Families on TANF in Illinois: Employment Assets and Liabilities

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

Project Officer:
John Tambornino

By:
Gretchen Kirby, Thomas Fraker, В LaDonna Pavetti, and Martha Kovac
Mathematica Policy Research, Inc.

Project Director:
Thomas Fraker

Survey Director:
Martha Kovac

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Acknowledgments

Many individuals and organizations contributed in significant ways to the study of families on TANF in Illinois. This study could not have been conducted without financial support. The Annie E. Casey Foundation and the David and Lucile Packard Foundation provided funding for the design of the study and the collection of administrative and survey data. The Office of the Assistant Secretary for Planning and Evaluation (ASPE) in the U.S. Department of Health and Human Services provided funding for the analysis of the data and the preparation of this report. We thank these three organizations for their generous financial support.

At the Illinois Department of Human Services, David Gruenenfelder, Alan Whitaker, and Terry Husky supported the study by providing us with timely data on the state TANF caseload from DHS administrative records. They also cheerfully and quickly responded to our many questions regarding those data. David Gruenenfelder and John Knight reviewed a draft of this report and provided helpful comments and additional information on Illinois' TANF policies. At the Illinois Criminal Justice Information Authority, Gerald Ramker assisted us in obtaining access to criminal records data for the members of our survey sample.

Several individuals at ASPE provided valuable contributions to this study. John Tambornino was the project officer and in that role supported our acquisition of criminal records data, contributed to the development of the study's analytic objectives, and carefully reviewed and commented on drafts of this report. Under a different project, Susan Hauan and Julia Isaacs provided critical coordination of and substantive input into the development of a prototype for the survey instrument that was used in this study. Don Oellerich contributed valuable suggestions for the design of the analysis and he and Canta Pian commented on drafts of the report.

Many staff at Mathematica Policy Research contributed to this project through the survey design, data collection, data analysis, and report production activities. In the Survey Division, Jason Markesich managed the day-to-day survey data collection operations. Cindy Steenstra, Barbara Benedict, Susan Golden, Terry Silverii and Marie Hannye-Scurato played important roles in supervising telephone center staff and performing other survey data collection tasks. A small corps of experienced MPR interviewers administered the survey. In addition, John Hall developed the survey sampling plan and the survey weights for the data analysis. Eric French oversaw programming activities necessary to conduct the survey.

In the Research Division, Jocelyn Lewis and Michelle McInnis collected the criminal records data on site from the Illinois Criminal Justice Authority. Jocelyn Lewis and Heather Hesketh provided research assistance throughout the data analysis and production of this report. Robin Dion reviewed a draft of this report and provided thoughtful comments. Donna Dorsey provided secretarial assistance in producing this report and Carol Soble and Daryl Hall edited the manuscript.

Last but not least, we thank the TANF clients in Illinois who took the time to respond to this study's survey. Over 78 percent of the sampled clients completed an interview, during which they shared information about their personal characteristics and circumstances and their efforts to obtain employment and achieve self-sufficiency.

How to Obtain a Printed Copy

To obtain a printed copy of this report, send the title and your mailing information to:

Human Services Policy, Room 404E
Assistant Secretary for Planning and Evaluation
U.S. Department of Health and Human Services
200 Independence Av, SW
Washington, DC 20201

Fax:  (202) 690-6562

Introduction

The Personal Responsibility and Work Opportunity Reconciliation Act of 1996 (PRWORA) dramatically altered the safety net for low-income families with children. Before PRWORA, families were entitled to cash assistance through the Aid to Families with Dependent Children (AFDC) program as long as their income and assets were below certain levels and they met categorical requirements related to, for example, household composition. Since the enactment of PRWORA, eligibility for cash assistance under TANF remains an entitlement in most states, in the sense that families are eligible to receive assistance as long as they meet the program requirements. However, the conditions under which assistance is provided to families differ markedly from those under AFDC. PRWORA introduced a 60-month lifetime limit on TANF assistance and established stronger work requirements. By 2000, the heads of single-parent TANF cases were required to work at least 30 hours per week.

Partly as a result of these changes in program requirements and partly due to a strong economy, welfare caseloads fell by about half from 1994 through 2000. This dramatic drop spawned numerous studies of the employment experiences and well-being of the families that left welfare in the latter half of the 1990s. As a consequence of those studies, we now understand the characteristics of the families that left public assistance and their circumstances following exit. Until recently, however, families on TANF have received far less attention from policy researchers.

The limited information on TANF families suggests that they are likely to be among the most vulnerable and least job ready of all low-income families with children. While it is not clear that these families are, in fact, harder to employ than those receiving AFDC prior to TANF, evidence suggests that liabilities such as low education, lack of work experience, physical and mental health problems, and domestic violence are prevalent among current TANF recipients and more prevalent than among former welfare recipients (Danziger 2001; Loprest and Zedlewski 1999). These liabilities may impede the progress of some recipients in the labor market or prohibit others from entering the labor market at all. The findings presented in this report, based on a study conducted by Mathematica Policy Research (MPR) of single-parent families on TANF in Illinois, will increase our knowledge of the current welfare caseload.

Illinois is a particularly interesting state in which to examine the current welfare caseload. It is in the top third of states in terms of the average number of families on TANF, and the caseload is mostly urban, with just over 80 percent of recipients residing in the Chicago area (Cook County). In addition, the state has a unique set of policies that encourage work through incentives as well as penalties. The incentives include a 67 percent earnings disregard and stopping the TANF five-year benefits clock for months in which single-parent recipients work 30 or more hours per week. The penalties can amount to full grant sanctions for continued noncompliance with work requirements.

This study builds on the data from a number of recent surveys of TANF recipients but comes closest to developing a full picture of the current TANF caseload in a state. This picture is based on a survey of single-parent families in Illinois that were on TANF in November 2001. We deliberately incorporated a number of measures and scales in the survey that were used in recent studies conducted in Nebraska and in Michigan (the Womens Employment Study) for purposes of comparison. Although we refer to these studies throughout the report, they had longer periods between sampling and the start of data collection, making their findings somewhat less representative of current TANF recipients than the findings from this study.⁽¹⁾

Our survey is also based on the instrument used in studies of the TANF caseload now underway in California, Colorado, Maryland, Missouri, South Carolina, and the District of Columbia. Consequently, the findings presented in this report will be comparable to the forthcoming findings from those studies. The combined findings from these seven studies will provide policymakers and program administrators with much richer information for making decisions about the best ways to meet the needs of current TANF recipients.

This study was made possible through a collaboration of sponsors. The David and Lucile Packard Foundation and the Annie E. Casey Foundation sponsored the development of the survey instrument and survey data collection in Illinois. The Office of the Assistant Secretary for Planning and Evaluation of the U.S. Department of Health and Human Services sponsored the data analysis and production of this report.

 

Research Objectives

This study was designed to describe the characteristics, circumstances, and job readiness of single-parent TANF families in Illinois and, more specifically, the heads of these families (i.e., the adult grantees). Three main questions and a number of related subquestions guided the research and structure of this report.

1. What are the welfare and employment experiences of TANF recipients? What percentage of current single-parent TANF cases are long-term welfare recipients? What is their status with respect to time limits and sanctions? What is the employment history and current employment status of heads of TANF cases? What are the characteristics of their current or most recent jobs? What are their earnings and total household income?
2. What assets and liabilities do TANF recipients bring to the labor market? What human capital for employment do the heads of TANF cases possess? How prevalent among them is poor physical or mental health? What other personal and family challenges do they face that may be liabilities for employment? What logistical or situational challenges to employment do the heads of TANF cases face?
3. What are the effects on employment of the number and type of liabilities? How common among the heads of single-parent TANF cases are multiple liabilities for employment? How do those liabilities, separately and in combination, affect the employment of such individuals?

