Analysis
How Liberal Democracy Can Survive an Age of Spiraling Crises: A Conversation With Daron Acemoglu
The 2024 Nobel laureate explains why democracy’s survival depends on working-class prosperity—and what happens when institutions fail to deliver
When only 28% of Americans express satisfaction with how their democracy functions—a historic low recorded in January 2024—the warning signals are impossible to ignore. This isn’t merely a statistical artifact of partisan frustration. It represents something more fundamental: a crisis of delivery, where democratic institutions have systematically failed to fulfill their core promises to ordinary citizens.
Daron Acemoglu, the MIT economist who received the 2024 Nobel Prize in Economic Sciences, argues that liberal democracy flourished when it pursued its core promises of shared prosperity, democratic governance at the local and national level, and the free pursuit of knowledge. But those promises now ring hollow for millions who have watched inequality skyrocket while their own economic prospects stagnate. The question facing advanced democracies isn’t whether they’re under threat—the data confirms they are—but whether they possess the institutional capacity to reform themselves before it’s too late.
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The Polycrisis: When Multiple Failures Converge
We live in what scholars call a “polycrisis”—a condition where multiple, overlapping emergencies compound one another in ways that transcend their individual impacts. The numbers tell a stark story: between 2016 and 2024, the number of people living with democratic rights fell from 3.9 billion to 2.3 billion. This isn’t gradual erosion; it’s a democratic recession affecting nearly 1.6 billion people in less than a decade.
The Varieties of Democracy (V-Dem) Institute documents this retreat with precision. As of 2024, 42 countries are experiencing ongoing episodes of autocratization, a process where elected leaders systematically dismantle the very institutions that brought them to power. What makes this wave particularly insidious is its legalistic veneer—authoritarianism advancing through the ballot box rather than military coups.
But the democratic crisis doesn’t exist in isolation. It intersects with economic turbulence that has reshaped the social contract across industrialized nations. Consider the wealth concentration dynamics: In the United States, households in the top 10% of the wealth distribution own more than half—specifically 52%—of all total household wealth, with this share reaching as high as 79%. Meanwhile, income inequality measured by the Gini coefficient varies dramatically across OECD countries, ranging from approximately 0.22 in the Slovak Republic to more than double that in Chile, Costa Rica, and the United States.
This economic bifurcation creates what Acemoglu calls the preconditions for democratic decay. When democracy stops delivering shared prosperity, citizens begin questioning whether democratic institutions serve their interests at all.
Acemoglu’s Diagnostic: The Narrow Corridor and Institutional Balance
To understand how democracies survive—or fail—Acemoglu and his longtime collaborator James Robinson developed what they term “the narrow corridor” theory. The concept, detailed in their 2019 book of the same name, rejects the notion that liberty emerges naturally from either strong states or weak ones. Instead, freedom arises from a delicate balance between state power and an empowered society, where institutions provide education, healthcare, infrastructure, and protection from violence while remaining constrained enough that they cannot become predatory.
This framework helps explain puzzling variations in democratic outcomes. Why did some countries successfully democratize while others with similar initial conditions descended into autocracy or chaos? The answer lies in institutional design and the continuous tension between state capacity and societal mobilization.
Acemoglu’s research with Robinson and others has found that democracy directly contributes to economic growth, though it takes time—countries that democratize generally grow faster and invest more in education and health. But this relationship isn’t automatic. It depends on whether democratic institutions remain genuinely inclusive or become captured by narrow elites.
The extractive-versus-inclusive framework provides the analytical foundation. Extractive institutions concentrate power and wealth in the hands of a small elite, extracting resources from the broader population. Inclusive institutions, by contrast, distribute political power widely and create incentives for education, innovation, and broad-based economic participation.
History offers abundant examples. For three decades following World War II, democracy delivered shared prosperity as real (inflation-adjusted) wages increased rapidly for all demographic groups and inequality declined, but this trend ended in the late 1970s and early 1980s. Since then, the compact has broken down. Wages for workers without college degrees have stagnated while inequality has exploded—creating precisely the conditions under which populist demagogues thrive.
