Imagine a politician announcing a massive tax cut and then promising it won't cost the government a single dollar. The logic goes like this: lower taxes spark economic growth, more growth generates more income, and more income means the tax revenue comes flooding back. It sounds almost too good to be true. That's because it usually is.

This is the world of dynamic scoring—a method governments use to predict how tax changes will ripple through the economy. It's a genuinely useful idea that has become one of the most politically abused tools in public finance. Understanding how it works, and how it gets twisted, is essential for anyone who wants to evaluate what politicians are actually promising when they talk about taxes.

The basic idea behind dynamic scoring isn't crazy. When the government cuts taxes, people and businesses keep more of their money. Some of that extra cash gets spent or invested, which can stimulate economic activity. More activity means more taxable income, corporate profits, and consumer spending. So yes, a tax cut can generate some additional revenue that partially offsets the initial cost. This is the feedback loop that dynamic scoring tries to capture.

The key word there is partially. Decades of real-world evidence suggest that tax cuts rarely pay for themselves entirely. The United States saw this after the Reagan tax cuts of the 1980s, the Bush tax cuts of the 2000s, and the 2017 Tax Cuts and Jobs Act. In each case, revenue fell short of what dynamic models had predicted. Growth effects exist, but they tend to recover maybe 10 to 30 percent of the lost revenue—not 100 percent.

Think of it like giving your employees a raise and hoping their increased productivity covers the cost. It might help. They might work a little harder, stay a little longer, produce a bit more. But expecting the raise to entirely pay for itself through productivity gains? That's wishful thinking dressed up as accounting. The growth effects are real but modest, and pretending otherwise is where trouble begins.

Takeaway

Tax cuts can stimulate some growth, but the feedback effect almost never fully replaces the lost revenue. Partial offset is not the same as free money.

Here's where dynamic scoring gets genuinely dangerous. The models used to predict economic responses to tax changes depend on a long list of assumptions: How much will people work if their taxes drop? How much will businesses invest? How sensitive is consumer spending to extra disposable income? How quickly do these effects materialize? Each assumption is a dial, and turning any one of them slightly can shift the final number by billions of dollars.

For example, if a model assumes that a corporate tax cut will increase business investment by 5 percent, it might project strong GDP growth and modest revenue loss. But change that assumption to 2 percent—still a positive number—and suddenly the projected deficit balloons. The difference between a policy that "nearly pays for itself" and one that "blows a hole in the budget" can come down to a single parameter buried deep in a spreadsheet that almost nobody outside the modeling team will ever examine.

This is the fundamental vulnerability of dynamic scoring. It's not that the models are bad—many are sophisticated and built by serious economists. The problem is that reasonable-sounding assumptions can be strategically chosen to produce a desired result. Two credible economists can look at the same tax proposal and, using defensible but different assumptions, arrive at projections that are hundreds of billions of dollars apart. When the output depends this heavily on the input, the model becomes less of a forecast and more of a mirror reflecting whoever commissioned it.

Takeaway

A model's predictions are only as honest as its assumptions. When small, hard-to-scrutinize changes in inputs produce enormous swings in output, the real question isn't what the model says—it's who chose the assumptions and why.

Politicians face an uncomfortable reality: voters love tax cuts and government services. Promising both simultaneously should be impossible—less revenue means either less spending or more debt. Dynamic scoring offers a seductive escape from this bind. If you can claim your tax cut will supercharge the economy enough to replace the lost revenue, you get to promise everything and sacrifice nothing.

This is why dynamic scoring has become a partisan football. When one side wants to pass a tax cut, they push for dynamic scoring to make the price tag smaller. When the other side proposes spending programs, they might argue those investments will also generate growth—and want their proposals dynamically scored too. The Congressional Budget Office in the United States has increasingly been pressured to incorporate dynamic effects, and the question of which models and assumptions get used has become intensely political.

The deeper issue is accountability. When a government passes a tax cut based on dynamic projections that never materialize, there's no mechanism to undo the policy retroactively. The revenue shortfall just becomes next year's deficit problem. Meanwhile, the politicians who sold the rosy projection have moved on. Dynamic scoring, in its most cynical application, is a way to borrow credibility from the future—making promises today that reality will quietly break tomorrow, long after anyone's paying attention.

Takeaway

When a fiscal policy claim sounds like it costs nothing, ask who built the model and what happens if the growth projections are wrong. The bill always comes due—the only question is who pays it and when.

Dynamic scoring isn't inherently dishonest. Trying to account for how tax changes affect the broader economy is a legitimate improvement over pretending the economy stands still. The problem is that the technique's complexity makes it easy to exploit—and hard for citizens to challenge.

The next time you hear a politician promise that a tax cut will pay for itself, remember: the question isn't whether growth effects exist. They do. The question is how large they'll be, and whether the person making the promise has any incentive to give you an honest answer.