Methodology and Data Sources

To address the studys three main research questions, MPR selected as its study population all of the 33,495 single-parent cases in Illinois that were authorized to receive a TANF grant in November 2001. A single-parent case generally includes an unmarried adult with children under the age of 18. We defined a single-parent case such that it excludes child-only casesi.e., cases in which there is no adult grantee. The grantee is the person in whose name the TANF benefit is issued. The study population also included a small proportion (nine percent) of zero benefit cases, which were officially eligible for TANF in November 2001 but did not receive a cash grant in that month. However, they continued to receive Medicaid and food stamps, if eligible and enrolled. Sanctions, recoupment, and work-first requirements accounted for most of the zero benefit cases.

We defined the study population as all single-parent families in Illinois that were authorized to receive a TANF grant in November 2001 because we wanted to answer the overarching question, Who are the families that are on TANF in Illinois? A states TANF caseload at a point in time is a function of the process whereby families enter the TANF program, receive assistance for varying lengths of time, and then exit the program. This process is such that there are relatively more long-term and fewer short-term recipients at a point in time than there are among all families that entered the program in the period leading up to that point. Consequently, the findings presented in this report, while applicable to Illinois November 2001 TANF caseload, are generally not applicable to all families that entered TANF up to November 2001.

The data for this study came from five sources: (1) a telephone survey of TANF cases in which we sought to interview the case head, (2) administrative records for individual TANF cases from the Illinois Department of Human Services, (3) wage records for TANF case heads from the Illinois Department of Employment Security, (4) criminal history records for TANF case heads from the Illinois Criminal Justice Information Authority, and (5) aggregate demographic and employment data on Illinois counties and five-digit zip codes from the U.S. Bureau of the Census and the U.S. Bureau of Labor Statistics. The administrative records from the Illinois Department of Human Services and the Illinois Department of Employment Security provided data on the studys full population of 33,495 single-parent TANF cases. The survey and the criminal history records provided data on a sample of about one percent of that population.

The survey was based on a sample of 532 single-parent TANF cases randomly drawn from the studys full population within two strataresidence in Cook County or in the rest of the state (referred to hereafter as downstate).⁽²⁾ The sample was drawn in mid-November 2001 and interviewing began later that month and continued for 16 weeks, ending in early March 2002. We completed interviews with 416 of the sample members for a survey response rate of 78 percent. We took special care to complete the final interview as soon as possible after identifying the study population and selecting the survey sample in order to maximize the proportion of interviews completed with cases still receiving TANF. Eighty-six percent of the survey respondents reported that they had received a TANF grant in the month before their interview. The total percentage of respondents still on TANF at the time of the survey is likely to have been slightly higher given the possibility of zero-grant cases (the extent of which is unknown at the time of the survey). The survey findings presented in this report are based on data from the respondents that have been weighted to be representative of the entire population of single-parent TANF cases in Illinois.

Limitations of the Study

The findings presented in this report have several potential limitations common to studies based on data from sample surveys and state administrative records. The limitations related to the survey findings include bias resulting from nonresponse by some sample members, recall errors in responses to survey questions, and misreporting in responses to sensitive questions. Despite our strong efforts to minimize the incidence of these problems, 22 percent of the sample members did not complete an interview, either because they were not reached at all or because they ended the interview before completion. In addition, some sample members who did complete an interview undoubtedly provided erroneous answers to certain questions. We adjusted for survey nonresponse by weighting the respondents up to the full study population on the basis of characteristics obtained from state TANF administrative records. However, the weights are based on just three characteristics (county of residence, age, and receipt of a positive TANF grant), and the weighted survey respondents may differ from the full population in other characteristics.

The limitations related to the findings based on data from TANF records, Unemployment Insurance earnings records, and criminal records arise from the absence of data on out-of-state activities and incomplete coverage of in-state activities (e.g., some jobs are not covered by the Unemployment Insurance system, and information on some arrests and convictions is not forwarded to database administrators). Limitations in administrative data may also arise when clients misreport information to authorities (e.g., misreporting of educational attainment or marital status by case heads to TANF caseworkers).

Nevertheless, the incidence and magnitude of these limitations are likely to be no greater than in other similar studies of welfare populations. Furthermore, our survey-based findings are likely to be more reliable than the norm because of a short survey field period (which reduced the risk of recall error), a high response rate, and the use of survey weights to adjust for the nonresponse that did occur.

Characteristics of TANF Recipients

The demographic characteristics of the heads of single-parent TANF cases and their households can provide context for the findings on the main research questions. Based on administrative data for the studys full population, Table I.1 shows that four in every five single-parent TANF cases in Illinois reside in Cook County. Nearly all of the case heads are women, a large majority of whom are African American. An equally large majority has never married. About one-third of the heads of single-parent TANF cases are younger than 25 years of age.

The households of TANF case heads may include people in addition to those officially on the case. Based on data from the studys survey, Table I.2 presents characteristics of these households. Households occupied by only the TANF case head and children account for a slight majority of all households. However, two in every five households include other adults who may be the heads relative, friend, or partner. Although the study population is single-parent TANF cases, a small share of the households does not include children (one percent) or includes the heads spouse (four percent), reflecting changes that could have occurred in the brief interval between sample selection and the completion of interviews. On average, the households of single-parent TANF cases are occupied by 4.5 people, nearly three of whom are children under the age of 18. The average age of the youngest child in these households is slightly less than four years.

The Structure of This Report

Chapter II of this report, which focuses on the first research question, describes the welfare and employment experiences of TANF recipients. Chapter III addresses the second question by describing the assets that TANF recipients bring to employment and the prevalence of their various liabilities for employment. Chapter IV presents findings from a multivariate analysis to answer the third question on the effects of the number and type of liabilities on employment. The final chapter summarizes our principal findings and discusses their relevance to policymakers and program administrators.

Endnotes

⁽¹⁾ As in this survey, the Nebraska and Michigan surveys use a point-in-time sampling approach. In Nebraska, the sample of TANF recipients was selected in January 2000, and individuals were interviewed 10 to 12 months later. In Michigan, the sample was selected in February 1997, and interviews were conducted 7 to 10 months later. At the time of these surveys, 52 percent of individuals in Nebraska and 72 percent in Michigan were receiving TANF.

⁽²⁾Appendix A provides details on the study population, the survey sample, the fielding of the survey, the development of survey weights, and an assessment of the representativeness of the weighted survey respondents.

Welfare and Employment Experiences

The goal of state TANF programs is to provide temporary assistance to needy families while directing adults in those families to jobs so that their families can become self-sufficient. To promote this transition from welfare to work, the federal government has established minimum work participation rates for the TANF caseload in each state and a 60-month limit on assistance for families. Using the flexibility provided by PRWORA, states have taken a variety of approaches to encouraging TANF recipients to work. Illinois' approach includes both incentives and penalties. For instance, the state (1) stops the 60-month TANF "clock" for working families on assistance, (2) disregards 67 percent of earnings for an indefinite period, and (3) imposes a gradual sanction on families that do not comply with work requirements. As a result of these policies, the Illinois TANF caseload includes both working and nonworking families.

In this chapter, we describe the welfare and employment experiences of single-parent TANF recipients in Illinois. We examine both the amount of time they have spent on welfare and their current work experience, including the number of hours they work, the characteristics of their jobs, and the amount of money they earn. We also discuss their total household income and conclude with a summary of their circumstances.

Welfare Experiences

To gain a general sense of the welfare experiences of single-parent cases that were on TANF in November 2001, this section describes the duration of assistance, sanction status, and time-limit status of the subject cases. As appropriate, it describes the characteristics and experiences of those cases, their adult heads, or their households.

• Nearly two-fifths of current TANF cases have received cash assistance continuously for more than two years.

Thirty-nine percent of single-parent TANF cases in Illinois have been on assistance continuously for more than two years, having received benefits in each of the past 25 months (Figure II. 1). This share is somewhat lower than the 47 percent reported from a study of the TANF population of the nation as a whole based on data from the 1999 National Survey of American Families (Zedlewski and Alderson 2001). Long-term recipients always comprise a substantial share of the caseload at any point in time, even while, over time, the majority of TANF cases may be of short duration.