Economic Foundations of Democratic Fragility
The connection between economic inequality and democratic backsliding isn’t merely correlational. It operates through specific mechanisms that Acemoglu has spent decades documenting.
Democracy is in crisis throughout the industrialized world because its performance has fallen short of what was promised, with far-right and extremist parties benefiting from the fact that center-left and center-right parties are associated with wage stagnation, rising inequality, and other unfavorable trends. This isn’t hyperbole—it’s observable reality across Europe and North America.
The wealth inequality data reveals the scale of the problem. Brazil, Russia, and South Africa top global rankings for wealth inequality, each posting Gini coefficients around the low 0.8s on a scale where 0 represents perfect equality and 1 represents maximum inequality. But even wealthy democracies show troubling patterns. Among OECD countries in 2021, the ratio of average income between the richest 10% and poorest 10% of the population was 8.4 to 1.
These disparities matter because they shape political behavior. More than 60% of respondents across surveyed countries declared that disparities in income and wealth were too high or far too high in their country. When large swaths of the population feel economically abandoned, they become receptive to politicians promising to overturn the existing system—democratic norms be damned.
Acemoglu’s recent work emphasizes how technological change amplifies these dynamics. Automation and artificial intelligence threaten to further concentrate wealth and eliminate middle-skill jobs, precisely the economic foundation that historically sustained democratic stability. Without deliberate policy interventions to ensure technology creates broadly shared prosperity rather than extracting value for a narrow class of owners and investors, the economic pressure on democracy will only intensify.
The Polarization Multiplier
Economic anxiety doesn’t operate in a vacuum—it interacts with political polarization to create a toxic feedback loop threatening democratic stability.
In spring 2024, only 22% of U.S. adults said they trust the federal government to do the right thing just about always or most of the time, up slightly from the previous year’s historic low of 16%. This institutional mistrust reflects and reinforces partisan divisions. The Centers for Disease Control, for instance, received a 78% favorable rating among Democrats but only 33% approval from Republicans in 2024—a 45-percentage point chasm reflecting not scientific evidence but tribal identity.
The share of Americans who consider themselves on the far left or far right of the political spectrum is particularly high in the United States, with 11% placing themselves on the far left and 19% on the far right. Compare this to Germany, where only 6% identify as far left and 7% as far right, and the distinctive character of American polarization becomes clear.
This affective polarization—the emotional hostility between political tribes—proves more destabilizing than mere policy disagreements. Research shows it enables voters to excuse antidemocratic behavior by their own side while viewing identical actions by opponents as existential threats. Three-quarters of Americans said in 2023 that the future of American democracy was at risk in the 2024 presidential election, with both sides viewing the other as the primary threat.
The international context provides little comfort. Since 2000, 45 countries have experienced significant decline in the free and fair nature of their elections, relating to the spread of misinformation, interference from foreign actors, and erosion of public trust. These trends aren’t unique to any single nation—they represent a global pattern threatening the third wave of democratization.
Institutional Resilience: Pathways Forward
Despite documenting democracy’s current travails, Acemoglu’s analysis isn’t fundamentally pessimistic. The narrow corridor framework suggests that democratic renewal remains possible—but only through specific institutional reforms and renewed social mobilization.
Democracy has long promised four things: shared prosperity, a voice for the citizenry, expertise-driven governance, and effective public services. Rebuilding these pillars requires concrete policy changes, not merely rhetorical commitments.
First, the economic compact must be restored. This means policies explicitly designed to ensure technology creates good jobs rather than merely automating existing ones. Acemoglu and co-author Simon Johnson argue in their recent work that AI deployment should be shaped by tax policy, regulation, and public investment to favor labor-augmenting rather than labor-replacing technologies.
Second, political institutions need structural reforms to rebuild representativeness. This includes addressing gerrymandering, campaign finance distortions, and the ways money translates directly into political power—all of which allow narrow interests to capture democratic processes.
