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Use of TANF Work-Oriented Sanctions in Illinois, New Jersey, and South Carolina

Publication Date
Apr 29, 2004

By:
LaDonna Pavetti, Michelle K. Derr, Gretchen Kirby, Robert G. Wood, and Melissa A. Clark

Submitted to:
U.S. Department of Health and Human Services
Office of the Assistant Secretary for Planning and Evaluation

Project Officers:
Elizabeth Lower-Basch and Alana Landey

Submitted by:
Mathematica Policy Research, Inc.

Project Director:
LaDonna Pavetti

Contract No.: HHS-100-01-0011
MPR Reference No.: 8902-602

"

Acknowledgements

This report would not have been possible without the cooperation and support we received from staff at all levels in each of the study states. Program administrators fielded many questions from us about formal TANF sanction policies and procedures, and local staff talked openly with us about how those policies and procedures play out in practice. Marilyn Edelhoch and David Patterson from the South Carolina Department of Human Services, Dave Gruenenfelder and Diane Darnell from the Illinois Department of Human Services, and Rudy Myers, and Beth Connolly of the Division of Family Development at the New Jersey Department of Human Services provided us with administrative data and, in some cases, survey data for the quantitative analysis for this report. Marilyn Edelhoch, David Gruenenfelder, Rudy Myers, Suzanne Borys (NJ) and Gayle Riesser (NJ) also reviewed and provided comments on an initial draft of the report We would like to thank everyone who graciously shared their time with us for making this report possible.

We would also like to thank staff from the U.S. Department of Health and Human Services, Office of the Assistant Secretary for Planning and Evaluation, for providing guidance and feedback throughout this project. As project officers, Elizabeth Lower-Basch and Alana Landey monitored each project task and provided useful suggestions for improving the study and final synthesis report. Don Winstead, Deputy Assistant Secretary for Human Services Policy, also reviewed the final report and provided us with suggestions for improving it.

The work for this project was completed as a team effort, involving staff from Mathematica Policy Research, Inc. (MPR) and our subcontractor, AFYA, Inc. As project director, LaDonna Pavetti led all aspects of this study from beginning to end. Michelle K. Derr conducted site visits, authored state site visit summaries, and co-authored the final synthesis report. Gretchen Kirby conducted the administrative and survey data analysis for Illinois and South Carolina and summarized the general findings from the quantitative data analysis across the study states in Chapter 3 of the final report. Robert Wood and Melissa Clark conducted the quantitative data analysis for New Jersey and contributed to the final report. A team of senior and assistant programmersВ  Mark Brinkley, Carol Razafindrakoto, Lucy Lu, Elizabeth McClintock, and Melissa FauxВ  worked together to prepare and carry out the administrative and survey data analysis for this study. Heather Hesketh and Jesse Gregory managed the project. Alan Hershey provided quality assurance. Daryl Hall and Karen Rosenthal edited this report. Alfreda Holmes provided ongoing and consistent administrative support.

Our subcontractors, AFYA, Inc., participated in the site visits for this study. As project director at AFYA, Inc., Harry Day supervised project staff and reviewed project deliverables. Shani Rolle participated in each of the site visits and co-authored a site visit report.

Introduction

The 1996 Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA) made unprecedented changes to the welfare system in the United States, eliminating the 60-year-old Aid to Families with Dependent Children (AFDC) program and replacing it with a block grant to states to create the Temporary Assistance for Needy Families (TANF) program. A system that once focused on the accurate delivery of cash benefits now focuses on encouraging families to make the transition from welfare to work. Part of this shift translates into a dramatic increase in the range of circumstances in which families' welfare benefits can be reduced or canceled. In particular, sanctions--financial penalties for noncompliance with program requirementsВ  have become central features of most states' efforts to promote self-sufficiency through their TANF programs. A primary goal of work-oriented sanctions is to encourage TANF recipients who might not be inclined to participate in work activities to do so. A secondary goal is to encourage greater reporting of earnings, especially among families who work in jobs where earnings are not reported through official channels. The logic behind sanctions is that adverse consequences can be used to influence the decisions clients make. Sanctions have long been used to enforce program requirements. However, with the emergence of "full-family" sanctions that eliminate all of a family's cash grant, the imposition of work requirements on a greater share of the TANF caseload and greater emphasis on encouraging TANF recipients to become self-sufficient, they have taken on much greater significance.

While consensus holds that sanctions have been an important policy change implemented through state welfare reform efforts, they are among the least studied. Additional information on the role sanctions have played in welfare reform can help inform policy discussions regarding whether all states should be required to impose more stringent sanctions and help program administrators identify strategies for using sanctions to promote greater compliance with program requirements. This report presents findings from a study of the use of sanctions in two local welfare offices in each of three statesВ  Illinois, New Jersey, and South Carolina. In this chapter, we provide a brief context for the study, outline the study design, and describe the study states. Chapter II presents our findings on how the study sites implemented sanctions. Chapter III describes our findings on how often sanctions are used, how the characteristics of sanctioned and nonsanctioned families compare, and how sanctioned families fare over time. Finally, Chapter IV summarizes our findings and identifies important unanswered research questions.

Sanctions and Welfare Reform

Before the passage of PRWORA, welfare offices reduced the AFDC payment for families with a household head who failed to participate in the work activities mandated under the Job Opportunities and Basic Skills (JOBS) training program. Believing that the penalty was not sufficiently severe to influence household heads' participation decisions, beginning in the early 1990s, many states applied for and received waivers to impose more stringent sanctions for program noncompliance. The majority of states then used TANF's flexibility to implement more stringent sanctions, though some chose to retain the structure that was in place before the advent of TANF. Under TANF, states are required to impose at least a "pro-rata" grant reduction for noncompliance but can impose a greater penalty if they choose to do so. It is also important to note that while state sanction policies are most often compared on the amount and structure of the benefit reduction, they often differ along other important dimensions such as the minimum duration, cure requirements, and approaches to repeated noncompliance (Pavetti et al. 2003).

Currently, state approaches to sanctioning follow one of four models: (1) partial, (2) gradual full-family, (3) immediate full-family, and (4) pay for performance. Fourteen states and the District of Columbia have implemented a partial sanction, which, as the name implies, reduces a family's cash assistance grant though the family continues to receive some portion of its benefits. In most cases, a partial sanction eliminates the noncompliant adult(s) from the grant, which all states did before the implementation of welfare reform. Some states that impose a partial sanction have deviated from this structure and instead reduce the family's grant by a specified percentage.

Seventeen states have implemented an immediate full-family sanction. When such a policy is in place, a family loses all of its cash assistance soon after it is identified as noncompliant. In some states, such cases become "zero-grant" cases and are counted as part of the TANF caseload for some specified period (usually three months). In most states, the case is closed with a sanction closure code that distinguishes families exiting TANF because of a sanction from those that have left for other reasons.

Nineteen states have implemented either gradual full-family or pay-for-performance approaches to sanctions, which include elements of both partial and full-family sanctions. Under a gradual full-family sanction policy, failure to comply with work requirements leads to an initial grant reduction for a period ranging from one to six months, depending on the state. If a family comes into compliance before the end of the period, it reverts to full-grant status, but if it remains noncompliant at the end of the period, it loses the entire grant. The philosophy behind such sanctions is that full-family sanctions should be imposed only when lesser penalties have failed to promote compliance. Pay for performance, implemented only in Wisconsin, can resemble either a partial or full-family sanction, depending on whether a family is fully or partially noncompliant. Under this model, a family receives assistance only for the hours it participates in required work activities. If it does not participate at all, it does not receive any assistance; thus, the policy operates in the same manner as an immediate full-family sanction. However, if the family participates to some degree, it receives payment for the hours of participation such that the policy functions like a partial sanction.

Research Questions

The implementation of more stringent sanctions has been accompanied by keen interest in how sanctions are used and their associated outcomes. In a review of earlier studies on the use and effectiveness of TANF sanctions (Pavetti, Derr, and Hesketh, 2003), we found the following:

  • Sanctions are imposed relatively often, with studies following a cohort of recipients reporting sanction rates between 45 and 52 percent over a 12- to 18-month period.
  • Despite some variation, most studies find that sanctioned families are more likely than nonsanctioned families to exhibit one or more characteristics that make them harder to employ.
  • Studies consistently find that families that have left the welfare rolls due to a sanction are less likely than their nonsanctioned counterparts to be employed and more likely to return to the welfare system.
  • The few studies that have investigated variations in state sanction policies to determine whether stricter sanction policies influence TANF recipients' participation decisions find that stricter sanctions lead to greater caseload declines and increased exits from TANF to employment.

The research questions examined in this study are similar to those addressed in previous studies. However, two features make the present study unique: (1) we use comparable methodologies and data from multiple states, which provides much greater contextual information for understanding how and how often sanctions are used, and (2) we combine analysis of case study, administrative, and survey data to provide a comprehensive analysis of the use of TANF sanctions. These features permit us to add to both the depth and breadth of our knowledge of how TANF sanctions are being used to encourage participation in work activities and movement toward self-sufficiency.

Our examination focuses on four important research questions:

  1. How have sanctions been implemented in local welfare offices? In most states, it is the state that formulates sanction policies. Despite considerable documentation on the structure of state sanction policies, little information exists on how these policies are applied in practice. Of particular interest is how much discretion TANF workers exercise in implementing sanctions and how workers and local program administrators balance individual client needs with work requirements.
  2. How often are sanctions imposed? Previous studies of TANF sanctions rely on a broad range of strategies to examine how often sanctions are used. However, differences in methodology have made it difficult to interpret estimates across studies. Thus, our study applies the same methodology in three states to increase our understanding of how often sanctions are used and to identify what factors might contribute to any observed differences.
  3. How do the characteristics of sanctioned and nonsanctioned recipients compare? Previous studies find that sanctioned recipients are more likely than nonsanctioned recipients to exhibit characteristics that are associated with longer welfare stays and lower rates of employment. However, only a few of these studies compare sanctioned versus nonsanctioned families in terms of the existence of personal and family challenges (such as mental health, substance abuse, and domestic violence issues) and logistical challenges (such as child care and transportation). This information can help clarify whether particular groups of families are at higher risk of receiving sanctions. By relying on survey data collected to examine the characteristics of the current TANF caseload in two of the three study states, the present study can compare the presence of a broad range of assets and liabilities among sanctioned and nonsanctioned recipients.
  4. How do sanctioned recipients fare over time? Given that many sanctioned families face the potential of eventually losing all their cash assistance, policymakers have expressed considerable interest in knowing how sanctioned recipients fare over time. What proportion eventually complies with program requirements? What proportion finds employment at the time of the sanction or shortly thereafter? By exploiting the longitudinal nature of the administrative data available in all the study states and using detailed information available on employment status over time in one state, we are able to explore these questions in some depth.

Data Sources

We selected the three study states based on the availability of data collected for other research studies, which could be used to examine the use of TANF sanctions.(1) In each state, we supplemented the existing data with additional data collected specifically for the present study.

Administrative Data. In each of the study states, we use administrative data on single- parent families (excluding child-only cases) to examine how often TANF sanctions are imposed and how the rate of return to the welfare system compares between sanctioned and nonsanctioned families. Our analysis examines the use of TANF work sanctions among a cohort of recipients on the TANF caseload whom we follow over time. In all three states, the administrative data include information on basic demographic characteristics as well as welfare receipt and sanctioning status over time. The time at which the administrative data sample was selected for the study varies across the states, but in all cases it occurred several years after major reforms were implemented and after substantial caseload declines had already occurred.

In New Jersey, the data come from administrative records on all 51,539 single-parent families that received TANF benefits at any time between July 2000 and June 2001. In Illinois, the data come from administrative records for the 33,495 single-parent cases that were authorized to receive a TANF grant in November 2001. Also included in Illinois are a small number of "zero-benefit cases," which include some fully sanctioned families whose TANF grants had not yet been closed. In South Carolina, the data come from administrative records for the 10,852 single-parent cases that received a TANF grant in June 2002.

Survey Data. Survey data are available for a randomly selected subsample of recipients in all three states, and comparable data are available in South Carolina and Illinois. South Carolina and Illinois both fielded a telephone survey of a subsample of recipients to examine the assets and liabilities of the "current" TANF caseload. While each survey included some state-specific questions, most questions were identical, ensuring comparability across the states. In Illinois, a sample of 416 single parents was interviewed between November 2001 and March 2002. In South Carolina, a sample of 1,128 families was interviewed between August and November 2002. In New Jersey, a follow-up survey of 1,219 families conducted between April and August 2002 as part of the Work First New Jersey evaluation gathered detailed information on a wide variety of topics, including timelines of employment and earnings. In this study, we analyze information for a subset of 126 single parent cases from the Work First New Jersey survey who received a full family sanction during the follow-up period and had a year of follow-up data after receiving a sanction.(2)

Case Studies. For purposes of the present study, we conducted case studies of the implementation of TANF work sanctions in two local offices in each of the three states. The states selected the local sites, although we asked the states to select at least one local site that illustrates innovative approaches to implementing sanctions and demonstrates success in overcoming implementation challenges. We asked for the second site to be located near the first and, if possible, for that site to have followed a different approach to implementing sanctions. We conducted site visits to each study site in winter and spring 2003. A two-person team, made up of a researcher from Mathematica Policy Research, Inc. (MPR) and a research analyst from our subcontractor, AFYA, Inc., conducted the visits, which lasted about three days per state. During the visits, we interviewed TANF administrators, case managers, eligibility workers, and employment service providers. We also reviewed a small number of cases with workers and obtained written reports and copies of sanction notices and other relevant materials.

Study Limitations

This study was designed to increase our understanding of how and how often work-oriented sanctions are used. As is true of many studies of its kind, this study suffers from several important limitations. First, the study uses data that was collected for other purposes. While some comparable administrative data is available for all the states, some data of interest is available for only one or two states. More importantly, because the study states were selected based on the availability of data they do not represent the full range of state experiences in using TANF work-oriented sanctions. Because information on the use of sanctions is scant, we have no way of knowing how well their experiences represent the experiences of other states. Second, because we do not have data that compares the experiences of recipients who have and have not been subject to a sanction or have been subjected to different sanction policies, we cannot answer important questions about the effectiveness of sanctions in general or the relative effectiveness of different types of sanctions. Finally, because our site visits were conducted to only two local sites and we conducted interviews with a limited number of program staff, we cannot be certain that we captured all important aspects of how sanctions have been implemented at the local level.

Characteristics of the Study States and Local Study Sites

Sanction and Related Policies. The three study states all implemented some variant of a full-family sanction (see Table I.1). Illinois and New Jersey both implemented a gradual full-family sanction while South Carolina implemented an immediate full-family sanction. When Illinois sanctions a family for the first time, it reduces the grant by 50 percent for up to three months and then eliminates the grant entirely. New Jersey eliminates the adult portion of the grant for three months and then closes the case. Illinois and New Jersey both require a sanction to be in place for a minimum of one month before lifting it. South Carolina lifts the sanction immediately after the recipient comes into compliance with program requirements; however, recipients are required to participate for 30 days before they are considered to be in compliance, making the minimum sanction period comparable to that in New Jersey and Illinois. In New Jersey, recipients must participate in program activities for 10 consecutive days before their sanction is lifted. In Illinois, the compliance period and requirements are left to the discretion of the case manager.

