Is Public Safety Realignment
Reducing Recidivism in California?
June 2014

Magnus Lofstrom, Steven Raphael, and Ryken Grattet
with research support from Brandon Martin

Supported with funding from the Smith Richardson Foundation

Summary
California has had one of the highest recidivism rates in the nation for more than a decade. This contributed
to overcrowding in the state’s expensive prison system and helped to motivate wide-ranging corrections
reform legislation in 2011, commonly referred to as public safety realignment. Realignment essentially halted
the practice of sending parole violators back to state prison and instead made counties responsible for
supervising and sanctioning most released offenders. It also cut in half the maximum sentence for a
supervision violation—from one year to six months.
How are these changes affecting the state’s recidivism rates? We find that the post-realignment period has
not seen dramatic changes in arrests or convictions of released offenders. In the context of realignment’s
broad reforms to the corrections system, our findings suggest that offender behavior has not changed
substantially.
Overall arrest rates of released offenders are down slightly, with the proportion of those arrested within a
year of release declining by 2 percentage points. At the same time, the proportion of those arrested multiple
times has increased noticeably, by about 7 percentage points. These higher multiple arrest rates may reflect
the substantial increase in the time that released offenders spend on the streets—a result of counties’ limited
jail capacity (Lofstrom and Raphael 2013).
Convictions among released offenders have increased, but this increase does not appear to reflect changes in
offender behavior so much as changes in arrest procedures and prosecutorial approaches. The likelihood
that an arrest will lead to a conviction has increased by roughly 3 percentage points. Furthermore, the
proportion of released offenders who are actually convicted has increased about 1.2 percentage points—a
small but statistically significant rise—and nearly all of these new convictions are for felonies. Together,
these findings suggest that new offenses are increasingly being processed through the courts as formal
felony charges and convictions, rather than as technical violations through the Board of Parole Hearings.
Finally, our analysis shows that realignment has, as intended, led to a considerable 33 percentage point drop
in the proportion of released inmates who are returned to state prison. This demonstrates that realignment
has made substantial progress in one of its main goals: reducing the use of prison as a sanction for parole
violations and minor criminal offenses.
Taken together, our findings suggest that county efforts are at least partly offsetting the effects of increased
street time among released offenders. Changes in arrest and conviction rates have been modest—but these
rates remain high in the post-realignment period. State and local authorities need to develop more effective,
targeted policies aimed at both deterring crime and connecting released offenders to rehabilitative services.
California needs such strategies to bring recidivism rates down to levels that will relieve pressure on state
prison and county jails, and help the state reach the federally mandated prison population threshold.

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Is Public Safety Realignment Reducing Recidivism in California?

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Contents
Summary

2

Figures

4

Tables

4

Abbreviations

5

Introduction

6

Realignment Has Dramatically Changed Reliance on Prisons

8

Measures of Recidivism and Methods for Gauging the Effect of Realignment

11

Adjusting for changes in the composition of release groups

12

Empirical Strategy

14

Changes in Offender Characteristics Affected Recidivism Rates

17

Conclusions

27

References

29

About the Authors

30

Acknowledgments

30

Technical appendices to this paper are available on the PPIC website:
www.ppic.org/content/pubs/other/614RGR_appendix.pdf

Figures
1

Parolee returns to California state prisons stood out before realignment

9

2

Released inmates have served longer terms and are less likely to be released
after a parole revocation

13

3

Prisons in California are no longer housing inmates for short stays

14

4

Unadjusted recidivism rates fell with realignment

18

5

Recidivism trends are different after adjusting for released prisoner characteristics

19

6

Key recidivism trends declined after realignment after adjusting for released
offender characteristics

20

7

Returns to custody without arrest are disappearing

21

8

Felony arrests are higher among post-realignment offenders

21

9

Released offender misdemeanor conviction rate fell post-realignment

22

10 Felony conviction rates rose after adjusting for released prisoner characteristics

22

11 Statistically adjusted conviction rates are higher after realignment

23

12 Multiple arrests vary noticeably across release cohorts

25

13 Post-realignment released offenders are more likely to be arrested multiple times

26

14 The increase in multiple arrest is especially noticeable

26

Tables
1

Differences between pre- and post-realignment released offenders are notable

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4

Abbreviations
CDCR

California Department of Corrections and Rehabilitation

PRCS

Post-Release Community Supervision

RTC

Return-to-Custody

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Is Public Safety Realignment Reducing Recidivism in California?

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Introduction
Recidivism is the term corrections policymakers and experts use to describe the return to offending by
individuals previously convicted of a crime. It is the most salient measure of a correctional system’s overall
performance. For more than a decade, California has had one of the highest recidivism rates in the United
States (PEW Center on the States 2011), widely regarded as a mark of the failure of the state’s correctional
system. 1 Historically, unique features of California’s system partly explained its high rates. Most importantly,
California placed every released offender under state parole supervision and returned large numbers of released
offenders to prison for parole violations as measured by returns to prison (Grattet, Petersilia, and Lin 2008).
In 2011, California enacted Assembly Bill 109, known as public safety realignment. This legislation
significantly changed the system. Instead of state parole, most inmates released from state prison now go to
county probation as Post-Release Community Supervision (PRCS) cases. Individuals who violate PRCS rules
and most of those who remain under the state parole system are now locally sanctioned. They serve short jail
terms or some non-jail alternative instead of returning to state custody. Former prison inmates under PRCS
or state parole are eligible for discharge from supervision if they have no violations for six months, down
from 13 months before realignment. Under realignment, it is difficult to return released inmates to prison.
Released offenders must be convicted either of a new crime involving a serious, violent, or sexual offense, or,
for people with histories of serious, violent, or sexual offenses, of a new felony. Moreover, the maximum
sentence for a supervision violation is reduced from one year to six months and the state parole board no
longer has authority to return offenders to prison. Thus, realignment has essentially ceased the flow of
released inmates back to prison. As a result, prison and state parole populations have dropped dramatically
(Lofstrom and Raphael 2013a; Grattet and Hayes 2013a; Grattet and Hayes 2013b).
In this report, we assess how these changes have affected recidivism among inmates released from the state
prison system. Realignment has eliminated the practice of returning parolees to state prison for parole
violations, reduced the maximum sentences for a supervision violation from one year to six months, placed
more emphasis on local sanctions, and relaxed thresholds for early discharge from community corrections
supervision. Former inmates who before realignment would probably be in prison for parole violations are
no longer behind bars. In other words, the reform has increased the “street time” of former prisoners
(Lofstrom and Raphael 2013a). We explore how these changes have affected measures of recidivism,
including arrests and convictions. 2
Our study does not include one important group of released prisoners convicted of a felony: so-called
1170(h) felons. These are lower-level offenders convicted of nonsexual, nonviolent, and non-serious crimes
(so-called triple-non offenses) who do not have such crimes on their criminal records. Realignment requires
that they serve their sentences in county jail instead of state prison. Statewide data do not currently track
these offenders.

1 Citing the state’s high rate of recidivism, the Little Hoover Commission declared the state’s parole system “a billion dollar failure” (Little
Hoover Commission. 2007. Solving California’s Corrections Crisis: Time is Running Out. p. ii.)
2 Measuring recidivism poses difficult challenges. CDCR historically focused on return to custody. Other groups favor arrest, conviction, or
felony arrest or conviction for particular, sometimes self-interested, reasons. No single measure of recidivism truly captures offender behavior.
Instead, discretionary system responses to offender behavior can cause variation in the significance of arrest, conviction, and return to custody.
These measurement challenges are currently the focus of state efforts to standardize a recidivism definition. For this report, we rely on measures
available in the CDCR data: arrest, conviction, and return to prison. However, proper interpretation of these measures requires further
clarification, which we provide in the report.