A substantial portion (42 percent) of single-parent cases in Illinois have current TANF spells of a year or less (Figure II.2). Current spells on TANF are extremely short--six months or less--for 26 percent of recipients. Another 16 percent have current spells of 7 to 12 months. Some of the cases with current spells under one year are short-term recipients who need TANF to see them through a brief period, while some are "cyclers" who move on and off TANF over time. For example, we see in Figure II.1 that 30 percent of cases have received TANF for less than half of the past 25 months (or about 12 months), a lower share than those whose current spell is under a year in Figure II.2. Cyclers account for this difference. The median duration of the current TANF spell for all single-parent cases is 16 months.

• One in every four TANF cases has experienced a sanction.

In Illinois, as in most states, TANF recipients face sanctions, or reductions in their cash grant, for failure either to participate in a required activity or to cooperate with child support enforcement. Sanctions in Illinois become more severe as noncompliance persists. Initially, the cash grant is reduced by 50 percent; after three months of noncompliance, it is eliminated altogether (Illinois Department of Human Services 1999). With the third instance of noncompliance, the state immediately imposes a full-grant sanction that must remain in place for at least three months. Overall, 26 percent of TANF cases have experienced a sanction, with almost all attributable to failure to participate in a required activity (Figure II.3). Of the sanctioned cases, 9 percent have experienced a full-grant sanction (results not shown).

• The TANF 60-month clock has been stopped for one in every four TANF cases.

In Illinois, any month in which the head of a single-parent case consistently works 30 or more hours per week, attends a postsecondary degree program full time, or provides full-time care for a related child under age 18 or a spouse because of a medical condition does not count toward the 60-month TANF time limit (Illinois Department of Human Services 2002).⁽¹⁾ The TANF clock has been stopped for 26 percent of single-parent cases.⁽²⁾

Stopping the clock rewards those who are working by indefinitely supplementing their wages as long as they continue to work at least 30 hours per week. For example, a recipient who has received cash assistance for 18 months and has worked 30 hours per week for 6 of those months would log not 18 but 12 months on her TANF benefits clock. Only three percent of TANF recipients in Illinois have more than 48 months on their benefits clock and, hence, less than one year during which they can receive TANF without working or attending school (Figure II.4).⁽³⁾ Most recipients (58 percent) have logged no more than 24 months on their benefits clock. The median elapsed time for all single-parent cases is 20 months.

Employment and Earnings

Since the enactment of PRWORA, large numbers of TANF recipients nationwide have entered employment. While some recipients who find work leave TANF, others remain, despite relatively substantial earnings, because of the generous earned-income disregards in some states. In this section, we examine the extent to which current TANF recipients in Illinois are employed. To assess whether those jobs could be springboards toward greater self-sufficiency, we also examine the characteristics of these jobs and recipients' earnings.

Employment

• Two in every five TANF recipients are employed, and most of these recipients work 30 or more hours per week.

Thirty-nine percent of TANF recipients in Illinois are employed, more than three-quarters of whom work at least 30 hours per week (Figure II.5). The state's generous 67 percent earned-income disregard enables recipients to combine work and welfare up to an earnings level of about $1,100 per month for a family of three.⁽⁴⁾ And as noted, the state turns off the 60-month benefits clock for recipients who work 30 or more hours per week. Given these two strong incentives, it is not surprising that Illinois TANF recipients combine work and welfare at a higher rate than is reported nationally. Results from the 1999 National Survey of American Families indicate that 32 percent of TANF recipients nationwide were working at the time of the survey (Zedlewski and Alderson 2001).

The 61 percent of TANF recipients who are not currently employed have a broad range of reasons for not working.⁽⁵⁾ The principal reason is being pregnant or caring for a newborn (Table II.1). Other reasons for not working include physical or mental health problems, child care problems, and lack of education or work experience. Thirteen percent of unemployed recipients cited a poor local labor market--one that provides either no jobs or only low-wage jobs--as their principal reason for not working. Another 10 percent of recipients are not working because they are in education or training programs.

Job Characteristics

The characteristics of the jobs held by recipients can influence job duration and advancement. Several studies have found that starting out in jobs in certain occupations that offer higher wages or fringe benefits are more likely to lead to sustained employment and job advancement (Strawn and Martinson 2000). In this section, we describe the characteristics of the primary current or most recent job held by TANF recipients who have ever worked for pay. We refer to these jobs interchangeably as the "most recent job" or "the current or most recent job" and consider whether their characteristics are such that they are conducive to progressing toward self-sufficiency. ⁽⁶⁾

• Illinois TANF recipients tend to hold jobs in the same occupations and industries as recent TANF recipients in other states.

The jobs most recently held by TANF recipients in Illinois are concentrated in the same industries and occupations as those held by individuals who have recently left welfare in selected states, as documented by studies of TANF "leavers" (Richer, Savner, and Greenberg 2001). Nearly one in every three (29 percent) TANF recipients in Illinois works in the retail industry (Table II.2). In addition, just over half (53 percent) work in service industries. Among TANF recipients, the initial occupation (not just the industry) is an important determinant of long-term success in the labor market. Strawn and Martinson (2000) report that individuals who make the transition from welfare to work by starting out in sales positions tend to have shorter periods of employment and lower earnings growth. In Illinois, 17 percent of TANF recipients hold sales positions. Most recipients (54 percent) work in service occupations.

• Most recipients have a day job. The typical job is full time and lasts approximately five months.

More than half of recipients (56 percent) work a day shift in their most recent job (Figure II.6). A day shift is typically the most desirable and sustainable shift for single parents because it dovetails with more child care options and greater child care availability (Ross and Paulsell 1998). In addition, public transportation tends to be more widely available during daytime hours. Notwithstanding the advantages of a day shift, a substantial share of TANF recipients--about one-third--works either a night shift or an irregular shift, which can present challenges for arranging child care and transportation.

The current or most recent job for 59 percent of TANF recipients in Illinois is a full-time job, that is, at least 35 hours per week (Table II.3). Although this is a substantial portion of full-time workers on TANF, it is lower than the percentage of full-time workers among those who have left the welfare rolls. Loprest (2001) reports that, nationally, 68 percent of employed former recipients worked 35 hours or more per week at the time of the 1999 National Survey of American Families.

The jobs most recently held by TANF recipients in Illinois tend not to last long; the median duration is just five months. One explanation for this short duration is that more than one in four of the most recent jobs is temporary or seasonal.

• Recipients have jobs that pay low wages and offer limited benefits.

Despite some positive attributes, the quality of the most recent jobs held by TANF recipients is low in two important respects: the hourly rate of pay and fringe benefits. One in every five TANF recipients is paid less than the minimum wage of $5.15 per hour (Table II.4). A large proportion of these very low-wage workers provide child care or other personal services (e.g., housecleaning) in their own home or in the homes of their clients, and are often paid "under the table" on what appears to be a piecework basis. ⁽⁷⁾ These low wages may not lead to greater self-sufficiency and a movement off of welfare. For example, the median hourly rate of pay received by TANF recipients in Illinois on their most recent job is $6.50, which is about 10 percent lower than the median hourly wage among individuals who have left TANF across the nation, reported by Loprest (2001) at $7.15 based on the 1999 National Survey of American Families (or nearly 15 percent lower when Loprest's figure is adjusted to $7.60 per hour in 2001 dollars).

Extensive menus of fringe benefits are not available to most Illinois TANF recipients in their current or most recent job. Paid holidays and vacation time, the most common fringe benefits, are available to only two in every five TANF recipients at their most recent job (Table II.4). Health insurance and paid sick leave are available to only one-third of employed recipients, and a retirement plan is offered by less than one-quarter of the jobs most recently held by TANF recipients. Moreover, TANF recipients may not have participated in or received the fringe benefits, despite their availability, for such reasons as high co-payments or lack of longevity on the job to earn or qualify for them.