In Illinois and New Jersey, sanctions are more stringent if the client is noncompliant for a second or third time. In both states, the minimum sanction period increases to three months for the second period of noncompliance; in New Jersey, the case closes in the second month if the family is not complying with program requirements. In both Illinois and New Jersey, a third incident of noncompliance results in immediate case closure.

Table I.1.
Major Dimensions of State Sanction Policies
Dimension All States Illinois New Jersey South Carolina
  # of States
Type of sanction Partial
Gradual full-family
Immediate full-family
Pay for performance
15
18
17
1
Gradual full-family Gradual full-family Immediate full-family
Minimum duration No minimum, until compliance
1 month
2-3 months
28
15
8
1 month 1 month No minimum
Cure requirements Willingness to comply
Period of compliance
Unknown
9
26
16
Willingness to comply Compliance for 10 consecutive days Compliance for 30 consecutive days
Approach to repeated noncompliance More stringent sanction
Longer minimum duration
Stricter cure requirements
Reapplication for benefits
Life-time ban on assistance
10
32
24
24
7
3-month minimum duration;
immediate full-family for third sanction
3-month minimum duration;
immediate full-family for third sanction
Same as for first instance
Source: Welfare Rules Database, Urban Institute 2000; State Policy Documentation Project.

The role sanctions play in welfare reform may be a function not only of the structure of sanctions but also of the context in which they are applied. Of particular importance is whether a state or local welfare office imposes any preapproval work-related requirements that might effectively serve as a sanction. Among the study states, Illinois is the only state to impose such a requirement. All families applying for TANF in Illinois are assessed and must complete a Responsibility and Service Plan (RSP) that contains goals and activities in which the client must participate while their application is pending. Many applicants are expected to participate in a 30-day up-front job search program, however, some might be asked to obtain services such as mental health or substance abuse treatment. If a family fails to follow their RSP, their application for TANF benefits can be denied. In practice, this requirement functions much like an immediate full-family sanction; the only difference is that, in the case of the up-front requirement, the TANF case is never opened. We would expect such a policy to reduce the number of families sanctioned, because some families that might have been sanctioned once on the rolls never actually become a TANF case.

The "Cost" of a Work-Oriented Sanction. The cost of a work-oriented sanction depends on the initial grant amount and the influence of the sanction on other benefits (see Table I.2). The financial cost of the initial grant reduction for a family of three in Illinois and New Jersey is $198 and $141, respectively; for a full-family sanction, the cost is $396 in Illinois and $424 in New Jersey. The cost of a full-family sanction in South Carolina is $201. South Carolina adds to the cost of the sanction by eliminating Medicaid benefits for the noncompliant adult. In all three states, families are not eligible to receive child care and other work supports until they begin participating in work activities.

Table I.2.
The "Cost" of Work-Oriented Sanctions for a Family of Three
  Illinois New Jersey South Carolina
TANF grant Initial partial sanction:
Half grant: $198
Full-family: $396
Initial partial sanction:
Adult portion: $141
Full-family: $424
Full-family: $201
Medicaid No change due to sanction No change due to sanction Loss of eligibility for nonpregnant adults
Work supports (e.g., child care, transportation) Eligible only if participating in work activities Eligible only if participating in work activities Eligible only if participating in work activities
Source: Welfare Rules Database, Urban Institute 2000; State Policy Documentation Project.

Client Characteristics. The characteristics of the single-parent caseloads in the three study states are similar in many respects but also show some important differences (see Table I.3). The age distribution is almost identical in Illinois and New Jersey, but the caseload in South Carolina is considerably younger; 43 percent of the caseload in South Carolina is age 24 or younger compared with 35 and 33 percent in Illinois and New Jersey, respectively. African Americans account for the largest share of each caseload, but for a smaller share of the caseload in New Jersey  the only study state that includes a substantial number of Hispanic families. South Carolina's single-parent population is somewhat more educated, with almost two-thirds having completed high school. The caseload in New Jersey has the largest representation of families with just one child and the fewest number of families with a child under the age of three. Finally, the states show different durations of the current TANF spell. With 39 percent of its caseload in the midst of a TANF spell that has lasted 25 or more months, Illinois claims the greatest representation of long-term cases on its caseload. In New Jersey, 27 percent of cases have received TANF continuously for 25 or more months while, in South Carolina which has a two-year time limit, only 6 percent of the caseload has received assistance for this long. (Illinois and New Jersey both have a 60-month time limit and Illinois "stops the clock" for families who are working 30 or more hours per week.)

Table I.3.
Characteristics of TANF Recipients in the Study States
(Percentages unless otherwise indicated)
Characteristics Illinois New Jersey South Carolina
Female 98 95 98
Age (years)
Younger than 20 8 9 11
20-24 27 24 32
25-29 21 19 20
30-39 30 31 25
40 or older 13 17 12
Race/Ethnicity
AfricanAmerican,Non-Hispanic 82 57 73
White,Non-Hispanic 12 14 26
Hispanic/other 7 29 1
Marital Status
Never married 84 78 71
Ever married 17 22 29
Education
Lessthanhighschooldiploma/GED 49 46 36
High school diploma/GED 40 41 50
More than high school diploma/GED 11 10 14
Number of Children on TANF Case
0 2 4 1
1 29 54 37
2 28 25 34
3 20 11 18
4 or more 21 6 10
Age of Youngest Child on Case(years)
Younger than 1 27 15 11
1-3 26 18 37
3-5 17 20 22
6 or older 30 47 31
Duration of Current TANF Spell (months)
Fewer than 6 22 51 52
6-11 18 10 28
12-24 21 12 15
25ormore 39 27 6
Number of TANF Cases 33,478 51,539 10,852
Source: Analysis of state administrative data by Mathematica Policy Research, Inc.
Note: Some distributions do not add to 100 due to missing data or rounding.

TANF Administrative Structure. The implementation of welfare reform required local welfare offices to expand their capacity to provide employment services and monitor their use. Many expanded their reliance on contracted service providers and restructured staff responsibilities. As shown in Table I.4, the study sites use a variety of administrative arrangements to provide employment services to TANF recipients and to track program participation.

In each of the study sites, in-house welfare agency staff provide case management. Welfare case managers have primary responsibility for conducting assessments, developing employment plans, monitoring and tracking participation, and imposing and lifting sanctions. In some offices, they may also provide job readiness services to TANF recipients on their caseload, assisting with such tasks as completing a resume or filling out a master application. In addition to its regular case managers, one local welfare office in New Jersey uses intensive case managers with reduced caseloads to work with hard-to-employ clients and those nearing the welfare time limit. When contracted employment service providers are used, TANF clients referred to these providers receive additional case management from staff at the providers. However, primary responsibility for developing and monitoring an employment services plan rests with the case managers in the TANF agency.

In all the local sites, employment and training service providers (some contracted and some in-house) play an important role in implementing TANF sanctions. Their responsibilities include: (1) providing information to recipients on work requirements and consequences for noncompliance; (2) providing work-related activities in which TANF recipients can participate; (3) monitoring daily participation in work activities; and (4) participating in case staffings, conciliation reviews, and case conferences for TANF recipients who are experiencing participation problems or are at risk of sanction. In four of the six sites, one or more contractors deliver these services. In the two sites in South Carolina, specialized employment units staffed by workers employed by the TANF agency deliver the needed services.

Several of the welfare offices created specialized positions or units to streamline the process for implementing TANF sanctions. In one local office in Illinois, an employment and training liaison handles monitoring and tracking of all 900 TANF recipients participating in employment and training services. Both local offices in New Jersey created separate units to implement eligibility changes for sanctioned TANF recipients. The units handle all transactions involved in executing a sanction and monitoring its progression over time. Finally, one local office in New Jersey hired a specialized social worker to help clients reverse their sanction. She conducts a weekly sanction compliance meeting and assists clients with meeting the work requirements so that their sanction can be lifted.

Table I.4.
Administrative Arrangements for Implementing Work Requirements and Sanctions
  Illinois
Office A
Illinois
Office B
New Jersey
Office A
New Jersey
Office B
South Carolina
Office A
South Carolina
Office B
TANF caseload:
Total
Work mandatory

1,400
500

1,500
900

4,200
2,000

2,400
1,400

1,513
690

833
350
Approach to case management Combined eligibility and case management Combined eligibility and case management Separate eligibility worker and case manager Separate eligibility worker and case manager Separate eligibility worker and case manager Combined eligibility and case management
Caseload size per case manager 115 TANF cases 150-160 TANF cases 150-200 TANF cases 100-125 TANF casesa
150-170 TANF cases 200 benefit cases (50 TANF)
Employment services provided in-house Case management Case management Case management Case management Case management
Home visits
Job search and job readiness (specialized unit)
Case management
Job search and job readiness (specialized unit)
Contracted employment service providers 10 service providers 6 service providers 1 provider 5 service providers None None
Types of responsibilities contracted out Employment and training services
Employment and training services
Mental health/substance abuse
Employment and training services Employment and training services
n/a n/a
Employment service provider's involvement with the implementation of TANF sanctions Monitoring and tracking
Participation in conciliation reviews
Monitoring and tracking
Participation in conciliation reviews
Monitoring and tracking
Monitoring and tracking Monitoring and tracking Monitoring and tracking
Frequency and types of reporting on program participation Monthly reports Monthly reports Weekly reports Weekly reports Immediately after non-participation Immediately after non-participation
Specialized units or staff for implementing or lifting sanctions None Employment and training liaisonb Sanctions unit (manages eligibility changes) Sanctions unit (manages eligibility changes)
Specialized social worker
None None
a Case managers in the EFFORTS program for hard-to-employ recipients carry caseloads of 40-50 cases. Social workers for those nearing the time limit carry caseloads of 50-75 cases.
b The employment and training liaison monitors and tracks 900 TANF recipients served in office B. She imposes and lifts all TANF sanctions.

Endnotes

(1) In New Jersey, data were collected for a comprehensive evaluation of Work First New Jersey, a multiyear study conducted by Mathematica Policy Research, Inc., for the state of New Jersey. In Illinois, data were collected for a study of the characteristics and service needs of Illinois' current TANF caseload. The study was conducted by Mathematica Policy Research, Inc. with funding from ASPE and the Annie E. Casey Foundation. In South Carolina, data were collected as a part of an ASPE-funded multistate project to understand the characteristics and needs of families receiving TANF cash assistance.

(2) All three of the surveys had a response rate of at least 75 percent.

From Policy to Practice: Implementing TANF Sanctions

In most states, state law specifies the approach to sanctioning noncompliant TANF recipients. To ensure that all noncompliant families face the same penalty, states often specify in great detail the amount of the sanction, its duration, and the actions a TANF recipient must take to come into compliance. While it is relatively easy to catalogue state sanction policies, we know little about how sanctions are applied in practice and how their use varies. Federal law is silent on how TANF sanctions should be implemented. For example, we do not know if TANF staff routinely apply sanctions for all recipients immediately after a specified period of noncompliance or if they consider a client's circumstances before imposing a sanction. Similarly, we do not know what, if any, actions workers take to encourage compliance before imposing a sanction. To gain greater insight into how sanctions are used to promote participation in work activities, this chapter presents analyses of detailed case study data on the implementation of TANF sanctions in each of two welfare offices in the three study states.

Two fundamental research questions guide our analysis:

  • What is the relative importance of policies, administrative procedures, and worker discretion in determining how TANF sanctions are implemented?
  • What influence do individual client circumstances have on the implementation of TANF sanctions?

To answer these questions, we divide the implementation of TANF sanctions into six tasks: (1) informing clients about work requirements and sanctions, (2) defining program expectations and requirements, (3) monitoring participation in work activities, (4) deciding whether to impose a sanction, (5) imposing a sanction, and (6) reengaging sanctioned recipients in program activities. We consider each of the tasks in the order in which they typically occur.

For the present analysis, we gathered information on the implementation of TANF sanctions from several sources and using various case study methods. In each local office, we conducted semistructured interviews with program administrators, eligibility workers, case managers, and employment services staff, reviewed a small number of cases, and examined written program materials and documents. Given that we conducted interviews with a small number of staff in only a few offices in states with different sanction approaches, it is difficult to make broad generalizations about many aspects of the implementation of TANF sanctions. The information presented in this chapter represents our efforts to identify common themes within and across offices based on the information provided to us. We acknowledge that there may be a broader range of approaches and perceptions about the challenges to implementation than we uncovered.

Informing Clients About Work Requirements and Sanctions

Sanctions are intended to encourage recipients who otherwise might not be inclined toward work or program participation to participate in work activities. Accordingly, clients must know what is expected of them and understand the associated consequences. In addition, they must believe that sanctions will be enforced and recognize that adverse effects could result from them. Similar to other studies (U.S. DHHS 1999; Nixon, Kauff, and Losby 1999; Overby 1998), we find that TANF clients routinely receive information on work requirements and sanctions, but case managers are skeptical about how well they understand it, at least initially. To increase the effectiveness of sanctions, some case managers regularly remind clients that a sanction will be imposed if they do not participate in work activities.

Key Findings:
Informing Clients about Work Requirements and Sanctions
  • Clients in the study sites receive information about work requirements and sanctions often and in many forms. However, case managers believe that both personal and organizational issues undermine some clients' ability to fully grasp the consequences associated with nonparticipation.
  • Many case managers believe that sanctions can influence some clients' program participation decisions. Therefore, they regularly use the prospect of a sanction to encourage recipients to participate in work activities.

In each of the study sites, TANF clients routinely receive information on work requirements and sanctions both when they apply for assistance and when they begin a work activity, especially group job search. Information is primarily provided verbally in both one-on-one and group sessions. In some cases, the verbal information is supplemented with written materials.

In all the sites, clients first learn about work requirements and sanctions in their initial intake interview. Work requirements are described as a condition of eligibility, with sanctions presented as the consequence for not meeting them. In programs that offer group job search activities, the information is reiterated in a group orientation session that often serves as a gateway to the program. Case managers focus on work requirements and sanctions in great detail when they develop an employment, self-sufficiency, or individual responsibility plan with a TANF client. In all the sites, case managers typically give clients a copy of their signed employment plan, which outlines their rights and responsibilities. In one of the local offices in South Carolina, case managers visit clients in their homes to provide an overview of the TANF program, conduct an initial assessment, and develop an employment plan. As a part of the meeting, they give clients a "rights and responsibilities" handout that describes what is required of them and the consequences of not following through with their responsibilities.

Despite efforts to inform clients about sanctions, case managers believe that personal and organizational issues sometimes undermine clients' ability to grasp fully the consequences associated with nonparticipation. First, case managers acknowledge that the volume of information clients receive about other welfare policies (e.g., time limits, diversionary assistance, earned income disregards) and the resources available to help them find employment (e.g., job search programs and child care assistance) may interfere with their ability to understand completely the TANF work requirements and associated sanctions. The receipt of so much information at one time makes it difficult for clients to focus on any one aspect of the program requirements or consequences.

