Daron Acemoglu, an MIT economist who won the 2024 Nobel Prize in Economics, published a detailed critique of UBI in June 2019. He calculated that paying every American adult $1,000 per month would cost about $4 trillion annually, nearly double the entire federal tax revenue at the time.

To fund it, tax rates would need to increase so dramatically that they would discourage work and investment across the economy. Acemoglu pointed out a fundamental inefficiency: UBI collects taxes from and then gives money right back to the same people, creating unnecessary economic drag. He argued that a targeted negative income tax could achieve better poverty reduction at a fraction of the cost.

OpenResearch conducted a randomized controlled trial from 2020 to 2023 across Illinois and Texas, enrolling 3,000 low-income participants who received $1,000 monthly and 2,000 control participants who received $50 monthly.

The study found that recipients reduced their work hours by 1.3 to 1.4 hours per week on average and were 3.9 percentage points less likely to be employed at any given time. Participants did not use the freed-up time for education or skills training. While recipients reported greater well-being, the study showed no increase in earned income, meaning the cash transfer did not help people become more self-sufficient. This is notable because the study was funded by a UBI supporter (Sam Altman of OpenAI), yet still found labor supply reductions.

Researchers from NYU, Princeton, and the Jain Family Institute studied a two-year unconditional cash transfer program in Compton, California. A total of 695 low-income households were randomly assigned to receive about $500 per month, while 1,402 households served as controls.

Earned income (not counting the transfer) declined by $333 per month on average. Part-time workers at the start of the study saw their labor force participation fall by a full 13 percentage points. Household spending also dropped by $302 per month, meaning recipients were not spending more and boosting the economy. Most of the money went to paying off debts.

John Cogan and Daniel Heil at Stanford''s Hoover Institution built an economic model to estimate what would happen if the U.S. adopted a UBI program. Their analysis concluded that aggregate labor supply would fall by 2.6%, with UBI recipients specifically cutting their work hours by 22.4%.

This would permanently reduce total U.S. economic output by 1.3%, amounting to roughly $270 billion per year in lost production. The excess spending required for UBI would need to be covered either by higher taxes or more government borrowing. Higher taxes would further reduce work and investment incentives, creating a negative feedback loop.

Hilary Hoynes and Jesse Rothstein, both professors at UC Berkeley, published a comprehensive review in the Annual Review of Economics in 2019. They examined how UBI proposals compare to existing U.S. safety net programs.

They concluded that a UBI generous enough to actually increase transfers to low-income families would cost an enormous amount. A key finding was that UBI would direct much larger shares of transfers to childless, non-elderly, non-disabled households and to middle-income rather than poor households, essentially wasting money on people who do not need it. They also concluded that any UBI would reduce labor supply in the short run, based on decades of economic research.

The Seattle-Denver Income Maintenance Experiment was the largest of four negative income tax experiments conducted in the U.S. during the late 1960s and 1970s. It was bigger than the other three experiments combined and ran for the longest period.

The results showed clear reductions in work: husbands reduced their labor supply by the equivalent of about 2 weeks of full-time work per year (a 9% reduction). Wives cut their work by about 3 weeks per year (a 20% reduction). Single female heads of households cut their work by about 4 weeks per year (a 25% reduction). These findings were so influential that they contributed to the political defeat of guaranteed income proposals in the 1970s.

In December 2018, IMF economists Maura Francese and Delphine Prady modeled a UBI set at 25% of each country''s net median income per capita, a relatively modest amount, and found that even at this low level, the fiscal cost was substantial in every case.

They examined three ways to pay for it: replacing all existing welfare transfers, raising income taxes, or adding a new proportional tax on disposable income. Each option came with serious tradeoffs. Replacing existing programs would leave many vulnerable groups worse off. Raising taxes would dampen economic activity. The study concluded that while UBI could reduce inequality, the sheer cost makes it difficult to implement without causing significant fiscal strain.

Andre Victor Doherty Luduvice, an economist at the Federal Reserve Bank of Cleveland, built a detailed macroeconomic model to simulate the effects of replacing the current U.S. income security system with a UBI, published in the Journal of Monetary Economics in 2024.

He found that a $1,000 monthly UBI ($12,000 per year) would require raising the consumption tax rate by 22 percentage points to balance the government budget. This massive tax increase, combined with the effect of receiving unconditional cash, would cause people to work less, reducing aggregate labor supply. The result was a decrease in total economic output and employment. Only a budget-neutral version with far smaller payments could avoid these negative effects.

Rema Hanna (Harvard) and Benjamin Olken (MIT) published a study in the Journal of Economic Perspectives comparing UBI to targeted transfers using real data from Indonesia and Peru. They found that despite imperfections in identifying who is poor, targeted transfers produced substantially higher welfare gains than universal programs when working with the same total budget.

The reason is straightforward: if you give money to everyone instead of just the poor, each poor person gets much less. The administrative costs of targeting were small, about $42 million every three years in Indonesia (a country of 270 million people), with annual costs of just $1.1 million in Peru. The savings from targeting far outweigh the costs of running the targeting system.

Robert Greenstein, founder of the nonpartisan Center on Budget and Policy Priorities, published an analysis arguing that UBI would likely increase poverty rather than reduce it. He examined UBI versions that would fund universal payments by abolishing programs like food stamps, the Earned Income Tax Credit, housing vouchers, Medicaid, Head Start, and child care assistance.

These existing programs collectively lift tens of millions of people, including millions of children, out of poverty each year. Spreading that same money across the entire population, including wealthy individuals who do not need it, would mean far less going to those at the bottom. Even versions that do not eliminate existing programs face the problem that a $10,000-per-person UBI would cost about $3 trillion annually, close to total federal tax revenue.

In 2017, the Ontario provincial government launched a basic income pilot in three communities: Hamilton, Thunder Bay, and Lindsay. About 4,000 low-income residents were enrolled, with individuals earning under $34,000 receiving up to $16,989 annually.

The program was designed to run for three years, but in August 2018, just one year in, the newly elected government cancelled it. The social services minister stated the program was "failing to help people become independent contributors to the economy." Because the plug was pulled early, researchers never received complete data. The cancellation highlights a key sustainability problem: UBI programs are politically vulnerable because of their high cost, and governments may terminate them before they can prove their value.