Third, strengthening the civic infrastructure that enables ordinary citizens to organize, deliberate, and hold power accountable. Some countries like Austria, Chile, Nepal, and South Africa faced early warning signs of deterioration but demonstrated onset resilience to autocratization, providing examples of how mobilized societies can push back against democratic backsliding.
The comparative evidence suggests these interventions work. Countries that have successfully reversed democratic decline share common features: active civil society, reformed electoral systems, and economic policies that deliver tangible improvements in living standards for working families.
The Working-Class Imperative
Perhaps Acemoglu’s most urgent recent argument concerns democracy’s relationship with working-class voters—the constituencies that democratic institutions were originally designed to empower.
While Democrats have won recent elections with support from Silicon Valley, minorities, trade unions, and professionals in large cities, this coalition was never sustainable because the party became culturally disconnected from, and disdainful of, precisely the voters it needs to win. This diagnosis applies beyond American politics to center-left parties across the industrialized world.
The policy implications are clear: More good jobs—finding ways to create good jobs in communities and spreading prosperity that way—must become the organizing principle of democratic governance. This isn’t about nostalgia for manufacturing employment but about ensuring that economic growth translates into broadly shared gains rather than concentrated windfalls for asset owners.
Historical precedent supports this emphasis. The golden age of democratic stability in advanced economies—roughly 1945 to 1980—corresponded precisely to the period when working-class incomes grew fastest. Democracy thrived when it delivered economic security. It now struggles because that delivery system has broken down.
Technology, AI, and Democratic Futures
The technological landscape adds new complexity to democracy’s challenges. Artificial intelligence, in particular, presents both opportunities and acute risks for democratic governance.
On one hand, AI could enhance state capacity, improve public service delivery, and accelerate scientific progress in ways that benefit everyone. On the other, it threatens to concentrate economic power even further, eliminate millions of middle-skill jobs, enable unprecedented surveillance, and flood information ecosystems with AI-generated propaganda.
Acemoglu has testified before the U.S. Senate warning that AI deployment, if left to pure market forces, will likely accelerate inequality and undermine social cohesion. The technology itself is neutral, but its institutional context determines whether it strengthens or erodes democracy. Companies designing AI systems for automation rather than augmentation—replacing human judgment rather than enhancing it—make choices that ripple through the entire political economy.
The policy challenge involves steering technology toward inclusive outcomes without stifling innovation. This requires active industrial policy, thoughtful regulation, and potentially significant changes to how we tax capital versus labor. None of this is simple, but the alternative—allowing technological change to further hollow out the economic middle class—represents a clear pathway to democratic collapse.
Can Democracy Deliver Again?
The central question isn’t whether democracy faces a crisis—democracy is going through a very, very tough stretch, in part because it has not realized its promise for all people, particularly those at the lower end of the labor market. The question is whether democratic systems retain sufficient institutional capacity to reform themselves.
Acemoglu’s framework suggests cautious optimism grounded in historical realism. Democracies have weathered serious challenges before—the Great Depression, World War II, the civil rights struggles. Each time, reform came not from benevolent elites but from mobilized citizens demanding that institutions live up to their stated values.
The narrow corridor theory reminds us that democratic liberty has never been the default state. It emerges only from continuous struggle—the Red Queen effect, where state and society must keep running just to stay in place. Complacency leads to drift toward either despotism or anarchy.
Current global trends provide both warning and possibility. In Thailand, Zambia, and other nations, democracy eroded but people resisted growing authoritarianism, allowing these countries to partially or fully restore previous levels of liberal democracy. These reversals demonstrate that when democracy deteriorates, its fate isn’t sealed—institutions can be reclaimed through organized citizen action.
The Stakes: Liberty and Prosperity
The conversation with Acemoglu ultimately centers on what we risk losing. Democracy isn’t merely a set of procedures for selecting leaders—it’s the institutional foundation for both human liberty and shared prosperity.