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Evidence presented in two CDCR Office of Research reports (2013a, 2013b) suggests little change in
recidivism under realignment. Arrests of released prisoners are down slightly and convictions are about the
same. As anticipated, far fewer released offenders are returning to CDCR custody. The CDCR reports that
arrest and conviction rates apparently declined in each month of the post-realignment period.
In this report, we build on the CDCR reports by expanding the analysis along several dimensions. First, we
reanalyze recidivism trends by defining pre- and post-realignment groups of released prisoners. We examine
one-year follow-up periods that fall entirely in either the pre-realignment or post-realignment periods. This
allows a cleaner comparison of outcomes before and after realignment. This reanalysis confirms the CDCR
finding of declining arrest rates of former inmates within a year of release. It also confirms declining
conviction rates for new felonies. We also document the sharp decline in the probability that a released
inmate will return to a state prison within a year of release. Interestingly, for parolees whose observation
year partially extends into the post-realignment period, the decline began a year before realignment’s
implementation.
Our analysis shows that changes in the characteristics of released prisoners are contributing to these
improvements in recidivism. Specifically, inmates released from prison today have on average served more
time and are much less likely to have been in prison for a parole violation. In other words, prisoners released
post-realignment are less likely to be like the pre-reform “frequent flyers” who cycled in and out of prison on
parole revocations.
Our goal is to determine whether two comparable individuals, one released pre-realignment and one postrealignment, differ in recidivism. Specifically, we want to know whether recidivism is affected by the shift in
responsibility from states to localities, potentially shorter supervision terms, and/or the increase in street
time among former inmates. 3 An answer to that question must take into account the changes in the
composition of the released inmate population noted in the previous paragraph. We use statistical methods
to adjust for these changes, allowing us to make apples-to-apples comparisons.
Our report begins by placing California in the national context, noting how realignment has all but ended
the state’s practice of returning parolees to prison via the parole board. We then discuss the channels
through which realignment may affect recidivism rates. Using CDCR data, we describe how recidivism
patterns are changing after realignment. We finish with a series of analyses comparing pre- and postrealignment released offenders, adjusting for differences in the two populations and other factors.

3 The increased street time arises from sentencing changes and county incarceration patterns under realignment. These include split sentencing,
with reduced incarceration periods because the sentence consists of a jail term followed by a period of probation, and reductions of maximum
incarceration sentences for probation or parole violations from one year to six months. Split sentencing does not apply directly to our inmate
sample because they are all released from state prison. In addition, released offenders are now eligible for discharge from supervision after six
months compared with 13 months before realignment. Furthermore, counties now must bear the full cost of locally served incarceration for
parole and probation violations, which is likely to reduce incarceration of post-realignment released prisoners. Findings consistent with these
patterns are reported in Lofstrom and Raphael (2013a).

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Realignment Has Dramatically Changed
Reliance on Prisons
In the decade before realignment, recidivism rates among California’s released offenders were consistently
among the highest in the nation (PEW Center on the States 2011). CDCR’s primary recidivism measure, the
proportion of inmates released from CDCR who returned to prison within three years, did decline before
realignment from 67.5 percent of released offenders in 2005–2006 to 61.0 percent of released offenders in
2008–2009 (CDCR 2014). Three-year arrest rates and reconviction were relatively flat, ranging between 75.3
and 77.2 percent and 47.7 and 51.5 percent, respectively.
Historically, several practices set the state apart from the rest of the nation. First, parole revocation rates for
technical violations were strikingly high. Second, parole terms were relatively lengthy, increasing the
proportion of released offenders at risk of revocation and return to prison. A recent Bureau of Justice
Statistics (BJS) report using data from 42 states provides a national context. The BJS does not provide
information on the probability that a given group of released inmates will return to prison. However, the BJS
does track the size of the parole population and total prison admissions due to parole failure. Dividing
parolee admissions over a year by the parole population at the beginning of the year provides a rough
estimate of a parolee’s risk of going back to prison during the year. This calculation allows a comparison of
California with other states in the pre-realignment period.
Figure 1 shows the number of released offenders who were returned to prison in 2010 divided by the parole
population at the beginning of the year. During the pre-reform period, California’s 68 percent return ratio
was the highest in the nation. North Dakota was a distant second at 43 percent. Strikingly, the average for all
states except California was 15 percent.

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FIGURE 1
Parolee returns to California state prisons stood out before realignment

Parolees returned to custody during 2010
divided by parole population at beginning of year

0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1

California
North Dakota
Colorado
Illinois
Utah
Arizona
Minnesota
Massachusetts
Florida
Rhode Island
West Virginia
Nebraska
South Dakota
Kansas
Kentucky
Montana
Idaho
New York
Indiana
Michigan
Wisconsin
Vermont
Maryland
Wyoming
Hawaii
Arkansas
Pennsylvania
Missouri
New Jersey
South Carolina
Oregon
Tennessee
Georgia
Nevada
Louisiana
North Carolina
Virginia
Texas
Alabama
Ohio
Alaska
Oklahoma

0

SOURCE: U.S. Bureau of Justice Statistics (Glaze and Bonczar, 2013).
NOTE: The bars represent parolee admissions to prison in 2010 as a share of the parole population at the beginning of the year.

In the post-realignment period, the pattern is drastically different. Bureau of Justice Statistics state-level data
are not yet available for 2012. However, we can glean from various sources how California’s return rate has
changed. We estimate it fell from 68 percent during the pre-realignment period to 9 percent post-realignment. 4
In other words, realignment has brought California more in line with the rest of the country in terms of
returns to prison among released inmates.
Realignment has made it much harder to send released inmates back to state prison. Before realignment, a
released offender arrested for a criminal or noncriminal parole violation had a hearing before the Board of
Parole Hearings (BPH). These procedures generally resulted in an average return to prison of four months
but sometimes as much as a year (Grattet, Petersilia, and Lin 2008). The BPH’s high return-to-custody rate
reflected several factors. First, the BPH’s evidentiary standard, the preponderance of evidence, is much less
stringent than the beyond-a-reasonable-doubt standard that applies in criminal court. Second, parolees were
technically still under state supervision, which made parole revocation relatively straightforward and
common. Third, from the viewpoint of local corrections, it was cheaper and easier to send a released inmate
back to prison via parole revocation rather than a new criminal conviction. A study of the pre-realignment
period revealed that authorities frequently used parole revocations rather than new criminal prosecutions to

4 The Bureau of Justice Statistics estimates that the combined parolee/PRCS population was 111,703 on January 1, 2012. CDCR reports that,
during 2012, 8,030 active parolees returned to its custody. We assume this does not include returns to custody of those on PRCS for new felony
convictions. Hence, we add to the total 7.2 percent of the average of the PRCS populations at the beginning of 2012 and end of 2012 (see Bonczar
and Glaze 2013 for PRCS population estimates). The 7.2 percent is our estimate of the rate at which prisoners released in the first six months of
2012 returned to state custody. This adds 1,636 admissions, generating a total admissions estimate of 9,666. Dividing by 111,703 gives a return-tocustody rate of 0.09.