• Only 6 percent of the jobs most recently held by TANF recipients have the characteristics most conducive to achieving greater self-sufficiency.

For TANF recipients to move from welfare to work, they must obtain jobs with characteristics that will facilitate their transition to self-sufficiency. We have selected the following four characteristics that define jobs with the potential to lead to greater self-sufficiency: a rate of pay higher than $8.00 per hour, a day shift, work that is not temporary or seasonal, and the availability of both paid leave (vacation and/or holidays) and health insurance. Only 6 percent of the jobs most recently held by TANF recipients in Illinois have all four of these desirable characteristics (results not shown). We emphasize that this estimate reflects the characteristics of the jobs held by individuals who were on TANF at a specific point in time--November 2001. It is probable that individuals who obtain jobs with these desirable characteristics move off the caseload fairly rapidly, so an analysis of the job characteristics of TANF recipients over time would likely yield a higher percentage of recipients who obtain such jobs.

Employment in jobs with the preceding desirable characteristics tends to be stable. Rangarajan, Schochet, and Chu (1998) report that TANF recipients with jobs that pay more than $8.00 per hour are employed for longer than are those with lower-paying jobs. Consistent with this earlier study, we found that TANF recipients in Illinois working in a job with the four desirable characteristics remain in that job for two months longer, on average, than recipients in other types of jobs. Given that the average duration of the most recent job is just under a year, the difference is relatively large (17 percent) in addition to being statistically significant.

• TANF recipients perceive some opportunity to advance on their jobs.

About two-thirds (65 percent) of currently or previously employed TANF recipients believe that they have or had an opportunity, however small, for job promotion in their current or most recent job (Figure II.7). Almost all (92 percent) of the 6 percent of recipients whose most recent job has the characteristics conducive to greater self-sufficiency believe that they have the opportunity to advance.

Earnings

• While employment is an important feature of the lives of many TANF recipients, their earnings are not high enough to allow them to become self-sufficient.

Two out of every five TANF case heads were employed in the most recent month. However, 28 percent of those with earnings earned $400 or less in that month (Table II.5), which is far less than they are permitted to earn under Illinois' generous earned-income disregard while remaining eligible for TANF. The median monthly earnings of employed case heads is $600. This survey-based finding is broadly supported by quarterly data from the Illinois Unemployment Insurance (UI) system. For 2000 and 2001, these data indicate that the median earnings of employed TANF recipients ranged from $1,392 to $1,658 per quarter, or $464 to $553 per month (results not shown). These median values of monthly earnings, whether based on the survey data or the UI data, are substantially lower than would be predicted on the basis of the median amount of work (35 hours per week, Table II.3) and the median rate of pay ($6.50 per hour, Table II.4) in the current or most recent job held by TANF recipients. This gap between actual and predicted earnings is consistent with the failure of TANF recipients to sustain employment at the median levels of work and pay for extended periods.

• The earnings of TANF recipients have been stagnant over time.

The two-year quarterly earnings histories of the heads of TANF cases in November 2001 show little progress toward self-sufficiency. Among all case heads, regardless of their employment status, the average earnings per quarter ranged from a low value of $632 in the third quarter of 2001 to a high of $851 in the fourth quarter of 2000 (Figure II.8). The pattern of quarterly averages does not show any consistent growth in earnings over time but mirrors instead the slight variations in quarterly employment rates. When we examine the earnings histories only of those case heads who worked in at least half of the eight quarters, we find the same pattern (results not shown); earnings fluctuate with employment rates without any discernable growth over time.

Household Income

Because the heads of single-parent TANF cases have earnings that are, on average, low, they often rely on multiple sources of income to meet household expenses (Edin and Lein 1997). These sources may include the earnings of other members of the household and various forms of public assistance.

• Over half of TANF cases are in households that receive income from earnings, typically from the case head, but earnings contributed by other household members can be substantial.

Two-fifths of TANF cases receive income from the earnings of the case heads, which have an average value of $616 per month (Table II.6). In addition, 21 percent of TANF cases are in households that receive income from the earnings of other household members averaging $927 per month. So, although few TANF cases receive income from the earnings of other household members, those that do, receive substantial amounts. Considering all household members, slightly more than half (54 percent) of TANF cases receive income from earnings, with an average monthly value of $817.

Other studies of current and former TANF recipients have also found that people other than the case head may contribute large amounts of earned income to the household. For example, Kauff et al. (2002) found that in Iowa, 37 percent of one- and two-parent TANF cases that left welfare two years before the time of the survey received income from the earnings of other household members. The average amount of those earnings was $1,502 per month. Rangarajan and Johnson (2002) found that, in New Jersey, only 15 percent of one- and two-parent TANF cases received income from the earnings of the head's spouse or partner 40 months after going on assistance. However, at $1,383 per month, on average, those contributions were substantial for the cases that did receive them. Our focus on single-parent cases currently on assistance may account for finding lower, but still substantial, average earnings of other household members relative to the Iowa and New Jersey studies.

• Almost all TANF cases receive food stamps, which provide somewhat more income than TANF cash grants.

Given the eligibility criteria for public assistance programs, almost all of this study's subjects can be expected to have income from various forms of assistance in addition to TANF. Eighty-six percent receive a TANF cash grant with an average value of $273 (Table II.6). ⁽⁸⁾ Food stamps are an even more important source of household income for TANF cases. Ninety-three percent of cases receive food stamps that are valued, on average, at $317 per month. Only a small portion of TANF cases (15 percent) receive Supplemental Security Income (SSI), but they receive an average of $559 per month through that program. ⁽⁹⁾

TANF cases may also receive income from many other sources, such as child support, unemployment benefits, alimony payments, and gifts from friends or relatives. Thirteen percent receive income from one or more such source; 10 percent receive it from child support alone. The average income received from these sources is $244 per month (Table II.6).

• The average total household income of TANF cases is $1,058 per month, more than half of which comes from public assistance.

Even though more than half of TANF cases receive income from earnings, it is nevertheless true that most of the income received by TANF cases comes from public assistance. TANF, food stamps, and SSI account for 57 percent of the total household income received by TANF cases (Table II.7). Earnings by all household members account for 40 percent of total income. Other sources, including child support, account for only 3 percent of total household income.

For TANF cases in which the head has earnings, earnings from all household members are the primary source of total household income. In fact, the relative importance of earnings and public assistance is reversed for these cases relative to all TANF cases. Earnings account for 58 percent of total income, and public assistance for 39 percent (Table II.7).

• The majority of TANF recipients in Illinois live in extreme poverty, but those with earnings are less likely than those without earnings to be extremely poor.

A comparison of monthly household income with Census Bureau poverty thresholds reveals that 93 percent of TANF cases are in households with an income below poverty, and 65 percent are in extremely poor households, that is, those with an income below 50 percent of poverty.⁽¹⁰⁾ However, recipients with earnings do fare better than those without; workers are only half as likely to live in extreme poverty, and are twice as likely to live above the poverty line (Figures II.9 and II.10). We would not expect many TANF recipients to live above poverty, even with Illinois' generous earned-income disregard. The case head of a family of three in Cook County cannot earn more than $1,100 per month--an amount that is about equal to the poverty line--and still qualify for a TANF grant.

Families have other resources available to them that are not reflected in this poverty analysis. The official poverty measure does not include food stamps, which, as shown in Table II.7, contributes nearly one-third of total household income for TANF recipients in Illinois. Working recipients can also benefit from the earned income tax credit (EITC). We did not measure the contributions of the EITC toward household income in this study, but in general, the extra boost it provides can be substantial. For example, families with one child receive refundable tax credits of up to 32 percent of their earnings, and families with two or more children receive credits of up to 40 percent (Center on Budget and Policy Priorities 2001).

