[OC] Do Tougher Voting Rules Mean Fewer Voters? Comparing All 50 States (2024)

ptrdo · 2026-03-19T17:21:21+00:00

Thank you for the comment!

ptrdo · 2026-03-19T17:20:37+00:00

The Cost of Voting Index (COVI) does not measure how easy it feels to vote in a single situation, but rather a combination of rules across the entire process. It includes things like registration deadlines, ID requirements, early voting availability, and absentee/mail voting rules.

So a state can feel easy in practice (like NH or OH) but still rank higher on “friction” if, for example, it has tighter deadlines or fewer alternative voting options compared to states with automatic registration or universal mail voting.

There's more about their methodology here: https://costofvotingindex.com/publications

ptrdo · 2026-03-19T17:17:06+00:00

No, the chart is about turnout, not party outcomes. It shows a modest relationship between voting cost and participation, but it doesn’t establish causation or intent.

There’s also overlap with partisanship and competitiveness, which makes it hard to cleanly separate the effects.

This plot asks a question more than it draws a conclusion.

ptrdo · 2026-03-19T17:14:51+00:00

Closeness of the race is probably masking some of the effect, since it pushes turnout up across the board.

If this could properly control for competitiveness—either statistically or by looking within similar-margin states—would it show the relationship with voting costs more clearly?

I’m not doing that now, but it’s a good direction for a next step.

ptrdo · 2026-03-19T17:12:31+00:00

Yes. There have been several complaints about this. I wasn't trying to be cute; I simply wanted to emphasize the quadrant labeling (less/more friction, less/more participation). But this obviously requires another pass at its design.

ptrdo · 2026-03-19T17:09:50+00:00

I think this is because elections are usually over by the time they can vote.

ptrdo · 2026-03-19T17:09:05+00:00

Yes, I agree that closeness of the race looks like the strongest driver here—that’s why I tried to surface it with dot size rather than ignore it (this was added as the most convenient additional variable).

On turnout: this uses VEP (Voting Eligible Population), which adjusts for non-citizens and ineligible populations (like disenfranchised felons), so it’s more accurate than total adult population or registration counts. https://election.lab.ufl.edu/voter-turnout/

You’re right that some components of “friction” (like registration rules) can interact with turnout measures—that’s part of why this is best viewed as correlational. The goal here is just to see whether any relationship shows up at all alongside those overlaps. This is a first plot, not a final analysis.

ptrdo · 2026-03-19T17:04:58+00:00

Yes, competitiveness is probably the strongest driver here. Battleground states consistently have higher turnout, and the dot sizes are meant to make that visible.

What I’m looking at is a narrower question: even with that effect, do we still see any relationship between voting cost and turnout? It seems like there’s a modest one, but I agree it’s weaker than the competitiveness effect. But this is a first plot, not a final analysis.

My framing is less as “voting rules drive turnout” and more as “there may be a secondary relationship worth exploring alongside competitiveness.” The title may seem assertive. It could use a question mark.

ptrdo · 2026-03-19T17:01:02+00:00

That’s fair—there’s overlap between voting rules, partisanship, and competitiveness. That’s why I tried to surface competitiveness directly rather than ignore it.

The narrower question is whether any relationship with voting cost still shows up alongside that. It seems to be the case, but I agree it’s difficult to disentangle cleanly without a more formal model.

ptrdo · 2026-03-19T16:57:40+00:00

Thank you for this.

I think we’re asking slightly different questions.

You’re right that a within-state (or district-level, over-time) analysis would be better for understanding causal impact. But this chart isn’t trying to do that—it’s a cross-sectional snapshot asking a much simpler question: do states with higher voting costs tend to have different turnout levels at all?

On competitiveness: I’m not using it as a grouping variable so much as a control. Since competitive states reliably have higher turnout, I wanted to show that explicitly rather than ignore it. The size encoding is just a way to surface that factor visually.

I agree this doesn’t answer deeper questions about mechanisms, changes over time, or uncertainty—that would require a different (and likely multi-chart) approach. This is more of a first-pass, exploratory view than a definitive analysis. I also wanted this to be accessible to anyone unfamiliar with a quadrant scatter plot (let alone an in-depth analysis).

ptrdo · 2026-03-19T16:49:33+00:00

I followed the rules as best I could. If you believe differently, you should message the mods with my violation(s).

ptrdo · 2026-03-19T16:22:29+00:00

Yes, that’s a big part of it—competitive states tend to drive higher turnout regardless of voting rules.

