Modern Problems, Smarter Solutions
Three ideas shaping the opportunity debate last month
In January, FREOPP scholars tackled some of the most pressing policy debates in economic opportunity, safety-net reform, and education innovation. From affordability proposals that sound good but fail in practice, to a promising bipartisan effort to fix welfare cliffs, to the right way to approach AI in education, our work focused on separating good intentions from good policy.
Bad Economic Ideas Make Affordability Worse
Why simplistic fixes often deepen the very problems they aim to solve
Why it matters: Affordability is top of mind for families, but some of the most popular proposals being floated today risk backfiring especially for low-income Americans.
What we found: Policies like government-mandated caps on credit card interest rates or banning institutional investors from buying single-family homes ignore basic economic realities. Interest rate caps would likely reduce access to credit for higher-risk borrowers, pushing them toward worse alternatives. Housing purchase bans would do little to lower prices while reducing rental supply and market liquidity.
The policy points:
Price controls on credit (like interest-rate caps) historically reduce access to legal credit for higher-risk borrowers, disproportionately harming low-income households.
Credit contraction doesn’t eliminate demand- it shifts borrowers toward less transparent, higher-risk alternatives.
Institutional investors represent a small share of single-family home purchases nationally; banning them would have a negligible impact on home prices.
Reducing investor participation can decrease rental supply, pushing rents higher in already-tight markets.
Affordability challenges are primarily driven by supply constraints, regulatory barriers, and inflation - not investor activity or credit pricing alone.
Policymakers often confuse symptoms (high prices) with causes (restricted supply and distorted incentives).
What policymakers should do: Focus on reforms that expand supply, competition, and access rather than blunt restrictions that distort incentives and reduce options for consumers.
Senator Husted’s Bill to Tackle Welfare Cliffs
A smart federal pilot to unlock state-driven innovation
Why it matters: Millions of working families face “welfare cliffs,” where earning a little more leads to losing far more in benefits discouraging advancement and trapping households in place.
What we found: The bipartisan Upward Mobility Act would allow selected states to consolidate funding from multiple federal safety-net programs and redesign benefits so they phase out more smoothly as income rises. States would compete for pilot funding and commit to rigorous evaluation.
The policy points:
Welfare cliffs function as implicit marginal tax rates that can exceed 100%, penalizing work and advancement.
Federal programs are siloed, with overlapping eligibility rules that compound benefit losses as income rises.
The Upward Mobility Act preserves the safety net while allowing states to redesign benefit phase-outs more rationally.
Competitive pilot selection encourages innovation while limiting federal risk.
Independent evaluation requirements help separate what sounds compassionate from what actually improves outcomes.
State flexibility paired with federal accountability offers a scalable model for broader safety-net reform.
What policymakers should do: Advance pilot programs that allow states to test and evaluate benefit-cliff solutions, building evidence for broader reform that supports families without discouraging progress.
AI in Education: Fix the Flaws Without Nixing the Model
Why banning innovation would be the wrong response
Why it matters: As AI tools enter classrooms, policymakers are under pressure to act, but overreaction could worsen educational inequities and stall progress.
What we found: The biggest problems associated with AI in education stem not from the technology itself, but from poor implementation, weak accountability, and lack of educator support. Broad bans would eliminate promising tools instead of addressing these root causes.
The policy points:
AI tools amplify existing instructional strengths and weaknesses, they are not neutral, but neither are they inherently harmful.
Blanket bans tend to entrench inequities by limiting access to tools that could benefit under-resourced schools.
Poor outcomes are often tied to lack of teacher training, unclear implementation goals, and weak performance measurement.
Innovation without guardrails is risky, but prohibition eliminates learning, iteration, and improvement.
Policymakers should distinguish between tool misuse and tool design when regulating educational technology.
Transparent data on student outcomes is essential to responsible AI adoption in classrooms.
What policymakers should do: Set clear guardrails, invest in teacher training, and require transparency on outcomes so AI is used to enhance learning rather than undermine it.
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