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return parolees arrested for technical parole violations and a wide range of felonies to prison. Revocations
were even used for arrests involving very serious felonies (Grattet, Petersilia, and Lin 2008). This back-end
sentencing through the BPH contributed greatly to California’s high parole failure rate (Travis 2007).
Realignment has upended this system. It is now nearly impossible for authorities to send released offenders
back to prison for a technical parole violation (Petersilia and Greenlick Snyder 2013). 5 Former inmates under
PRCS or parolees with no history of serious or violent offenses may go to state prison only if they are
convicted of new serious, violent, or sexual felonies. (Parolees with histories of serious or violent crimes may
go back to prison if they are convicted of any new felony.) Instead, violators are sanctioned locally, which
may include incarceration in county jails for short stays, sometimes referred to as flash incarcerations. The
intent is to carry out these sanctions with certainty and swiftness. Local authorities may also revoke parole or
impose various forms of graduated sanctions.
These changes may affect recidivism through a number of channels. On one hand, realignment gives county
officials discretion to use a mix of sanctions and intervention to tailor programs locally. Counties may use
realignment money to fund community-based alternatives, programs based on approaches that research
shows reduce recidivism (evidence-based practices), and other initiatives. To the extent that these
alternatives have been effective, recidivism rates may have declined. In addition, shorter supervision times
and the prospect of early discharge may dissuade released offenders from committing crimes.
On the other hand, realignment has substantially reduced the number of released prisoners behind bars,
increasing their presence in the community (Lofstrom and Raphael 2013a). This increased “street time”
provides more opportunities to commit crimes, which in turn generates more arrests and convictions. 6
Furthermore, locally supervised PRCS populations face a far different set of incentives than did inmates who
left prison before realignment. For example, they face different sanctions for violating conditional release
terms. These range from flash incarceration in county jail, to community service, mandatory treatment,
electronic monitoring, or other county-imposed penalties. Recidivism may drop if released offenders perceive
local sanctions as swift and certain (Hawken and Kleinman 2009). By contrast, recidivism might increase if
local sanctions are perceived as less severe than in the past. Similarly, the lower probability of prison time
under realignment could embolden some parolees to commit crimes (Lofstrom and Raphael 2013a).
Other aspects of realignment, however, may deter released inmates from committing felonies. PRCS
offenders arrested for new felonies may now be more likely to face prosecution and conviction because the
option to send them back to prison by revoking parole no longer exists. New felony convictions carry stiffer
sentences than do technical parole violations. Moreover, county jail space is costly and limited, which may
further increase the probability that re-offending will lead to prison time.
In the rest of the report, we examine whether changes in California’s recidivism rates are due to realignment.
We compare data on arrests, convictions, and returns to state prison (known as return-to-custody or RTC) in
the pre- and post-realignment periods to assess how realignment has affected recidivism among former state
prisoners. Specifically, we analyze changes in the rates of arrest, multiple arrests, new criminal convictions,
and returns to state prison within one year.

5 Released offenders who have served an indeterminate life sentence may still go back to prison for a parole violation (Petersilia and Greenlick
Snyder 2013).
6 The increase in offender street time caused by realignment led to a slight increase in property crime in the first post-realignment year (Lofstrom
and Raphael 2013b).

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Measures of Recidivism and Methods for
Gauging the Effect of Realignment
In this section, we describe in detail the data we use and our statistical methodology. The California
Department of Corrections and Rehabilitation (CDCR) Office of Research provided us with individual
administrative records for all inmates released from state prison between October 1, 2009, and June 30, 2012.
In most respects, these are comparable with the data used in the CDCR reports on recidivism and
realignment (2013a, 2013b). We requested release data going back further than the period analyzed by
CDCR to allow us to construct a comparison group of inmates not affected by realignment.
The CDCR records include information on post-release arrests, criminal convictions, and returns to state
prison due either to parole revocation or new conviction, referred to as a parole revocation with a new term.
The data combine CDCR administrative records with information from automated individual criminal
history files maintained by the California Department of Justice. We track each released inmate for one year
following release. Within this year, we can observe arrests, the arrest charge, and conviction for a new crime.
We also consider the probability that a released offender will be arrested or convicted multiple times. In
addition, we determine whether released offenders go back to prison. However, we do not have information
on local sanctions imposed for supervision violations, including time in county jail.
We divide released offenders into three groups that vary in the extent to which the one-year observation
period following release coincided with realignment. State parole authorities supervised members of the first
two groups. County probation personnel monitored the larger share of the third group, while state parole
authorities supervised the rest.
The first group consists of inmates released between October 1, 2009, and September 30, 2010. Their one-year
post-release observation period ended before implementation of realignment on October 1, 2011. Hence,
observation of this group occurs entirely under the pre-realignment state parole supervision system.
The second group includes inmates released under state parole supervision between October 1, 2010, and
September 30, 2011. Offenders who would have been eligible for PRCS, but were released in the year before
October 1, 2011, spent part of the one-year observation period under the old parole system and part under
the new system. Notable changes included a six-month discharge for parolees with no violations and
incarceration in county jail rather than state prison for parole revocations. The degree to which this group
was exposed to realignment varied. The earlier released inmates, for example those released from prison
soon after October 2010, had relatively little exposure. The later released inmates, for example those released
closer to October 2011, had more exposure. To illustrate, an inmate released in early July 2011 experienced
three months under the old system and nine months under the new. Given the decline in returns to prison
for parole revocation, prison admissions rates should have fallen even for inmates released as much as one
year before realignment’s implementation.
The final group of inmates includes those released between October 1, 2011, and June 30, 2012, supervised
either by state parole or county probation (PRCS). As these release dates follow the implementation of
realignment, the full one-year observation period occurs under the new realignment structure for all members
of this group. Of course, those released to PRCS arguably experienced the greatest practical changes in postrelease supervision as they were monitored by county probation departments rather than state parole
authorities. Our primary estimates of realignment’s effects on recidivism compare the first and third groups.
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Is Public Safety Realignment Reducing Recidivism in California?

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However, we also analyze what happened to inmates partially exposed to the reform. By contrast, the
CDCR’s analysis compared released inmates in our second group with inmates in our third group.
It is important to note, again, that this study focuses solely on recidivism among released prison inmates.
We do not analyze recidivism among nonviolent, nonsexual, non-serious offenders sentenced to local
sanctions under section 1170(h) of the amended penal code.

Adjusting for changes in the composition of release groups
We examine recidivism before and after realignment to evaluate how released inmates are doing under the
new rules, compared to how they fared under the old parole system. Based on the CDCR reports, the raw
trends suggest that released offenders are doing well under realignment, that is, recidivism rates are
generally lower. However, we must be cautious before concluding realignment has led to this improvement.
First, as we have noted, for those released from prison in the twelve months before the beginning of
realignment, part of their one-year follow-up extended into the post-realignment period. For those released
just before October 1, 2011, nearly all the follow-up occurred after realignment. A more valuable assessment
is to compare recidivism among a group of offenders not affected by realignment with recidivism in a group
entirely exposed to the reform. The CDCR reports do not do this.
Second, the characteristics of inmates released from prison began to change quickly after the reform’s
implementation. The parolee return-to-custody rate in the pre-realignment period was high. Parole
revocations accounted for the great majority of state prison admissions. Often these inmates served very
short prison terms. Consequently, in the pre-realignment period, a disproportionate number of prison
releases consisted of inmates leaving prison after a short stay following parole revocation. These individuals,
who cycled in and out of prison on very short spells, were sometimes called “frequent flyers.” 7
Figure 2 shows the proportion of inmates released in a given month who have been released after a parole
revocation (that is to say, the proportion that are re-releases or “frequent flyers”) as well as the average time
served for the most recent prison stay among those released. 8 Vertical lines demarcate our three groups.
Before October 2011, the proportion of inmates who were released following a parole revocation hovered
between 43 and 45 percent. Nine months into the reform, this proportion dropped below 10 percent. The frequent
flyers were no longer going back to prison. Meanwhile, in the pre-realignment period, the average time a
released offender served was slightly more than 400 days. In the post-realignment period, it rose to more
than 800 days. Recent research demonstrates that recidivism rates are lower for inmates who have served
more time (Kuziemko 2013). Thus, the sharp drop in imprisonment for parole violations and longer prison
stays would both tend to reduce recidivism rates independently of any effect of changes in post-release
supervision practices.