Summary

Illinois' generous earned-income disregard, combined with its provision that excludes months with employment from the 60-month limit on assistance, provide TANF recipients with the incentive to combine work and welfare. Indeed, two-fifths of the heads of single-parent TANF cases in Illinois are employed. Those who do hold jobs usually work full time, but half of these jobs last for five months or less. Despite their earnings, employed recipients still rely on public assistance for a substantial share of their household income. To become self-sufficient, these employed recipients would need jobs that pay higher hourly wages, provide fringe benefits, and are compatible with the available child care. Another group of recipients needs to gain a secure foothold in the labor market, as three out of every five heads of single-parent TANF cases are not currently working, and one in four has not worked in the past year. Most of these individuals face personal, logistical or situational challenges that make finding and keeping a job difficult--a topic we explore in the next chapter.

Endnotes

1. The TANF clock is stopped for up to 36 months for recipients who are enrolled in postsecondary degree programs only if they maintain a cumulative grade point average of at least 2.5 on a 4-point scale.

2. The TANF clock is also stopped for months in which the family has a severely disabled child in the home under a Home and Community-based Care Waiver, for recipients in the experimental group of the Employment Retention and Advancement project, and for a domestic violence exclusion.

3. Families may continue to receive assistance after they reach their 60-month limit without working or attending school if they request and qualify for an exception from the Illinois Department of Human Services.

4. Based on monthly allowances for an assistance unit that includes caretaker relatives and children (Illinois Department of Human Services 2002).

5. Only 3 percent of the heads of single-parent TANF cases in Illinois have never worked for pay. They are, of course, included among the 61 percent in Figure II.5 who are not currently employed.

6. If a TANF case head is currently employed, then the job described in this section is the principal current job. If a case head is not currently employed but has been employed in the past, then the job described is the most recent job. In the case of several "most recent jobs," then the principal job is the reference one.

7. The statistics on hourly wages reported in Table II.4 are based primarily on hourly wage rates reported directly by the participants in MPR's 2001-02 survey of TANF cases in Illinois. However, some of the survey respondents (51 cases) were unable to report an hourly wage but did report earnings and hours worked over a specific period. We used that information to calculate the hourly rates of pay received by these respondents. Of the 51 cases that were calculated in this way, 41 had wages below $5.15 per hour. Such calculated wage rates account for approximately half of the wages below $5.15 per hour reported in the table. Excluding these cases, 12 percent of all case heads directly reported wages below $5.15 per hour.

8. There are two reasons why some members of the sample for this study reported no income from TANF in the month before the survey interview. First, zero-benefit cases comprise 9 percent of the study population from which this sample was selected, as discussed in Chapter I. Second, some sample members may have left TANF in the brief interval between the time when they were their selected for the sample and when they were interviewed.

9. Presumably, the grantee was not receiving SSI at the time of the interview if they were still receiving TANF, rather it was other members of the household who were likely to have been receiving income from this source.

10. The poverty thresholds are the U.S. government's official yardstick for measuring poverty. The poverty thresholds do not take income from food stamps into account and, therefore, food stamps are excluded from this analysis. The U. S. Bureau of the Census updates the thresholds each year, taking into account the number of family members and their ages. The poverty thresholds have been designed to be compared with annual income. For the purpose of this report, we converted the threshold values for 2001 to monthly values, which we compared with monthly income. Monthly income is more volatile than annual income; consequently, the poverty statistics presented here may not accurately reflect the poverty status of TANF cases over the course of a year. In addition, we calculated the incidence of poverty by using household-based measures of size and income, whereas the poverty thresholds were designed to be based on family size and to be compared with family income.

Employment Assets and Liabilities

As TANF programs nationwide continue to focus on employment, program administrators and staff have expressed great interest in identifying the assets and liabilities that TANF recipients bring to the labor market. Given the sharp reduction in the welfare rolls that occurred after the passage of PRWORA in 1996, program administrators, policymakers and researchers have made assumptions about the characteristics and circumstances of those individuals who remain on welfare. In this chapter, we take a closer look at the assets that the heads of single-parent TANF cases in Illinois may bring to a job. We also consider the prevalence of characteristics that may pose liabilities for employment.

Employment Assets

The employment and earnings potential of individuals is strongly associated with their education, training, and work experience--the key elements of the human capital that individuals bring to the labor market. While TANF recipients generally have low levels of human capital, some have strengths that are applicable to work. In this section, we examine the assets that the heads of single-parent TANF cases in Illinois can bring to the labor market in terms of education, training, employment history, and experience with common job tasks.⁽¹⁾

• Slightly more than half of TANF case heads have at least a high school diploma or its equivalent, and three in every four participated in some educational, training, or job preparation activity during the past year.

Fifty-six percent of TANF case heads have at least a high school diploma or its equivalent, and half of this group has some education beyond the high school level (Figure III.1). Still, the level of education among TANF clients in Illinois is low, even in comparison with welfare clients in other states. Recent surveys conducted in Michigan and Nebraska show rates of high school completion by TANF case heads of 69 and 78 percent, respectively, although the respondents to these surveys included some clients who had recently left welfare (Danziger et al. 2000; Ponza et al. 2002). During the past year, most heads of TANF cases in Illinois (74 percent) participated in a program to enhance their education, skills, job readiness, or work experience (Figure III.2). Specifically, 49 percent participated in an education or training program, 55 percent participated in a job preparation program (job readiness or job search), and 23 percent participated in a work experience program.

TANF recipients who are not employed are more likely than those who are employed to have participated in a job preparation or work experience program during the past year, presumably because they had more time to do so, perceived a greater financial return on the investment in their own human capital, and/or were required to participate under TANF rules. Another group of TANF recipients--those without a high school diploma or its equivalent--could also benefit from education and training, job preparation, and work experience to augment their human capital, but they are no more likely than high school graduates to have participated in such programs during the past year (results not shown).

• About three in every four TANF case heads have recent work experience and are familiar with common job tasks.

While lacking in education, most TANF case heads in Illinois have recent paid work experience and the skills important for entry-level jobs. The majority of case heads (77 percent) worked at least one quarter in calendar years 2000 and 2001, and 12 percent were employed in all eight quarters (Figure III.3). Nearly half (45 percent) of all case heads have substantial recent work experience, having worked at least four quarters in 2000 and 2001. Only 3 percent of case heads have never worked for pay since their 18^th birthday. While working, 72 percent of heads performed at least four of nine common job tasks, and they often performed those tasks frequently--daily or weekly rather than monthly (Table III.1). This prevalence of experience and skills suggests that many TANF case heads have the basic pre-requisites for entry-level employment.

Employment Liabilities

Any person may have a host of potential liabilities for employment. This is especially true for single parents receiving TANF, whose employment assets are modest and financial assets are few. In addition, the jobs available to them tend to have inflexible work schedules and offer sick or annual leave that is limited relative to their special needs or circumstances (Ross and Paulsell 1998a). These factors may make it particularly difficult for TANF recipients to overcome their employment liabilities. In this section, we examine two broad categories of liabilities for employment: personal challenges and logistical and situational challenges. Broadly speaking, personal challenges are individual characteristics, while logistical and situational challenges are family, logistical, or environmental circumstances.

Personal Challenges

Using information from the client survey, we examined six types of personal challenges, each measured over the year preceding the survey interview: (1) physical health, (2) mental health, (3) chemical dependence, (4) severe physical domestic violence, (5) possible learning disability, and (6) difficulty with English. We asked case heads a series of questions about their characteristics and/or behavior as part of itemized scales that indicate the presence or absence of the particular challenge. When possible, we used validated scales to determine, for example, the extent of mental health problems and chemical dependence. Validated scales allowed us to measure characteristics consistently across all recipients.⁽²⁾ In addition, we used administrative data on the survey respondents from the Illinois Criminal Justice Information Authority to examine a seventh type of personal challenge, which is the existence of a criminal record.

