Who Will Pay for Democratic Socialism’s $200 Trillion Cost?

By Adam N. Michel of Cato.

"The Democratic Socialists of America (DSA) propose new spending that could more than triple federal outlays. They propose the government pay for health care, housing, higher education, and electricity. Jobs are government-guaranteed, retirement benefits are expanded, paid family leave is universal, fossil fuels are eliminated, and reparations are paid. 

The DSA platform claims that the bill for all this will be sent to “the richest individuals and corporations.” Tally up that bill, and it ballparks between $71 trillion and $212 trillion in new spending over the next decade. Confiscating every dollar of high-end wealth and corporate profits would cover only a fraction of those costs. The DSA agenda necessitates high taxes on middle-class Americans. 

$200 Trillion in New Spending 

Totaling up nine of the largest proposals in the DSA platform would mean new federal spending equivalent to between 18 percent and 53 percent of GDP. 

Table 1 reports various low-end and high-end estimates of proposals for programs that approximate the DSA’s vague descriptions. Each proposal’s original spending estimate is converted to a share of GDP and then applied to the 2027–2036 projected GDP, so all estimates are in current dollars. 

  

Medicare-for-All-style proposals for universal healthcare would increase federal spending by $40 trillion to $75 trillion over 10 years. Reparations, a federal jobs guarantee, infrastructure, green energy investment, larger retirement benefits, free housing, paid family leave, and no-cost college would increase spending by tens of trillions of dollars more. In total, the DSA’s new spending would cost between $71 trillion and $212 trillion over the next decade. 

This exercise is inherently imperfect, which is why the estimates vary so widely and should be understood as orders-of-magnitude estimates. They likely overstate the cost where programs overlap with each other or existing spending. They understate the cost by failing to fully capture behavioral responses, broader economic effects, and the comprehensive scope contemplated by the DSA. Each estimate comes from different authors using different methods and assumptions, and builds on a similar methodology by David Burton. 

Internationally High Spending

In the US, federal, state, and local governments spent almost 40 percent of GDP in 2024. The average across the European Union is 49 percent, ranging from 58 percent in Finland to 22 percent in Ireland. 

Using the lower-bound estimates, the DSA agenda would raise US spending to more than 57 percent of GDP. Among large, industrialized countries, only Finland would have a larger government. France comes in a third of a percentage point under the US’s low estimate. Add the high-end estimates, and US government spending would reach 92 percent of GDP. 

No comparable country on Earth spends anywhere close to that amount. The DSA agenda’s spending could give the government a claim on national output much closer to estimates of state control under Soviet-style communism than to today’s European welfare states. 

 

 Who Pays? 

The federal government is projected to collect $70 trillion in taxes over the next decade, roughly 18 percent of GDP. Paying for the DSA agenda would require roughly doubling federal revenue at the low end and quadrupling it at the high end, in addition to the revenue needed to cover the Congressional Budget Office’s $24 trillion projected ten-year deficit. 

The DSA suggests that the richest Americans and corporations will pay for all these new outlays. The problem is, there simply aren’t enough resources at the top to make this plan work. 

 

The 400 wealthiest Americans were worth a record $6.6 trillion in 2025. Confiscating all of their wealth would cover only about 9 percent of the low-end revenue requirement and 3 percent of the high-end estimate. Their wealth could be seized only once, and attempting to liquidate trillions of dollars in assets would, in turn, drive their value down. 

Domestic corporate profits after federal taxes are projected to be about $35 trillion over the next decade. Seizing every additional dollar of corporate profits would fund half of the low-end estimate and 17 percent of the high end. This also assumes that firms continue operating normally while the government takes every cent of profit. Without a profit motive, businesses would cease to exist. 

Higher earners are also not a source of vast untapped revenue. A recent report by economists at the Joint Committee on Taxation concluded that raising top federal income tax rates to their revenue-maximizing level would result in revenue gains of less than 0.1 percent of GDP, equivalent to roughly $400 billion over a decade at today’s projected GDP levels. 

