibility is that Black and White Americans inhabit different “racialized informational environments.” Political discourse in Black communities may focus more on concrete issues such as racial inequality and systemic injustice, while discourse in White communities may more often invoke ideological labels like “liberal” and “conservative.” Another explanation builds on the idea that the Democratic Party — with which most Black Americans identify — is itself less oriented around ideology and more around social groups and issue bundles, whereas the Republican Party is more explicitly ideological. This may lead to less exposure to ideological terms among Black Americans.

*Research-in-Brief prepared by Adam Fefer.

Motivation & Overview:

The effects of the climate crisis are thought to be extremely far-reaching, from declining economic growth and agricultural productivity to housing displacement and job loss. An important set of consequences are psychological, relating to how climate change can exacerbate anxiety and one’s sense of hopelessness about an uninhabitable future. These psychological impacts are heightened for members of vulnerable and marginalized groups, as well as for those in poor and underdeveloped places that struggle to address climate change.

In “Adolescent psychological health, temporal discounting, and climate distress under increased flood exposure in Bangladesh,” Liza Goldberg and her coauthors examine the psychological well-being of 15 to 18-year-olds in two Bangladeshi cities that have been differentially affected by floods. The authors conduct surveys and focus groups with adolescents in the low-flood-risk capital city of Dhaka and the high-flood-risk city of Barisal. They find that although adolescents in both cities fear the personal impacts of climate change, rates of anxiety and depression are significantly higher in Barisal. In addition, those with anxiety and depression exhibit greater temporal discounting, meaning that short-term consequences are favored over longer-term ones. Discounting is an important — if neglected — consequence because adolescents will emerge as household decision-makers who must plan to adapt to climate change. The article is notable in increasing our knowledge of how floods harm members of an already vulnerable population.

Case Selection and Hypotheses:

Bangladesh is among the world’s most climate-vulnerable countries. This is due to its “deltaic” geography (i.e., its low, flat land, crossed by many rivers) and consequent flood exposure, extreme temperature and humidity, and poor air quality. Barisal — a city of over 500,000 that is roughly 115 kilometers from Dhaka — is highly vulnerable to flooding, as well as being poorer (relative to Dhaka) and limited in its “climate adaptation infrastructure.” Partly for these reasons, rates of migration from Barisal to Dhaka are the highest in Bangladesh. By contrast, Dhaka — the capital city of over 24 million — is less flood-exposed and is slightly wealthier. Respondents in Barisal and Dhaka reported around four floods and one flood per year, respectively.
 

Figure. Study site locations in Bangladesh. Study sites at Dhaka (A) and Barisal (B) are shown in red.
 

The authors hypothesize that Barisal’s greater flood exposure would be associated with more anxiety and depression among its adolescents, and that anxiety and depression would be associated with greater temporal discounting. (In other words, they do not expect that flood exposure would be directly associated with discounting.) In addition, the authors expect that these negative psychological effects would be especially pronounced among poor Bangladeshis, girls, and those with a greater awareness of the climate crisis.

Data and Findings:

The authors surveyed 1200 Bangladeshi adolescents in 24 schools immediately after the flood season, which usually runs from May to September. In addition, 16 focus groups were conducted with around 160 total participants. Adolescents in both cities expressed a high familiarity with climate change. However, and consistent with the authors’ expectations, those in Barisal expressed significantly higher levels of agreement with statements about climate distress. For example 97% of those in Barisal compared to just 68% in Dhaka agreed that “My family’s security will be threatened,” 93% in Barisal and 58% in Dhaka agreed that “The things I most value will be destroyed,” and 98% in Barisal and 67% in Dhaka agreed that “My feelings about climate change negatively affect my daily life.” 
 

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Table 3. Climate distress survey results disaggregated by region.
 

The focus groups corroborated this unequal sense of despair, especially concerning the future and one’s educational and career goals. In Barisal, a boy said, “We expect that we will have to continue withstanding this [flooding] for many years to come,” while a girl said, “I used to want to become a teacher myself, but now I believe I will need to get married immediately after school because my father keeps losing his job during the floods.” By contrast, and because flooding in Dhaka is so infrequent, adolescents did not expect climate change to meaningfully threaten their life trajectories.

In terms of anxiety and depression, 86% of those in Barisal reported anxiety symptoms, compared to 71% in Dhaka, while 98% in Barisal and 88% in Dhaka reported depressive symptoms. After adjusting for factors like sex, wealth, and climate change awareness, the odds of being anxious and depressed in Barisal were nearly twice as high and more than 3.5 times as high, respectively. Across both cities, females were more than 1.75 times as likely to experience anxiety. And the odds of being depressed were over 1.85 times as high for those with a greater awareness of climate change.

