Profile of SNAP Usage at the State 

and County Levels: 

Evidence from Texas & New York 

Administrative Records and the American 

Community Survey 

Benjamin Cerf Harris 

U.S. Census Bureau 

2013 FCSM Research Conference 

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

the authors and not necessarily those of the U.S. Census Bureau or the U.S. Department of Agriculture Economic Research Service. 
 

 

 

 

 

 

 

Background 

• Food and Nutrition Service (FNS) encourages states to 

provide the Census Bureau with recipient information in 

Administrative Records (AR) from the Supplemental 

Nutrition Assistance Program (SNAP) for mutually 

beneficial research 

• Collaborative work between states, USDA Economic 

Research Service, Census, and academic researchers 

through Research Data Centers 

• Active research using SNAP AR from Texas and New 

York 

• Data from additional states expected during 2014 

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SNAP Access at the State and 

County Levels 

Using Texas SNAP Administrative 

Records linked to the American 

Community Survey 

Constance Newman Erik Scherpf 

Economic Research Service Economic Research Service 
 

 

 

 

 

 

 

 

Data 

• Texas SNAP Administrative Records for calendar years 

2008–2009 

• American Community Survey (ACS) 2009 

• Individual records in the ACS linked to administrative 

records by Protected Identification Key (PIK) 

• ACS used to model individuals’ eligibility for SNAP 

during a 12-month period 

• SNAP participation of each individual determined using 

SNAP administrative records 

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• Variable of interest: Group-specific SNAP Access Rate 

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Methods 

• SNAP Units 

– Construct SNAP units from ACS households 

– Infer some family relationships 

• Eligibility 

– Account for excess shelter, earned income and 

standard deductions 

– Model ineligible immigrants, college students, and 

individuals with disabilities 

– Not included: deductions for medical expenses, child 

support payments and dependent care 
 

 

 

 

 

 

 

 

 

Access Rates by Age in Select Texas Counties, 2008-2009 

Texas Bexar Dallas El Paso Harris Hidalgo Tarrant Travis 

Overall 62.8 64.2 57.3 71.0 55.1 78.2 58.9 60.2 

Age 

0 to 17 76.5 81.3 69.4 84.8 67.2 87.8 71.8 76.9 

18 to 29 56.4 54.6 50.5 65.9 46.8 75.3 53.5 51.4 

30 to 39 63.3 67.4 53.9 71.5 54.4 81.9 57.4 55.9 

40 to 49 55.0 54.1 49.6 68.5 46.0 70.4 47.7 52.9 

50 to 59 46.8 43.8 45.9 51.2 44.5 53.5 43.5 36.2 

60 to 69 43.2 45.4 39.4 51.3 35.2 59.2 30.5 33.8 

70+ 39.4 34.3 35.7 48.8 39.2 56.2 32.9 40.7 

Source: Texas SNAP administrative records 2008-2009 linked to 2009 ACS 

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SNAP Access Rates of Elderly Individuals in 

Texas, by Household Composition, 2008-2009 

Living with at least one non-elderly 

Living with only other elderly 

Living alone 

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0 10 20 30 40 50 60 

Source: Texas 2008-2009 SNAP administrative records linked to 2009 ACS. 
 

 

 

 

 

 

Profile of SNAP Eligibility and Access 

at the State and County Levels 

2008–2010: 

Evidence from New York SNAP Administrative 

Records and the American Community Survey 

Benjamin Cerf Harris Erik Scherpf 

U.S. Census Bureau Economic Research Service 
 

 

 

 

 

 

 

 

Data and Methods 

• Data 

– New York SNAP Administrative Records for 

2007–2010 

•

– American Community Survey 2008–2010 

– Individual records linked by PIK 

Methods 

– Identical methods for constructing SNAP 

households 

•

– Identical model for predicting eligibility 

Main innovation 

– Several years allow for dynamic analysis 

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Eligibility and Access Rates by Age, 2008–2010 

Total 

Age 

0 to 17 

18 to 29 

30 to 39 

40 to 49 

50 to 59 

60 to 69 

70+ 

2008 

27.0 

35.5 

30.8 

25.6 

22.8 

19.7 

21.3 

25.1 

Eligibility Rate 

2009 

28.4 

36.5 

33.6 

27.0 

24.1 

21.7 

22.1 

25.5 

2010 % Change 

32.4 20.0 

41.3 16.3 

38.5 25.0 

31.8 24.2 

27.8 21.9 

25.1 27.4 

24.0 12.7 

27.8 10.8 

2008 

58.7 

68.1 

55.9 

55.4 

54.4 

51.3 

53.8 

55.4 

Access Rate 

2009 

63.8 

72.2 

62.1 

58.7 

60.5 

58.1 

60.7 

59.9 

2010 % Change 

64.6 10.1 

73.9 8.5 

61.0 9.1 

62.1 12.1 

61.4 12.9 

58.8 14.6 

60.6 12.6 

60.3 8.8 

Source:New York SNAP administrative records 2007-2010 linked to 2008-2010 1-year ACS 

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Within and Across County Variation in 

SNAP Misreporting: 

Evidence from Linked American Community Survey 

and SNAP Administrative Records 

Benjamin Cerf Harris 

U.S. Census Bureau 
 

 

 

 

 

 

 

 

 

Research Questions and Motivation 

• False negative and false positive reporting 

• Research Questions: 

– Cross-county variation in survey misreporting rates 

– Persistence of misreporting rates within counties 

– County-level correlates with misreporting rates 

• Motivation 

– Cross-county differences will bias cross-county 

comparisons 

– Within-county persistence will bias estimates of program 

effects 

– Researchers can assess the threat of bias using public 

data on county characteristics 

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Data and Methods 

• Data 

– New York SNAP Administrative Records, 2007–

2010 

– Texas SNAP Administrative Records, 2005–2009 

– American Community Survey, 2006–2010 

• Methods 

– Compare ACS to AR to identify individual false 

negative and false positive responses 

– Obtain county-level false negative and false 

positive rates for each year 
 

 

 

 

 

 

 

 

 

Key Findings 

• Substantial variation in SNAP misreporting rates 

across counties in a given year 

• Persistence of false negative rates within counties, 

especially highly populous counties. 

• County correlates: 

– Percent male 

– percent foreign born 

– average length of SNAP spell 

– percent participating in other transfer programs 

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Autocorrelation of County Misreporting, Populous Counties 

false Negative Rates false Positive Rates 

t t-1 t-2 t t-1 t-2 

t 1.0 t 1.0 

t-1 0.7*** 1.0 t-1 0.5*** 1.0 

t-2 0.4*** 0.7*** 1.0 t-2 -0.1 -0.1 1.0 

Source: New York and Texas SNAP administrative records linked to the ACS, 2007 to 

2010. Unit of observation is the county. Counties with at least 60,000 residents and 1,500 

observations are included. 

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Discussion 

• Data sharing and record linkage benefit 

both the state agencies and the Census 

– Inform states about performance and outreach 

– Improve survey products and record linkage 

• Availability of additional states and years 

would expand the potential for benefits 

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Thank you! 

benjamin.c.harris@census.gov 

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