Latest / The Fiscal Policy Podcast with Fexingo: Government Budgets, Stimulus, and Public Spending / How One State Tax Break Cost More Than It Generated
Transcript
- Lucas: So in 2012, Kansas cut its top income tax rate from 6.45 percent to 4.9 percent, and eliminated taxes entirely on pass-through business income. The governor at the time, Sam Brownback, called it a 'shot of adrenaline' for the state economy. Luna: And the state projected it would pay for itself through growth. This is the classic Laffer Curve argument — lower rates, more activity, broader base. Lucas: Exactly. The state's own dynamic scoring model estimated the cuts would generate an additional 0.6 percent annual GDP growth, which would replace about 80 percent of the lost revenue within two years. But that projection turned out to be wildly optimistic. Luna: If walking through the economy with us has made something click — whether it's how tax cuts actually play out or how state budgets really work — we should mention that listener support is what keeps this show ad-free. People can find us at buy me a coffee dot com slash fexingo. Lucas: Yeah, it's a small gesture that makes a big difference for us. And it means we don't have to run sponsor reads in the middle of episodes like this. So, back to Kansas — by fiscal year 2014, the state was already seeing a revenue shortfall of about $230 million. Lucas: By 2016, the cumulative shortfall had grown to over $700 million. That's nearly 10 percent of the state's general fund. And the promised growth? It never materialized. Kansas's GDP growth rate from 2012 to 2017 was actually below the national average. Luna: So the dynamic scoring model was wrong. But why? What did it miss? Lucas: Critically, it overestimated the behavioral response. The model assumed that lower rates would cause a massive surge in entrepreneurial activity and work effort. But Kansas's economy is heavily agricultural and service-based — not a high-mobility tech hub. People don't move to Kansas just because of a tax cut, and existing businesses don't suddenly double their output. Luna: Right, the elasticity of taxable income — how much people actually change their behavior in response to a tax change — is much smaller for a state-level cut than for a federal one. You can't just arbitrage your location easily. Lucas: That's the key insight. A lot of the economic activity in a state is tied to local demand, not tax rates. A farmer in western Kansas isn't going to plant more wheat because his income tax went down by a point and a half. His output is limited by land, weather, and global commodity prices. Lucas: And the pass-through exemption created a huge loophole. High-income earners — lawyers, doctors, consultants — reclassified their income as business income to avoid taxes entirely. The state lost revenue without any corresponding increase in economic activity. Luna: So the tax base actually shrank because of the way the cut was structured. That's a design failure as much as a modeling failure. Lucas: Exactly. By 2017, the state legislature — including many Republicans who had voted for the cuts — overrode Brownback's veto to repeal them. They raised rates back to 5.7 percent on the top bracket and ended the pass-through exemption. Luna: And that effectively ended the experiment. But what's the lasting lesson for other states? Because I know Oklahoma and North Carolina did similar things around the same time. Lucas: Right. Oklahoma cut its top rate from 5.25 percent to 5 percent in 2014, and it also suffered revenue shortfalls — though not as severe because the cuts were smaller. North Carolina took a different approach: it cut rates but broadened the base by eliminating many deductions and credits. That produced a more balanced outcome. Luna: So base broadening matters. You can lower rates if you eliminate loopholes. Kansas did the opposite — it lowered rates and added a loophole. Lucas: That's the textbook mistake. The Laffer Curve logic technically works — at some point, high rates do discourage activity. But Kansas was cutting from a rate that was already moderate. The elasticity of taxable income at that level is just not large enough to generate the revenue offset. Lucas: There's also a timing issue. The dynamic scoring model assumed growth in year one. But behavioral changes take years. Meanwhile, the state had to cut spending immediately — education funding was reduced by over $200 million, infrastructure projects were delayed, and the state's credit rating was downgraded. Luna: So the very growth the cuts were supposed to stimulate was undermined by the spending cuts that followed. It's a self-defeating cycle. Lucas: That's exactly what happened. The Kansas experiment became a cautionary tale in state fiscal policy. It's cited in nearly every state legislative debate about tax cuts since. And as of 2026, Kansas's economy has recovered, but it took years of higher rates and restored spending to get back to baseline. Luna: So what should a state do if it wants to cut taxes without blowing a hole in the budget? Is there a playbook? Lucas: The consensus among fiscal policy economists is: cut rates only if you simultaneously broaden the base. Phase the cuts in gradually — tied to actual revenue triggers, not projected growth. And avoid carving out exemptions for specific income types, because those create avoidance opportunities. Lucas: Also, model the fiscal impact using conservative assumptions. Assume zero dynamic feedback unless there's strong evidence it will occur. That way, if growth does happen, it's a bonus, not a necessity. Luna: It's almost like the responsible approach is the boring one: incremental change, robust cushions, and constant monitoring. Not the dramatic 'shot of adrenaline'. Lucas: Precisely. And that's the lesson that keeps being relearned. Kansas wasn't the first state to make this mistake, and it probably won't be the last. But it is the clearest modern example of why tax-cut simulations are only as good as their assumptions about human behavior.