The entire wealth of the richest Americans, plus every dollar of corporate profit and maximum top income tax rates, still leaves the DSA agenda between $29 trillion and $169 trillion short. 

The only remaining source of revenue large enough to cover the DSA agenda is the same one every large European welfare state relies on: the middle class. France and Finland don’t fund their large governments by only taxing billionaires. They impose high income, payroll, and consumption taxes on ordinary households. 

To cover the DSA’s high-end spending estimate and current deficits, every $1 the federal government collects today would need to become about $4.36. Mechanically applying that increase to individual income-tax rates would push the 24 percent bracket above 100 percent and the top rate above 160 percent. 

The DSA is promising Americans a world in which someone else will pay for potentially hundreds of trillions of dollars in new benefits. The problem is that there aren’t enough rich people or corporations to pay for Democratic Socialism. Eventually, the bill will come for the rest of us."

There was a huge collapse in wealth inequality in the UK between 1900 and 1980

Tweet from Sylvain Catherine. He is a professor at Wharton, the business school of the University of Pennsylvania. Excerpts:

"If . . .we look at the top 1% . . . there was a huge collapse in wealth inequality in the UK between 1900 and 1980, and basically no change since then. And that is before taking state pensions into account. The same thing is true when you look at the top 10%."

The graph shows the share or percent of total wealth going to the top 1% and the top 10% over time. Those shares fell dramatically.  

 

 

California's Minimum Wage Hike

From Jeffrey Miron. 

"Firms respond to minimum wage hikes in multiple ways.

One study considers a 2023 California bill that raised the minimum wage for fast food workers from $16 to $20 per hour.

The researchers estimated

a 4.9–5.1 percent increase in fast-food prices and a 2.1–2.2 percent increase in full-service prices. … Additionally, [the] findings suggest that price increases reduced consumers’ demand for fast food by 3.9–4.1 percent and for full-service meals by 1.7–1.8 percent.

Further, the wage hike had

distributional implications, as lower-income households spend a larger share of their budgets at fast-food restaurants.

All in all,

this large, sector-specific minimum wage increase raised labor costs, [which] firms passed … through to consumers by raising prices, and the resulting decline in demand reduced employment.

Exactly what standard economics would predict."

Obama’s CEA on Reforming Health Care

The CEA’s Contradictions on Obamacare

By David R Henderson. Excerpt:

"What was strange about Duggan’s discussion of adverse selection and moral hazard is that he ignored his own discussion later in the chapter. On adverse selection, for example, he laid out how asymmetric information leads to adverse selection, writing:

Insurers cannot perfectly determine whether a potential purchaser is a large or small health risk. (p. 186.)

But then later, in discussing the House and Senate bills, he writes:

These regulations would correct insurance market failures by preventing health insurers from responding to adverse selection by raising rates and denying coverages . . . . (p. 202)

Huh? Just 16 pages after laying out that the adverse selection problem occurs because insurers can’t adjust rates to risk, he says that these regulations, which he seems to think are good, will prevent insurers from adjusting rates to risk.

On moral hazard, Duggan writes:

A second problem with health insurance is moral hazard: the tendency for some people to use more health care because they are insulated from its price. When individuals purchase insurance, they no longer pay the full cost of their medical care. As a result, insurance may induce some people to consume health care on which they place much less value than the actual cost of this care or discourage patients and their doctors from choosing the most efficient treatment. (p. 187)

But in a section titled, “Declining Coverage among Non-Elderly Adults,” Duggan writes:

The generosity of private health insurance coverage has also been declining in recent years. For example, from 2006 to 2009, the fraction of covered workers enrolled in an employer-sponsored plan with a deductible of $1,000 or greater for single coverage more than doubled, from 10 to 22 percent. The increase in deductibles was also striking among covered workers with family coverage. For example, during this same three-year period, the fraction of enrollees in preferred provider organizations with a deductible of $2,000 or more increased from 8 to 17 percent. Similar increases in cost-sharing were apparent for visits with primary care physicians. The fraction of covered workers with a copayment of $25 or more for an office visit with a primary care physician increased from 12 to 31 percent from 2004 to 2009. (p. 192)

If the goal is to have people pay more attention to cost when buying health care, a goal that the vast majority of health economists, whatever their political stripe would share, this is good news. Yet Duggan seems to lament it.