• About one in every five TANF recipients in Illinois has a general physical health problem.

About one-quarter (26 percent) of case heads assess their general health as fair or poor (Figure III.4). Based on age-specific national norms, nearly half (47 percent) fall in the lowest quartile for physical functioning.⁽³⁾ We used these two measures to create a summary indicator of a physical health problem. This indicator produces a conservative estimate of those with a physical health problem by identifying case heads who rate their general health as fair or poor and whose physical functioning lies in the lowest quartile. According to this indicator, 21 percent of TANF clients have a physical health problem.⁽⁴⁾

• One-quarter of TANF case heads have a mental health problem.

About 1 in every 10 TANF clients (12 percent) experienced psychological distress in the past 30 days (Figure III.5). Psychological distress was measured with a validated scale that scores client responses to questions about feelings of depression, hopelessness, restlessness, worthlessness, and nervousness. Scored responses closely replicate a diagnostic assessment of serious mental illness. In addition, during the past year, 23 percent of case heads had a major depressive episode that lasted for two or more consecutive weeks as measured by another validated scale. The two scales essentially measure the same thing--a diagnosable mental, behavioral, or emotional disorder--but they do so for intervals of different lengths.⁽⁵⁾ We would expect the estimate of major depression to be higher than the estimate of psychological distress because the former is based on a scale that measures symptoms experienced over the past year, while the latter is based on a scale that measures symptoms experienced in the past month. The percentage of recipients with a major depressive episode is comparable to that among TANF recipients in Michigan at 25 percent (Danziger et al. 2000) but lower than the 33 percent found in Nebraska (Ponza et al. 2002).

We combined the two measures to classify TANF case heads as having a mental health problem if they experienced psychological distress in the past 30 days or a major depressive episode in the past year. Based on this classification scheme, one-quarter of TANF case heads have a mental health problem. They appear to experience mental health problems at a rate higher than in the general population. For example, preliminary estimates developed by the National Center for Health Statistics (2002) from the 2002 National Health Interview Survey (NHIS) indicate that 3 percent of women age 18 to 44 experienced serious psychological distress in the past 30 days, whereas this was true for 12 percent of the case heads in this study. An estimate from the 2001 National Household Survey on Drug Abuse (NHSDA) indicates that 9 percent of adult females have serious mental illness (Substance Abuse and Mental Health Services Administration 2002) compared to the 25 percent we found among TANF case heads in Illinois.⁽⁶⁾

• It is not unusual for TANF clients to have a history of arrests or convictions.

More than one in every three TANF clients (36 percent) was arrested during the past six years, according to data from criminal records provided by the Illinois Criminal Justice Information Authority (Figure III.6). Although most such clients were arrested only once, multiple arrests are not uncommon. Sixteen percent of clients were arrested at least twice during the past six years.

Nearly one in every five TANF clients (18 percent) has been convicted of a felony or misdemeanor in Illinois (Figure III.6).⁽⁷⁾ Most were convicted of a misdemeanor only, while the remainder were convicted of at least one felony and may have also been convicted of a misdemeanor. The overall rate of convictions reported here is the same 19 percent rate reported by Losby et al. (2002) for short-term TANF recipients in Iowa. However, those researchers found higher conviction rates for long-term recipients: 22 percent for those who eventually left assistance and 45 percent for those who were never observed to leave.

• More than 1 in every 10 TANF clients recently experienced severe physical domestic violence.

During the past year, 13 percent of the female heads of single-parent TANF cases experienced severe physical violence at the hands of a domestic partner (Figure III.7). We modeled this measure on a modified version of the Conflict Tactics Scale used in the Michigan Women's Employment Study (WES). The measure of severe physical violence includes incidents of hitting, beating, choking, using or threatening use of a weapon, or forcing sexual activity. These actions have a higher probability of causing injury or more extreme intimidation than actions considered more moderate (e.g., pushing, grabbing, slapping, kicking, or biting). Danziger et al. (2000) report that the prevalence of severe physical domestic violence is much higher among TANF cases than among the population as whole, with rates of 15 percent found among Michigan TANF cases compared with about 3 percent documented among women nationally.

We did not observe differences between employed and not employed female case heads with regard to severe physical domestic violence in the past year, although a broader examination reveals a noteworthy pattern. Employed and not employed heads were equally likely to have experienced moderate or severe physical domestic violence during the past year (Figure III.8). However, the percentage of employed case heads experiencing moderate or severe violence before the past year is significantly higher than the percentage of not employed heads (26 percent versus 15 percent). Considered together, these two findings suggest that women who have escaped domestic violence have done so through employment.

• A small percentage of TANF recipients are chemically dependent.

Past survey findings on the incidence of problems associated with the use of chemicals (drugs and alcohol) among TANF recipients vary considerably depending on the measurement methodology. The evidence generally indicates that the incidence of chemical dependence is lower than the incidence of chemical abuse, the former being the more severe. For example, using a validated short scale that accurately diagnoses dependence, Danziger et al. (2000) report that 3 percent of Michigan TANF recipients are dependent on alcohol and 3 percent on drugs.⁽⁸⁾ In contrast, based on the widely used CAGE Drug and Alcohol Abuse screener, Ponza et al. (2002) report that 17 percent of TANF recipients in Nebraska have a problem with chemical abuse. We used the same methodology as the Michigan study and found that rates of chemical dependence among Illinois TANF recipients are 2 percent for alcohol, 2 percent for drugs, or 3 percent for either (Figure III.7).⁽⁹⁾ These rates are not unlike those in the general population. The 2001 NHSDA found rates of 1.6 percent for drug dependence, 2.4 percent for alcohol dependence, and 3.6 percent for any chemical dependence among all individuals age 12 or older (Substance Abuse and Mental Health Services Administration 2002).⁽¹⁰⁾

• More than 1 in 10 TANF case heads show signs of a learning disability.

We used the Washington State Learning Needs Screening Tool to assess the possible presence of a learning disability among the heads of single-parent TANF cases in Illinois. The tool revealed that 12 percent of case heads showed signs of a learning disability (Figure III.7), which is comparable to the 15 percent found by Ponza et al. (2002) among TANF recipients in Nebraska.

Only 2 percent of the TANF recipients in Illinois have difficulty speaking, reading, or writing English because it is not their native language (Figure III.7).

Logistical and Situational Challenges

For TANF case heads, liabilities for employment stem not only from personal challenges but also from the logistical and situational challenges presented by the people who rely on them for support and by their environment in general. We examined seven types of logistical and situational challenges to employment: (1) health or special needs of family members or friends, (2) presence of a very young child, (3) transportation, (4) child care, (5) housing, (6) discrimination, and (7) neighborhood conditions. Our measures of these challenges are based predominantly on the self-reports of TANF case heads.

• One-third of TANF case heads are caring for a child, another family member, or a friend with a health problem or special need.

Many case heads are caring for family members or friends with special needs that arise primarily from health problems. One in every three TANF case heads has a child with a health problem, behavioral problem, or other special need (Figure III.9). Among these case heads, about half (53 percent) have a child whose condition limits his or her activities, and about one-quarter (27 percent) have a child who receives SSI benefits (Table III.2).

Moreover, TANF clients may have responsibilities for persons other than their children that may likewise constitute liabilities for employment. The heads of slightly over 1 in every 10 TANF cases (12 percent) are caring for an elderly, sick, or disabled family member or friend. When these broader responsibilities are considered along with the responsibilities for children, we observe that 35 percent of TANF case heads are caring for either a child, another family member, or a friend with a health problem or other special need (Figure III.9).

• More than one-third of TANF case heads are pregnant or caring for a young child.