7

The improved economy in California is another factor that may contribute to lower recidivism rates.
The declines in time served and percent of re-releases are direct consequences of realignment. Re-releases have been falling because parolees no
longer return to custody for parole violations or for non-violent, non-serious new crimes. Nor can parolees or offenders released under PRCS be
imprisoned while a revocation is pending and then returned to the community, as sometimes happened before realignment. Realignment limited
the time these offenders could spend in custody. Subtracting them from the prison population would necessarily increase the average time
served by those who were released.
8

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FIGURE 2
Released inmates have served longer terms and are less likely to be released after a parole revocation

900

No Realignment
Exposure

Some Realignment
Exposure

All Realignment
Exposure

60%

Days in Custody
Re-Releases

800
50%

40%

600
500

30%
400
20%

300

Share of re-releases

Days in custody

700

200
10%
100
0%

0
-24 -22 -20 -18 -16 -14 -12 -10

-8

-6

-4

-2

0

2

4

6

8

Realignment month
SOURCE: Authors’ calculations based on CDCR individual administrative data.
NOTE: The figure shows the share of re-releases (those released after a parole revocation) and average number of days in
custody at release by monthly release cohort. These cohorts are defined by month of release relative to realignment. For
example, realignment month 0 consists of all offenders released in October 2011, the first month of realignment.

The dramatic change in the composition of released inmates is even more striking when we examine in
greater detail the amount of time served among those released. Figure 3 compares those released during
two specific pre- and post-realignment periods: May through June 2010, with no exposure to realignment;
and May through June 2012, with full exposure to realignment. 9 The figure breaks down days served by
percentile. For example, during the no-exposure-to-realignment period, at the 10th percentile, 10 percent of
released offenders were in CDCR custody for 21 days or less and 90 percent for more than 21 days. In the
full-exposure-to-realignment period, the 10th percentile level rose to 201 days. At the 25th percentile level,
one quarter of released offenders served 83 days or less in prison before realignment compared with 285 days
after realignment. The median time served by a released prisoner is the level at which half of all offenders
served less time and half served more. In the pre-reform period, the median offender had served slightly
longer than six months. After reform, the median rose to more than 14 months.

9

These are the most recent releases in our data.

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FIGURE 3
Prisons in California are no longer housing inmates for short stays
2,000

May to June 2010 releases
1,751

Days in CDCR custody
at time of release

1,800

May to June 2012 releases

1,600
1,400
1,200
1,000

823

859

800
600

437

400
201

200

397

285
21

197
83

0
10th

25th
50th
75th
Percentile of distribution of days in custody

90th

SOURCE: Authors’ calculations based on CDCR individual administrative data.

Comparisons of released prisoners before and after realignment clearly illustrate that the characteristics of
offenders have changed in important ways. Released offenders are now substantially less likely to be frequent
flyers. Furthermore, many newly convicted lower-level felons now serve time in county jail instead of state
prison. That means that released prisoners are likely to have been convicted of different types of crimes under
realignment than before the reform. Other factors also may affect the probability of recidivism. Any attempt
to isolate the effects of realignment on recidivism must take into account these compositional changes.

Empirical Strategy
Analyzing the effects of realignment on recidivism requires several adjustments. First, we must separate prerealignment and post-realignment groups. That means comparing released offenders for whom the one-year
follow-up is entirely in the pre-realignment period with those for whom the follow-up is completely postrealignment. To make this clean comparison, we set aside our second group of released offenders, those let
out between October 1, 2010, and September 30, 2011, whose one-year follow-up spans the pre-realignment
and post-realignment periods. 10 Rather than using the combination of the ”Some Realignment Exposure”
and “All Realignment Exposure” groups as the pre-period comparison group (similar to what is done in the
CDCR recidivism reports), our primary analysis compares the ”No Realignment Exposure” to the ”All
Realignment Exposure” group. We do however include the “Some Realignment Exposure” group in our
graphical analysis of statistically adjusted trends to illustrate some gradual changes that have occurred in
recidivism outcomes.
Second, we need to account for changes in the characteristics of released prisoners in our assessment of
whether recidivism rates have changed with realignment. Table 1 illustrates these changes. The table
compares the average characteristics of a pre-realignment group of inmates released between October 1,

10

This is the “Some Realignment Exposure” group in Figure 2.

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2009, and June 30, 2010, with a post-realignment group released between October 1, 2011 and June 30, 2012.11
Table 1 shows differences between the pre- and post-realignment release cohorts in average age, race/
ethnicity, criminal history, mental health status, and other variables. There is a large difference in the
percentage who are re-releases (those released after being sent to prison on a parole revocation); 45.6 percent
were re-releases in the earlier period compared with 26.5 percent in the later period. Another key difference
lies in the average days in CDCR custody. This increased from 406.7 days in the pre-realignment period to
609.5 in the post-realignment period. As expected, fewer post-realignment inmates served time for property
and drug crimes.
In our empirical analysis, we statistically adjust for the differences in the pre-realignment and post-realignment
cohorts shown in Table 1 using multivariate regression modeling. We present results with and without these
statistical adjustments. This permits us to reproduce CDCR’s analysis and assess whether recent trends in
unadjusted recidivism measures are in part due to the changing characteristics of those released from state
prison. We provide a detailed discussion of our statistical methodology in the technical appendix.

11

To ensure seasonality is not affecting recidivism, we use two cohorts that cover the same nine months, October through June, of releases.

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TABLE 1
Differences between pre- and post-realignment released offenders are notable
Pre Cohort

Post Cohort

Released between
Oct 1, 2009–
Jun 30, 2010
36.1

Released between
Oct 1, 2011–
Jun 30, 2012
36.0

Male

89.6%

90.8%

1.2%

1.4%

White

30.8%

29.6%

-1.3%

-4.1%

Age at Release

Difference
Level
-0.1

%
-0.2%

Hispanic

37.8%

40.0%

2.2%

5.9%

Black

26.7%

25.4%

-1.4%

-5.2%

4.7%

5.1%

0.4%

9.0%

Other race/ethnicity
Sex Offender

8.7%

10.1%

1.5%

16.9%

CDCR Serious Indicator

11.1%

13.8%

2.7%

24.2%

CDCR Violent Indicator

10.7%

14.6%

3.9%

36.6%

Prior Serious Crime

12.0%

13.7%

1.6%

13.4%

Prior Violent Crime

10.3%

11.2%

0.9%

9.2%

Number of Prior Serious Crimes

0.16

0.18

0.02

12.1%

Number of Prior Violent Crimes

0.15

0.17

0.02

10.1%

Violent Offense Category

25.9%

31.3%

5.4%

20.9%

Property Offense Category

32.4%

30.5%

-1.8%

-5.7%

Drug Offense Category

28.6%

24.4%

-4.2%

-14.5%

Other Offense Category

13.1%

13.7%

0.6%

4.3%

Second Striker

13.1%

14.9%

1.8%

13.9%

Determinate Sentence

86.6%

84.5%

-2.1%

-2.5%

0.3%

0.6%

0.3%

102.2%

2.7%

3.1%

0.4%

13.3%

21.0%

21.2%

0.2%

0.8%

Life Sentence
Mental Health Status
Enhanced Outpatient Program
Correctional Clinical Case Mgmt System
Static Risk Assessment Score
CSRA Risk: High, Violent Crime