Along the way, though, Duggan does give little nuggets that suggest that health insurance markets work better than he originally claimed. For instance:

Forty-four states now permit insurance companies to deny coverage, charge inflated premiums, or refuse to cover whole categories of illnesses because of preexisting medical conditions. (p. 188)

“Inflated” in the above quote simply means high and, given the risk, it makes sense to charge high rates. Here again Duggan undercuts his own “adverse selection” critique of insurance markets.

What do the data tell us about insurance companies rescinding coverage and refusing to pay claims if individuals fail to list any medical conditions? Here’s what Duggan writes:

A House committee investigation found that three large insurers rescinded nearly 20,000 policies over a five-year period, saving these companies $300 million that would otherwise have been paid out as claims (Waxman and Barton 2009). (p. 188)

Now, 20,000 sounds like a large number but remember that these are three large insurers who could easily, among them, have one million policy holders. 20,000 over five years is 4,000 a year. So taking the one-million assumption, which I think is too low, one would conclude that 4/10 of a percent of insured people every year lost their insurance in this way.

DRH note in 2026: I probably way underestimated the number of policy holders that the three large insurers insured. I bet that it was at least 10 million. So 4,000 people per year having their policies rescinded would constitute 1/25 of one percent. Should a huge intervention in the health market be justified on the basis of a problem for 1/25 of 1 percent of insured people.

Another nugget is his number on uncompensated care, which he estimates at $56 billion in 2008. Given that approximately 255 million had insurance at any given time that year, this amounts to $220 per insured person. That’s large, but it’s not huge. The Samaritan’s Dilemma, it appears, is smaller than many have thought."

Regulated Markets Are Slow to Handle Change

From Alex Tabarrok. 

"Gowrisankaran, Langer and Reguant have an excellent paper, Energy Transitions in Regulated Markets (WP), in the latest AER.

The basic idea is that regulation designed to prevent utilities from building useless power plants can induce them to keep obsolete power plants. Some background. We regulated electric utilities under the theory that they were natural monopolies and therefore we would do better by pushing their prices down. What’s a reasonable price? Hard to say, so regulated utilities were allowed to recoup their operating costs plus a fair return on their “rate base”—their capital stock. Makes sense, but once profits depended on the size of the capital stock, utilities had an incentive to build too much—the classic Averch–Johnson effect. Regulators responded with “prudence” requirements and the rule that capital must be “used and useful.” In a stable world, that rule is a check, albeit an imperfect check, on so-called gold-plating.

But now consider what happens in a time of technological change, such as a rapid decrease in the cost of generating electricity with natural gas (driven by fracking and improvements in combined-cycle natural-gas (CCNG) technology). In a free market, large decreases in costs would cause firms to abandon coal and move to natural gas—some would do this to make profits, others to avoid losses. In short, the market forces sunk investments to be abandoned when not profitable.

But there is another possibility under regulation. Tell the regulator that your plants are still viable. Well, telling is cheap talk so you keep burning coal to prove that the plant remains useful. If you can keep your base operating that’s better than abandoning it and to signal how valuable your coal plant still is, it may even be worth while to burn coal when the cost exceeds the price of electricity! The authors have some nice data on exactly this point.

Figure 3 takes a little work to understand, but the pattern is clear. Each point represents a state. In panel A, the vertical axis shows how much less likely a coal plant is to run when the cost of coal exceeds the price of electricity. Obviously, a strongly negative coefficient is the economically sensible response: when burning coal is more expensive than buying electricity, the plant should burn less.

The red points represent restructured states and the green points regulated states. In restructured states coal burning falls when prices fall, just as expected. Coal burning in regulated states responds much less. (I.e., the red points generally lie below the green points.) Indeed, the six states with the largest reductions in coal operation are all restructured states.