Girls in the Barisal focus groups revealed that flooding was linked to domestic violence. Fathers facing financial insecurity were reported to engage in violence against their mothers as a consequence of this stress. As one girl put it, “The floods keep getting worse and worse. So, I may experience even more violence than my mother does.” By contrast, few girls in Dhaka expressed worsening family dynamics, and none reported domestic violence owing to flooding. Adolescents in Dhaka believed that floods in their region were simply too fleeting to result in such abuse.

Finally, only 7% and 6% of adolescents in Barisal and Dhaka showed signs of temporal discounting. However, the odds of discounting were twice as high for those with anxiety and almost 2.5 times as high for those with depression. The authors find some evidence of discounting in the focus groups, but no meaningful differences across cities. This absence may be due to discounting behaviors emerging around adulthood, which is older than the adolescent study population. Taken together, the authors’ findings imply that mental health support will be essential for those affected by climate change — especially in impoverished areas — to help them manage stress and to improve their ability to plan for the future.

*Research-in-Brief prepared by Adam Fefer.

Motivation

Political parties have long reflected  dividing lines between groups in a society, often called political ‘cleavages’. Examples include workers vs. business owners, Protestants vs. Catholics, and urban vs. rural constituents. Civil society organizations (CSOs) — such as unions, churches, and chambers of commerce — have historically shaped the content and strength of these cleavages.

However, both CSOs and cleavages have changed in recent decades. For one, traditional cleavages have declined in importance, and new divides have emerged, such as between the so-called winners and losers of globalization or between those on one side or the other of the culture wars. In addition, formal CSOs have seen declining membership and reduced political influence, while informal groups and more episodic activism have grown. While CSOs and political parties used to have highly formalized relationships, they now tend to engage with each other more opportunistically and sometimes antagonistically. It seems clear that CSOs continue to influence political cleavages — both old and new — in the 21st century. But how exactly does this occur?

Contribution

In “Cleavage Theory Meets Civil Society,” Alex Mierke-Zatwarnicki, Endre Borbáth, and Swen Hutter examine the varied historical and contemporary relationships between CSOs, cleavages, and political parties in Western Europe. The authors develop a general framework for understanding the relationship between CSOs and cleavage development, providing insights into how contemporary politics reflects long-term changes in the structure of civil society. 

The paper is set against social science research on cleavages, which can be divided into two broad streams. First, classical scholarship emphasized the importance of early 20th-century mass associations, such as unions, in shaping cleavages and party politics. By contrast, newer work, written against the backdrop of a changing CSO landscape, has viewed CSOs as largely irrelevant, arguing that opposition parties shape cleavages via direct interactions with voters. Neither body of previous work provides a compelling framework for understanding how contemporary CSOs — given their fragmentation, informationalization, and politicization -- matter for cleavages.

The authors also shed light on the phenomenon of polarization, which is a key part of democratic backsliding. Indeed, electorates are polarized around several cleavages — economic, religious, and cultural — that populist leaders have used to justify excluding their opponents from politics, portraying them as existential threats to a specific way of life.

Processes and Mechanisms

The authors suggest that cleavage development can be seen as the culmination of three processes, which CSOs may influence in key ways. The first is “group formation,” which concerns how individuals come to identify as workers, congregants, or otherwise. The second process is “political institutionalization,” which entails cleavages being embodied in party competition. The third is “political stabilization,” whereby cleavages are reinforced over time by parties.
 

Table 1. Role of civil society across stages of cleavage development.
 

To understand how CSOs might shape these three processes, the authors outline two mechanisms. The first is “linkage,” whereby CSOs communicate group demands and pressure political parties to represent them. Linkage is hypothesized to be more important during the latter processes of institutionalization and stabilization; it was historically important in group formation but less so today because of the aforementioned decline of formal CSOs.

The second mechanism is “social closure,” which concerns how group boundaries are solidified. CSOs are hypothesized to contribute to social closure by bringing group members together and organizing them around shared demands, increasing their sense of ingroup identification. This mechanism is important for group formation as well as  political stabilization.

CSOs still appear to facilitate linkage and social closure, albeit in different ways than in the early 20th century. For example, CSOs are less likely to have formal links to parties but continue to exert pressure by organizing around individual issues, candidates, and elections. Voters’ relationships to CSOs are also more varied, creating divisions within the electorate between highly-active individuals who have a strong sense of group identity and people who are less ‘anchored’ to the cleavage. The authors also hypothesize that some of these dynamics may produce asymmetric changes across the left and right, as the strength and tactics of CSOs vary.
 