30.9%

32.4%

1.6%

5.1%

CSRA Risk: High, Property Crime

17.7%

16.8%

-0.9%

-5.3%

CSRA Risk: High, Drug Crime

11.6%

9.5%

-2.1%

-18.0%

CSRA Risk: Medium

24.3%

24.4%

0.0%

0.2%

CSRA Risk: Low

15.5%

16.9%

1.4%

9.1%

Days in Custody
Re-release
Number of Released Offenders

406.7
45.6%
81,539

609.5
26.5%

202.8

49.9%

-19.2%

-42.0%

49,798

SOURCE: Authors’ calculations based on CDCR individual administrative data.

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Changes in Offender Characteristics
Affected Recidivism Rates
In this section, we present our findings in a series of charts. We depict trends in recidivism outcomes for
released offenders by their month of release and present evidence on trends with and without statistically
adjusting for changes in the characteristics of released offenders. We then formally estimate the effect of
realignment on recidivism by comparing the pre-realignment and post-realignment cohorts.
Figure 4 shows unadjusted one-year arrest rates, conviction rates, and returns according to month of release
for inmates leaving California prisons. 12 The measurement period includes each of the 24 months preceding
realignment’s implementation and the first nine months of the post-reform period. Months are measured
along the horizontal axis. The value of October 2011 is set to zero and other months are measured relative
this month of implementation.
We use two alternative definitions of arrests: arrest and arrest adjusted for return to custody (RTC). The first
measures the proportion of released offenders arrested and officially booked at a California police station or
jail, which generates a new record of arrest in an individual’s criminal history record maintained by the
California Department of Justice. The second definition includes arrests made by parole officers. When a
parole officer takes a detained parolee directly to a prison reception center, the arrest is not always recorded
in the individual’s criminal history. Under realignment, state parole authorities supervise many fewer released
offenders and RTCs are greatly restricted. Thus, these types of parolee arrests are increasingly rare and
don’t occur at all for former prisoners released under PRCS. 13 This point is important because a pre- and
post-realignment comparison of arrests not adjusted for the RTC factor will understate pre-realignment
arrests much more than post-realignment arrests.
Figure 4 reveals that one-year arrest rates declined among post-realignment released offenders. The arrest
rate not adjusted for direct returns to custody rose leading up to the reform’s implementation. However,
the adjusted arrest rate, including arrests made by law enforcement and parole officers, was relatively
stable in the pre-reform period. As expected, the two series converged in the post-realignment period.
Parole officers could no longer directly revoke most paroles. As a result, virtually all parolee arrests began
to include an official booking.

12

We define each release cohort by the first prison release for all those released in a given month. It is possible, but extremely rare, to be released
twice in a month.
13 CDCR recidivism reports also make this adjustment.

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FIGURE 4
Unadjusted recidivism rates fell with realignment

One year recidivism rate

70%

No Realignment
Exposure

Some Realignment
Exposure

All Realignment
Exposure

60%

Arrested

50%

Arrested (Adjusted for RTC
w/o arrest)
Convicted

40%

Return to Prison
30%
20%
10%
0%
-24 -22 -20 -18 -16 -14 -12 -10 -8

-6

-4

-2

0

2

4

6

8

Realignment month
SOURCE: Authors’ calculations based on CDCR individual administrative data.
NOTE: The figure presents recidivism outcomes for groups of released offenders defined by month of release relative to realignment.
For example, realignment month 0 includes all prisoners released in October 2011, the first month of realignment.

Returns to prison exhibited the most dramatic trend. Among prisoners released before October 2010,
roughly 43 percent went back to prison within one year of release. However, beginning with the October 2010
release cohort, the return rate showed a steady decline over the year. In the post-realignment period, the
return-to-prison rate stabilized below 10 percent. The sharp drop in the year leading up to realignment
occurred because inmates released in the year preceding realignment were partially exposed to the reform
during the year follow-up period. With the implementation of the realignment legislation, prison admissions
due to parole violations dropped sharply and quickly (Lofstrom and Raphael 2013a). Hence, someone released
in, say, July 2011, was under the old parole system from July through September 2011. That individual then
came under the new system, with lower revocation rates, from October 2011 through July 2012. The closer a
prisoner’s release month was to October 2011, the more that prisoner’s one-year follow-up fell in the postrealignment period. This factor drove down the RTC rate in the year leading up to realignment’s implementation.
Finally, Figure 4 shows the proportion of ex-prisoners convicted of a new crime in the year following release.
Inmates released in the year before realignment appear to have had slightly increased conviction rates. After
realignment, conviction rates decreased for each monthly release cohort.
Figure 5 shows recidivism trends after adjusting for changes in the characteristics of released prisoners. The
adjusted trends are noticeably different. We interpret Figure 5 as illustrating what recidivism trends would
have been if the characteristics of released inmates had not changed over our analysis period. Alternatively,
the differences between Figures 5 and 4 can be attributed to the fact that relatively fewer released offenders
today are re-releases (those released after a parole revocation) and today’s released offenders have served
more time than those released pre-realignment.
Figure 5 shows both arrest measures were stable for “No Realignment Exposure” offenders. After
realignment, arrest rates were also stable across monthly release groups. Arrests not including direct RTC
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increased slightly, while arrests including RTC fell a bit. After adjustment, the proportion of inmates
returned to prison within a year still fell sharply. However, in the first few months of realignment, the
statistically adjusted RTC rate rose from roughly 7 to 14 percent. Finally, when we adjust for released
prisoner characteristics, the post-realignment decline in conviction rates evident in Figure 4 vanished and the
rate increased slightly.
FIGURE 5
Recidivism trends are different after adjusting for released prisoner characteristics

70%

No Realignment
Exposure

Some Realignment
Exposure

All Realignment
Exposure

One year recidivism rate

60%
50%

Arrested
Arrested (Adjusted for RTC
w/o arrest)
Convicted

40%
30%

Return to Prison

20%
10%
0%
-24 -22 -20 -18 -16 -14 -12 -10 -8

-6

-4

-2

0

2

4

6

8

Realignment month
SOURCE: Authors’ calculations based on CDCR individual administrative data.
NOTE: The figure presents statistically adjusted recidivism outcomes for groups of offenders defined by month of release relative
to realignment. For example, realignment month 0 includes all prisoners released in October 2011, the first month of realignment.

Figure 6 shows average recidivism measures for pre-realignment and post-realignment groups with and
without adjustment for changes in released offender characteristics. Thus, the figure presents our formal
estimates of the effect of realignment on recidivism.
Without statistical adjustment, the probability of arrest within a year of release, not counting direct returns
to custody, decreased slightly. With adjustment, the probability increased 2.6 percentage points, which is
marginally statistically significant. 14 However, when direct returns to custody are included, both the
unadjusted and adjusted estimates showed statistically significant declines in one-year arrest rates. The
decline in arrest rates adjusted for RTC is one of the principal findings of the CDCR analyses. We are able to
reproduce the department’s results here using distinct pre- and post-realignment comparison groups.

