1 Introduction
In every state, otherwise voting-eligible individuals incarcerated pretrial or to serve a misdemeanor
sentence remain legally entitled to vote while incarcerated (The Sentencing Project,2020,2022).
The vast majority of the approximately 650,000 individuals incarcerated in county jails on any
given day are being held pretrial or to serve misdemeanor sentences (Sawyer and Wagner,2022).
Anecdotal evidence suggests, however, that many of those incarcerated in county jails are not be-
ing given adequate opportunities to exercise their right to vote (The Sentencing Project,2020).
Concerns have also been raised about possible racial disparities in ballot access for those incarcer-
ated in county jails (The Sentencing Project,2022). Yet we lack reliable causal estimates of the
impacts of being incarcerated in a county jail on the exercise of the right to vote, and of any racial
heterogeneity in those impacts.
Some recent papers have sought to estimate the impacts of prison and jail incarceration on indi-
viduals’ post-release voting behavior (Gerber et al.,2017;White,2019b;McDonough, Enamorado
and Mendelberg,2022). White and Nguyen (2022) describe the extent of voting from prison in
Maine and Vermont—the two states permitting individuals serving felony sentences to vote from
prison—but do not estimate the causal impacts of prison incarceration on voting from prison.
We leverage new data on daily individual-level jail records from the Jail Data Initiative and
exploit the timing of incarceration to estimate the causal effects of being incarcerated in a county
jail during 2020 general election voting days on the probability of voting. We probabilistically match
944,985 individual-level booking records from 936 jail rosters with 195,655,326 voter records from 42
corresponding statewide files for a period of 180 days centered on Election Day (November 3, 2020).
We identify individuals whose periods of jail incarceration began during 2020 voting days in their
state (either mail-in or in-person), or within windows ranging between 7 and 42 days after Election
Day. Our primary analyses are conducted within the sample of jailed individuals who match to
voter records with match probability p > 0.75; we also replicate analyses for the sample with match
probability p > 0.95. We interpret matches as indicating registered voters who were incarcerated
in county jails during our time period of interest. We source information about jailed registered
voters from both jail and voter records. For post-Election Day control group windows ranging
between 7 and 42 days, we conduct a series of balance tests on individual-level and booking-level
characteristics, including age, race, gender, partisanship, and number and kind of booking charges,
to identify the pre-Election Day treatment group windows within which individuals booked into
county jails during 2020 voting days (either mail-in or in-person) were observably indistinguishable
(joint F-test p-value >0.10) from individuals booked into the same jails during post-Election Day
control group windows. For records with match probability p > 0.75, the balanced samples range
in size from 57,821 (28-day control group window) to 103,091 (42-day control group window).
Our identification strategy rests on the assumption that individuals booked into the same jail
within a narrow temporal window, who are indistinguishable on observed characteristics, are also
indistinguishable on unobserved characteristics. If this assumption is correct, we can use the 2020
turnout of individuals booked into county jails just after the last 2020 voting day as a valid coun-
1