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Linking Administrative BJS Data: Better Understanding of 

Prisoners’ Personal Histories by Linking the National Corrections 

Reporting Program (NCRP) and CARRA Data 

E. Ann Carson 

Bureau of Justice Statistics 

810 7th Street, NW 

Washington, DC 20531 

Proceedings of the 2015 Federal Committee on Statistical Methodology (FCSM) Research Conference 

The size, costs, and social impacts of corrections in the United States, and in particular of prison populations, are 

ongoing national policy issues. Imprisonment, the nation’s most serious punishment for crime short of execution, is 

its most costly sanction. State governments spent $38.6 billion dollars on institutional corrections alone in 2012 

(Kyckelhahn, 2015), almost 4 times (in real dollars) what they spent in 1982. During this period, the number of 

inmates held under state jurisdiction grew three and a half times, from 384,133 in 1982 to 1,352,582 in 2012 

(Carson, 2014). While state prison populations decreased in 2010 from an all-time high of 1,365,688 in 2009, the 

number of inmates increased during 2013. In recent years, states have made sizable investments in managing their 

prison populations, which has led to renewed calls about the purposes and benefits of incarceration. These debates 

have only intensified as states’ budgets have suffered in the current economic climate. 

Imprisonment also results in consequences that are not easily measured in dollars and cents, with the 

disenfranchisement of former felons perhaps the best known penalty. Myriad additional collateral consequences 

vary by state and crime type, such as released prisoners being disqualified from many job opportunities and from 

housing and welfare benefits. These sanctions affect not just former felons, but their entire households. They also 

add to the social issues that arise from removing a person from a household and community for sometimes multiple 

years on end. Families of imprisoned persons often suffer financial hardship due to the decrease in household 

income, and minor children of prisoners are more likely to drop out of school before graduation and become 

involved in crime themselves (Dallaire, 2007). 

States’ attempts to control social and monetary costs 

During the past few years, states have attempted to reign in the monetary and social costs associated with 

incarceration with alternatives to imprisonment. Some alternatives target communities to reduce crime before it 

occurs, while others divert offenders from prison sentences to other forms of corrections including treatment and 

community supervision. Finally, some interventions are directed at released prisoners returning to their communities 

to reduce the likelihood these persons will reoffend in the future. 

California is the most salient example, delegating the responsibility for inmates convicted of nonviolent, nonserious, 

nonsexual crimes to the counties instead of taking custody at the state level. The state has given its counties money 

so their judicial, executive, and legislative officials can create alternative forms of punishment for these crimes, 

including incarceration in local jails, more liberal use of split jail–community sentences, sentencing to substance 

abuse programs in lieu of incarceration, and more probation officers to deal with the increasing number of offenders 

being supervised in the community. To further reduce overcrowding in the state prisons and local jails, Californians 

recently passed Proposition 47, which reduces low-level drug and property offenses from felonies to misdemeanors. 

While other states have not undertaken as radical an overhaul of their corrections systems as California, there is 

growing accord across political viewpoints that the current state of mass imprisonment is not good for states’ 

budgets or society at large. The Indiana state legislature passed sentencing reforms in 2014 to enhance sentencing 

guidelines for violent criminals while diverting low-level offenders to county jails. In 2012, Pennsylvania relocated 

all of its inmates previously held in out-of-state prisons to facilities in Pennsylvania and cancelled construction of a 

new prison. The federal government has granted millions of dollars to 27 states under the Justice Reinvestment 
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Initiative (JRI) and the Second Chance Act (SCA) to help them develop policies and programs that will reduce 

imprisonment and encourage successful reentry of released prisoners into the community. Texas was one of the first 

states to obtain a JRI grant, with which it expanded its substance abuse and mental health treatment programs, 

changed its community-corrections policies to decrease the number of technical violators returned to prison, and 

reinvested the savings into community-level programs for offenders (La Vigne et al., 2014). 

BJS works with CARRA to expand data use 

While many of these efforts are based on “evidence-based practices” that have demonstrated success in specific 

counties or states, no one believes that a single program will be successful in all communities. Although reliable 

measures of the social and economic consequences of imprisonment exist, they cannot be analyzed in direct relation 

with data on persons in prison. The Bureau of Justice Statistics (BJS) is addressing this deficiency by partnering 

with the Center for Administrative Records Research and Applications (CARRA), part of the U.S. Census Bureau’s 

Center for Economic Studies (CES). Through this partnership, BJS is collecting individual-level data from various 

aspects of the criminal justice system, including victims of crime, state and federal court cases, and persons serving 

sentences in state and federal prisons. 