14 See the formal analysis in Technical Appendix Tables A1 and A2 and the accompanying discussion for a more complete examination of the
statistical significance of the estimates in this section.

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FIGURE 6
Key recidivism trends declined after realignment after adjusting for released offender characteristics

Estimated diiferences in recidivism outcomes,
pre- and post-realignment

5%

2.6%

1.2%

No statisitcal adjustment

0%
-5%

-1.1%

-2.0%

Statistically adjusted

-0.9%

-6.1%

-10%
-15%
-20%
-25%
-30%
-35%

-33.1%
-35.4%

-40%
Arrested

Arrested Adjusted
for RTC w/o arrest

Convicted

Returned to prison

SOURCE: Authors’ estimates based on CDCR individual-level administrative data.
NOTE: See Technical Appendix Tables A1 and A2 for formal estimation results with standard errors.

Without adjustment, we estimate a slight, statistically insignificant decline in new conviction rates. Adjusting
for released prisoner characteristics, we estimate, on average, the “Full Realignment Exposure” group was
1.2 percentage points more likely than the “No Realignment Exposure” group to acquire a new conviction.
As we will show shortly, this increase in the conviction rate for post-realignment offenders is likely driven in
its entirety bv a notable increase in the likelihood of conviction among former inmates who are arrested
following release. Finally, our unadjusted and adjusted measures show 35 and 33 percentage point drops in
the probability of return to prison within a year. These are very large declines.
Figure 7 displays the unadjusted changes in arrest patterns in the months before and after realignment
subdivided into supervision violations, felonies, and misdemeanors. For supervision violations, we show
both standard arrest rates and return-to-custody rates, which allows us to account for the pre-realignment
practice of returning parole violators to prison without recording an arrest. Before realignment, the
difference between arrest and RTC rates ranged from about 4 to 6 percentage points. After realignment, the
lines tracked each other in a registering a sharp 8-percentage-point drop before tacking up slightly among
prisoners released in later months. The proportion of released offenders arrested for felonies rose slightly
among those let out immediately after realignment. However, for groups released in subsequent months, the
felony arrest rate fell. Misdemeanor arrest rates declined steadily after realignment. The tiny proportion of
arrests for unknown causes increased slightly.

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FIGURE 7
Returns to custody without arrest are disappearing
No Realignment
Exposure

30%

Some Realignment
Exposure

All Realignment
Exposure

One year arrest rate

25%

Supervision Violation/RTC
Supervision Violation

20%

Felony
Misdemeanor

15%

Unknown

10%
5%
0%
-24 -22 -20 -18 -16 -14 -12 -10 -8 -6 -4
Realignment month

-2

0

2

4

6

8

SOURCE: Authors’ calculations based on CDCR individual administrative data.
NOTE: The figure presents recidivism outcomes for groups of released offenders defined by month of release relative to realignment.
For example, realignment month 0 includes all prisoners released in October 2011, the first month of realignment.

Figure 8 presents comparable arrest trends after statistically adjusting for changes in the characteristics of
released prisoners. Misdemeanor arrests dropped by a statistically significant 1.2 percentage points.
Supervision violation arrests dropped on average by 3.7 percentage points but increased for those released in
the last months of the measurement period. Felony arrests averaged 2.1 percentage points higher in the postrealignment period but fell slightly among the later groups of released offenders.
FIGURE 8
Felony arrests are higher among post-realignment offenders

30%

No Realignment
Exposure

Some Realignment
Exposure

All Realignment
Exposure

One year arrest rate

25%
Supervision Violation/RTC

20%

Supervision Violation
15%

Felony
Misdemeanor

10%

Unknown

5%
0%
-24 -22 -20 -18 -16 -14 -12 -10 -8 -6 -4
Realignment month

-2

0

2

4

6

8

SOURCE: Authors’ calculations based on CDCR individual administrative data.
NOTE: The figure presents regression-adjusted recidivism outcomes for groups of released prisoners defined by month of release relative
to realignment. For example, realignment month 0 includes all prisoners released in October 2011, the first month of realignment.

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Figure 9 presents estimates of the proportion of each release cohort convicted of a new felony or a new
misdemeanor within a year of release. The figure shows that the proportion of released offenders convicted
of a felony in the first few months following realignment’s implementation rose slightly then declined. Postrealignment, the proportion convicted of a new misdemeanor fell almost uniformly.
FIGURE 9
Released offender misdemeanor conviction rate fell post-realignment
No Realignment
Exposure

16%

Some Realignment
Exposure

All Realignment
Exposure

One year conviction rates

14%
12%
10%

Felony
Misdemeanor

8%
6%
4%
2%
0%
-24 -22 -20 -18 -16 -14 -12 -10

-8

-6

-4

-2

0

2

4

6

8

Realignment month
SOURCE: Authors’ calculations based on individual level administrative data provided by CDCR.
NOTE: The figure presents recidivism outcomes for groups of released offenders defined by month of release relative to realignment.
For example, realignment month 0 is all offenders released in the month of October 2011, the first month of realignment.

Figure 10, controlling for changes in released offender characteristics, shows a modest, but more sustained
increase in the felony conviction rate. With adjustment, post-realignment misdemeanor convictions declined
modestly, but showed no statistically significant difference from the pre-realignment period.
FIGURE 10
Felony conviction rates rose after adjusting for released prisoner characteristics

One year conviction rate

16%

No Realignment
Exposure

Some Realignment
Exposure

All Realignment
Exposure

14%
12%

Felony

10%

Misdemeanor

8%
6%
4%
2%
0%
-24 -22 -20 -18 -16 -14 -12 -10 -8 -6 -4
Realignment month

-2

0

2

4

6

8

SOURCE: Authors’ calculations based on individual CDCR administrative data.
NOTE: The figure presents regression adjusted recidivism outcomes for groups of offenders defined by month of release relative
to realignment. For example, realignment month 0 is all offenders released in October 2011, the first month of realignment.

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Figure 11 presents our formal estimates of the effects of realignment on felony and misdemeanor conviction
rates with and without statistical adjustment. Unadjusted felony convictions declined slightly postrealignment. With adjustment, the likelihood of a felony conviction rose by roughly one percentage point
under realignment. Unadjusted misdemeanor convictions edged down a statistically significant 0.9
percentage point. With adjustment, we estimate the misdemeanor conviction rate increased a slight but
statistically significant 0.2 percentage point.
Hence, the increase in new convictions among released inmates is mostly driven by an increase in the
likelihood of a felony conviction. Which mechanisms are leading to this increase in conviction rates? This
question is especially important in light of our finding that the proportion of released offenders arrested
within one year has declined. There are two broad possibilities. First, the greater amount street time
associated with realignment may yield higher offending levels among those likely to be arrested. In this case,
realignment would be directly contributing to higher crime rates. Alternatively, prosecutors may be
choosing to prosecute cases that in the pre-realignment period would have been diverted (often by default)
to the Board of Parole Hearings, resulting in higher conviction rates relative to what was observed in the
past. We are able to partially explore this issue by assessing whether the likelihood of being convicted, given
an arrest, has changed. To the extent that this probability increases, an arrest today is more likely to result in
a new conviction relative to an arrest in the past, when an arrest could lead to prison incarceration through a
parole revocation.
Figure 11 presents unadjusted and statistically adjusted estimates of the effects of realignment on this
probability. With no adjustment, we observe an increase of 2.5 percentage points in conviction rates among
those arrested within one year. Adjusting for the changes in the composition of released offenders increases
this estimate to 3.1 percentage points. Both are statistically significant.
FIGURE 11
Statistically adjusted conviction rates are higher after realignment

Estimated diiferences in recidivism outcomes,
pre- and post-realignment

3.5%

3.1%

3.0%
2.5%

2.5%

No statistical adjustment
Statistically adjusted

2.0%
1.5%
1.0%

1.0%
0.5%

0.2%

0.0%
-0.02%

-0.5%
-1.0%

-0.9%

-1.5%
Felony conviction

Misdemeanor conviction

Convicted conditional on
arrest

SOURCE: Authors’ estimates based on CDCR individual administrative data.
NOTE: See Technical Appendix Tables A1 and A2 for formal estimation results with standard errors.