Second, case managers believe that the complexity of clients' lives sometimes interferes with their ability to focus on future consequences. In the experience of case managers, clients overwhelmed by personal and family challenges such as substance abuse, physical and mental health conditions, domestic violence, and child behavioral problems have difficulty focusing on anything other than how to address their most immediate needs and problems. Third, case managers express concern that clients may be aware of TANF sanctions but do not believe they will be imposed. Case managers think that clients' skepticism stems from limited use of sanctions before welfare reform and the uneven and changing imposition of sanctions in the current system. Finally, case managers believe that because some clients have other sources of support (e.g., unreported employment income, family, a spouse or partner, other government assistance, and so forth), they pay little attention to any information they receive on sanctions, and do not respond when a sanction is imposed, presumably because the adverse consequences are buffered by the availability of other supplemental resources.

Still, case managers report that, for some clients, the possibility of a sanction is sufficient to motivate them to participate in work activities. Thus, some case managers remind clients about the consequences of nonparticipation at every opportunity, but especially during telephone conversations and meetings, during conciliation reviews, and by means of sanction notices. Many case managers in the study sites indicated that the current sanction policies give them more leverage to enforce participation than previous sanction policies, thus making them more likely to use them to encourage participation. Case managers believe that, through their efforts, they are able to influence the behavior of some recipients, reducing the need to impose sanctions. Thus, they believe that sanction rates may not fully capture the impact of sanctions on increasing participation in work activities.

Defining Program Expectations and Requirements

PRWORA established broad rather than specific parameters to encourage participation in work activities, leaving states and localities with some flexibility to decide who must participate and in which activities. In general, states follow one of two approaches in determining who should be required to participate in work activities. They rely on either a universal engagement model, whereby they require all recipients to participate in work-related activities, or an exemption model, whereby they do not impose any work requirements on recipients who possess certain characteristics or face particular employment barriers. Common reasons for granting exemptions include personal and family challenges such as mental or physical health conditions that limit work and logistical challenges such as the lack of transportation or child care that also limit work.

States or local offices that have adopted a universal participation requirement often encourage participation in a broad range of program activities and permit flexibility in the required number of hours of participation. In contrast, states or local offices that exempt recipients tend to focus on placing recipients in more traditional work activities, primarily those defined as "countable" activities under PRWORA. The implementation of a universal participation requirement typically affords line staff considerable latitude to decide both how much and in what activities a recipient should be required to participate. In contrast, the implementation of an exemption approach often requires adherence to a defined set of procedures to determine who should be exempt and the placement of nonexempt recipients in a defined set of program activities.

The study sites all exempted some clients from participation in work activities and took similar approaches for doing so. All the study states grant exemptions for household heads who are experiencing physical and mental health conditions, are caring for a disabled family member, or are a current victim of domestic violence. The states also grant exemptions for household heads in their last trimester of pregnancy. New Jersey requires parents to begin participating in program activities when their youngest child turns four months; Illinois and South Carolina do not require parents to start participating until their youngest child is a year old.

In general, case managers follow an explicit set of procedures to determine who should be required to participate in work activities. While case managers exercise some discretion in modifying participation requirements, they expect most recipients to participate in countable activities for the number of hours per week specified in current federal law.

Key Findings:
Defining Program Expectations and Requirements
  • Although the study sites have instituted formal procedures for identifying recipients who should be exempt from work requirements and for assessing the needs of nonexempt recipients, potential barriers to employment often are not uncovered until participation problems arise.
  • Staff believe that more flexibility in how work requirements are implemented would provide them with greater opportunities to engage all mandatory participants in work activities.

Case managers rely on a combination of formal screening tools, assessment skills, and professional experience to identify clients' assets and liabilities and to determine which clients should be required to participate in work activities. Assessment generally begins at intake and continues throughout service delivery. Case managers use several techniques for assessing clients and identifying their needs, including initial screenings, formal assessment tools, informal interactions with the client, and intra- and interagency case conferences and sanction conciliation reviews.

Initial Screenings. Welfare staff begin to identify clients who qualify for an exemption from work requirements during the initial intake interview or immediately after clients are deemed eligible for cash assistance. Formal exemptions generally require additional documentation and undergo periodic review to determine if the client is ready to participate. Given the usually clear specification of exemption criteria, screening is a straightforward and rapid process. The challenge for case managers is to encourage clients to return the documentation required to verify the circumstances that qualify them for an exemption and to disclose hidden barriers to employment (such as substance abuse, mental health conditions, domestic violence) that may pose problems for participation.

Formal Assessments. In all the study sites, the development of employment plans for nonexempt clients begins with in-depth assessments of clients' assets and liabilities. Some sites use formal assessments throughout the service delivery process. Welfare staff, employment and training service providers, and licensed professionals conduct the assessments. Welfare staff conduct an upfront assessment to determine the types of work activities to include in the client's employment plan and to identify the employment and training service provider to which they should be referred. The upfront assessments also focus on identifying logistical barriers such as transportation and child care and, in some cases, hidden barriers such as domestic violence, mental health issues, and substance abuse. Employment and training service providers' assessments reflect the types of services the agency provides. Agencies that provide education and training services administer basic skills tests (e.g., COPES, COPS, TABE), career interest inventories, and learning style assessments. Assessments conducted by agencies that primarily provide job search services tend to focus on personal and family challenges that may interfere with employment. Assessments conducted by employment and training providers may be conducted individually or in groups. Finally, clients who appear to have mental health or substance abuse problems may be referred for a more specialized clinical assessment. For example, in Illinois, mental health and substance abuse treatment staff who are colocated in the welfare office assess clients and link them to services. In South Carolina, a licensed psychologist at the South Carolina Department of Vocational Rehabilitation conducts in-depth psychological assessments. TANF recipients in New Jersey may be assessed either through specialized mental health or substance abuse initiatives or by vocational rehabilitation specialists.

Interactions with Welfare and Employment Services Provider Staff. According to case managers, clients are more likely to disclose barriers to employment when they trust the staff working with them. Typically, trust develops over time during routine interactions. Case managers report that smaller workloads and an emphasis on individualized case management help them develop trusting relationships that allow them to uncover hidden barriers that often contribute to participation problems.

Case Conferences/Conciliation Reviews. Welfare staff indicated that, in many cases, clients do not reveal hidden barriers to employment until they are faced with a sanction. Sometimes, clients may not be aware of how personal and family challenges interfere with working until they attempt to work or participate in program activities and fail in these endeavors. In such cases, the imposition or possibility of a sanction forces clients to acknowledge the presence of a hidden barrier and provides staff with an opportunity to work with clients to develop a plan for addressing the obstacle. Clients can address these issues formally through case conferences and conciliation reviews.

Exemptions eliminate work requirements only for those with the most serious barriers to employment. Regardless of their circumstances, all other recipients are expected to meet the same 30- or 35-hour per week participation requirement. In view of the wide variation in client circumstances, case managers report that they face many challenges in trying to encourage high levels of participation in work activities. Initially, the study sites almost always place recipients in a standard set of program activities. When participation problems arise, case managers can sometimes grant "good cause" exemptions to excuse clients temporarily from work activities. In addition, case managers can sometimes modify clients' work requirements to account for individual circumstances. Both strategies involve considerable case manager discretion.

Compared with formal exemptions, good cause exemptions are more immediate, temporary, and typically do not require formal documentation. Good cause exemptions often are provided for doctor's appointments, caring for a sick child, or attending a court hearing. They also may be granted for a situation that is expected to last for a short time (e.g., a temporary medical problem). While good cause can be used to excuse clients fully from their work requirement, it is more often used to grant an "excused absence" for missed hours or days.

In the study sites, most TANF recipients are required to participate in a relatively standard set of work activities, mainly group job search, and, in some instances, short-term training and work experience programs. The two sites in Illinois expect most recipients to participate in work activities at least 30 hours per week. In one local office, clients may be assigned to a paid work placement for which they receive the full amount of the TANF check for working at least 30 hours per week. The grant amount is reduced for each hour that falls below the 30-hour requirement unless there is good cause. In South Carolina, the Department of Social Services (DSS) specialty unit provides a range of work activities (e.g., job search, job club, basic and advanced family life skills workshops) for TANF recipients who, like Illinois TANF recipients, are required to participate at least 30 hours per week. In New Jersey, all recipients are required to participate in activities for 35 hours per week. Clients usually are assigned to activities that count toward the federal work participation rate.

Even though the study states rely primarily on a "work first" approach, case managers may modify work plans for clients with barriers. For example, clients with a mental health condition may be allowed to count the hours in therapy toward their required work hours, or the case manager may temporarily reduce the number of hours clients are required to participate in work activities. According to case managers, flexibility allows them to develop attainable requirements for clients with serious and persistent barriers. To provide modified opportunities to clients, the sites relied on various strategies to improve access to specialized services. For example, mental health or substance abuse treatment providers may be colocated at the welfare office or with the employment service provider. One of the New Jersey offices contracts with the Division of Mental Health to provide counseling services for 100 TANF recipients. An employment service provider in one of the Illinois offices offers a series of workshops focusing on mental health conditions, substance abuse, and domestic violence. Another program provides intensive case management, parenting classes, and GED services for teen parents.

While we observed some flexibility in work requirements, staff indicate that they face considerable pressure to place clients in countable work activities in order to meet the federal work participation requirements. One program administrator complained that, in some cases, the limited flexibility forces staff to adopt unrealistic expectations of TANF recipients, particularly hard-to-employ recipients, who are at higher risk for sanctions. Case managers believe that limited flexibility sometimes creates a mismatch between what clients are required to do and what they are able to do. Case managers and program administrators believe that more flexibility would help them in setting realistic participation expectations for families experiencing several challenges in their lives.

Monitoring Participation in Work Activities

Monitoring participation in work activities is an integral component of implementing TANF sanctions. Careful monitoring provides case managers with the information they need to identify clients who are not participating in program activities and therefore are at risk of sanctions. Given that several case managers and several agencies are often involved in arranging and monitoring employment-related services for TANF recipients, the development of an effective monitoring system is a complicated endeavor. Effective monitoring and tracking of participation in work activities requires frequent contact with clients, clear communication between case managers and employment service providers, and efficient and timely reporting procedures.

The study sites all have systems in place for monitoring participation in program activities. The specific procedures used to monitor participation varied across the sites, but the case managers uniformly reported that they had access to the information they needed to monitor compliance with work requirements and that the information was provided to them in a consistent and timely manner. Still, local TANF administrators reported that monitoring participation is an ongoing challenge.

Key Findings:
Monitoring Participation in Work Activities
  • Although several workers and, in most cases, several agencies in the study sites play roles in providing services and monitoring participation, case managers consistently reported receiving the information they need to identify participation problems and make sanctioning decisions.

Because of the way we selected the sites for the study, we have no way of knowing the degree to which the experiences of the study sites are representative of the experiences of most other local welfare offices. It was clear that the offices in the study sites had invested considerable time and energy to develop monitoring and tracking systems that allowed them to monitor program participation closely and in a timely manner. In a study of pre-welfare reform employment programs, Hamilton and Scrivener (1999) found that programs with a high level of enforcement, including close monitoring and tracking, produce higher participation rates than programs with a low level of enforcement. Effective monitoring may also benefit clients: knowing that their participation may be closely monitored might motivate clients to participate in program activities to avoid sanctions. Close monitoring of program participation also may expedite the identification of clients who are not participating because of one or more personal or family challenges or logistical barriers.

Each of the local welfare offices we visited during the study rely on formal and informal mechanisms for monitoring and tracking client participation. The offices use the information gathered on participation to make decisions about granting regular and good cause exemptions and imposing and reversing sanctions. Case managers rely little on client self-reports to track participation. Instead, the local welfare agencies we visited rely heavily on employment service providers or in-house employment units to manage monitoring and tracking responsibilities. In most cases, the welfare agencies themselves provide at least some employment-related services, making it possible for them to observe directly whether a client is participating. While monthly monitoring and tracking reports are the main source of information on participation, case managers also used other formal and informal communication strategies to obtain information on current participation and to confer with their colleagues about strategies for overcoming participation problems.

Monitoring and Tracking Reports. Most employment service providers in the study sites submit a weekly or monthly tracking report to the welfare office as a condition of their service contract. The reports summarize the number of hours and types of activities in which clients participated for the designated time period. In local offices with high caseloads where managers have less face-to-face contact with clients, welfare staff rely heavily on the monitoring and tracking reports to identify clients who are not participating in work activities.

Direct Notification. In addition to formal reports, employment service providers in each of the sites we visited during the study contact the case manager directly by telephone or e-mail when a client fails to attend a workshop session or participate in some other work activity. In most cases, employment service providers notify case managers within a few days if a client is not participating in work activities.

Formal Case Conferences. In some of the local offices, welfare and employment service provider staff meet regularly to discuss cases. For example, in one local office in New Jersey, staff from the local community college and welfare office conduct biweekly "Job Link" meetings in which they discuss problem cases, including clients not participating in work activities. In one South Carolina office, unit supervisors meet monthly with case managers to identify clients who are not participating and to determine how they may reengage them in program activities.

Informal Contact Between Welfare and Employment Service Provider Staff. Within most local welfare offices, welfare and employment service provider staff engage in frequent exchanges. In one local office, the administrator from the employment service provider visits the welfare office weekly to interact with staff. In some cases, employment service providers are colocated in the welfare office or are otherwise nearby. In one of the South Carolina offices, the in-house specialty unit provides employment services to TANF clients in a double-wide trailer located in the parking lot of the welfare office. Such proximity facilitates regular interaction among staff, making it easy to share information on clients who are not participating in work activities.

Deciding Whether to Impose a Sanction

Nonparticipation in work activities triggers the start of a process whereby case managers decide whether to impose a sanction. Case managers might simply base their decision on a client's record of participation, or they might follow a more personal approach, taking into account a client's unique circumstances. The two approaches afford case managers markedly different degrees of discretion: the first approach offers little discretion while the second approach offers considerable discretion. While less discretion may result in more equitable application of sanctions, case managers' exercise of more discretion provides clients with the opportunity to disclose and resolve issues that may have contributed to their inability to participate in program activities.

The study sites used a combination of the two approaches. When a recipient shows no record of participation in program activities and has had no contact with any program staff, case managers almost always decide to impose a sanction. The process for handling cases that show some record of participation is much more complicated, resulting in some variation among case managers within a site and substantial variation across sites.

Key Findings:
Deciding Whether to Impose a Sanction
  • Case managers often exercise considerable discretion in deciding whether and when to initiate a sanction; office culture, workload, individual work styles, and client circumstances all influence their decisions.
  • Except when workload issues prevent them from doing so, case managers in most offices try to reengage clients in program activities before initiating a sanction.

When case managers need to decide whether to impose a sanction, they weigh the cost of imposing the sanction against potential benefits. When sanctions are not imposed, the result may appear inequitable to other clients who are sanctioned for nonparticipation. In addition, if clients do not believe that a sanction will be imposed, they may be less likely to comply with program requirements. Case managers work in different office cultures, carry varying workloads, and build different relationships with their clients, all of which influence how they approach their work generally and how they approach sanctions specifically.