It’s very difficult to maintain economic inclusion when ruled by the iron fist of an autocrat, Acemoglu notes. The extractive institutions that characterize autocracies systematically prevent the broad-based innovation, education, and entrepreneurship that drive sustained economic growth.
The stakes extend beyond economics to human dignity and freedom. Autocratic alternatives promise efficiency and decisive action, but they deliver neither. Instead, they concentrate power in ways that ultimately serve narrow interests while suppressing the very social dynamism that makes societies vibrant and productive.
For liberal democracy to survive this age of spiraling crises, it must rediscover its core promise: building inclusive institutions that genuinely serve the broad public rather than narrow elites. This requires confronting economic inequality, repairing social trust, reforming broken political systems, and ensuring that technological change serves human flourishing rather than extractive concentration.
The narrow corridor ahead is treacherous. But it remains navigable—if we choose to walk it with clear eyes and determined purpose.
About the Research
This analysis draws on Daron Acemoglu’s extensive body of work, including “Why Nations Fail” (2012) with James Robinson, “The Narrow Corridor” (2019), and his recent Project Syndicate commentaries on democratic crisis and working-class politics. Data sources include the Varieties of Democracy (V-Dem) Institute, OECD inequality statistics, Pew Research Center political surveys, and World Bank inequality metrics.
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Analysis
Asia Pacific Emerges as Global Travel Growth Engine — China Outbound to Surpass 225 Million Trips
Asia Pacific travellers have a 50% higher intention to increase travel spending than those in Europe and the US, cementing the region’s position as the world’s growth engine for travel. According to one study, 88% of global travellers plan to increase or maintain their travel budgets in 2026.
China’s outbound market is the powerhouse. China’s outbound travel in 2026 is projected to exceed 225 million trips, surpassing pre-pandemic levels and marking a transition from recovery to a structurally different phase of growth. Chinese travellers report the highest expected mean spend at **$7,748 per international leisure trip**, followed by Australian travellers at $7,124 and Indian travellers at $5,154. International visitor spending in China rose by 10.5% to $135 billion, exceeding pre-pandemic levels and outperforming the global average growth of 3.2%.
The World Travel and Tourism Council expects China’s travel and tourism sector to grow 7% annually over the next decade, contributing $3.8 trillion to GDP by 2035. China is on track to surpass the US as the world’s leading travel and tourism economy.
Corporate travel is also booming. Business travel expenditure across Asia Pacific is forecast to reach $70.09 billion in 2026, marking a year-on-year increase of 10.9%. The region is expected to contribute more than 40% of total global outbound business travel spending, underlining APAC’s central role in international commerce and aviation growth. China alone is projected to account for $40.8 billion of this spending — 58% of the regional total.
What’s driving this surge? Expanding visa-free access, a stronger yuan, and pent-up demand from Chinese consumers eager to explore the world. MMGY’s survey of 4,000 travellers shows that Chinese and Indian travellers are planning 3.2-3.5 trips annually versus 1.9-2.3 for Australia, Japan, and South Korea. The destinations winning Chinese travellers are those offering premium experiences, seamless digital payments, culturally resonant offerings, and visa facilitation.
The spending differential is significant. Chinese travellers not only travel more frequently but spend substantially more per trip than travellers from other major Asia Pacific markets. This makes them the most coveted segment for destinations worldwide, driving intense competition among tourism boards to attract and retain Chinese visitors through targeted marketing, direct flights, and culturally tailored experiences.
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AI
The AI Debt Bubble: How Data Centers Are Reshaping Credit Markets
The dominant narrative around artificial intelligence investment has always centred on equity valuations — Nvidia’s market capitalisation, hyperscaler earnings multiples, the concentration of the S&P 500 in a handful of AI-exposed names. That narrative is now incomplete. The more consequential shift underway in 2026 is happening in credit markets, and regulators are starting to say so explicitly.