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Is Public Safety Realignment Reducing Recidivism in California?

23

This change, likely reflecting a change in practice by prosecutors across the state, is of sufficient magnitude
to fully explain the increase in conviction rates in our statistically adjusted models. 15 Our estimates indicate
that the probability of conviction given an arrest increase about 0.031 (that is, an increase of about 3.1
percentage points). Our analysis of arrest trends show that in the pre-realignment period the one-year arrest
probability is roughly 0.6, that is 60 percent were arrested within one year. With an arrest probability of 0.6
and an increase in the likelihood of conviction conditional on arrest of 0.031, the change in the proportion
convicted of a new crime due to a prosecutorial change alone would be about 1.9 percentage points (found
by multiplying 0.6 x 0.031). As we observe an increase in conviction rates of 1.2 percentage points, the higher
likelihood of a conviction among those arrested is of sufficient magnitude to explain the entirety of the
increase in conviction rates.
Our final set of results assess changes in the proportion of released offenders who are arrested or convicted
multiple times within the year after their release. As we have noted in our earlier work (Lofstrom and
Raphael 2013), “street time” for offenders released from state prison has increased. As a result, offenders
released after realignment who are motivated to commit crime have greater opportunity to do so and thus
more opportunity for interaction with the criminal justice system—therefore, any given released offender
may generate a greater number of formal arrests.
We have already shown that the likelihood of conviction conditional on arrest has increased. Increases in
street time could drive up convictions just as it may have done for arrests. Also, given that realignment
eliminated the parole board’s management of “frequent flyer” offenders, it would follow that prosecutors
might increase their propensity to seek convictions in relation to those offenders.
Figure 12 presents, by month of release, the unadjusted proportion of inmates who are arrested and
convicted multiple times during the year following their release from prison. The figure reveals that
the proportion experiencing multiple arrests increased among pre-realignment releases as we approach
October 2011, suggesting that as exposure to the post-realignment changes in parole revocations
increased, the likelihood of multiple arrests also increased. However, in the post-realignment period
this proportion declined each month.

15 To be specific, note that the conviction rate is equal to the number of individual convicted within one year divided by the population total for
the specific release cohort. With a simple re-writing of this formula, one can show that the convictions rate is equal to the one-year arrest rate
𝑐𝑜𝑛𝑣𝑖𝑐𝑡𝑖𝑜𝑛𝑠
𝑎𝑟𝑟𝑒𝑠𝑡𝑠
𝑐𝑜𝑛𝑣𝑖𝑐𝑡𝑖𝑜𝑛𝑠
multiplied by the conviction rate among those arrested, or 𝐶𝑜𝑛𝑣𝑖𝑐𝑡𝑖𝑜𝑛 𝑅𝑎𝑡𝑒 =
=
.
.
𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛

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𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛

𝑎𝑟𝑟𝑒𝑠𝑡𝑠

Is Public Safety Realignment Reducing Recidivism in California?

24

FIGURE 12
Multiple arrests vary noticeably across release cohorts

50%

No Realignment
Exposure

Some Realignment
Exposure

All Realignment
Exposure

One year multiple arrest
and conviction rates

45%
40%
35%

Multiple Arrests

30%

Multiple Convictions

25%
20%
15%
10%
5%
0%
-24 -22 -20 -18 -16 -14 -12 -10 -8

-6

-4

-2

0

2

4

6

8

Realignment month
SOURCE: Authors’ calculations based on CDCR individual administrative data.
NOTE: The figure presents recidivism outcomes for groups of released offenders defined by month of release relative to
realignment. For example, realignment month 0 is all offenders released in October 2011, the first month of realignment.

Figure 13 presents the comparable trends after statistically adjusting for the changing composition of
released offenders. The statistically adjusted trends clearly show that post-realignment, released offenders
are substantially more likely to experience multiple arrests within one year of release. Comparing Figures 12
and 13, it becomes clear that the post-realignment decline in multiple arrests is driven by the changing
characteristics of who is released (in particular, there are fewer offenders released after a parole revocation in
the post-realignment months). The proportion of released offenders convicted multiple times over the course
of one year is very low in both figures (below 5 percent) and relatively stable through the policy changes.

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FIGURE 13
Post-realignment released offenders are more likely to be arrested multiple times

40%

No Realignment
Exposure

Some Realignment
Exposure

All Realignment
Exposure

One year recidivism rate

35%
30%
Multiple Arrests
25%

Multiple Convictions

20%
15%
10%
5%
0%
-24 -22 -20 -18 -16 -14 -12 -10

-8

-6

-4

-2

0

2

4

6

8

Realignment month
SOURCE: Authors’ calculations based on CDCR individual administrative data.
NOTE: The figure presents regression adjusted recidivism outcomes for groups of released offenders defined by month of release
relative to realignment. For example, realignment month 0 is all offenders released in October 2011, the first month of realignment.

Figure 14 presents our formal estimates of realignment’s effects on multiple arrests and convictions. Without
adjustment, the proportion of released offenders with multiple arrests increased approximately 4.1
percentage points and, with adjustment, about 7.4 percentage points. Both estimates are highly statistically
significant. The unadjusted data show a small and statistically insignificant increase in the proportion of
offenders with multiple convictions. With adjustment, we estimate a slightly larger, statistically significant
increase of about 0.4 percentage points.
FIGURE 14
The increase in multiple arrest is especially noticeable

Estimated diiferences in recidivism outcomes,
pre- and post-realignment

8%

7.4%

7%
No statistical adjustment
6%

Statistically adjusted

5%
4.1%

4%
3%
2%
1%
0.1%

0.4%

0%
Multiple arrests

Multiple convictions

SOURCE: Authors’ estimates based on CDCR individual administrative data.
NOTE: See Technical Appendix Tables A1 and A2 for formal estimation results with standard errors.

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Is Public Safety Realignment Reducing Recidivism in California?