Sanction Message. Several factors converge to create a unique culture in each welfare office. With respect to sanctions, program administrators often set the tone as to how they are implemented. For example, a local administrator may decide that sanctions should be imposed only as a last resort; others, believing that the imposition of sanctions will lead to greater participation, might decide to impose sanctions without delay. In some cases, the local office culture may reflect a position taken by state administrators and handed down to local administrators. The use of sanctions in South Carolina over time illustrates the extent to which program administrators influence the decision on whether to impose sanctions. After a change in administration, the fraction of cases closed because of a sanction dropped from 25 percent to between 5 and 10 percent. At the outset of welfare reform, South Carolina's state welfare administrator emphasized a strong "work first" message that used immediate full-family sanctions to promote participation in work activities. His replacement, with pressure from local advocacy groups, changed the state's sanction philosophy from using sanctions as a first to a last resort.

Case Manager's Workload. When case managers carry large caseloads, they are more likely to rely solely on participation reports to decide whether to impose a sanction. Large caseloads make it impossible for case managers to individualize case management activities and less likely to be able to do the work necessary to uncover the conditions that might be contributing to participation problems. When case managers carry large caseloads and need to follow complex procedures for imposing a sanction, time constraints alone lead to the imposition of few sanctions. In fact, local offices with high workloads tend to automate rather than individualize the sanction process. For example, in one local office in New Jersey with heavy workloads, case managers rely on reports from employment service providers to determine when to impose sanctions. In another local office in New Jersey where case managers carry more manageable workloads they conduct home visits, telephone clients, and send letters to clients before imposing a sanction.

Complexity of the Sanction Process. In study sites characterized by a complex sanction process, case managers often are reluctant to impose sanctions because of the time needed to navigate the sanction process. For example, in one of the local sites, the review process for imposing a sanction includes a conciliation review, an extensive written report, and approval from the supervisor and local office administrator--a process that takes between two and four months. Accordingly, workers report that they use sanctions to encourage compliance but rarely impose them.

Relationship with the Client. Case managers in the study sites frequently mentioned that their decisions about whether to impose sanctions are influenced substantially by their relationships with their clients. Case managers report that they are less likely to initiate a sanction if the client consistently communicates with them about their circumstances. It is when clients do not respond to case managers' telephone calls or letters that case managers tend to initiate a sanction. Case managers also indicated that they will continue to work with a nonparticipating client without imposing a sanction if the client is willing to "meet them halfway" by making an effort toward progressing in their work plan. For example, for a client seeking a medical exemption from work activities, the case manager may identify a doctor who will conduct the evaluation but require the client to make the appointment to obtain the necessary documentation.

Comfort Level in Imposing Sanctions. Case managers vary in their comfort level in imposing sanctions. Some case managers worry about the sanction's adverse consequences on a family. Other case managers feel strongly that a sanction encourages recipients otherwise not inclined to participate to do so. When they are able to take steps to make sure that clients do not have any personal or family challenges that may limit their ability to participate, some case managers are more comfortable in imposing sanctions. Some case managers, believing that certain nonparticipating clients have access to other resources, are less concerned about adverse consequences and more willing to impose a sanction.

Number and Types of Personal and Family Challenges. Some case managers noted that they often give substantial leeway to clients with several serious barriers such as homelessness, mental or physical health problems, and learning disabilities, among others. If they believe that clients are facing circumstances that interfere with their ability to work or participate in work activities, they might delay the imposition of a sanction. Some case managers also take extra time to learn what might be causing a participation problem. For example, a case manager in one of the sites reported "a gut feeling" about a client who was not participating in her case plan. After conducting a home visit, the case manager discovered that the client had a child with severe behavioral problems and another child who was sick. Another case manager indicated that she checks the case record to see if nonparticipating clients have access to child care and transportation benefits. If they lack such supports, the case manager does not initiate a sanction.

Efforts to Reengage Clients Before Imposing a Sanction. In most of the sites we visited, case managers described extensive efforts to reengage nonparticipating clients before imposing a sanction. Case managers in each of the local offices send clients a sanction warning notice or letter advising them that that they are out of compliance, describing what they must do to meet participation requirements, and outlining the consequences of continued nonparticipation. Case managers in most of the local offices said that they contacted noncompliant clients by telephone. Two local offices, one in New Jersey and one in South Carolina, conduct home visits to nonparticipants. In some local offices, employment service providers also attempt to reengage nonparticipating clients. In all of the local offices, program administrators emphasize to case managers the importance of documenting efforts to reengage nonparticipating clients in the event that clients appeal the sanction. In both offices in South Carolina, the local office administrators will not approve a sanction unless case managers have documented that they made several attempts to reengage the nonparticipating client.

Imposing a Sanction

Imposing sanctions is one of many tasks performed by TANF eligibility workers. As such, the procedures for imposing a sanction are often closely related to the procedures for handling other eligibility functions. Imposing a sanction usually involves several steps: (1) documenting program noncompliance, (2) sending sanction notices to clients, (3) conducting sanction conciliation reviews, (4) changing eligibility codes in the automated system to reflect changes in program status and the grant amount, and (5) monitoring the level and duration of the sanction. While the decision to impose a sanction involves considerable worker discretion, the actual process for imposing a sanction after that decision has been made is primarily procedural and involves little worker discretion.

In the study sites, the process for imposing a sanction ranges from relatively simple to highly complex. The more complex processes occurred at two stages. The first set of complexities occurred at the documentation stage and involved several levels of review to ensure the appropriate documentation of program noncompliance. The second set of complexities occurred at the eligibility stage and involved several actions on the part of eligibility workers to impose and then monitor the level and duration of a sanction. Early in the implementation of welfare reform, several of the sites struggled with how to impose sanctions efficiently. Simple processes for implementing TANF sanctions that do not require several levels of review make it easy for workers to impose sanctions but do not necessarily provide assurance that sanctions are implemented properly.

Key Findings:
Imposing a Sanction
  • The ease with which a sanction can be imposed in the study sites is influenced by the design of the state's sanction policy, the state and local philosophy regarding sanctions, and the degree to which the sanction process is automated.
  • In all the study sites, processes are in place to promote proper use of sanctions.

Design of the State's Sanction Policy. Two of the study states (Illinois and New Jersey) implemented gradual full-family sanctions; South Carolina implemented immediate full-family sanctions. Given the interaction of several factors, it is difficult to tell how much the design of the state's sanction policy influenced the ease with which sanctions were implemented. Nonetheless, the state sanction policies clearly influenced the sanction process. In South Carolina, the design of the sanction policy (immediate full-family sanction) makes it relatively straightforward to change a recipient's eligibility status to take the sanction into account--the case is simply closed with a code indicating that the sanction was the reason for the closure. Because Illinois's and New Jersey's sanction policies are more complex and require multiple grant changes, they require more staff attention. In both states, case workers must initially reduce the grant and then later close the case if the family does not come into compliance. To streamline the process of imposing a sanction, both offices in New Jersey created separate sanction units to process all the eligibility changes for sanctioned TANF recipients. In one office in Illinois, these changes all are handled by one worker.

State and Local Philosophy Toward Sanctions. The experience in South Carolina demonstrates the way in which the state and local philosophy toward sanctions can influence the implementation of sanctions. When South Carolina made an explicit decision to reduce the use of sanctions, the approach to implementing sanctions shifted dramatically. After the decision, one local site required case managers to submit a detailed two- to three-page report describing the client's barriers, assigned work activities, and missed appointments; the case manager's efforts to reengage the client in work activities; and the outcome of reengagement efforts. The change in philosophy resulted in the imposition of fewer sanctions, along with substantial safeguards to reduce the inappropriate imposition of sanctions. (When these changes were implemented in South Carolina, the fraction of cases closed due to a sanction dropped from 25 percent to just 5 to 10 percent.)

Automation of the Sanction Process. As noted above, Illinois and New Jersey operate under similar sanction policies with gradual full-family sanctions and several levels of sanction for repeat instances of noncompliance. In both states, workers initially enter a code to reduce the grant, then they must follow-up at the appropriate interval to eliminate the full grant or close the case. The automated eligibility system calculates the amount of the grant, taking the sanction into account. However, workers must prompt the eligibility system to go from the initial partial sanction to the full-family sanction.

Despite variation across the study sites in the ease with which a sanction could be imposed, all sites have processes in place to promote proper use of sanctions. Local advocacy groups in South Carolina and Illinois were particularly influential in increasing awareness about the appropriate use of sanctions. The sites we visited during the study use different review processes to promote proper use of sanctions. All of the study sites require conciliation or supervisory reviews before imposition of a sanction. South Carolina requires approval from the supervisor and the county TANF director, and case managers use formal conciliation reviews to determine why clients are not participating in work activities as well as informal reviews to attempt to address clients' problems before imposing sanctions. One office in Illinois invites employment service staff and other community partners to attend conciliation meetings. Clients in all the study sites can appeal a sanction after it is imposed, although they rarely do so. The only sites in which clients brought appeals regularly were in New Jersey; one local site in that state received about 50 sanction appeals in one year.

Review processes also are in place for identifying clients who still receive TANF even though they are not complying with work requirements. Case managers acknowledged that sometimes clients "fall through the cracks." In one local office, supervisors gather information from participation reports and meet regularly with case managers to discuss cases in which sanctions have not been imposed on nonparticipating clients. The purpose of the review processes is to support case managers and clients and to ensure equity in the imposition of sanctions.

Reengaging Sanctioned Recipients in Program Activities

Sanctions are intended to encourage families otherwise not inclined to participate in work activities to do so. In some cases, reluctant participants might decide to participate immediately after they are informed of the financial penalties associated with not participating or after they receive a notice advising them that their grant will be reduced or terminated. However, some families may not respond to these early warnings. Thus, programs must develop strategies for reengaging recipients in program activities after they are sanctioned. In addition to providing opportunities for sanctioned families deciding to comply on their own, the strategies might include proactive outreach efforts designed to encourage families to come into compliance.

The study sites all had instituted explicit procedures (known as "cure" requirements) for reengaging sanctioned recipients in work activities. While local offices had some flexibility in the implementation of the procedures, they were largely constrained by state policy decisions. None of the sites had implemented outreach strategies designed to encourage recipients to comply following the imposition of sanctions.

Key Findings:
Reengaging Sanctioned Recipients in Program Activities
  • In developing procedures for reengaging recipients, states and local welfare offices face the difficult challenge of developing cure requirements that are achievable for most recipients without creating a revolving door that makes it easy for families to cycle in and out of participation.

States need to strike a delicate balance in developing and implementing cure requirements. Case managers believe that clients who complete strict cure requirements demonstrate that they have the capacity and willingness to participate in work activities. However, case managers worry that some clients with personal and family challenges may face barriers that preclude them from fulfilling the requirements. In addition, cure requirements perceived as too demanding may deter sanctioned clients from ever trying to comply. On the other hand, case managers fear that cure requirements that are too lenient may encourage clients to come into compliance, only to stop participating shortly thereafter. This revolving door increases the workload for welfare staff and may reduce the incentive for recipients to participate at the levels specified in federal law.

The study sites took different approaches to establishing cure requirements. In South Carolina, clients are required to participate in work activities for 30 consecutive days before the sanction is cured. New Jersey requires clients to participate for 10 consecutive days. If clients begin but do not complete the 10-day probationary period, they move to the next level of sanction, which is more stringent. In Illinois, clients must sign a "commitment to participate" form. Although state law specifies no minimum period of participation, Illinois case managers may impose a minimum probationary participation period. If the TANF case is closed, families must reapply for benefits and complete the 30-day up-front job search diversion requirement. All the states requiring a probationary period give sanctioned clients work supports (e.g., transportation and child care) as they try to cure their sanction.

In an effort to streamline the sanction compliance process, as a first step in curing their sanction, one of the local offices in New Jersey requires all sanctioned clients to attend a sanction compliance meeting held every Monday from 9:30 a.m. to 11:00 a.m. The purpose of the meeting is to (1) screen and assess clients, (2) advise clients what they must do to reverse their sanction, and (3) assist clients in obtaining child care and transportation assistance. The meeting is conducted by a case manager designated to work exclusively with sanctioned clients who need to cure their sanctions. She manages the entire process for reversing the sanctions. According to case managers, centralization of reengagement efforts reduces their workload since many clients who indicate an interest in curing their sanction do not follow through with participation in required activities. In the other sites, individual case managers work with clients as they reapply for benefits or try to have their benefits restored.

In all the sites, responsibility for initiating the process to cure sanctions resides with the client. Clients who want to cure their sanction are required to contact their case manager and complete the steps for lifting the sanction. None of the study sites has formal processes in place to conduct outreach to sanctioned TANF recipients once their TANF case is closed. All proactive efforts to encourage participation occur before imposition of the sanction.

Summary

This analysis suggests that sanction policies, administrative procedures, and case manager discretion all influence how sanctions are implemented at the local level. Sanction policies provide a framework for implementing TANF sanctions while administrative procedures provide case managers with the information and tools they need to impose the sanctions. In all the sites, case managers were well schooled in the structure of sanction policies and how to apply them. In deciding whether to impose a sanction, case managers consider both the severity of the sanction and the ease with which it can be applied. Some managers are hesitant to impose a more stringent sanction if they believe it will create too much hardship for a family, and many choose not to apply sanctions if the administrative procedures are cumbersome.

The extent to which case managers use their discretion in deciding whether to impose sanctions largely depends on their workload. When workloads are high and administrative procedures not particularly cumbersome, managers tend to base their sanction decisions solely on client participation, relying little on their discretion. When workloads are more manageable, case managers exercise considerable discretion in deciding whether and when to impose sanctions. Case managers often choose not to impose a sanction when they know that a family is facing serious personal and family challenges and actively working to overcome those challenges. Case managers with more manageable workloads also invest time in trying to reengage recipients in work activities before imposing a sanction. Only after those efforts fail do they begin the process of imposing a sanction.

In all the study sites, case managers report that encouraging the participation of all TANF recipients in a standard set of work activities (primarily job search) is an ongoing challenge because of the broad array of personal and family challenges clients face. Case managers rely on alternative program options when they are available and needed but feel that their efforts to address clients' individual circumstances often are constrained because of the emphasis on engaging recipients in a standard set of countable work activities. While they have some flexibility to modify recipients' employment plans, case managers would prefer a system that routinely permits them to engage recipients in a broader range of program activities. They also feel that their efforts to address recipients' individual needs are hampered by recipients themselves. Despite routine assessments, case managers report that many personal and family challenges often remain unidentified until after participation problems arise.

Imposing TANF Sanctions: How Often, On Whom, and With What Outcomes?

The implementation of more stringent sanctions has raised the level of interest in understanding how often sanctions are imposed, on whom, and with what outcomes. Information on the frequency of sanctions can help us understand the role sanctions play in encouraging participation in work-related activities and helping families move towards self-sufficiency. It can also help us estimate how many recipients might be at risk of adverse consequences associated with the imposition of sanctions. Comprehensive information on sanctioned recipients can enhance our understanding of the demographic characteristics associated with higher rates of sanctioning and determine whether families facing personal and family challenges are at higher risk of sanctions. Finally, this information, combined with information on the employment of sanctioned recipients, can answer questions about how sanctioned recipients are faring.