The National Corrections Reporting Program (NCRP) collects data on various life events of persons in the custody 

of state prisons through individual-level administrative records. These include an annual collection of all prison 

admissions and releases and of all persons in the custody of state correctional authorities on December 31 of a given 

year. NCRP obtains administrative records on entries and exits from post-custody community supervision (PCCS) 

programs (formerly known as parole programs) from the majority of states as well. BJS began collecting NCRP data 

in 1983 from between 32 and 39 state departments of corrections. Since 2000, at least 40 states have submitted at 

least one type of NCRP data. Ten states began submitting data to NCRP during the past 3 years, participating either 

for the first time or after lapses of at least 5 years. Additionally, 17 states submitted data to backfill previous years’ 

collections and, since 2011, all 50 states have submitted at least one type of NCRP record. 

Annually, state departments of corrections (DOCs) submit NCRP data from the previous calendar year to BJS for 

each prisoner in their system who was admitted to, released from, or in the custody of DOC or private prisons in the 

state. Each cohort contains a common core of variables, and each cohort except the admissions cohort includes 

additional variables pertaining to the stage in the corrections system process represented by the cohort. The core 

variables collected for all five cohorts include measures of the— 

 date of admission 

 type of commitment (e.g., a new court commitment stemming from a felony conviction, entry as a parole or 

conditional release violator, transfers, and unsentenced commitments) 

 offenses for which offenders have been sentenced to prison 

 lengths and types of sentence imposed 

 time served in jail prior to admission 

 demographic attributes of offenders, such as date of birth, age, race, gender, and education level completed 

 entity responsible for offenders (such as the state maintaining jurisdiction over an offender) 

 identification variables, including first and last name, identification numbers the state uses for designating 

individuals (BJS requests fingerprint-based IDs, including state ID and FBI ID, if possible), social security 

number (SSN) and address of last known residence (in 2015, OMB gave BJS permission to collect SSNs 

and address of last known residence),. 

In addition, the yearend custody records include the common core plus measures of expected (or projected) dates of 

release from prison. The prison release data include actual dates of release, actual time served, and method of release 

(e.g., conditional release to parole or unconditional release). The PCCS entry and exit datasets, which are only for 

offenders released conditionally, also include the type of entry and discharge from PCCS (e.g., success or failure) 

and dates of entry to and exit from community supervision. 

In the past, BJS has used NCRP data to track changes in sex, generate data on race/ethnicity and age distributions of 

state prison populations, and identify groups that may be disproportionately affected by prison. The distinctiveness 

of the NCRP (that it gathers data at the individual level) makes it central to BJS in accomplishing its mission, which 
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is, in part, to describe trends in state correctional systems. These trends include changes in the size and composition 

of the prison population; the flow of admissions, releases, and lengths of stay; and sentencing practices. The NCRP 

data form the backbone of BJS’s recidivism research, including offenders’ returns to state prison as well as the 

performance of offenders released to PCCS programs. While the NCRP does not provide information on subsequent 

arrests or charges brought against released prisoners, it does generate expectations about future prison populations 

based on the offenders released in a current period and measuring returns to prison. 

As a collection, the NCRP data can describe the stock and flow of offenders through state prison and PCCS 

programs over time, but they can only be used to establish general trends in recidivism or analyze the efficacy of 

certain programs (e.g., all persons admitted in the year after a split-sentence strategy was implemented for drug 

offenders in the state). Data beyond the NCRP collections are required to better understand external factors that 

could contribute to offenders’ successful reentry into the community or are associated with higher levels of 

recidivism. During 2014, BJS funded and executed an interagency agreement with CARRA to link the NCRP data to 

the Social Security Administration’s (SSA) Numident file, housed behind the U.S. Census Bureau’s secure firewall. 

Then analysts in the CARRA group assigned a personal identification key (PIK) to each inmate and deleted all 

personal identifying information. 

Four states have provided BJS with inmates’ SSNs for several years, and these will serve as the pilot sample for 

matching to the Numident file. BJS has asked CARRA to match these records using SSNs and then again using only 

names and dates of birth to determine whether SSNs significantly improve linkage results. If the match rate using 

only names and dates of birth is satisfactory, BJS will send all NCRP records with names to CARRA for linkage 

(approximately 11 million records). Once the data are linked, BJS and CARRA staff will evaluate the results to 

determine whether those records without PIKs differ in any way from those matched in the Numident file. 

The PIK would let the NCRP data be linked to a number of federal datasets including— 

Supplemental Security Income receipt record (SSA) 

Medicare/Medicaid enrollee data (Center for Medicare and Medicaid Services (CMS)) 

Change of Address file (U.S. Postal Service, USPS) 

Temporary Assistance for Needy Families (TANF) 

Death Master File (SSA) 

Decennial Census (U.S. Census Bureau) 

American Community Survey (ACS) 

Public housing and rental assistance history (Housing and Urban Development (HUD)) 

HUD-insured mortgage program (HUD) 

Unemployment insurance wage data (Internal Revenue Service (IRS), linkage requires additional 

 permissions) 

Tax returns (IRS, linkage requires additional permissions) 

Veterans benefits records (Veterans Business Administration (VBA)). 