Under TANF, states have some flexibility to determine who is required to participate in work or work-related activities. Illinois has decided to exempt from these requirements case heads caring for an infant (i.e., a child under age one). Twenty-eight percent of recipients have an infant in their household. An additional 8 percent are pregnant. Taken together, 36 percent of case heads in Illinois are either pregnant or caring for an infant (Figure III.10). This situation presents unique employment challenges, as employers may be reluctant to hire pregnant women, and child care is often expensive and difficult to find for infants. In addition, recipients may decide to remain unemployed during pregnancy because of health concerns, or they may prefer to remain home while their child is very young.

• Nearly one-third of TANF clients with a child younger than age 13 recently had child care problems that interfered with their ability to work or participate in work-related activities.

During the past year, approximately half (48 percent) of TANF clients with a child younger than 13 used child care other than that provided by a parent, and nearly one-third (31 percent) experienced child care problems during the same period (Table III.3). Among the latter, the predominant concerns are the unreliability and limited availability of providers--38 and 30 percent, respectively--rather than the cost of care (15 percent). Clients with a preschool-age child are much more likely than those with a school-age child to have encountered unreliable providers (43 percent versus 10 percent).⁽¹¹⁾ Because many welfare-reliant families live in communities with high rates of crime and drug use, child care arrangements with a caregiver who can be trusted are very highly valued by parents. For preschool-age children, particularly infants, the need for a trustworthy caregiver often leads to a preference for relatives and friends as caregivers (Ross and Paulsell 1998b). However, child care provided by relatives and friends tends to be highly informal and therefore the least reliable type of arrangement. It is possible that many TANF recipients in Illinois prefer informal care but find that they cannot depend on it as a support of steady employment.⁽¹²⁾

• Most TANF clients rely on public transportation for travel to work or work-related activities; nevertheless, transportation is a problem for one in every five clients.

The heads of TANF cases in Illinois rely heavily on public transit to get to work or work-related activities. It is the primary mode of transportation for 61 percent of case heads. This figure is not surprising, given that 81 percent of the state's single-parent TANF cases reside in Cook County, which has an extensive public transit system. Nevertheless, nearly one-quarter (22 percent) of case heads statewide drive themselves to work or work-related activities.

A case head's specific circumstances influence whether the transportation options available pose a barrier to employment. For example, depending on access to public transportation, the absence of a driver's license or a car may represent a major challenge for some individuals but less of a challenge, if any, for others. So, rather than base an overall measure of transportation as a liability for employment on the number and type of options available, we based it on self-reports by TANF clients of whether transportation was, at any time over the past year, such a problem that it adversely affected their ability to work or participate in work-related activities. According to this measure, transportation posed a problem for employment for 21 percent of TANF clients (Table III.4).

• The housing situation of nearly one-quarter of TANF recipients is unstable.

Unstable housing can be a liability for employment because it can disrupt family life and act as a source of stress for the family head. One in every five TANF recipients moved two or more times during the past year, and 1 in every 20 was evicted during the same period (Figure III.11). We have combined these two measures in a summary measure of unstable housing. The measure indicates that 23 percent of all TANF recipients have unstable housing as a consequence of either having moved at least twice during the past year or having been evicted during the same period.

• One-fifth of TANF case heads believe that a potential employer recently discriminated against them because of their characteristics or circumstances.

Most TANF recipients do not perceive discrimination to be a problem. Among TANF case heads who ever worked for pay, 11 percent believe that a potential employer refused to interview or hire them during the past year because of their status as a welfare recipient (Figure III.12). And 10 percent believe that they were discriminated against because of some personal physical characteristic. Smaller percentages believe that they experienced discrimination because of their race/ethnicity or gender. If we combine these categories, 20 percent of TANF recipients who have ever worked for pay believe that a potential employer discriminated against them during the past year for some reason.

• TANF recipients live in counties with moderate unemployment and in neighborhoods with high concentrations of racial and ethnic minorities. Many believe there are serious problems in their neighborhoods.

Almost all Illinois TANF recipients (93 percent, results not shown) live in counties where the unemployment rate in 2001 was less than 6 percent. The rate reflects the fact that 81 percent of all Illinois TANF recipients live in Cook County, which had an unemployment rate of 5.9 percent in 2001. By comparison, the national unemployment rate in 2001 was about a point lower, at 4.8 percent.⁽¹³⁾ TANF recipients also live in neighborhoods with high concentrations of racial and ethnic minorities. Figure III.13 shows that, on average, they live in five-digit zip code areas where 61 percent of residents are African American, 22 percent are white, and 14 percent are Hispanic of any race. ⁽¹⁴⁾ They also live in neighborhoods where most of the residents are of their own race and ethnicity. On average, both African American and white TANF recipients live in neighborhoods where 71 percent of the residents are of their own race and ethnicity.

Many TANF recipients believe that their neighborhoods have serious problems associated with unemployment, illicit drug activity, other crime, or poorly maintained properties.⁽¹⁵⁾ The rates of perception of serious problems range from a high of 42 percent for illicit drug activity to a low of 17 percent for poorly maintained properties (Figure III.14). At least one of these neighborhood conditions is perceived to be a serious problem by 55 percent of TANF recipients.

Employment Status Relative to Assets and Liabilities

This section discusses findings from an analysis of whether employment rates for the heads of single-parent TANF cases in Illinois differ systematically for those with and those without the various assets and liabilities outlined in this chapter. For purposes of the analysis, employment is defined as working 30 or more hours per week on a current paid job. The definition is consistent with federally mandated work requirements under PRWORA.

Assets and Employment

Of the three hypothesized assets for employment introduced in this chapter and summarized in Table III.5, substantial recent work experience appears to confer a labor market advantage to the heads of single-parent TANF cases in Illinois. It has a significant positive association with current paid employment, but the same is not true for possession of a high school diploma or experience in performing common job tasks.

• TANF case heads with substantial recent work experience are more likely than those without substantial experience to be employed at least 30 hours per week.

TANF case heads who were employed in at least four of the seven last quarters are much more likely than those without such recent work experience to be working for pay at least 30 hours per week (41 percent versus 22 percent, respectively, as shown in Table III.5). ⁽¹⁶⁾ This finding suggests that interventions that are designed to increase human capital through work experience may facilitate the transition to paid work among unemployed TANF recipients. Employment rates for case heads with and without a high school diploma or its equivalent are similar, as are employment rates for case heads with or without experience with common job tasks.

Liabilities and Employment: Personal Challenges

This chapter has introduced eight personal challenges that may constitute liabilities for employment (Table III.6). Our analysis reveals that most of these challenges are not, in fact, significantly associated with current paid employment among TANF case heads, although we observed several exceptions to this pattern. Case heads with personal health problems, either physical or mental, or a record of multiple arrests are much less likely than those not facing these challenges to be working 30 or more hours per week.

• TANF case heads with a physical or a mental health problem are much less likely than those without such problems to be employed.

About one-fifth of TANF case heads have a physical health problem (Figure III.4), and one-fourth have a mental health problem (Figure III.5). These individuals are about half as likely as those without these problems to be employed at least 30 hours per week. The employment rate for case heads with a physical health problem or with a mental health problem is 18 percent, compared with 33 percent for heads without these problems (Table III.6). These findings substantiate the notion that personal physical and mental health problems are serious employment liabilities for the heads of single-parent TANF cases in Illinois.

• TANF case heads with multiple recent arrests are much less likely than those with a less extensive arrest record to be employed.

An extensive record of recent arrests, rather than a criminal conviction, has a strong negative association with current employment among TANF clients. We initially expected that many of the 18 percent of clients convicted of a felony or criminal misdemeanor (Figure III.6) would have difficulty finding work because potential employers can learn of convictions through criminal background checks. However, clients with and without criminal convictions are equally likely to be employed at least 30 hours per week (Table III.6)). This finding suggests that employers either are not conducting criminal background checks or are not using the information obtained through such checks when making hiring decisions. It may also reflect an effort by Illinois TANF caseworkers to direct ex-offenders to employers who do not discriminate on the basis of a criminal record.