This chapter uses administrative and survey data from the three study states to answer five research questions:

  • How often are sanctions imposed?
  • How do the characteristics of sanctioned and nonsanctioned recipients compare?
  • What is the impact of personal, family, and logistical challenges on the likelihood of a household receiving a sanction?
  • How do sanctioned recipients fare over time?
  • Do sanctions promote compliance with work requirements?

Because of data limitations, we cannot answer each question in all three of the study states. Instead, we expand our knowledge of the use of sanctions by exploiting the strengths of the data we have for each state. In all three study states, we are able to (1) document how often sanctions are imposed; (2) examine how often sanctioned recipients come into compliance, either because the sanction is lifted or because their TANF case is reopened; and (3) compare a limited set of background and demographic characteristics of sanctioned and nonsanctioned recipients. In South Carolina and Illinois, we can compare the presence of personal and family challenges and logistical barriers among sanctioned and nonsanctioned recipients. In Illinois, we can examine how these challenges and barriers independently influence the likelihood of being sanctioned when all other factors are held equal. Finally, in New Jersey, relying on the rich data collected for the Work First New Jersey evaluation, we can examine the employment and TANF status of families who were subject to a full family sanction for a year after the sanction was imposed.

How Common Are Sanctions in the Three Study States?

Comparable to earlier studies by Fein and Lee (1999) and Holcomb and Ratcliffe (2000), our analysis provides information on the use of sanctions for a cohort of recipients that we follow over time. The analysis allows us to answer the question: What fraction of current TANF recipients is now sanctioned or will eventually be sanctioned? We believe that the study's estimates provide a reliable picture of the extent to which the study states impose sanctions, the extent to which recipients come into compliance after a sanction is imposed and a relatively complete accounting of the number of families that may be adversely affected for extended periods by the financial penalties imposed on them. Because some recipients might have been sanctioned before our period of observation, our estimates provide a lower bound of the likelihood that a recipient has ever been or ever will be sanctioned. Importantly, these estimates do not account for all families whose behavior might have been influenced by the state's sanction policy. For example, they do not account for potential sanctions that are resolved through a reconciliation process prior to being imposed or for families who may have changed their behavior in response to the possibility of a sanction being imposed.

There are many factors that might influence how often sanctions are imposed. Before presenting our findings for the study states, we highlight particular factors that we expect could influence the rates we observe. Owing to differences in the design of South Carolina's sanction policy and lower benefit levels, we expected  before undertaking our analysis  that the state's sanction rate would be lower than the partial but higher than the full-family sanction rate in Illinois and New Jersey. We based our prediction on two assumptions. First, we assumed that the use of an immediate full-family sanction in South Carolina would encourage greater compliance before imposition of the sanction, thus lowering the state's sanction rate to somewhere below the partial sanction rates in Illinois or New Jersey. Second, we assumed that the greater financial penalty associated with a full-family sanction (due to higher grant levels) in Illinois and New Jersey would encourage greater compliance than the lower financial penalty in South Carolina, resulting in a higher full-family sanction rate in South Carolina. After learning through our site visit to South Carolina that the state has chosen to use sanctions only as a last resort, we revised our expectations and anticipated that we would observe a very low sanction rate in South Carolina, which would be lower than the full family sanction rate in either New Jersey or Illinois.

Illinois's and New Jersey's sanction policies are nearly identical and their benefit levels, similar; however, we expected to see a lower sanction rate in Illinois because of its applicant job search requirement and because of the presence of more longer-term recipients. The applicant job search requirement is intended to engage families in work activities rapidly and to provide TANF benefits only to those willing to look for work actively or who can demonstrate that they are experiencing personal or family challenges that limit their ability to work. Almost certainly, among the families that do not fulfill the job search requirement are those that would have experienced difficulty in meeting the work requirement if their application for assistance had been approved; such families would have been candidates for sanctioning if the requirement were not in place. Our visits to the two local offices confirmed that the offices enforce this requirement, with administrators reporting that many families that apply for assistance never complete the process.

In both Illinois and New Jersey, case managers appear to impose sanctions regularly when recipients are not complying with work requirements and they have exhausted their efforts to reengage them. Since recipients are expected to begin meeting their work requirements shortly after they begin receiving assistance, we would expect sanctions to be imposed less frequently on longer-term recipients who presumably are meeting their work requirements or they would have already been sanctioned. Since Illinois has more long-term recipients on their caseload, we would expect their sanction rate to be somewhat lower than New Jersey's.

As we anticipated, the rate at which the study states impose sanctions differs somewhat between Illinois and New Jersey and, substantially between South Carolina and the other two study states (see Table III.1). Over 10 months  the maximum period for which we have data for all three states  only 5 percent of South Carolina TANF families had received a full-family sanction. In Illinois and New Jersey, the full-family sanction rate over the same 10-month period was 10 and 12 percent, respectively. Over this same time period, 24 percent of families in Illinois and 30 percent of families in New Jersey experienced any type of sanction, including a full-family sanction. When we consider the full 18-month time period for which we have data, the percentage of families with any grant reduction due to a sanction in Illinois and New Jersey increases to 31 and 39 percent, respectively. In both Illinois and New Jersey, about 40 percent of those sanctioned over the 18-month follow-up period were sanctioned within the first three months and about 60 percent were sanctioned within the first six months.

The sanction rates in all three states are lower than those found in previous studies using a similar methodology. For example, in their analysis of the use of partial sanctions in Indiana, Holcomb and Ratcliffe (2000) found a sanction rate of 45 percent over a 12-month period. In their analysis of the use of gradual full-family sanctions for participation in work-related activities in Delaware, Fein and Lee (1999) found a sanction rate of 52 percent over an 18-month period.

Table III.1.
Incidence and Timing of Sanctions
(Percentages, Unless Otherwise Indicated)
  Illinois New Jersey South Carolina
Initial Partial Full Any Initial Partial Full Any Full
Full Sample
Ever received sanction through month:
1 6 3 8 8 0 8 1
3 10 5 13 15 3 16 2
6 16 7 19 23 8 25 3
9 20 9 24 28 11 30 4
10 21 10 25 29 12 31 5
12 23 11 27 32 14 33 n.a.
15 25 12 29 35 16 37 n.a.
18 26 13 31 38 17 39 n.a.
New Entrants Only
Ever received sanction through month:
1 1 3 4 2 0 2 0
3 4 4 8 10 1 10 1
6 10 5 14 22 5 23 3
9 16 7 20 27 11 29 4
10 17 7 21 29 12 30 5
12 19 8 23 31 14 33 n.a.
15 21 9 25 34 16 35 n.a.
18 22 10 26 36 17 38 n.a.
Sample Size
Full sample 33,478 51,539 10,852
New entrants only 2,246 23,267 961
Source: Analysis of state administrative data by Mathematica Policy Research, Inc.
Note: "New entrants" are defined as those whose case opened in November 2001 in Illinois; those who were not receiving TANF in June 2000, but who entered or returned to the program some time during the one-year period, July 2000 to June 2001 in New Jersey; and those whose case opened in June 2002 in South Carolina.
n.a. = Data are not available.

Surprisingly, in all three states, the sanction rates for new entrants are almost identical to those for all recipients. Working on the assumption that many noncompliant families would have already been sanctioned off the rolls, we would have expected the sanction rate for new entrants to be higher. The similarity in rates might reflect the presence of many short-term recipients on the caseloads, creating less of a distinction between current recipients and new entrants than was evident before welfare reform. In addition, in some cases, these new entrants may be clients who are returning to TANF after receiving a full-family sanction and may, therefore, be particularly prone to receiving another sanction.

The availability of county-level data in New Jersey and Illinois allows us to compare sanction rates in different localities that are operating under the same set of policies. In New Jersey, we find that sanctioning rates vary substantially by county, even after adjusting for differences across counties in the demographic characteristics of their caseloads (not shown). Adjusted partial sanctioning rates across the New Jersey counties during a 12-month period range from less than 20 percent of recipients sanctioned in some of the more rural counties in the northwestern part of the state to 41 percent sanctioned in Essex County, New Jersey's largest and most urban county (where Newark is located). Similarly, adjusted full-family sanctioning rates range from 5 percent or less in some smaller, more rural counties to 20 percent for full-family sanctions in Essex County. In Illinois, those living outside Cook County (where Chicago is located) were slightly more likely to experience any sanction but equally likely to experience a partial sanction. Since New Jersey has a county-administered and Illinois has a state-administered TANF system, the differences in these findings are not surprising. Because it is a county-administered system, counties in New Jersey have more discretion in how they implement sanction and other work-related policies than counties in Illinois.

Which Recipients Are Most Likely to Be Sanctioned?

Consistent with previous studies, we find that, based on several measures, TANF recipients who are sanctioned are more likely to have characteristics that are associated with longer welfare stays and lower rates of employment. All else equal, those who are younger, less educated, or have never been married are significantly more likely to experience an initial sanction-related grant reduction or to be fully sanctioned in Illinois and New Jersey than families without these characteristics (see Table III.2).(3) We also find that, controlling for other characteristics, African Americans are more likely to be sanctioned than other racial and ethnic groups, while Hispanics and other nonwhites (typically Asians) are the least likely to be sanctioned in these two states. For example, African Americans in Illinois have a 24 percent probability of receiving an initial sanction-related grant reduction, while whites have a 20 percent probability; Hispanics, 18 percent; and other nonwhites, only 12 percent.

In South Carolina, younger and less educated TANF recipients are also more likely to be fully sanctioned. Other factors do not appear to affect significantly the probability of a full-family sanction, but the low rate of sanctioning in South Carolina makes it harder to identify important differences between various groups.

Table III.2.
Probability of Being Sanctioned, Controlling for Other Characteristics
  Predicted Probability of Initial Partial Sanction Predicted Probability of Full Sanction
Illinois New Jersey Illinois New Jersey South Carolina
Overall 23 32 11 14 5
Age in Years
Younger than 20 28 38 13 18 7
20 to 24 24*** 35*** 11** 15*** 6
25 to 29 20*** 33*** 9*** 14*** 3***
30 to 39 16*** 31*** 7*** 13*** 1***
40 or older 11*** 25*** 6* 10*** <1***
Ethnicity/Race
Non-Hispanic, African American 24 36 11 16 5
Non-Hispanic, white 20*** 27*** 10** 10*** 4
Hispanic, any race 18*** 26*** 8*** 11*** 2
Other 12*** 21*** 5*** 7*** 2
Marital Status
Never married 24 33 11 14 5
Separated, divorced, widowed 21*** 28*** 9*** 11*** 5
Married 20*** 27*** 10 11*** 3
Education
Less than high school diploma/GED 26 35 13 15 6
High school diploma/GED 21*** 30*** 9*** 13*** 4***
More than high school diploma/GED 19*** 27*** 8*** 11*** 3***
Number of Children in TANF Case
1 24 32 10 14 4
2 23 32 11 13*** 4
3 23 32 11 13*** 5
4 or more 23 32 10 13* 5
Age of Youngest Child in TANF Case
Younger than 1 24 31 9 13 5
1 to 2 25** 30 12*** 13 4
3 to 5 23 33** 11*** 15*** 4
6 or older 21*** 33*** 11*** 14** 5
Duration of Current TANF Spell
Less than 6 months 22 32 8 13 4
6 to 11 months 26*** 33** 11*** 16*** 5
12 to 24 months 25*** 31 12*** 15*** 5
25 months or more 22 32 12*** 14*** 4
Sample Size = 33,478 in Illinois; 51,545 in New Jersey; 10,852 in South Carolina
Source: Analysis of state administrative data by Mathematica Policy Research, Inc.
Note: Tests of statistical significance reported here refer to the difference between the predicted probability for clients with the particular characteristic and the predicted probability for those in the reference category (indicated by italics) in each group. For example, for the characteristic "age," the reference category is "younger than 20," and all significance tests compare the predicted probability for those in a particular age category to the value for those who are younger than 20.
*/**/*** Difference between the predicted probability for clients with this characteristic and for those in the italicized reference category significant at the .10 level / .05 level /.01 level/

Additional factors that can significantly affect the probability of being sanctioned in Illinois or New Jersey are the number of children on the TANF case, the age of the youngest child, and the duration of the current TANF spell, although findings along these dimensions are not as consistent across the states or between types of sanctions (initial partial or full-family) as those previously discussed. For example, in Illinois, in comparison to recipients whose youngest child is under the age of one, recipients whose youngest child is between the ages of one and two are significantly more likely to be partially sanctioned, but recipients whose youngest child is six years or older are significantly less likely to be partially sanctioned. Recipients whose youngest child is younger than one are significantly less likely than families with older children to be fully sanctioned. In New Jersey, families whose youngest child is between the ages of three and five or six and older are significantly more likely to be partially or fully sanctioned than recipients whose youngest child is under the age of one. We do find that recipients whose recent TANF spell has lasted longer than six months are more likely to be fully sanctioned in both states. However, part of this effect could simply be attributable to the greater opportunity for sanctions over time.

How Do Personal Liabilities Influence the Likelihood of a Sanction?

We matched survey data on detailed personal characteristics (or what we term personal liabilities and assets) with the administrative data on sanctions in Illinois and South Carolina to examine factors beyond basic background and demographic characteristics that may help identify those recipients at greater risk of a sanction.(4) Based on a bivariate analysis presented in Table III.3, we find that those with a physical health problem, those with a learning disability, those caring for a family or friend with a health problem or special need, or those who are pregnant or have a child under age one in the household are more likely to be fully sanctioned in South Carolina. Differences in other characteristics between ever- and never- sanctioned recipients in South Carolina are relatively large but not statistically significant, presumably because of the small sample size of sanctioned cases.

In Illinois, recipients with no high school diploma, with limited recent work experience, with a physical or mental health problem, with two or more arrests, or with a child care problem are much more likely to be sanctioned (either partially or fully) (see Table III.3). A logistic regression model confirmed the bivariate analysis results.

Table III.3.
Personal Liabilities by Sanction Status
  Illinois South Carolina
Ever Sanctioned Never Sanctioned All Ever Sanctioned Never Sanctioned All
Human Capital Deficits
No high school diploma or GED 54** 40 44 42 38 38
Limited recent work experience 73*** 54 59 70 57 57
Performed fewer than four common job tasks 26 29 28 30 25 25
Personal Challenges
Physical health problem 26* 19 21 42*** 21 22
Mental health problem 35*** 21 25 34 30 30
Criminal record n.a. n.a. n.a. 12 10 10
Multiple arrests 25*** 13 16 n.a. n.a. n.a.
Severe physical domestic violence in past year 12 13 13 10 14 14
Chemical dependence 5 2 3 1 1 1
Signs of a learning disability 10 13 12 28*** 11 12
Difficulty with English 1 3 2 4 1 1
Logistical and Situational Challenges
Child or other family member or friend with a health problem or special need 32 35 34 51** 32 33
Pregnant or child under age one in household 38 34 35 43* 28 28
Child care problem 42*** 28 32 24 31 31
Transportation problem 25 19 21 22 32 31
Unstable housing 28 21 23 16 22 22
Sample Size 114 302 416 56 1067 1123
Source: MPR analysis of the 2001-02 survey of Illinois TANF cases, the 2002 survey of South Carolina TANF cases, and administrative data on the TANF caseload provided by Illinois and South Carolina
Note: Ever sanctioned is defined as: ever being fully sanctioned within 10 months in South Carolina; and ever being either partially or fully sanctioned within 12 months in Illinois.
*/**/*** Difference between the predicted probability for clients with this characteristic and for those in the italicized reference category significant at the .10 level / .05 level /.01 level/
n.a. = Data are not available.

