Developing a Longitudinal Database to 

Facilitate Research on SNAP Participation

Renuka Bhaskar, Maria Perez-Patron, Brad Foster, Sarah James, 

Brian Knop, Veronica Roth, and Erik Vickstrom

U.S. Census Bureau

FCSM Research and Policy Conference

October 26, 2023

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Disclaimer: This research is released to inform interested parties and to encourage discussion. The views expressed are those of the authors 

and not necessarily those of the U.S. Census Bureau.
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Source: SNAP National Data Bank estimates available from USDA

Great Recession COVID-19

Supplemental Nutrition Assistance Program (SNAP), 2000-2022

• Largest nutrition assistance program aimed at reducing domestic hunger by providing low-income 

households benefits that can be used to purchase food at authorized retailers

• SNAP has been shown to reduce food insecurity, improve health outcomes and has provided 

essential assistance in economic downturns and disaster situations
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Source: SNAP National Data Bank estimates available from USDA

Great Recession COVID-19

Supplemental Nutrition Assistance Program (SNAP), 2000-2022

In December 2022, SNAP 

benefits reached:

42.5 million people in

22.5 million households

• Largest nutrition assistance program aimed at reducing domestic hunger by providing low-income 

households benefits that can be used to purchase food at authorized retailers

• SNAP has been shown to reduce food insecurity, improve health outcomes and has provided 

essential assistance in economic downturns and disaster situations
Who participates in SNAP?

• USDA’s Food and Nutrition Service 

releases estimates on the 

characteristics of SNAP participants

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Source: https://fns-prod.azureedge.us/sites/default/files/resource-files/Characteristics2019.pdf

SNAP, FY 2019
Who participates in SNAP?

• USDA’s Food and Nutrition Service 

releases estimates on the 

characteristics of SNAP participants

• Estimates over time provide 

understanding of how the SNAP 

population is changing over time 

but do not tell us about length of 

participation or breaks in 

participation spells

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Source: https://fns-prod.azureedge.us/sites/default/files/resource-files/Characteristics2019.pdf
Longitudinal SNAP research

• Research on longitudinal participation in SNAP has largely relied on 

longitudinal surveys 

• Baum 2011; Vartanian and Houser 2020; Pak and Kim 2020

• Survey data is limited by potential under-reporting of SNAP receipt 

• Meyer et al. 2022, 2009; Rothbaum et al. 2021 Colby et al. 2017 

• Research using administrative records has examined SNAP 

participation dynamics during early childhood

• Danielson et al 2020; Hefling et al. 2021

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SNAP administrative records at the Census Bureau

• Through joint efforts with USDA’s Food and Nutrition Service (FNS) 

and Economic Research Service (ERS), the Census Bureau has entered 

into agreements with states to receive administrative data on SNAP 

participants

• Long-standing project to better understand SNAP eligibility and access 

at granular levels

• More recent effort to begin development of a SNAP Longitudinal 

Database

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SNAP administrative records process

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Census Bureau 

and State 

agencies establish 

MOUs

States prepare 

and extract data 

from systems 

Data are sent to 

the Census 

Bureau using 

secure transfer 

methods

Census Bureau 

ingests and 

processes the 

data through the 

Person Validation 

System (PVS)

State SNAP 

Administrative 

Records 
Estimating SNAP Eligibility and Access

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American Community 

Survey

(ACS)

State SNAP 

Administrative 

Records 

• ~ 3.5 million households 

sampled annually

• Define SNAP units and estimate 

individual SNAP eligibility

• Monthly records on participating 

clients and cases

• Data are linked at the individual 

level using Census-Bureau 

assigned identifiers

• Methodology based on work by Newman and Scherpf (2013)
Estimating SNAP Eligibility and Access

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American Community 

Survey

(ACS)

State SNAP 

Administrative 

Records 

• ~ 3.5 million households 

sampled annually

• Define SNAP units and estimate 

individual SNAP eligibility

• Monthly records on participating 

clients and cases

• Data are linked at the individual 

level using Census-Bureau 

assigned identifiers

• Methodology based on work by Newman and Scherpf (2013)

Estimates of SNAP

Eligibility and Access
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Cross-sectional estimates:

Annual SNAP Table Packages 

& Data Visualization

Note: Estimates shown above are mock data for a hypothetical state/year.

Source: https://www.census.gov/library/visualizations/interactive/snap-eligibility-access.html
Supplemental Nutrition Assistance Program Longitudinal 

Data Project (SNAP-LDP)

• The 2018 Farm Bill required FNS to 

develop a SNAP longitudinal research 

database and prior to approval, consult 

with Federal research agencies including 

the Census Bureau

• Goal is for the database to be used 

“solely to conduct research on 

participation in and the operation of the 

supplemental nutrition assistance 

program, including duration of 

participation in the program” 

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States participating in the SNAP-LDP

See: https://www.fns.usda.gov/snap/longitudinal-data-project-ldp
State data for the SNAP-LDP

• States have the opportunity to apply for grant funding from FNS to 

support their participation in the SNAP-LDP

• States are encouraged, but not required, to use some portion of their 

grant funds to standardize their data to a pre-specified format 

(https://www.fns.usda.gov/snap/longitudinal-data-project-ldp)

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State data for the SNAP-LDP

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CASE FILE

• Monthly information about the SNAP 

household

• Case unit identifiers

• Benefit amount information

• Dates related to certification

• Active participant flag

• Net and gross income

• Address information

• Census adds: unique address identifiers 

INDIVIDUAL FILE

• Monthly information about the 

individuals in each case

• Case unit and client identifiers

• Demographic characteristics and 

relationship to primary applicant

• Active participant flag

• Employment and income 

• Personally Identifiable Information

• Census adds: unique person identifiers
SNAP-LDP Database Development 

integration

c. Database

b. Standardization of data files

a. Evaluation for fitness for use

d. Quality Assurance

State SNAP 

Administrative 

Records 

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Fitness for use evaluation: example

• To assess quality of State data, we compare monthly counts of SNAP 

cases and individuals to SNAP National Data Bank estimates published 

by FNS

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Jan-22 Feb-22 Mar-22 Apr-22 May-22 Jun-22 Jul-22 Aug-22 Sep-22 Oct-22 Nov-22 Dec-22 Jan-23 Feb-23 Mar-23 Apr-23 May-23 Jun-23

Participation Persons Participation Households

Source: SNAP National Data Bank estimates available from USDA
Conclusions

• Goal of the SNAP-LDP is to facilitate research on SNAP participation 

over time and across state lines

• Plans for database include:

• Multi-state

• Anonymized linkage keys to enhance research capabilities

• Standardized across states to the extent possible 

• Accompanied by documentation

• Eventually be available as a restricted dataset for researchers working through 

Federal Statistical Research Data Centers

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Thank you!

Census Bureau contacts: 

renuka.bhaskar@census.gov

ces.snap.ldp.list@census.gov

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