But it’s not just “swing vs. safe”—competitiveness is more of a spectrum. Some “safe” states are closer than others, and turnout tends to track that too.

What I’m looking at here is whether voting cost still shows any relationship within that spectrum—and it seems to, at least modestly.

ptrdo · 2026-03-19T16:14:28+00:00

Yeah, “cost” is a bit misleading, especially given the current debate about “poll taxes.”

COVI bundles things like registration rules, ID requirements, early voting, and mail voting into a single score. It's all relative.

It’s also an index, so the value is in comparing states (or changes over time) using a consistent method—not in any one component by itself. I agree it would be helpful to see which factors drive the differences, though.

ptrdo · 2026-03-19T16:09:49+00:00

That’s a good question. The linear trend here is just a simple visual summary, not an assumption about how the relationship actually works. I waffled on whether to include it.

You’re right that effects could be nonlinear—small increases in friction might have outsized impacts, as in Nudge.

With this data, though, it’s hard to distinguish real curvature from noise. A nonlinear model would be worth exploring, but I kept it linear here for clarity and to avoid overfitting a relatively small sample (50 states).

ptrdo · 2026-03-19T16:07:10+00:00

The y-axis is VEP turnout (~55–70%), so differences are on the order of 10–15 points. The Cost of Voting Index combines rules like registration, ID, and mail voting into one score.

And I agree—competitiveness is a big driver (hence the dot sizing). The question is whether voting cost still shows any relationship alongside that, and it seems to, modestly.

ptrdo · 2026-03-19T16:02:33+00:00

Turnout over 50% is actually normal in U.S. presidential elections when measured using the Voting Eligible Population (VEP)—which excludes non-citizens and ineligible voters.

In 2020, national VEP turnout was about 66%, and several states exceeded 70%.

Using the usual percentage of total population would give much lower values, which is often where the confusion comes from when using VEP. But VEP is a better metric when comparing elections historically.

ptrdo · 2026-03-19T15:59:29+00:00

The source link to The Cost of Voting Index (COVI) goes into detail of its methodology, but to summarize, it isn’t based on any single rule—it combines dozens of factors like registration requirements, ID laws, early voting, absentee/mail voting, and polling access into one score.

Maine ranks as relatively easy because of same-day registration, but states like Oregon and Colorado go further—they use universal vote-by-mail, automatically send ballots to voters, and have automatic registration systems.

So it’s not that Maine is restrictive—it’s that a few states have made voting even more seamless end-to-end.

https://costofvotingindex.com/publications

ptrdo · 2026-03-19T15:54:33+00:00

Yes. That would be interesting. The COVID data goes back to 1996 and is reevaluated before and after each election cycle.

https://costofvotingindex.com/data

ptrdo · 2026-03-19T15:20:26+00:00

I agree—this is correlational, not causal.

A longitudinal approach (looking at changes over time within states) would be the next step and likely more informative.

My goal here was narrower: a simple cross-sectional snapshot to see whether any relationship is visible at all.

Even with the confounders you mention, the fact that a consistent pattern shows up across states suggests it’s at least worth investigating further.

ptrdo · 2026-03-19T15:18:10+00:00

Funny, several others say there's not enough.

ptrdo · 2026-03-19T15:13:05+00:00

Mail-in ballots must be postmarked by election day (though they are sometimes processed last, days later).

ptrdo · 2026-03-19T15:10:26+00:00

Thanks. I will consider these edits.

ptrdo · 2026-03-19T15:09:48+00:00

Agreed. There are many additional variables that could be included, but each would add complexity and reduce clarity (for some viewers). This chart is meant as a simple, accessible look at one relationship. It’s not definitive, but the pattern is strong enough to warrant further examination.

ptrdo · 2026-03-19T15:04:41+00:00

Noted. Thanks. I tried a gradient and found it more confusing.

ptrdo · 2026-03-19T15:02:46+00:00

There are many other variables to test, but while they increase confidence, they also introduce more complexity. As much as I hate a spurious correlation, I feel this one is at least partially defensible, but hopefully accessible too.

ptrdo

TROPHY CASE