Table III.4 presents predicted probabilities in Illinois based on a model that estimates the relative influence of each personal liability on the likelihood that a recipient is sanctioned (partially or fully), assuming that a TANF recipient exhibits "average" characteristics (such as age, race, marital status, and so forth) and only the liability under consideration. The model predicts that a TANF recipient with no personal liabilities has a 12 percent chance of receiving a sanction. Recipients without a high school diploma have an increased chance  at 19 percent  of receiving a sanction. Recipients with a physical health problem, mental health problem, or multiple arrests have a 20 to 21 percent chance of ever being sanctioned. Recipients with limited recent work experience or with a child care problem have an 18 and 19 percent chance, respectively, of ever being sanctioned.

We also find that the likelihood of ever being sanctioned increases substantially when a recipient has four or more liabilities. With one liability present, the likelihood of being sanctioned is 24 percent. When two or three barriers are present, the probability of being sanctioned is only slightly higher at 25 percent. However, when four or more barriers are present the probability increases dramatically, to 42 percent.

Table III.4.
Probability of Being Sanctioned in Illinois by Personal Liabilities
Liability Prevalence (%) Direction and Significance of Effect Predicted Probability of Being Sanctioned Difference from Probability with No Liabilities
No Personal Liabilities 4   12  
Human Capital Liabilities
No high school diploma or GED 44 + * 19 +7
Limited recent work experience 59 + 18 +6
Performed fewer than four common job tasks 28 - 11 -1
Personal Challenges
Physical health problem 21 + ** 21 +9
Mental health problem 25 + * 20 +8
Multiple arrests 16 + * 21 +9
Severe physical domestic violence in past year 13 - 9 -3
Chemical dependence 3 + 19 +7
Signs of a learning disability 12 - 8 -4
Difficulty with English 2 - 4 -8
Logistical and Situational Challenges
Child or other family member or friend with a health problem or special need 34 - 9 -3
Pregnant or child under age one in household 35 + 18 +6
Child care problem 32 + * 19 +7
Transportation problem 21 + 15 +3
Unstable housing 23 - 12 0
Source: Based on the results of a logit model predicting the probability of being sanctioned using data from 2001-02 survey of Illinois TANF cases and Illinois administrative data.
Note: The predicted probabilities presented here are based on the results from estimating logistic regression models for sanction rates within 12 months in Illinois. The model included and controlled for clients' sex, age, race/ethnicity, marital status, number of children, age of youngest child, and length of the current TANF spell.
*/**/*** Estimated effect of specified liability on being sanctioned is statistically significant at the .10/.05/.01 level.
n.a. = Data are not available.

How Do Sanctioned TANF Recipients Fare?

To analyze how sanctioned recipients fare over time, we first examine the duration of sanctions and then the employment and TANF experiences of fully sanctioned recipients. For the first component of the analysis, we use data from all three states to examine the length and disposition of partial sanctions and the rate of return to TANF for fully sanctioned cases. For the second component, we exploit the availability of the rich survey data collected for the Work First New Jersey evaluation to examine the employment and welfare experiences of TANF recipients receiving full-family sanctions for the year after the sanction is imposed. (Similar data are not available in Illinois or South Carolina.)

How long do sanctions last?

Given the nature of sanctioning policy in Illinois and New Jersey, initial partial sanctions are typically short. If the recipient does not comply with work requirements, initial partial sanctions proceed to full-family sanctions within three months in both states. For this reason, more than 80 percent of initial partial sanctions in New Jersey and more than 90 percent of initial partial sanctions in Illinois end within three months (see Table III.5). In Illinois, initial partial sanctions end within one month for nearly half of the cases under such sanctions, suggesting that many individuals make efforts to cure an initial sanction quickly. Similarly, nearly 40 percent of initial partial sanctions end within one month in New Jersey.

Partial sanctions can end because the sanction is lifted and the full TANF grant is restored, because a full-family sanction is imposed, or because the family exits TANF for another reason. In New Jersey, the proportion of partial sanctions ending for each of these reasons are roughly evenly distributed, with a slightly lower proportion ending as a result of TANF exits for reasons other than a sanction (see Table III.5). In Illinois, over half of partial sanctions end when sanctions are lifted and the full grant is restored.

Table III.5.
Duration of Partial Sanctions and Reasons These Sanctions Ended Among TANF
Recipients in Illinois and New Jersey
(Percentages)
  Illinois New Jersey
Partial Sanction Ended Within
1 month 49 37
2 months 72 62
3 months 94 83
4 or more months 100 100
(Average length in months) (1.7) (2.3)
(Median length in months) (2) (2)
Partial Sanction Ended Because
Sanction lifted, full grant restored 55 36
Full family sanction imposed 22 38
Exited TANF for another reason 23 26
Sample Size 7,762 19,502
Source: Analysis of state administrative data by Mathematica Policy Research, Inc.
Note: Analysis is based on cases that received a partial sanction within 12 months of baseline. Baseline is defined as November 2001 in Illinois and, in New Jersey, the time the case first received cash assistance during or after July 2000.

Full-family sanctions end if the family returns to TANF.(5) Most fully sanctioned families in Illinois and New Jersey ultimately do return to TANF, many within only a few months (see Table III.6).(6) For example, respectively 43 and 47 percent of those who leave TANF in Illinois and New Jersey because of a full-family sanction return within three months, suggesting that many families decide to comply with work requirements shortly after the full-family sanction is imposed. Within the first year, the majority of sanctioned leavers  55 percent in Illinois and 63 percent in New Jersey  return to TANF. These TANF return rates are much higher than those for families that left TANF for reasons other than a sanction. Among other TANF leavers, only 26 and 39 percent returned to TANF within a year in Illinois and New Jersey, respectively.

Table III.6.
Sanctioned and Other Leavers Returning to TANF
(Percentages)
  Sanctioned Leavers Other Leavers All Leavers
Illinois
Returned to TANF Within
3 months 43 21 24
6 months 52 23 27
9 months 54 25 29
12 months 55 26 30
Sample Size 2,801 16,760 19,561
New Jersey
Returned to TANF Within
3 months 47 24 28
6 months 56 31 35
9 months 60 35 40
12 months 63 39 43
Sample Size 7,238 30,727 37,965
South Carolina
Returned to TANF Within
3 months 25 16 16
6 months 31 21 22
9 months 32 22 23
Sample Size 273 3,265 3,538
Source: Analysis of state administrative data by Mathematica Policy Research, Inc.
Note: Illinois sample was truncated in order to observe a full 12 months after TANF exit. New Jersey sample includes cases who exited TANF within 12 months of baseline. "Baseline" pertains to the time the sample member first received cash assistance during or after July 2000. South Carolina sample was truncated in order to observe a full 9 months after TANF exit.

The rate of TANF returns is lower in South Carolina for both sanctioned and other TANF leavers, possibly because the TANF grant is about half that of the other two states and may provide less incentive for return or because the lower eligibility threshold makes it less likely that families with any earned income will be eligible for benefits. Also, since fewer sanctions are imposed, those who receive them may be the least likely to come into compliance. However, the pattern still holds that those who leave as a consequence of a sanction are more likely to return to TANF than those who leave for other reasons. Within nine months of exiting TANF, 32 percent of sanctioned leavers return while 22 percent of other leavers return.

What are the employment and welfare experiences of sanctioned recipients over time?

From previous research, we know very little about what happens to families after they are fully sanctioned. Advocates and some policymakers have expressed concern that full family sanctions may contribute to material hardship. Others posit that fully sanctioned families must have other sources of support or they would have returned to the welfare rolls for assistance. In this section, we use administrative data on TANF receipt combined with survey data on employment status from the Work First New Jersey evaluation to examine the employment and TANF status of fully sanctioned TANF recipients in the first year after the sanction was imposed. We restrict the analysis to the 126 survey respondents who received a full-family sanction during the survey follow-up period and for whom 12 months of post-sanction survey follow-up data are available. We only use data from New Jersey because it is the only one of the three study states for which we have the necessary monthly employment data to conduct this analysis.

Most recipients who received a full-family sanction either returned to TANF or found employment within the first year after being sanctioned. Only 12 percent spent all their time off TANF and showed no record of employment. On average, in the year after receiving a full-family sanction, recipients spent four months on TANF and not employed, one month on TANF and employed, three months off TANF and employed and four months off TANF and not employed (see Figure III.1).

Figure III.1.
Time Spent in Various Employment and TANF Statuses During the First 12
Months After a Full-Family Sanction in New Jersey
Figure III.1. Time Spent in Various Employment and TANF Statuses During the First 12 Months After a Full-Family Sanction in New Jersey
Source: TANF status from state administrative data. Employment status from a follow-up survey conduted by Mathematica Policy Research, Inc.
Note:Figures represent the experiences of the 126 survey respondents who received a full-family sanction 12 or more months prior to their survey date.

The economic circumstances of TANF recipients in the year after receiving a full-family sanction varied substantially depending on their employment status at the time the sanction was imposed. One in four recipients in New Jersey was employed when the full-family sanction was imposed (not shown). Among this group, recipients typically spent most of their time employed and off TANF in the year after receiving the sanction and spent relatively little time either back on TANF or off TANF and not employed (see Figure III.1). The relative economic success of these sanctioned recipients suggests that many in the group may have been working or looking for work and preparing to leave TANF even in the absence of a sanction. Consistent with this interpretation, the follow-up survey showed that 60 percent of those employed when they received a full-family sanction reported "getting a job" as the reason for leaving welfare while only 22 percent reported a sanction as the reason (not shown).(7) Recipients who were not employed at the time they were sanctioned spent little time employed while off TANF during the year after being sanctioned and split their time fairly evenly between being on TANF and being off TANF and not employed (see Figure III.1). While on TANF, these recipients were employed for an average of one month.

Do Sanctions Promote Compliance with Work Requirements?

In this analysis, we did not have comparative data to measure the relative effectiveness of imposing sanctions or imposing different kinds of sanctions. However, the data from Illinois and New Jersey strongly suggest that the imposition of a gradual full-family sanction does promote compliance with work requirements. Over an 18-month period, Illinois and New Jersey imposed initial partial sanctions on 26 and 38 percent of TANF recipients, respectively. As Table III.7 shows, in both states the majority of recipients who experience an initial partial sanction eventually come into compliance with work requirements (67 percent in Illinois and 60 percent in New Jersey). Eighty percent of recipients who come into compliance in Illinois and 60 percent in New Jersey do so before a full-family sanction is ever imposed. These results suggest that the imposition of an initial partial sanction is sufficient to encourage a substantial number of families to participate in program activities. What we cannot tell from these data is whether families would have responded differently if the initial grant reduction was not followed by a full-family sanction. It is also important to note that about one-quarter of recipients who received an initial partial sanction left TANF for reasons other than the imposition of a full-family. Some of these families may have left because they had access to other resources, including unreported earned income or because they found employment on their own.

Table III.7
Summary of Compliance After the Imposition of an Initial Partial Sanction
in Illinois and New Jersey
  Illinois New Jersey
% of Families with an Initial Partial Sanction Imposed % of Families with an Initial Partial Sanction Imposed
Initial partial sanction imposed 100 100
Evidence of compliance1 after a sanction is imposed 67 60
Full tanf grant restored before full-family sanction imposed 55 36
Return to tanf after full-family sanction imposed 12 24
Some employment, no return to tanf n.a. 8
Record of compliance or employment after a sanction is imposed n.a. 68
Exited tanf for reasons other than the imposition of a full family sanction 23 26
1 We define compliance to include all cases where the full TANF grant was restored after an initial partial sanction was imposed and all cases that returned to TANF after a full family sanction was imposed. Using this definition, families who started participating in assigned activities and those who received an exemption or modification of their work participation requirements are considered to be compliant with work requirements.

Endnotes

(3) The predicted probabilities presented here and in Table III.2 are based on the results from estimating logistic regression models for sanction rates within 10 months in South Carolina and 12 months in Illinois and New Jersey. They represent the likelihood of the outcome in question for a client who has the particular characteristic in the table but who otherwise has the average characteristics of all clients. In addition to the client characteristics in the table, the models included and controlled for clients' gender and whether they had earnings either in the baseline month (New Jersey) or baseline quarter (Illinois and South Carolina).

(4) Similar data are not available in New Jersey. For a complete definition of employment assets and liabilities see Kirby, Fraker, Pavetti, and Kovac (June 2003), "Families on TANF in Illinois: Employment Assets and Liabilities." Washington, DC: Mathematica Policy Research, Inc.

(5) From a recipient's perspective, a full-family sanction could also end when she finds employment. However, this information is not necessarily known to the welfare office.

(6) In Illinois, cases officially remain open for three months while under a full grant sanction. For purposes of comparison to New Jersey and South Carolina, we considered these cases closed immediately upon being fully sanctioned. Similarly, cases that were in a "zero grant" status for reasons other than a sanction were considered closed.

(7) In contrast, among those who were not employed when they received a full-family sanction, 58 percent reported leaving TANF because of a sanction while 21 percent reported leaving for work.

Summary and Conclusions

This study was undertaken to increase our knowledge of how TANF sanctions are being used to encourage participation in work activities. In contrast to earlier studies that all have been conducted in a single state, we examined the use of TANF sanctions in two local sites in each of three states, affording us the opportunity to examine the use of TANF sanctions in several settings using comparable methodology. Another major contribution of this study is its use of several data sources in each of the study states in order to develop a more comprehensive picture of the use of work-oriented sanctions. While this study expands our knowledge of the use of TANF sanctions, it is important to note that the use of TANF sanctions in these three states does not necessarily represent the experiences of all states. Illinois, New Jersey and South Carolina were selected for this study because of the availability of data, collected for other purposes, that could be used to answer questions about the use of TANF sanctions In this chapter, we present our major findings for each research question and then suggest areas for additional research that would further our understanding of the use of TANF sanctions.

How Have TANF Sanctions Been Implemented?

The present study is the first post-welfare reform study to take a detailed look at how sanctions are being implemented in local welfare offices operating under a range of different welfare reform policies. Based on our findings, we draw several conclusions about the implementation of TANF sanctions. First, it is clear that the implementation of TANF sanctions requires substantial staff effort. Three of the six local sites we visited during the study had restructured their staff responsibilities so that at least one staff member focused exclusively on the implementation of TANF sanctions. Monitoring program participation, contacting clients to reengage them in program activities, documenting the reason for imposing a sanction, and making eligibility changes are all extremely labor-intensive tasks.