One objection to this analysis might be that utilities in general are just slow to respond to prices, so on the horizontal axis the authors plot how well utilities respond to a higher price of gas. Note that these coefficients are all negative and there is no obvious difference between regulated and restructured states. In both types of states, utilities respond well to the price of gas, but only in restructured states do utilities respond strongly to the price of coal. (Why coal and not gas? Because the used-and-useful standard binds on capital whose usefulness is in doubt—which, once gas got cheap, meant coal. In other words, the utilities have to defend coal to the regulators, not gas.)

Panel B on the right shows a slightly different way of presenting the same data. The vertical axis is again how much less likely a coal plant is to run when its cost exceeds the electricity price. The horizontal axis is the fraction of generation owned by electric utilities. Regulated states tend to be vertically integrated, while restructured states opened electricity generation to competition, so utility ownership and regulatory status are closely correlated. Regulated states generally have utility ownership above 60%, while all the restructured states but one are below 30%. The best-fit line slopes upward: in other words, the more generation a state’s utilities own, the less coal dispatch responds to price. A different perspective on the same story.

That is the direct empirical evidence. The authors then construct a more ambitious structural model. In theory, regulation could produce either too much or too little investment in the new technology; their estimates imply too much. Much, too much. Not only do regulated utilities retain too much coal, they also build too much gas capacity. In short, they accumulate both too much old capital and too much new capital. Averch–Johnson on steroids.

The bottom line is that regulation under dynamic conditions is much more difficult than under static conditions. My view is that it may not even be worth the candle"

Abstract

Natural gas has replaced coal as the dominant fuel for US electricity generation. However, utilities in regulated US states have retired coal more slowly than others. We build a structural model of rate-of-return regulation during an energy transition where utilities face trade-offs between lowering costs and maintaining and using legacy capacity. A regulated utility facing carbon taxes lowers short-run coal generation 48 percent as much as a cost minimizer would. Thirty years after a sudden energy transition, a cost minimizer has retired 71 percent more coal capacity than the regulated utility. Alternative regulations may jeopardize affordability and reliability goals during energy transitions.

 

Counties that build data centers are seeing new housing, higher home values, lower unemployment and more job growth

Tweet from Sara Eisen. 

 

 

Everything At the Grocery Store is On Sale Relative to 1980

By Jeremy Horpedahl.

"Back in May 2024, I wrote about grocery prices in 2024 compared to 1980. Relative to average wage increases, almost everything was more affordable — the one exception was bacon.

Grocery prices have continued to climb since 2024, but so have wages. What does the comparison look like now? Well, I have good news for bacon lovers:

Figure 1

  

The chart shows the change in relative affordability, as measured by how many minutes of work at the average wage it would take to purchase the item (using consistent product sizes and weights). As I wrote in that 2024 post, these are not items that I cherry picked. These are all 24 grocery items where BLS has price data in both 1980 and 2026 (out of about 150 items total). Perhaps there is some survivorship or selection bias as to which items are available in both years, but looking at the list this seems like a pretty reasonable shopping cart for a typical consumer (well, maybe there aren’t buying all the meats every week, but probably every month). The prices are updated through July 2026, with the CPI data just released this morning.

While I have used average wages here, that isn’t a trick. We don’t have a median wage for 2026 yet, but using a measure of median earnings you can see that average wages and median weekly earnings increased at exactly the same rate since 1980.

But consumers probably aren’t thinking about prices relative to 1980. Their time horizon is likely shorter. What if we made the same comparison to 2026 using the 2019 prices, which is right before the pandemic and within most shopper’s recent memory:

Figure 2 

 

Relative to 2019, things do look quite as rosy. Some items are “on sale” in terms of affordability, but a lot of items aren’t, especially a lot of proteins. And no doubt many consumers will focus on the items that are less affordable, rather than those that are more affordable (and even for these items, the nominal price is higher, so consumers might still be frustrated).

It is important to note that this basket of 24 items isn’t a perfect representation of all the items consumers purchase. Compared to the CPI “food at home” index, average wages have actually increased more since the beginning of 2019. But consumers are right to feel that beef and few other items are much less affordable than 2019, even if over the long run they are more affordable."

Figure 3