Picture U.S. wealth as stacks of $100 bills: the median household’s is about 9 inches tall. The average top-1% household’s is 145 feet, and it keeps getting taller and taller…
$1 Trillion of Wealth Was Created for the 19 Richest U.S. Households Last Year
Total household wealth for the richest 19 U.S. households jumped to about $2.6 trillion in 2024, after the biggest one-year increase on record.
The Top 1% of Americans Have Taken $50 Trillion From the Bottom 90%—And That's Made the U.S. Less Secure
A report shows that a $50 trillion redistribution of income to benefit the richest has made America less healthy, resilient, and secure
Is Inequality Inevitable?
Wealth naturally trickles up in free-market economies, model suggests
Billionaire wealth jumps three times faster in 2025 to highest peak ever, sparking dangerous political inequality | Oxfam International
Billionaires 4,000 times more likely to hold political office than ordinary people
Is Dollar Dominance Good for the U.S.?
Thoughts on the U.S.'s so-called exorbitant privilege.
Do the Rich Capture All the Gains from Economic Growth?
Adjusted for inflation, the US economy has more than doubled in real terms since 1975.
Why the super rich are inevitable
Why some mathematicians argue the economy is designed to create a few super rich people – unless we stop it.
The Divide — Jason Hickel
The Divide: A Brief Guide to Global Inequality and its Solutions Penguin Random House UK, 2017
BETTER THAN FREE | Edge.org
This super-distribution system has become the foundation of our economy and wealth. The instant reduplication of data, ideas, and media underpins all the major economic sectors in our economy, particularly those involved with exports — that is, those industries where the US has a competitive advantage. Our wealth sits upon a very large device that copies promiscuously and constantly.
Economic Inequality
How is inequality measured, who produces key databases, and what does the data tell us?
Economic Inequality
How is inequality measured, who produces key databases, and what does the data tell us?
The persistence of cognitive biases in financial decisions across economic groups
While economic inequality continues to rise within countries, efforts to address it have been largely ineffective, particularly those involving behavioral approaches. It is often implied but not tested that choice patterns among low-income individuals may be a factor impeding behavioral interventions aimed at improving upward economic mobility. To test this, we assessed rates of ten cognitive biases across nearly 5000 participants from 27 countries. Our analyses were primarily focused on 1458 individuals that were either low-income adults or individuals who grew up in disadvantaged households but had above-average financial well-being as adults, known as positive deviants. Using discrete and complex models, we find evidence of no differences within or between groups or countries. We therefore conclude that choices impeded by cognitive biases alone cannot explain why some individuals do not experience upward economic mobility. Policies must combine both behavioral and structural interventions to improve financial well-being across populations.
Who is rich in America, and why?
A review of “The Everywhere Millionaire” by Zidar and Zwick
AI Adoption and Inequality
There are competing narratives about artificial intelligence’s impact on inequality. Some argue AI will exacerbate economic disparities, while others suggest it could reduce inequality by primarily disrupting high-income jobs. Using household microdata and a calibrated task-based model, we show these narratives reflect different channels through which AI affects the economy. Unlike previous waves of automation that increased both wage and wealth inequality, AI could reduce wage inequality through the displacement of high-income workers. However, two factors may counter this effect: these workers’ tasks appear highly complementary with AI, potentially increasing their productivity, and they are better positioned to benefit from higher capital returns. When firms can choose how much AI to adopt, the wealth inequality effect is particularly pronounced, as the potential cost savings from automating high-wage tasks drive significantly higher adoption rates. Models that ignore this adoption decision risk understating the trade-off policymakers face between inequality and efficiency.
Household Need for Liquidity and the Credit Card Debt Puzzle
Abstract. In the 2001 U.S. Survey of Consumer Finances, 27% of households report simultaneously revolving significant credit card debt and holding sizeable