Matching NCRP data to the decennial census or ACS collections is particularly important because, once an 

individual is identified, all household members associated with that person can be followed. BJS is not interested in 

identifying persons who are not involved in the criminal justice system. However, BJS does want to better 

understand the household structure that the prisoner came from or may return to in the future. Imprisonment affects 

the entire family or household unit. Understanding the prisoner’s relationship to other household members and the 

type and size of the housing unit before, during, or after incarceration could explain some the economic and social 

challenges experienced by all upon an inmate’s release at a national level. Once an NCRP inmate’s PIK is identified, 

the PIKs of the other individuals in the household can be traced to determine whether they received public benefits, 

filed for unemployment compensation, or reported a decrease in wages when the inmate was removed from the 

household. 

Data from VBA and CMS can uncover potential health care benefits available to former prisoners after their release 

from prison. Veterans lose their VA benefits when they go to prison, and state corrections departments provide their 

health care. Once released, an offender’s ability to pay for and use medical care is an important factor in deterring 

future recidivism. With the Patient Protection and Affordable Care Act (ACA, PL 111-148) passed and Medicaid 

expanded in more than half the states, many former inmates may be able to afford medical insurance for themselves 

and their families. Because 41% of prisoners reported chronic medical conditions, and 66% of those were taking 
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prescription medication to control the condition (Maruschak, Berzofsky & Unangst, 2015), continuing care in the 

community is critical for successful reentry.

A case-control matched study of the recidivism rates of former inmates who qualify for ACA or VA health care 

benefits, and those who do not, using linked NCRP records could suggest whether access to affordable health care 

should be part of any state’s approach to reducing recidivism. 

Several factors about post-prison reentry and recidivism that BJS statisticians and other researchers could address 

after the NCRP data are linked to other federal datasets are listed below: 

• What is the rate of unemployment among former prisoners, and how long does it take before former 

prisoners obtain legal employment? 

• What are the risk factors (criminal justice and demographic characteristics) associated with multiple stints 

in prison? Does time served on a sentence impact recidivism? 

• What is the relationship between employment and recidivism? 

• What is the death rate of former prisoners over time? Is there a relationship between the time spent in

prison, where the inmate received health care, and the length of survival post-prison? 

• How mobile is the former prisoner population (interstate mobility), and does this affect recidivism rates in 

each state? 

• How does prison release affect household income and use of federal and state benefits? 

• Some offense categories carry mandatory collateral consequences, including rendering any household with

a convicted felon ineligible for housing assistance, food stamps, or other public benefits. How does 

household structure vary before and after prison release? 

• At what rate do veterans released from prison renew their relationship with the VA health care system?

• What is the relationship between access to and use of health insurance and recidivism? Does this vary by 

geography, demography, or household structure? 

Linking to other datasets would expand the uses for NCRP data. With this linked data, researchers could factor 

individual-level external factors into models to evaluate programs that divert offenders from prison and identify 

factors related to recidivism. The individual-level nature of NCRP, as well as its improved record in number of 

states providing data, make the collection unique in its ability to address these issues on the state level, in addition to 

providing national-level statistics. 

References 

Carson, E.A. (2014). Prisoners in 2013. BJS bulletin, NCJ 247282. Washington, DC: Bureau of Justice Statistics. 

Retrieved from http://www.bjs.gov/content/pub/pdf/p13.pdf 

Dallaire, D.H. (2007). Incarcerated mothers and fathers: A comparison of risks for children and families. Family 

Relations, 56(5), 440–453. 

Kyckelhahn, T. (2015). Justice expenditure and employment extracts, 2012. BJS statistical tables, NCJ 248628. 

Retrieved from http://www.bjs.gov/index.cfm?ty=pbdetail&iid=5239 

La Vigne, N., Bieler, S., Cramer, L., Lo, H., Kotonias, C., Mayer, D., McClure, D., Pacifici, L., Parks, E., Peterson, 

B., & Samuels, J. (2014). Justice Reinvestment Initiative state assessment report. Washington, DC: Urban Institute. 

Retrieved from http://www.urban.org/research/publication/justice-reinvestment-initiative-state-assessment-report 

Maruschak, L.M., Berzofsky, M., & Unangst, J. (2015). Medical problems of state and federal prisoners and jail

inmates, 2011–12. BJS special report, NCJ 248491. Washington, DC: Bureau of Justice Statistics. Retrieved from 

http://www.bjs.gov/content/pub/pdf/mpsfpji1112.pdf