Second, TANF case managers have considerable discretion in deciding whether to impose a sanction, although some tend to exercise that discretion more than others. Many factors influence their decisions, including their overall workload, the message they have received from program administrators regarding the use of TANF sanctions, the amount of work involved in imposing a sanction, client circumstances, and the relationship they have developed with their clients. When workloads are high, case managers tend to base their sanctioning decisions primarily on participation reports. When workloads are lower, however, case managers take a more individualized approach to sanctioning and make an extra effort to reengage clients in program activities.

Third, TANF case managers sometimes use the flexibility accorded them to adjust work requirements for clients experiencing personal, family, or logistical challenges that make participation in work activities difficult. However, some believe that the strong emphasis on the achievement of high work participation rates discourages the development of individualized employment plans and results in a mismatch between the level and type of participation that is expected and what clients can realistically achieve. Finally, local offices use various review mechanisms to encourage the proper use of sanctions. In some cases, the reviews occur before a sanction is imposed and, in others, after a sanction is imposed.

How Often Are TANF Sanctions Imposed?

New Jersey and Illinois impose sanctions on a modest proportion of the caseload to promote participation in work activities. On the other hand, South Carolina rarely imposes them. Over a 10-month period, 5 percent of recipients are fully sanctioned in South Carolina compared with 10 and 12 percent in Illinois and New Jersey, respectively. When initial partial sanctions and a longer time period (18 months) are considered, 31 percent of recipients in Illinois and 39 percent of recipients in New Jersey see their grants reduced as a consequence of a sanction.

South Carolina's experience illustrates the extent to which the message regarding the use of sanctions, and possibly the severity of the initial penalty, can influence the use of sanctions to promote participation in work activities. South Carolina's low rate of sanctioning is most likely attributable to an explicit state administrative decision to encourage the use of sanctions only as a last resort. The decision represents a response to advocacy groups and others that raised concerns about the large number of case closures attributable to full family sanctions. Procedural requirements implemented at the local level that have had the effect of discouraging case managers from imposing sanctions include (1) extensive documentation of all actions taken to address participation problems, (2) a multilayered review process, and (3) a considerable lag from the time of the initial sanction recommendation to the final sanctioning decision.

While Illinois and New Jersey impose sanctions more often, their rate of sanctioning is lower than that found in the two earlier cohort studies. Fein and Lee estimate that 52 percent of Delaware TANF recipients received work-related sanctions (partial or full) during an 18-month period. In a similar study, Holcomb and Ratcliffe (2000) estimate that, during a 10-month period, 45 percent of Indiana TANF recipients were partially sanctioned for failure to comply with work requirements. The later timeframe of the present study may, in part, explain why we find a lower incidence of sanctions. As welfare reform has progressed and policies and practices have become more systematic, it is possible that many noncompliant recipients already have been sanctioned off or have otherwise exited from TANF. Additionally, if sanctions have become more credible over time, more people may be complying with program requirements before a sanction is imposed.

Who Is Sanctioned?

We find that the demographic characteristics associated with sanctioning are those that, in previous research, have been associated with longer welfare stays and lower rates of employment. These findings are consistent with other studies that compare the demographic characteristics of families that have ever been sanctioned with those that have never been sanctioned. All else equal, those who are younger, less educated, never married and African American more likely to be sanctioned than recipients without the same characteristics.

We also find that families that experience one or more personal, family, or logistical challenges are more likely to be sanctioned than families that do not experience any of these challenges. These findings confirm what many case managers report and many program administrators and advocates have long suspected. Challenges that significantly increase the likelihood of receiving sanctions include limited recent work experience, the existence of a physical or mental health problem, several arrests, and child care problems. In most cases, the presence of one of these challenges increases by one-half to two-thirds the probability of being sanctioned. The effect is much greater when several barriers are present; the probability of being sanctioned when four or more liabilities are present is twice as high as the probability of being sanctioned when any one barrier is present.

How Do Sanctioned Recipients Fare?

In both Illinois and New Jersey, the majority of families who are sanctioned are back on TANF within a relatively short period of time. Many families never progress to a full-family sanction and the majority of those that do, return to TANF within a year. The number of fully sanctioned families who return to the TANF rolls is lower in South Carolina, possibly because of the lower grant amount and lower eligibility threshold. In New Jersey, where we have the most complete data on TANF receipt and employment for the year after a full family sanction is imposed, we find that families who are fully sanctioned experience some disruption in their income, but few show no connection to either the labor market or the welfare system (see Figure IV.1); families with no record of receiving TANF or working represent only 1.7 percent of the cohort of recipients examined for this study.

Figure IV.1.
The Sanction and Post-Sanction Status of TANF Recipients in New Jersey

Figure IV.1: The Sanction and Post-Sanction Status of TANF Recipients in New Jersey.

Note: All Percentage are based on the current caseload.

Potential Next Steps

The present study did not set out to examine the extent to which sanctions promote compliance with work requirements. However, the results suggest that program participation is probably higher than it would be without the use of sanctions. Case managers often use the prospect of a sanction to promote compliance, and many sanctioned families eventually do come into compliance. A question of interest not addressed by the present study is whether a more stringent sanction promotes greater participation in work activities. None of the study states imposed only a partial sanction; therefore, we do not know how the use of sanctions and recipients' responses to them might differ in an environment where the potential for adverse consequences is not as great. In South Carolina, the stringency of the sanction almost certainly contributed to concerns about the number of families that were sanctioned. However, we don't know whether the stringency of the sanctions might also have contributed to greater compliance. We do know that the state set the bar higher than other states for imposing a sanction, but other factors may also be at play. With sanction policies similar in New Jersey and Illinois, our findings there do not allow us to draw any conclusions about how the design and structure of sanctions influence the rate of participation in work activities.

A study that looks at the relationship between state sanction policies and work participation and employment rates may offer some insight into whether a particular approach to sanctions, controlling for state characteristics and other welfare reform policies, contributes to higher work participation rates. Such a study could build on earlier studies that look at the relationship between various state TANF policies and caseload declines. A key methodological challenge of such a study would be developing a strategy to account for employment among recipients who leave the TANF rolls and for participation in employment activities for those who remain.

Finally, a study that looks at the relationship between sanctions and time limits could provide greater insight into how these policies work together or separately to encourage families to become self-sufficient. In states where sanctions are imposed routinely for non-compliance, fewer families than expected may reach time limits. This could occur if sanctions encourage recipients who might have been long-term recipients to engage in activities that help them to move towards self-sufficiency more rapidly or if they remove recipients from the TANF rolls who do not comply with program requirements and who may have stayed for an extended period in the absence of sanctions. In contrast, in states like South Carolina where sanctions are only applied as a last resort, more families may reach time limits and lose their TANF benefits as a result of them.

References

Fein, David J. and Wang S. Lee (May 1999). "The ABC Evaluation: Carrying and Using the Stick: Financial Sanctions in Delaware's A Better Chance Program." Prepared for Delaware Health and Social Services. Cambridge, MA: Abt Associates Inc.

Hamilton, Gayle, and Susan Scrivener (1999). "Promoting Participation: How to Increase Involvement in Welfare-to-Work Activities." New York, NY: Manpower Demonstration Research Corporation.

Holcomb, Pamela, and Caroline Ratcliffe (Spring/Summer 2000). "When Welfare Recipients Fail to Comply with Work Requirements: Indiana's Experience with Partial Benefit Sanctions." Journal of Applied Social Sciences, volume 24, no. 1.

Nixon, Lucia A., Jacqueline F. Kauff, and Jan L. Losby (August 1999). "Second Assignments to Iowa's Limited Benefit Plan." Washington, DC: Mathematica Policy Research, Inc.

Overby, Russell (1998). "Summary of Surveys of Welfare Recipients Employed or Sanctioned for Noncompliance." Memphis, TN: University of Memphis.

Pavetti, LaDonna, Michelle K. Derr, and Heather Hesketh (March 2003). "Review of Sanction Policies and Research Studies: Final Report." Washington, DC: Mathematica Policy Research, Inc.

United States Department of Health and Human Services, Office of Inspector General (October 1999). "Temporary Assistance for Needy Families: Educating Clients about Sanctions." Washington, DC: DHHS, OIG.

Appendix A: Methodology for Multivariate Analysis

To examine the affect of individual characteristics on being sanctioned in each of the three study states in a multivariate context, we use a series of logit models to estimate whether specific characteristics affects whether a TANF case head is sanctioned. The analysis is based on the single-parent TANF cases from each state who had no missing data on sanction status and the selected characteristics for study.(8) A list of variables included in the models and their means and standard deviations for each state are presented in Table A.1. The logit estimation results for the states are presented in Tables A.2, A.3, and A.4.

We estimate equation (1) to determine how each individual characteristic affects sanction status. This equation expresses sanction status as a function of select characteristics including gender, age, educational level, race/ethnicity, marital status, number of children on the TANF case, age of the youngest child on the TANF case, duration of the current TANF spell, and current earnings as represented in a series of 22 dummy variables.

(1) SancStati =  src=0 +  src= src=jLji +  src= src=k +  src=i
where:

  • SancStati = 1 if sanctioned; 0 otherwise
    Lji = 1 if specific characteristic j is present; 0 otherwise; j = 1,, 22
    Apa_letteru.gifi = random disturbance term
    Apa_lettera.gif0, Apa_lettera.gifj, Apa_theta.gifk = parameters to be estimated
    i = index for study population, i = 1,, 33,478(IL); 51,545(NJ); 10,852(SC)

The variable SancStat represents different sanction status' throughout the models. For Illinois--results presented in Table A.2--we examine being partially sanctioned within 12 months (Model 1) and being fully sanctioned within 12 months (Model 2). We do the same for New Jersey, with results for partial sanction within 12 months (Model 3) and full sanction within 12 months (Model 4) presented in Table A.3. Due to more recent study month selected for South Carolina, we have fewer follow-up months for study. For this reason, we examine we examine being fully sanctioned within 10 months in South Carolina. Results of this model (Model 5) are presented in Table A.4.

We then turn to the use of survey data from Illinois to estimate whether more specific personal liabilities or the number of such liabilities affects whether a TANF case head is sanctioned (partially or fully) within 12 months. The analysis sample includes the 375 survey respondents who had no missing data on sanction status, selected background characteristics, or any of the 15 personal liability measures. A list of variables included in these models and their means and standard deviations are presented in Table A.5. The logit estimation results are presented in Tables A.6 and A.7.

First, we estimate equation (2) to determine how each individual personal liability affects sanction status. This equation expresses sanction status as a function of 15 personal liabilities, and the same set of background characteristics as in equation (1).

(2) ASANC12i =  src=0 +  src= src=jLji +  src= src=kXki +  src=i
where:

  • ASANC12i = 1 if sanctioned (partially or fully) within 12 months; 0 otherwise
    Lji = 1 if specific liability j is present; 0 otherwise; j = 1,, 16
    Xki = set of background control variables, k = 1,, K
     src=i = random disturbance term
     src=0,  src=j,  src=k = parameters to be estimated
    i = index for survey respondents, i = 1,, 375

Next, we estimate equations (3) and (4) to determine whether the number of personal liabilities affects sanction status. These equations express sanction status as a function of the number of employment liabilities and a set of background characteristics. We specify the number of barriers as a series of seven dummy variables in equation (3) and as a series of three dummy variables in equation (4).

(3) ASANC12i =  src=0 +  src= src=jN1ji +  src= src=kXki +  src=i
where:

  • ASANC12i = 1 if sanctioned (partially or fully) within 12 months; 0 otherwise
    N1ji = 1 if the number of personal liabilities is j; 0 otherwise; j = 1,, 6
    N17i = 1 if the number of personal liabilities is 7 or more; 0 otherwise
    Xki = set of background control variables,(9) k = 1,, K
     src=i = random disturbance term
     src=0,  src=j,  src=k = parameters to be estimated
    i =index for survey respondents, i = 1,, 375

(4) ASANC12i =  src=0 +  src= src=jN2ji +  src= src=kXki +  src=i
where:

  • ASANC12i = 1 if sanctioned (partially or fully) within 12 months; 0 otherwise
    N21i = 1 if the number of personal liabilities is j; 0 otherwise; j = 1,, 6
    N22i = 1 if the number of personal liabilities is 7 or more; 0 otherwise
    Xki = set of background control variables, k = 1,, K
     src=i = random disturbance term
     src=0,  src=j,  src=k = parameters to be estimated
    i =index for survey respondents, i = 1,, 375

 

Table A.1.
Variable Descriptions
Variable Illinois New Jersey South Carolina
Mean Std. Dev. Mean Std. Dev. Mean Std. Dev.
Dependent Variable
Case head has been partially sanctioned within 12 months .23 .42 .32 .47    
Case head has been fully sanctioned within 12 months .11 .31 .14 .34    
Case head has been fully sanctioned within 10 months         .05 .21
Independent Variables
Female .98 .13 .96 .20 .98 .16
Age 20-24 .27 .44 .24 .43 .32 .47
Age 25-29 .21 .41 .19 .39 .20 .40
Age 30-39 .30 .46 .31 .46 .25 .44
Age 40 and over .13 .34 .17 .37 .12 .33
High school diploma or GED .40 .49 .41 .49 .50 .50
More than high school .11 .31 .10 .30 .14 .34
White, Non-Hispanic .12 .33 .14 .35 .26 .44
Hispanic .06 .23 .27 .44 .01 .08
Other, Non-Hispanic .01 .08 .02 .13 .00 .06
Separated, divorced, widowed .13 .33 .19 .39 .26 .44
Married .04 .19 .03 .18 .03 .17
Two children on TANF case .28 .45 .25 .43 .34 .47
Three children on TANF case .20 .40 .11 .31 .18 .38
Four or more children on TANF case .21 .41 .06 .23 .10 .30
Youngest child is age 1-2 .25 .43 .18 .38 .37 .48
Youngest child is age 3-5 .17 .38 .19 .39 .22 .41
Youngest child is 6 or older .29 .45 .45 .50 .31 .46
Current TANF spell of 6-11 months .18 .38 .10 .30 .28 .45
Current TANF spell of 12-24 months .21 .41 .12 .32 .15 .35
Current TANF spell of 25 months or longer .39 .49 .27 .45 .06 .23
Earnings during quarter .41 .49 .09 .28 .41 .49
Source: State administrative data from Illinois (N=33,478), New Jersey (N=51,545), and South Carolina (N=10,852).

