Latest / The Fiscal Policy Podcast with Fexingo: Government Budgets, Stimulus, and Public Spending / Why Government Budgets Are Built on Fantasy Revenue Forecasts
Transcript
- Lucas: Every government budget you've ever seen — federal, state, local — starts with a number that is almost certainly wrong. Luna: The revenue forecast. Lucas: Exactly. And not just a little wrong — systematically optimistic by billions of dollars, year after year. The Congressional Budget Office's 2025 projections for corporate income tax receipts missed by sixty-three billion dollars in the first twelve months. Luna: Sixty-three billion is not a rounding error. Lucas: No. It's roughly the entire annual budget of a state like Kentucky. And that was just one line item. The CBO is actually considered one of the more honest forecasters. State and local forecasts are often far worse. Luna: Why do governments keep using models that are clearly broken? Lucas: Short answer: because they have to. A budget has to balance on paper. If you tell lawmakers the truth — that revenue is uncertain and likely to fall short — you might trigger automatic spending cuts or tax increases that nobody wants to vote for. So the forecaster is under enormous political pressure to produce a number that makes the arithmetic work. Luna: So it's not bad math. It's bad incentives. Lucas: Exactly. There's a famous paper from the late 1990s by economists at the Federal Reserve Bank of Atlanta that looked at fifty states over two decades. They found that official revenue forecasts were, on average, overoptimistic by about three percent. In election years it was worse — closer to five percent. Luna: And that's before dynamic scoring, which is basically 'if we cut taxes, revenue will go up because growth' — a theory that almost never holds. Lucas: Right. Dynamic scoring gives politicians a way to claim a tax cut pays for itself. But the empirical evidence is thin. The Tax Foundation and the Joint Committee on Taxation both publish static and dynamic estimates. The dynamic ones almost always show a smaller revenue loss, but rarely does actual revenue match the dynamic projection. Luna: What's the worst example you've seen? Lucas: California in 2021. The state's Department of Finance projected a modest surplus — about fifteen billion dollars. Then the actual tax returns came in. The surplus was nearly one hundred billion. Nobody saw it coming because the model was built on assumptions from the pandemic recession, which was already over. The forecast was completely blind to the rebound in capital gains. Luna: So the state accidentally had a windfall they didn't plan for. But the flip side is when revenue collapses and the budget is already locked in. Lucas: That's what happened to Illinois in 2020. Their forecast from November 2019 assumed steady growth. Then COVID hit and revenue cratered by twelve percent. But the budget had already appropriated spending based on the optimistic number. Illinois had to borrow from the Federal Reserve's municipal lending facility just to cover payroll. Luna: So the forecast error can swing both ways — but the bias is consistently toward optimism. Why aren't there penalties for being wrong? Lucas: There's no mechanism for accountability. The forecasters are usually career civil servants or independent agencies like the CBO. They're not fired for missing a projection. But private-sector forecasters — the ones at banks and research firms — they get judged on their track record. And they consistently outperform the official numbers. Luna: Is there any jurisdiction that does it well? Lucas: Switzerland is often cited. Their fiscal rule requires the budget to be balanced over the cycle, and the revenue forecast is produced by an independent panel with no political input. They also publish a range — not a single point estimate. That's key. Luna: A range acknowledges uncertainty. The US federal government publishes a single number — the mid-range estimate — and treats it as gospel. Lucas: Right. And that single number becomes the baseline for every spending decision. If you're off by five percent on a five-trillion-dollar budget, that's two hundred fifty billion dollars that either has to be borrowed or cut. Luna: Which is exactly what happens: the shortfall gets funded by debt. The forecast error effectively becomes a hidden driver of deficit. Lucas: Exactly. And the public never hears about it. The news reports the deficit number, but not the fact that it was partly caused by an unrealistic revenue assumption made two years earlier. Luna: So what could fix this? Better models, more transparency, independent panels? Lucas: All of the above. But the simplest fix is to require every official forecast to also publish a private-consensus average. Let people see the gap. If the government says revenue will be five trillion and private economists say four point seven, voters can ask why. Luna: That's a simple transparency rule. But would politicians ever agree to it? Lucas: Probably not — because it would expose the gimmick. And that's the real problem. The forecast isn't broken by accident. It's broken by design. Luna: Speaking of things that are only sustainable because people choose to support them — you know, this podcast is ad-free and listener-supported. If walking through the economy with us has made something click, a couple of dollars a month genuinely keeps us going. You can find us at buy me a coffee dot com slash fexingo. Lucas: Yeah, it's a small thing that adds up. And it means we never have to tailor content for an advertiser. So if you've gotten value, that's where to help. Luna: Back to the numbers: one argument forecasters make is that a single number is easier for legislators to work with. But that's an excuse for laziness, not a reason. Lucas: Absolutely. Some states are experimenting with probabilistic forecasting — giving a probability distribution instead of a point estimate. Utah started doing that for sales tax revenue a few years ago. Early results show lawmakers actually make more conservative spending decisions when they see the range. Luna: So the transparency itself changes behavior. Lucas: It does. Because when the forecast says there's a thirty percent chance revenue will fall short, you can't pretend it's a sure thing. The politics shift from 'we have to spend this' to 'we should probably set some aside.' Luna: Which is basically a rainy day fund. Lucas: Precisely. And most states have those now, thanks to lessons from the Great Recession. But the size of the fund is often tied to the forecast error. If you know your forecast is typically optimistic by three percent, you should stash three percent of revenue. Most don't. Luna: So the fix is partly technical — better models — but mostly political: demand that forecasts be honest about uncertainty. Lucas: Right. And as a listener, you can start by looking at your own state's revenue forecast. Most are published online. Compare it to actual collections from two years ago. See if the error is positive or negative. I bet it's positive. Luna: I'll take that bet. And I'll check Colorado. Lucas: And I'll check the CBO again in 2027. Something tells me the pattern won't change — unless we start demanding better.