Table 2. Implications of the changing structure of civil society.
 

Cross-National and Case Study Evidence

The authors then analyze cross-national data on political parties and voters in Austria, France, Germany, the Netherlands, and Switzerland. One data source concerns the extent to which political parties are tied to CSOs and whether they receive large-scale CSO donations. A second source looks at whether party supporters are active in CSOs. Preliminary findings point to important differences between old, class-based parties (especially Social Democrats) and newer parties, with the latter much less tied to CSOs. However, within the new party families, Green parties are more tightly linked to CSOs than far-right parties, but there also exists variation within far-right parties. These patterns demand a more fine-grained analysis of specific cases.
 

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Figure 2. Members of civil society organizations among the electorate of political parties in Austria, France, Germany, the Netherlands, and Switzerland.

Note: The figure is based on the Joint EVS/WVS 2017-2022 Dataset (2022). It uses the battery of membership in organizations and partisanship questions. In the WVS, partisanship is measured with ‘Which party would you vote for?’; in the EVS, with ‘Which political party appeals to you most?’ For this figure, the two items are treated as functional equivalents. The percentage of members is calculated from all respondents indicating sympathy towards the respective party.
 

Finally, the authors qualitatively analyze three distinct cases: one New Left party and both old and new far-right populist parties — the German Green Party, the Swiss People’s Party (SVP), and the Alternative for Germany (AfD). Their analysis reveals key differences as regards the importance of CSOs in fostering linkage and social closure. CSOs played a key role in consolidating the Greens and SVP, whereas in the case of AfD, antipathy from German CSOs helped generate a more outsider identity.

The Greens emerged via linkages with left-libertarian social movements in the 1970s and 80s. This included groups supportive of environmental protection and feminism and opposed to nuclear proliferation. CSOs provided ideas and personnel, which helped build a sense of social closure among party supporters. This identity still persists in spite of the subsequent fragmentation of civil society.

By contrast, SVP emerged through connections to Swiss farmers' associations, rural economic networks, and local interest groups. SVP has been radicalizing since the 1990s, becoming one of Europe’s most successful far-right parties and aligning itself with Euroscepticism. SVP’s long history of rural and community penetration has helped strengthen social closure among its electorate.

Finally, AfD emerged in a more fragmented context, via its ties to right-wing protest networks. The party was a top-down vehicle that organized in response to what it saw as Germany’s mismanagement of the Eurozone crisis. AfD lacks dense connections to CSOs and has instead built informal and often volatile alliances with protesters. Many German CSOs — as well as German society more generally — explicitly oppose AfD, which has ironically helped AfD build an outsider identity because its supporters feel isolated and stigmatized.

The case studies vividly illustrate how varied CSO relationships shape cleavages and partisanship in three of the most important Western European parties.

*Research-in-Brief prepared by Adam Fefer.

Motivation & Overview

India’s services sector is internationally renowned and has helped propel the country’s economic growth. Indeed, in recent years, a majority of the value added to India’s GDP has been concentrated in services. Especially noteworthy are India’s software and computing services, which include large multinational conglomerates like Infosys and Tata Communications Services. 

Yet as Indian software has flourished, the growth of its computer hardware and manufacturing has been sluggish. Tellingly, India is still a net importer of hardware and other electronics. At first glance, this divergence is puzzling because both the software and hardware sectors should have benefited from India’s educated labor pool and infrastructure. How can these different sectoral outcomes be explained?
 

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Fig. 1: Electronics production value compared to software and software service revenues.
 

In “Comparing Advantages in India’s Computer Hardware and Software Sectors,” Dinsha Mistree and Rehana Mohammed offer an explanation in terms of state capacity to meet the different functional needs of each sector. Their account of India’s computing history emphasizes the inability of various state ministries and agencies to agree on policies that would benefit the hardware sector, such as tariffs. Meanwhile, cumbersome rulemaking procedures inherited from British colonialism impeded the state’s flexibility. Although this disadvantaged India’s hardware sector, its software sector needed comparatively less from the state, building instead on international networks and the efforts of individual agencies.

The authors provide a historically and theoretically rich account of the political forces shaping India’s economic rise. The paper not only compares distinct moments in Indian history but also draws parallels with other landmark cases, like South Korea’s 1980s industrial surge. Such a sector-based analysis could be fruitfully applied to understand why different industries succeed or lag in emerging economies. 