 

Table A.2.
Effects of Specific Characteristics on the Probability that a TANF Case Head
Is Sanctioned Within 12 Months in Illinois
  Model 1 (Partial Sanction) Model 2 (Full Sanction)
Coefficient Std Error Z P>|z| Coefficient Std Error z P>|z|
Female -0.28 0.11 -2.61 0.01 -0.12 0.15 -0.80 0.43
Age 20-24 -0.19 0.05 -3.78 0.00 -0.15 0.07 -2.14 0.03
Age 25-29 -0.27 0.06 -4.61 0.00 -0.25 0.08 -3.01 0.00
Age 30-39 -0.29 0.06 -4.73 0.00 -0.28 0.08 -3.30 0.00
Age 40 and over -0.37 0.07 -5.33 0.00 -0.17 0.09 -1.84 0.07
High school diploma or GED         -0.44 0.04 -10.86 0.00
More than high school         -0.51 0.07 -7.25 0.00
White, Non-Hispanic -0.22 0.05 -4.90 0.00 -0.16 0.06 -2.54 0.01
Hispanic -0.42 0.06 -6.71 0.00 -0.42 0.09 -4.70 0.00
Other, Non-Hispanic -0.85 0.22 -3.93 0.00 -0.78 0.30 -2.59 0.01
Separated, divorced, widowed -0.20 0.05 -4.17 0.00 -0.28 0.07 -4.15 0.00
Married -0.23 0.08 -2.89 0.00 -0.15 0.11 -1.43 0.15
Two children on TANF case -0.02 0.04 -0.47 0.64 0.08 0.05 1.57 0.12
Three children on TANF case -0.03 0.04 -0.81 0.42 0.09 0.06 1.60 0.11
Four or more children on TANF case -0.06 0.04 -1.31 0.19 0.02 0.06 0.39 0.70
Youngest child is age 1-2 0.09 0.04 2.50 0.01 0.39 0.05 7.60 0.00
Youngest child is age 3-5 -0.04 0.04 -1.02 0.31 0.27 0.06 4.49 0.00
Youngest child is 6 or older -0.14 0.05 -3.01 0.00 0.22 0.06 3.43 0.00
Current TANF spell of 6-11 months 0.21 0.04 4.88 0.00 0.39 0.06 6.17 0.00
Current TANF spell of 12-24 months 0.17 0.04 4.10 0.00 0.53 0.06 8.76 0.00
Current TANF spell of 25 months or longer -0.00 0.04 -0.12 0.91 0.48 0.06 8.25 0.00
Earnings during quarter -0.75 0.03 -25.59 0.00 -0.59 0.04 -14.86 0.00
Constant -0.20 0.12 -1.65 0.10 -1.97 0.17 -11.70 0.00
Chi-Square 1354.25       706.63      
Prob > Chi-Square 0.0000       0.0000      
Number of Observations 32,703       32,703      
Source: Results of multinomial logit models predicting the probability of being sanctioned (partially or fully) within 12 months using administrative data on single-parent TANF cases in Illinois in November 2001.

 

Table A.3.
Effects of Specific Characteristics on the Probability that a TANF Case Head
is Sanctioned Within 12 Months in New Jersey
  Model 3 (Partial Sanction) Model 4 (Full Sanction)
Coefficient Std Error Z P>|z| Coefficient Std Error z P>|z|
Female -0.06 0.05 1.15 0.28 -0.10 0.07 1.89 0.17
Age 20-24 -0.13 0.04 12.22 0.00 -0.18 0.05 13.99 0.00
Age 25-29 -0.24 0.04 31.81 0.00 -0.26 0.06 22.36 0.00
Age 30-39 -0.33 0.04 54.73 0.00 -0.37 0.06 42.41 0.00
Age 40 and over -0.63 0.05 163.06 0.00 -0.63 0.07 91.65 0.00
High school diploma or GED -0.22 0.02 103.15 0.00 -0.22 0.03 62.50 0.00
More than high school -0.38 0.04 110.19 0.00 -0.44 0.05 75.22 0.00
Missing education information -0.35 0.06 32.13 0.00 -0.38 0.09 18.50 0.00
White, Non-Hispanic -0.42 0.03 178.64 0.00 -0.51 0.05 127.39 0.00
Hispanic -0.49 0.02 414.92 0.00 -0.41 0.03 160.79 0.00
Other, Non-Hispanic -0.78 0.09 67.93 0.00 -0.93 0.15 39.92 0.00
Separated, divorced, widowed -0.24 0.03 70.32 0.00 -0.35 0.04 65.77 0.00
Married -0.31 0.06 25.67 0.00 -0.30 0.09 11.53 0.00
No children on TANF case -0.24 0.23 1.07 0.30 -0.21 0.32 0.44 0.51
Two children on TANF case -0.02 0.02 0.62 0.43 -0.09 0.03 7.49 0.01
Three children on TANF case -0.02 0.03 0.35 0.55 -0.14 0.05 7.97 0.01
Four or more children on TANF case -0.02 0.05 0.28 0.60 -0.11 0.06 2.96 0.09
Youngest child is age 1-2 -0.02 0.03 0.33 0.56 0.04 0.05 0.78 0.38
Youngest child is age 3-5 0.08 0.04 5.04 0.02 0.16 0.05 11.66 0.00
Youngest child is 6 or older 0.12 0.04 11.11 0.00 0.11 0.05 5.06 0.03
Youngest child age is missing -0.39 0.24 2.75 0.10 0.05 0.33 0.02 0.89
Current TANF spell of 6-11 months 0.07 0.03 4.22 0.04 0.22 0.04 27.82 0.00
Current TANF spell of 12-24 months -0.01 0.03 0.14 0.71 0.18 0.04 18.23 0.00
Current TANF spell of 25 months or longer 0.03 0.03 1.19 0.27 0.10 0.03 7.77 0.01
Earnings during month -1.10 0.04 636.34 0.00 -0.74 0.06 156.47 0.00
Constant -0.02 0.06 0.11 0.74 -1.13 0.09 175.33 0.00
Chi-Square 2546.57       1266.37      
Prob > Chi-Square 0.0000       0.0000      
Number of Observations 51,539       51,539      
Source: Results of multinomial logit models predicting the probability of being sanctioned (partially or fully) within 12 months using administrative data on single-parent TANF cases in New Jersey from July 2000 to June 2001.

 

Table A.4.
Effects of Specific Characteristics on the Probability That a TANF Case Head is
Sanctioned Within 10 Months in South Carolina
  Model 5 (Full Sanction)
Coefficient Std Error Z P>|z|
Female 0.02 0.37 0.05 0.96
Age 20-24 -0.21 0.13 -1.59 0.11
Age 25-29 -0.55 0.16 -3.44 0.00
Age 30-39 -0.84 0.17 -4.90 0.00
Age 40 and over -1.39 0.25 -5.52 0.00
High school diploma or GED -0.61 0.10 -6.02 0.00
More than high school -0.70 0.17 -4.07 0.00
White, Non-Hispanic -0.18 0.12 -1.48 0.14
Hispanic -1.14 1.01 -1.12 0.26
Other, Non-Hispanic -0.67 1.02 -0.65 0.51
Separated, divorced, widowed 0.01 0.15 0.05 0.96
Married -0.27 0.40 -0.68 0.50
Two children on TANF case 0.05 0.11 0.40 0.69
Three children on TANF case 0.14 0.13 1.05 0.30
Four or more children on TANF case 0.05 0.17 0.32 0.75
Youngest child is age 1-2 -0.05 0.16 -0.31 0.76
Youngest child is age 3-5 -0.14 0.18 -0.81 0.42
Youngest child is 6 or older 0.01 0.17 0.01 0.99
Current TANF spell of 6-11 months 0.16 0.11 1.44 0.15
Current TANF spell of 12-24 months 0.06 0.14 0.42 0.67
Current TANF spell of 25 months or longer -0.18 0.22 -0.82 0.41
Earnings during quarter 0.04 0.10 0.44 0.66
Constant -2.25 0.42 -5.35 0.00
Chi-Square 141.69      
Prob > Chi-Square 0.0000      
Number of Observations 10,789      
Source: Results of multinomial logit models predicting the probability of being fully sanctioned within 10 months using administrative data on single-parent TANF cases in South Carolina in June 2002.

 

Table A.5.
Variable Descriptions for Illinois Survey-Based Models
Variable Mean Standard Deviation
Dependent Variable
Case head has been sanctioned (partially or fully) within 12 months .27 .45
Independent Variables
Human Capital Liabilities
No high school diploma or GED .44 .50
Fewer than four quarters of recent work experience .59 .49
Performed fewer than four common job tasks .28 .45
Personal Challenges
Physical health problem .21 .41
Mental health problem .25 .43
Chemical dependence .03 .17
Severe physical domestic violence in past year .13 .33
Signs of learning disability .12 .33
Multiple arrests .16 .37
Difficulty with English language .02 .38
Logistical and Situational Challenges
Child/other family member/friend w/health problem or special need .35 .48
Pregnant .08 .80
Child under age one in household .28 .45
Transportation barrier .21 .54
Child care .31 .46
Unstable housing .23 .42
Counts of Liabilities
One .12 .33
Two .16 .37
Three .21 .41
Four .17 .37
Five .13 .33
Six .07 .26
Seven or more .10 .30
Source: 2001-02 survey of Illinois TANF cases, N=416.

 

Table A.6.
Effects of Specific Liabilities on the Probability That a TANF Case Head is Sanctioned
(Full or Partial) Within 12 Months in Illinois
  Model 6
  Coefficient Std Error T P>|t|

Human Capital Liabilities

       
No high school diploma or GED 0.55 0.28 1.94 0.05
Limited work experience 0.45 0.28 1.58 0.12
Performed fewer than four common job tasks -0.11 0.31 -0.36 0.72

Personal Challenges

       
Physical health problem 0.66 0.32 2.05 0.04
Mental health problem 0.57 0.33 1.74 0.08
Chemical dependence 0.51 0.74 0.70 0.49
Severe physical domestic violence in past year -0.34 0.43 -0.79 0.43
Signs of a learning disability -0.58 0.48 -1.21 0.23
Multiple arrests 0.63 0.35 1.77 0.08
Difficulty with English -1.38 1.02 -1.36 0.18

Logistical and Situational Challenges

       
Child/family member/friend w/health problem or special need -0.37 0.30 -1.25 0.21
Pregnant or child under age one in household 0.44 0.39 1.12 0.26
Transportation 0.26 0.34 0.75 0.45
Child care 0.52 0.29 1.75 0.08
Unstable housing -0.08 0.33 -0.25 0.80

Background Characteristics

       
Female -0.49 1.04 -0.47 0.64
Age 20-24 -0.18 0.49 -0.36 0.72
Age 25-29 -0.14 0.59 -0.24 0.81
Age 30-39 0.35 0.58 0.60 0.55
Age 40 and over -0.42 0.70 -0.60 0.55
White, Non-Hispanic 0.00 0.48 0.01 0.99
Separated, divorced, widowed -0.53 0.49 -1.08 0.28
Married 0.91 0.63 1.43 0.16
Two children on TANF case -0.12 0.38 -0.32 0.75
Three children on TANF case 0.14 0.40 0.35 0.73
Four or more children on TANF case 0.17 0.44 0.38 0.70
Youngest child is age 1-2 0.56 0.42 1.33 0.18
Youngest child is age 3-5 0.74 0.53 1.40 0.16
Youngest child is 6 or older 0.20 0.52 0.38 0.71
Current TANF spell of 6-11 months 0.49 0.44 1.11 0.27
Current TANF spell of 12-24 months 0.40 0.42 0.95 0.34
Current TANF spell of 25 months or longer 0.52 0.41 1.28 0.20
Constant -2.23 1.25 -1.78 0.08
F-Statistic 1.25      
Prob > F 0.1681      
Number of Observations 371      
Source:  Results of multinomial logit models predicting the probability of being sanctioned (partially or fully) within 12 months using data from 2001-02 survey of Illinois TANF cases.
Table A.7.
Effects of Multiple Liabilities on the Probability that a TANF Case Head is Sanctioned
(Full or Partial) Within 12 Months in Illinois
  Model 7
  Coefficient Std Error T P>|t|

Number of Liabilities

       
One 1.74 1.14 1.52 0.13
Two 1.42 1.12 1.26 0.21
Three 1.72 1.12 1.54 0.12
Four 2.01 1.13 1.79 0.08
Five 3.04 1.14 2.68 0.01
Six 2.78 1.20 2.32 0.02
Seven or more 2.06 1.18 1.75 0.08

Background Characteristics

       
Female -0.88 1.09 -0.81 0.42
Age 20-24 -0.02 0.44 -0.05 0.96
Age 25-29 -0.10 0.53 -0.20 0.84
Age 30-39 0.32 0.52 0.62 0.54
Age 40 and over -0.61 0.65 -0.93 0.35
White, Non-Hispanic 0.02 0.49 0.04 0.97
Separated, divorced, widowed -0.63 0.51 -1.22 0.22
Married 0.73 0.64 1.15 0.25
Two children on TANF case -0.17 0.35 -0.49 0.62
Three children on TANF case 0.00 0.40 0.01 0.99
Four or more children on TANF case 0.06 0.44 0.13 0.90
Youngest child is age 1-2 0.43 0.32 1.32 0.19
Youngest child is age 3-5 0.57 0.43 1.32 0.19
Youngest child is 6 or older 0.25 0.42 0.59 0.55
Current TANF spell of 6-11 months 0.46 0.41 1.11 0.27
Current TANF spell of 12-24 months 0.47 0.39 1.20 0.23
Current TANF spell of 25 months or longer 0.56 0.39 1.46 0.15
Constant -2.69 1.59 -1.70 0.09
F-Statistic 1.41      
Prob > F 0.0995      
Number of Observations 375      
Source: Results of multinomial logit models predicting the probability of being sanctioned (partially or fully) within 12 months using data from 2001-02 survey of Illinois TANF cases.
Table A.8.
Effects of Multiple Liabilities (Grouped Model) on the Probability that a TANF Case Head is Sanctioned
(Full or Partial) Within 12 Months in Illinois
  Model 8
  Coefficient Std Error T P>|t|

Number of Liabilities

       
One 1.75 1.15 1.52 0.13
Two to three 1.55 1.11 1.40 0.16
Four or more 2.40 1.12 2.14 0.03

Background Characteristics

       
Female -1.05 1.10 -0.96 0.34
Age 20-24 -0.02 0.45 -0.05 0.96
Age 25-29 -0.03 0.53 -0.05 0.96
Age 30-39 0.29 0.53 0.54 0.59
Age 40 and over -0.56 0.65 -0.86 0.39
White, Non-Hispanic -0.02 0.44 -0.04 0.96
Separated, divorced, widowed -0.70 0.48 -1.47 0.14
Married 0.93 0.61 1.54 0.12
Two children on TANF case -0.19 0.34 -0.56 0.58
Three children on TANF case -0.03 0.38 -0.07 0.94
Four or more children on TANF case -0.01 0.42 -0.01 0.99
Youngest child is age 1-2 0.31 0.32 0.96 0.34
Youngest child is age 3-5 0.38 0.41 0.94 0.35
Youngest child is 6 or older 0.12 0.41 0.30 0.77
Current TANF spell of 6-11 months 0.47 0.40 1.18 0.24
Current TANF spell of 12-24 months 0.47 0.38 1.21 0.23
Current TANF spell of 25 months or longer 0.56 0.38 1.46 0.15
Constant -2.37 1.59 -1.49 0.14
F-Statistic 1.37      
Prob > F 0.1339      
Number of Observations 375      
Source:   Results of multinomial logit models predicting the probability of being sanctioned (partially or fully) within 12 months using data from 2001-02 survey of Illinois TANF cases.

Endnote

(8) In New Jersey, we included cases with missing data on education status and the age of the youngest child on the TANF case with appropriate dummy variables indicating missing data in these areas.

(9) The background control variables are: age, race, marital status, number of children, presence of young children, percent of time on welfare in past 25 months, county unemployment rate, neighborhood racial concentration (i.e., 80 percent or more African-American).

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