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An Unprecedented Pace of Capital Deployment
The Bank of England’s July 2026 Financial Stability Report puts it plainly: the pace of AI-related investment is unprecedented historically, with AI companies increasingly turning to the financial system — and specifically to debt financing — to fund infrastructure buildouts. This marks a meaningful departure from the equity-heavy funding model that characterised the first wave of the AI boom, when cash-rich technology giants largely self-funded expansion from balance-sheet reserves.
Why Debt, and Why Now
The shift toward debt financing reflects simple scale economics: data-center construction costs have grown large enough that even the best-capitalised technology companies are choosing to preserve equity and cash flexibility by tapping bond and private credit markets instead. This dynamic accelerated sharply through the first half of 2026, coinciding with the same window in which China’s export data showed chips, computer parts and power equipment accounting for roughly half of the country’s export growth — evidence that the AI infrastructure buildout is now a genuinely global capital-expenditure cycle, not a US-only phenomenon.
The Leverage Concentration Problem
The Bank’s Financial Policy Committee has flagged a specific structural fragility: equity gains in AI-related names have been driven in significant part by a narrow, concentrated set of companies, with a substantial increase in the use of leverage tied to these positions. That combination — narrow concentration plus rising leverage — is precisely the mechanism that has historically turned isolated valuation corrections into broader, self-reinforcing liquidity events.
Separately, the Bank’s broader assessment of credit markets warns that vulnerabilities in risky asset valuations, sovereign debt markets and risky credit segments — including private credit specifically — remain, with some having become more pronounced since its previous report, as globally higher interest rates and energy-driven cost increases add pressure on corporate borrowers across the board, AI-related or otherwise.
The Sovereign Debt Connection
Perhaps the most significant — and least discussed — finding from the Bank’s analysis concerns how an AI-related equity correction could interact with sovereign bond markets. In its modelled scenario, debt-to-GDP ratios rise following a hypothetical AI valuation correction, but the Bank notes that both the US Treasury market and UK gilt market continued to function well under the scenario tested — with an explicit warning that had those markets come under pressure instead, the consequences could have been considerably more severe.
That finding sits uncomfortably alongside the Federal Reserve’s own hawkish pivot under Chair Kevin Warsh, detailed elsewhere in this series. A Fed moving toward rate hikes rather than cuts directly raises the cost of the debt financing now underpinning much of the AI infrastructure buildout — a tightening that could pressure highly leveraged data-center financing structures at precisely the moment the sector’s borrowing needs are accelerating.
What Regulators Are Doing About It
Rather than attempting to directly restrain AI-related credit growth — not typically a central bank mandate — the Bank of England is focused on strengthening the plumbing that would need to absorb a shock if one occurs. It points specifically to reforms already announced for money market funds across the UK and Europe, alongside exploratory changes to bolster resilience in the gilt repo market, as the primary tools available to prevent an AI-financing-driven credit event from cascading into broader market dysfunction.
The Investor Takeaway
For fixed-income investors and credit allocators, the practical shift is this: AI exposure can no longer be assessed purely through equity valuation multiples. The debt structures financing data-center buildouts — their leverage ratios, their sensitivity to a hawkish Fed, and their concentration among a narrow set of borrowers — now represent a distinct and growing risk factor in global credit markets, one that central banks on both sides of the Atlantic are actively modelling, even as they stop short of calling it a bubble outright.
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Is AI infrastructure being funded by debt or equity in 2026? AI companies are increasingly relying on debt financing rather than equity to fund data-center buildouts, a shift the Bank of England describes as historically unprecedented in pace, raising new financial stability questions around leverage concentration and credit market resilience.
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AI
AI Chip War 2026: How Singapore & Malaysia Got Caught Between US and China
New guidance from the US Department of Commerce issued in late May 2026 has tightened licensing requirements for Nvidia’s most advanced processors, including its Blackwell series, closing a loophole that let Chinese firms acquire restricted chips through overseas subsidiaries — and putting Singapore and Malaysia squarely in Washington’s crosshairs as the two Southeast Asian hubs most exposed to diversion risk (NaturalNews).
