Finding 6 — State policy as the lever

Young-voter turnout goes up as a state adds more access policies — automatic voter registration, same-day registration, online voter registration, pre-registration at 16 or 17, no-excuse absentee voting, and universal vote-by-mail.[6] The correlation is strongest in the groups where the access barriers in Finding 3 concentrate. For same-day registration and mail-ballot expansion, the peer-reviewed literature supports causal attribution and we cite those effects directly; elsewhere we report the correlation and leave causal interpretation open.

Policy score × youth turnout (2020 + 2022 + 2024 pooled)

The policy score sums six policies, sourced from the National Conference of State Legislatures (NCSL):[6]

Values range from 0 (none of the six in effect) to 6 (all six in effect).

Bars show average youth 18-29 turnout for states grouped by access-policy score (the count of the six policies above in effect), pooled across 2020, 2022, and 2024. Each bar averages the state-year turnout rates in its group; youth turnout climbs steadily from the lowest-access group to the highest. Hover any bar for its state-year count. Source: state_year_panel (Current Population Survey (CPS)[1] calibrated to McDonald voting-eligible population (VEP)[2] + NCSL policies[6]).

Policy score × youth-senior gap

The same relationship viewed through the gap lens: states with higher policy scores tend to show smaller senior-youth gaps. This is the turnout finding above seen from the gap angle — the same state-years, so it restates rather than adds. The points are available below for readers who want them.

Literature-supported causal effects

For two policies the peer-reviewed literature supports direct causal attribution for youth turnout effects, beyond the correlational view above:

For the remaining four policies (AVR, OVR, pre-registration, no-excuse absentee), the causal literature is moderate-to-strong in support of an effect but less precisely estimated for the youth sub-cohort specifically. The correlational finding above is consistent with the literature but should not be read as establishing causation state-by-state.

What this page establishes

  1. Higher state policy scores correlate with higher youth turnout in the 2020-2024 state-year panel.
  2. The policy effect is youth-asymmetric. State policy variation explains more variance in youth turnout than in overall turnout.
  3. Causal evidence concentrates on two levers — same-day registration and mail-ballot expansion — where the peer-reviewed youth effect range is +2 to +5 pp per policy.
  4. Correlation is not uniform across groups. States where the policy-score lift is largest are those with the highest access-barrier responses among non-registrants (see Finding 3 cross-cut).

Cross-references

So what

For Secretaries of State. Your state's current policy score places it in one of the access groups above (and on the full scatter, if you expand it). A one-unit move up the policy score is associated with an average youth-turnout change consistent with the literature ranges. State-Gap Explorer and Finding 3 let you identify which specific barrier is most cited by your state's non-registrants, directing attention to the policy that addresses that barrier.

For foundation officers. Policy-reform grantmaking sits at the $0-$5 per-marginal-voter end of the ROI catalog — dramatically lower than programmatic get-out-the-vote (GOTV) — because the per-cycle cost amortizes once the policy is in force.[13][14][15] The evidence strongest for same-day registration and mail-ballot expansion.

For the public. Where you live meaningfully shapes how much time, paperwork, and pre-planning it takes to register and vote. State policy variation is not about candidate preference; it is about the operational cost of participation.


Methodology. Policy score from NCSL as of 2026-04; effective dates backfilled from state statute citations (see data/external/ncsl_laws/). State-year panel combines CPS-calibrated turnout rates (Census P20 methodology), McDonald voting-eligible population (VEP) benchmarks, and NCSL policy flags. Correlational findings are state-year level; individual-level causal claims require within-state pre/post designs or the peer-reviewed literature cited above. Full provenance: methodology page.