Different Sectors, Different Needs

In order to become competitive — both domestically and (especially) internationally — hardware manufacturers often need much from the state, what the authors call a “produce and protect regime.” This can include the construction of factories and the formation of state-owned industries (SOEs), as well as tariffs to reduce competition or labor laws that restrict union strikes. Perhaps most importantly, manufacturers need a state whose legislators and bureaucrats can coordinate with each other in response to market challenges. Such a regime is incompatible with excessive “red tape” or with the “capture” of regulators by narrow interest groups. Because customers tend to view manufactured goods as “substitutable” with each other, firms will face intense competition as regards price and quality.
 

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Fig. 2: Inter-agency coordination required for sectoral success.
 

The situation is very different for service providers, whose success depends on building strong relationships with customers. States are not essential to this process, even if their promotional efforts can be helpful. Coordination across government agencies is similarly less important, as just one agency could provide tax breaks or host promotional events that benefit service providers. Compared with manufacturing, customers tend to view services as less substitutable — they are more intangible and customizable, which renders competition less fierce. Understanding India’s computing history reveals that the state’s inability to meet hardware manufacturers’ needs severely constrained the sector’s growth. 

The History of Indian Computing

Although India inherited a convoluted bureaucracy from the British Raj, the future of its computing industry in the 1960s seemed promising: political elites in New Delhi supported a produce-and-protect regime, relevant agencies and SOEs were created, and foreign computing firms like IBM successfully operated in the country. 

Yet by the 1970s, some bureaucrats and union leaders feared that automation would threaten the federal government’s functioning and India’s employment levels, respectively. Strict controls in both the public and private sectors were thus adopted, for example, requiring trade unions — which took a strong anti-computer stance — to approve the introduction of computers in specific industries. The authors make special mention of India’s semiconductor industry. It arguably failed to develop due to lackluster government investment, the need for manufacturers to obtain multiple permits across agencies, decision makers ignoring recommendations from specialized panels, and so on.

Meanwhile, implementing protectionist policies proved challenging. For example, decisions to allow the importation of previously banned components required permission from multiple ministries and agencies. After India’s 1970s balance-of-payments crisis, international companies deemed inessential were forced to dilute their equity to 40% and take on an Indian partner. IBM then left the Indian market. At the same time, SOEs faced growing competition over government contracts and workers, owing to the growth of state-level SOEs.

The mid-1980s represented a partial turning point as Rajiv Gandhi became Prime Minister and liberalized the computing industry. Within weeks, Rajiv introduced a host of new policies and shifted the government’s focus from supporting public sector production to promoting private firms, which would no longer face manufacturing limits and would be eligible for duty exemptions. Changes to tariff rates and import limits would not require approval from multiple agencies. Meanwhile, international firms reengaged with Indian markets via the building of satellite links, facilitating cross-continental work, such as between Citibank employees in Mumbai and Santa Cruz.

However, this liberalizing period was undermined and partially reversed after 1989, when Rajiv’s Congress Party (INC) lost its legislative majority and public policy became considerably more fragmented. Anti-computerization forces, especially the powerful Indian trade unions, worked to stymie Rajiv’s reforms. Pro-market reformists were forced out of their positions in Indian bureaucracies. Rajiv was assassinated in 1991, after which Congress formed a minority government with computer advocate P. V. Narasimha Rao as PM. Yet all of this occurred at a delicate time, as India was at risk of defaulting and had almost completely exhausted its foreign exchange.

By the late 1990s, both the hardware and software sectors should have benefited from the rising global demand for computers, yet India’s history of poor state coordination hindered manufacturers. Meanwhile, software firms were able to take advantage of global opportunities given their comparatively limited needs from state actors and political networks — for example, helping European Union banks change their computer systems to Euros. Ultimately, the Indian state has powerfully shaped the fortunes of these different sectors.

*Research-in-Brief prepared by Adam Fefer.

Motivation and Summary

Modern states depend upon bureaucracies effectively delivering services and enforcing regulations, from public health to environmental protection and postal services. When bureaucracies are plagued by inefficiency and incapacity and are unable to “deliver the goods,” elected representatives suffer. This can open the door for citizens to throw their support behind authoritarian leaders who promise to deliver more effectively.

A central question of bureaucratic design concerns the degree of autonomy that ‘principals’ — political actors like legislators — should delegate to bureaucratic ‘agents.’ Calibrating autonomy is crucial because principals cannot perfectly monitor or control agents, whose preferences often diverge from their own. On the one hand, highly autonomous bureaucrats may become unaccountable to their principals. Think of national security agencies that create secretive dissident watchlists or even authorize assassinations. On the other hand, bureaucracies with little autonomy will find their decision-making hamstrung by “red tape.” If public health agencies required extensive legislative approval for every aspect of vaccine delivery, infection rates would skyrocket. How, then, can bureaucracies be designed to achieve their goals, creatively respond to new problems, and minimize corruption, all while being perceived as legitimate?