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A Trillion-Dollar Market, and a Widening Grey Zone
Under the current three-tier US export framework, Singapore and Malaysia sit in “Tier 2” alongside roughly 120 other countries, including India and the UAE, meaning firms there must obtain individual licences or validated end-user authorisation before accessing the most advanced AI chips (Asia Times). That has not stopped both markets from becoming critical waypoints in the global AI supply chain: Singapore alone accounted for roughly one-fifth of Nvidia’s $215.9 billion in revenue for the fiscal year ended January 2026, making it the company’s second-largest market after the United States.
The scale of the enforcement challenge became public in May 2026, when the US Department of Justice charged three individuals connected to a technology supplier in a scheme involving roughly $2.5 billion worth of Nvidia-powered servers, allegedly routed to Chinese brokers using dummy replicas to defeat physical audits (Model Diplomat). That case echoes an August 2025 indictment involving chip shipments transiting through Malaysia and Singapore en route to Hong Kong, underscoring how the region has become a persistent pressure point for US export enforcement.
Malaysia Moves First, Thailand Lags Behind
Regional responses have diverged sharply based on exposure and regulatory capacity. Malaysia acted earliest, introducing a mandatory Strategic Trade Permit in July 2025 covering the export, transshipment and transit of high-performance US-origin AI chips — a move widely read as Kuala Lumpur choosing to tighten oversight rather than risk its reputation as what one Eco-Business analysis calls a “weak link” in the compliance chain (Eco-Business).
Thailand has proven more exposed. In May 2026, US authorities publicly flagged a Bangkok-based firm tied to the country’s national AI initiative for allegedly helping divert billions of dollars’ worth of Nvidia-powered servers to Chinese companies including Alibaba — a case that illustrates how national AI ambitions and export-control compliance can pull governments in opposing directions.
Beijing’s Answer: Building Around the Restrictions
China’s response to tightening controls has increasingly been to accelerate domestic substitution rather than simply seek workarounds. Nvidia CEO Jensen Huang told CNBC in May that he had effectively “conceded” the Chinese data-centre market to Huawei, with the company now assuming zero data-centre chip revenue from China going forward — a remarkable admission given that the Chinese market generated an estimated $12–15 billion in H20 chip sales as recently as 2024 (Model Diplomat).
China’s own supercomputing ambitions received a symbolic boost in June 2026 when the domestically built LineShine supercomputer, developed at Shenzhen’s National Supercomputing Center, reclaimed the top spot on the global TOP500 ranking, surpassing the US-built El Capitan system. Analysts tracking China’s fifteenth five-year plan note that Beijing has explicitly directed its AI sector to develop “extraordinary measures” to defeat export controls, with domestic players Huawei, Cambricon and SMIC forecast to reach at least 50% market share within China by the end of 2026.
Why Southeast Asia Cannot Simply Pick a Side
Chatham House’s assessment of the broader export-control strategy is unusually blunt: rapid global demand growth for AI compute makes enforcement extraordinarily difficult, and countries like Malaysia and Singapore have become de facto grey markets whether or not their governments intend that outcome (Chatham House). The US Chip Security Act, working its way through Congress, aims to close some of these gaps by requiring companies to verify that chips remain in authorised locations — but even proponents acknowledge that legislation alone cannot fully police a supply chain running through dozens of jurisdictions with varying regulatory capacity.
For Singapore and Malaysia, the dilemma is structural rather than merely diplomatic: both governments actively court data-centre investment from American and Chinese firms alike, because both flows generate genuine economic value, jobs and technology transfer. Neither wants to be forced into an exclusive alignment with Washington or Beijing on chip policy, yet the political and legal risk of appearing to enable diversion is rising sharply with each new DOJ indictment. The likeliest trajectory for the rest of 2026 is not a clean resolution but an intensifying game of regulatory whack-a-mole, with Southeast Asian governments tightening rules just fast enough to avoid becoming Washington’s next enforcement headline, without fully closing the door on Chinese capital.
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