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Conclusions
Prior to the implementation of California’s 2011 public safety realignment, the state’s prison system had one
of the nation’s highest recidivism rates. A major goal of the reform was to slow the flow of offenders
returning to prison, which had significantly contributed to overcrowding in the state’s expensive prison
system. Realignment stopped the practice of returning released offenders to prison for parole violations—
instead, these offenders are now sanctioned in the counties. The law also stressed county use of evidencebased practices to discourage return to crime.
These and other changes have transformed the landscape for released offenders. Periods of post-release
supervision are often shorter and released offenders are considerably less likely to be re-incarcerated for
technical parole violations. While released offenders are perhaps more likely to experience incarceration
spells in local jails, these spells are designed by law to be shorter than typical prison spells for revocation in
the pre-realignment period. Moreover, in many counties jail incarceration is likely limited by capacity
constraints.
Realignment’s success depends largely on efforts addressing recidivism among former prison inmates and
other convicted offenders diverted from prison as a result of the reform. This report has examined how
realignment has affected recidivism patterns, as measured by arrests, convictions, and returns to state prison.
We have stressed the importance of accounting for changes in the released offender population and also
noted recidivism patterns that may stem primarily from prosecutorial changes.
Our key findings include:



The rate at which released inmates are being returned to state custody has declined sharply. In a
relatively short period, California has gone from having the highest return-to-custody rate in the
nation to having a rate that is below the national average. However, after dropping dramatically,
returns to custody have begun to increase.



The proportion of released offenders arrested within a year has declined slightly. However, the
proportion arrested multiple times has increased about 7 percentage points. Higher multiple arrest
rates indicate that realignment has placed greater responsibility on local law enforcement and
community corrections. It also may signal limited jail capacity, which has led to a substantial
increase in released prisoner street time (Lofstrom and Raphael 2013).



Post-realignment conviction rates have increased roughly 1.2 percentage points, nearly all of which
reflect higher felony conviction rates. We also find an increased conviction rate of arrested
released offenders. Together, the increases in felony convictions and the rate at which arrests result
in convictions suggest that prosecutors are successfully prosecuting offenders for offenses that in
the past would have been processed administratively through the Board of Parole Hearings.



The proportion of released prisoners with multiple convictions has increased slightly by about
0.4 percentage points.

The slight declines in arrest rates and modest increase in conviction rates suggest that released inmates are
generally not offending at a higher rate in the post-realignment period, but that when they do offend they
are more likely to be formally prosecuted. The increase in multiple arrests may stem from increased street
time, which provides released offenders more opportunity to commit crime if they are inclined to do so. It is
also possible that this increase reflects the enhanced role of local authorities in monitoring and enforcing
compliance with an offender’s conditions of release from prison. In either case, the increase in the proportion

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Is Public Safety Realignment Reducing Recidivism in California?

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of released offenders with multiple arrests comes with considerable cost savings from reduced use of the
most expensive resource in the state criminal just system—the prison. Still, we need to understand better
the underlying causes of higher multiple arrest rates. We also need to make additional efforts to control
re-offending among those offenders who remain criminally active. These efforts may include further
targeted sanctions, which will probably require resources to address aging facilities and jail capacity in
a number of counties (Martin and Lofstrom 2014).
Our results suggest that parole violations involving actual new offenses are increasingly being processed
through the courts as formal felony charges and convictions, rather than as technical violations through
the Board of Parole Hearings. These patterns are consistent with the idea that realignment is encouraging
prosecutors to bring formal charges for new offenses rather than relying on “back-door” sentencing.
Offenders sentenced to prison for new crimes probably face longer terms than those imposed for parole
violations. However, other factors may be at work. For example, consider up-charging—prosecution for
prison-eligible crimes, which shifts incarceration responsibility back to the state. Up-charging is not aimed
at improving public safety, but rather at avoiding costs. One avenue for future research is to understand
prosecutorial responses to realignment. Both up-charging and increased prosecution of supervision violators
may be contributing to the recent increase in returns to state prison.
In all, these findings suggest that realignment has made substantial progress toward one of its main goals—
reducing the use of prison for sanctioning parole violations and minor criminal offenses. Arrests and
convictions have not increased dramatically under realignment. County efforts appear to be at least partially
offsetting the effects of increased street time among released offenders. These findings are consistent with a
previous PPIC report that found no convincing evidence that realignment had affected reported violent
crime and had only a limited effect on reported property crime (Lofstrom and Raphael 2013b). However,
among inmates released from state prison during realignment’s first year, arrest and conviction rates remain
high. This finding suggests the need for even more effective, targeted crime-deterring policies and for
improvements in connecting former inmates to appropriate programming and rehabilitative services. These
efforts are necessary to reducing recidivism and relieving pressures on state prisons and county jails—which
will ultimately allow California to reach its federally mandated prison population threshold.

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References
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Released from State Prison in the First Six Months of Public Safety Realignment. May 2013. Available at 
www.cdcr.ca.gov/realignment/docs/Realignment%206%20Month%20Report%20Final_5%2016%2013%20v1.pdf. 
California Department of Corrections and Rehabilitation. 2013b. An Examination of Offenders Released from State Prison  
in the First Year of Public Safety Realignment. December 2013. Available at 
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Lofstrom, Magnus and Steven Raphael. 2013a. Impact of Realignment on County Jail Populations. Public Policy Institute  
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About the Authors
Magnus Lofstrom is a research fellow at PPIC. He also holds appointments as research fellow at the Institute
for the Study of Labor (IZA) in Bonn, Germany; community scholar at the Julian Samora Research Institute
at Michigan State University; and research associate at the Center for Comparative Immigration Studies at
the University of California, San Diego. He is a member of the California State Controller’s Council of
Economic Advisors and serves on the editorial board of Industrial Relations. His research focuses on public
safety, immigration, entrepreneurship, and education. He has been widely published in academic journals
and books and has been funded by the Russell Sage, Kauffman, and Smith Richardson Foundations. Prior to
joining PPIC, he was an assistant professor of economics at the University of Texas, Dallas. He received his
Ph.D. in economics from the University of California, San Diego.
Steven Raphael is professor of Public Policy at the Goldman School of Public Policy at the University of
California, Berkeley. He is the author of the recently published book Why Are So Many Americans in Prison?
His research focuses on the economics of low-wage labor markets, housing, and the economics of crime and
corrections. His most recent research focuses on the social consequences of the large increases in U.S.
incarceration rates. His research interests also include immigration policy, racial inequality, the economics of
labor unions, social insurance policies, homelessness, and low-income housing. He is the editor in chief of
Industrial Relations and a research fellow at the University of Michigan National Poverty Center, the
University of Chicago Crime Lab, and the Institute for the Study of Labor (IZA) in Bonn, Germany. He holds
a Ph.D. in economics from the University of California, Berkeley.
Ryken Grattet is a research fellow at PPIC and a professor of sociology at the University of California, Davis.
He previously served as assistant secretary of research in the California Department of Corrections and
Rehabilitation. His current work focuses on California correctional policy at the state and local levels. He is
the author of Making Hate a Crime: From Social Movement to Law Enforcement (with Valerie Jenness), Parole
Violations and Revocations in California (with Joan Petersilia and Jeffrey Lin), and numerous articles in
professional and policy publications. His scholarship and public service contributions have been honored by
the American Sociological Association’s Section on the Sociology of Law, the Law and Society Association,
the Pacific Sociological Association, the Society for the Study of Social Problems Crime and Delinquency
Section, as well as the UC Davis Distinguished Scholarly Public Service Award and the College of Letter’s
and Sciences Dean’s Innovation Award.

Acknowledgments
This report has benefited significantly from comments and suggestions by Laurel Beck, Mia Bird, Lee Seale,
Susan Turner, and Lynette Ubois. We also would like to thank Denise Allen, Jay Atkinson, Brenda Grealish,
Jacqui Coder, and Loran Sheley of the California Department of Corrections and Rehabilitation for timely
and insightful assistance with data used in this study. Any errors are our own.

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independent, objective, nonpartisan research on major economic, social, and political issues. The institute’s goal
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