In “Calibrating autonomy,” Katherine Bersch and Francis Fukuyama disaggregate the concept of autonomy into two facets (independence and discretion), present hypotheses concerning how each facet relates to capacity and quality, and then test these hypotheses, primarily using survey data from Brazilian bureaucrats. Their findings caution against overly blunt efforts to calibrate autonomy across multiple bureaucracies, suggesting instead that policymakers should understand a given agency’s capacity to perform.

Argument and Hypotheses

The article builds on earlier research by co-author Francis Fukuyama, who in 2013 hypothesized a key moderating role for bureaucratic capacity in the relationship between autonomy and quality. Briefly, low-capacity agencies — lacking expertise and resources — will likely struggle to utilize their autonomy and deliver, whereas high-capacity bureaucracies will deliver effectively for opposite reasons. However, autonomy is itself a complex concept that ought to be disentangled before one can begin to spell out how it is linked to delivery.

Independence, the first “face” of autonomy, concerns the degree to which bureaucrats are constrained by actors who are close to politics, such as elected leaders or politically-appointed agency heads. More independent bureaucrats might allocate waste management contracts on the basis of cost-effectiveness or service quality records. Less independent bureaucrats might allocate according to the whims of politicians who wish to reward their allies. The degree of independence is oftentimes a function of the number and extent of political appointees in a given agency. 

The second face of autonomy is discretion, or rather, the extent to which agencies are constrained by laws, rules, or protocols. Waste management agencies with limited discretion may struggle to respond to sporadic garbage pile-ups, whereas those with high discretion may set unpredictable collection schedules. 

These two faces of autonomy lead to different expectations about how they are connected to quality. The authors hypothesize that independence and quality stand in a linear and positive relationship: agencies that are more unconstrained by political actors will deliver more effectively. By contrast, discretion and quality stand in a non-linear or “Goldilocks” relationship: too few and too many constraining rules will reduce quality. Following Fukuyama’s earlier research, capacity moderates these relationships; for example, less independence in specifically low-capacity agencies may strengthen quality, perhaps in cases where legislative actors are able to appoint highly qualified experts.

Methods and Findings

The authors select Brazil as their case, in part because it exhibits considerable internal variation in bureaucratic quality: some agencies are professional while others are incompetent. By focusing on one country, they avoid comparing fundamentally different national bureaucratic contexts. Further, selecting Brazil — with both strong and weak bureaucracies — reduces ‘selection biases,’ i.e., mistaking characteristics of only high- or low-quality agencies as causes of overall performance. From a global standpoint, Brazilian bureaucracies are solidly middle-ranged, neither outstanding nor abysmal. 

The main empirical part of the paper involves a 2018 survey of over 3200 Brazilian federal bureaucrats. About 60% of the respondents are political appointees and 40% are civil servants, which enables looking at bureaucrats who stand in different relationships to political actors. The authors exclude military personnel, teachers, nurses, and local police officers.

As hypothesized, respondents’ perceptions of agency independence increase their perceptions of quality in a linear way. This finding likely reflects Brazil’s coalitional style of government: politicians benefit electorally from strong government performance; without bureaucratic independence, political pressure and influence from the many coalition partners would likely hinder bureaucrats and weaken performance. Meanwhile, perceptions of discretion align with the authors’ non-linear expectations.
 

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Figure 3: (a) Impact of independence on quality at varying levels of capacity. (b) Impact of discretion on quality at varying levels of capacity.
 

These findings are mediated by capacity, which the authors measure in terms of resources, career length, salaries, and the proportion of agents in core or expert careers. The findings hold even when controlling for political factors like party membership or appointment type (political vs. civil servant), individual characteristics such as gender or years of service, and agency differences, including budget or size. These controls are based on administrative data from over 326,000 bureaucrats across Brazil’s 95 most important federal agencies.
 

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Figure 4: Quality at varying levels of capacity.
 

Contributions and Implications

“Calibrating autonomy” makes important conceptual and empirical contributions to our understanding of bureaucratic performance. By disaggregating the concept of autonomy into independence and discretion, it helps make sense of seemingly contradictory empirical findings, namely that both minimally and highly autonomous bureaucracies perform well. And by evaluating their hypotheses about the two faces of autonomy using Brazilian data, the authors guard against selection biases or problems from comparing countries with quite different bureaucratic landscapes.

The paper serves as a caution against overly simplistic or blunt “solutions” to poor bureaucratic performance. Merely limiting discretion or increasing legislative oversight can make matters worse if the relevant bureaucratic culture is not properly understood, especially when it comes to capacity.

*Research-in-Brief prepared by Adam Fefer.