Most employers in Illinois cannot access official state records on arrests; nevertheless, the 16 percent of TANF clients with a record of two or more arrests during the past five years (Figure III.6) are much less likely to be employed than are clients with no arrests or only one arrest. Only one in every five clients with multiple arrests is employed at least 30 hours per week, compared with one in every three clients without multiple arrests (Table III.6). This finding, when combined with the finding on convictions, suggests that the underlying characteristics, circumstances, or behavior of TANF clients with multiple arrests, rather than the responses of employers to their public criminal records, may be a serious liability for employment. TANF case heads who face other personal challenges, such as domestic violence or chemical dependence, are employed at about the same rate as heads who do not face such challenges. Apparently, TANF clients find ways to deal with these challenges such that they do not adversely affect employment.

Liabilities and Employment: Logistical and Situational Challenges

Some basic infrastructure must be in place in order for individuals to obtain and maintain employment. This chapter has introduced seven logistical and situational challenges faced by some TANF case heads that may represent weaknesses in that infrastructure (see the bottom part of Table III.6). Here we present statistical evidence that four of the challenges are associated with lower rates of employment.

• TANF clients who recently experienced a child care problem or who are pregnant and/or caring for an infant are less likely to be employed than are those not facing these challenges.

The challenges of pregnancy and caring for an infant, along with child care challenges are associated with lower rates of employment. Only 15 percent of TANF clients with a child care problem and 22 percent of clients who are pregnant or caring for an infant are employed 30 hours or more per week (Table III.6).

• TANF case heads who recently experienced transportation problems or unstable housing are less likely to be employed at least 30 hours per week than are those who do not face these challenges

Among TANF case heads who, during the past year, had a transportation problem (21 percent, Table III.4) or experienced unstable housing (23 percent, Figure III.11), only one in five is employed at least 30 hours per week. In contrast, one in three heads who did not face these challenges is employed (Table III.6). Thus, reliable transportation and housing do appear to be critical to the employment of TANF recipients.

Liabilities and Employment: Perceptions of TANF Case Heads

Many TANF case heads perceive problems with child care, their physical health, and transportation as liabilities for employment. Twenty to 30 percent of heads blame these problems for impeding their participation in work or work-related activities during the past year (Table III.7). Notably, the findings in Table III.6 also indicate that these three problems are serious liabilities. At the same time, few case heads perceive problems with housing, their mental health, and the existence of a criminal record as liabilities for employment, although our findings indicate otherwise.

Summary

Most heads of single-parent TANF cases in Illinois can bring some significant human capital assetsto the labor market. About three-fourths of them have had paid employment at some time during the past eight calendar quarters and nearly half were employed in at least four quarters (Table III.8). Three of every four TANF case heads are also familiar with at least four common job tasks. On the other hand, case heads have relatively weak educational backgrounds; a little more than half have a high school diploma or a GED.

In addition to limited education, TANF case heads have other liabilities that may present personal or logistical and situational challenges. The latter are more prevalent than the former. Over half of TANF case heads perceive serious problems in their neighborhood, problems that may influence comfort levels with travel outside the home and with child care. Caring for a family member or friend with a health problem or special need, being pregnant or caring for an infant in the household, and having a child care problem are also common logistical and situational challenges faced by TANF cases, each affecting about one-third of the case heads. The most prevalent personal challenges are poor physical and mental health, affecting one-fifth and one-quarter of TANF case heads, respectively.

Endnotes

1. An attempt was made through this study to also include a measure of work norms among the employment assets examined. The Illinois survey instrument included an experimental module on work norms from which we developed an exploratory measure based on understanding 3 of 5 work norms. The measure was not validated and preliminary findings suggested that further work is necessary. Therefore, we do not present a discussion of work norms in this report, but refer the reader to Table D.10 for further information.

2. Of the five challenges discussed, only difficulty with English is not based on a tested scale or assessment tool. This challenge is based on a single self-report question in the survey.

3. The measure of physical functioning is a scale based on self-reported ability to perform vigorous activities such as running or lifting heavy objects, moderate activities such as moving a table, and daily physical activities such as carrying groceries, climbing stairs, walking, and bending and kneeling. Appendix B provides more information on the physical functioning scale.

4. The summary indicator of a physical health problem is identical to that used in the Women's Employment Study (WES) of the University of Michigan. In the WES, 19 percent of the study subjects had a physical health problem (Danziger et al. 2000).

5. Serious psychological distress was measured using the K6 Psychological Distress Symptom Scale. The probability of major depression was determined using the methodology of the Composite International Diagnostic Interview Short Form (CIDI-SF). Both screening tools have been validated through methodological studies that determined that the scores from the screeners accurately diagnosis mental disorders. Refer to Appendix B for further information.

6. The NHSDA uses the K6 but asks respondents about symptoms during the one month in the past 12 months when he or she was the most depressed, anxious, or emotionally stressed. Because both the K6 and the CIDI-SF are short screening tools that measure mental illness, it is the timeframe that is important for purposes of comparison.

7. The data on arrests and convictions cover the full survey sample of 532 TANF cases and their heads, including both respondents and nonrespondents. Note that the time periods for the data on arrests and convictions differ. The data on arrests are limited to the five years preceding the selection of the study's survey sample in November 2001, plus the nine months that elapsed until the criminal data were extracted in September 2002. For expositional convenience, we refer to the data on arrests as covering a six-year period. The data on convictions are not time-limited; any convictions in the state of Illinois before September 2002 should be represented in the data (convictions in other states are not recorded).

8. Danziger et al. (2000) do not report a rate of dependence for either alcohol or drugs.

9. The probability of alcohol dependence and drug dependence was determined by following the methodology of the Composite International Diagnostic Interview Short Form (CIDI- SF). Refer to Appendix B for further information.

10. The NHSDA uses a broader battery of questions to assess dependence than the short scale used in this study of Illinois TANF recipients. However, both approaches are designed to measure dependence based on the criteria specified in the Diagnostic and Statistical Manual of Mental Disorders, 4^th edition (DSM-IV).

11. In the analysis, a TANF client with a child younger than 6 years of age and a child between 6 and 12 years of age was classified as having a child in the younger age category but not in the older age category.

12. The Illinois Families Study (Lewis 2002) found consistently high rates (just over 40 percent) of informal child care arrangements in two annual surveys of a longitudinal panel study of individuals who received TANF in 1998. These results include individuals who were both on and off TANF at the time of the follow-up surveys, but still suggest the child care preferences of current TANF recipients.

13. Unemployment statistics are from the Bureau of Labor Statistics, U.S. Department of Labor.

14. Aggregate statistics on race and ethnicity at the level of the five-digit zip code are readily available from the Bureau of the Census, U.S. Department of Commerce. Consequently, we adopted the five-digit zip code area as the definition of "neighborhood " in this analysis. The racial and ethnic categories are mutually exclusive. All Hispanic individuals, regardless of their race, are included in the "Hispanic " category. Thus, the categories "African American" and "white" do not include anyone of Hispanic ethnicity.

15. The definition of "neighborhood " in this analysis is not the five-digit zip code area. Rather, it is the survey respondent's perception of the area "right around" where he or she lives. The term "serious problem" refers to a neighborhood condition that is reported by the survey respondent to be a "big problem" as opposed to "somewhat of a problem" or "not a problem at all."

16. The fourth quarter of 2001, as the study quarter, was omitted from this analysis.

The Determinants of Labor Market Success or Failure

The previous chapter examined the specific assets and liabilities that may foster or impede TANF recipients' success in the labor market. Information on assets and liabilities is useful because it reflects the prevalence of certain characteristics among TANF recipients and provides a framework for thinking about how these characteristics can influence the ability to transition from welfare to work or meet work requirements while receiving TANF benefits. In this chapter, we expand the analysis by (1) examining the prevalence of multiple employment liabilities among case heads, (2) using a multivariate model to estimate how the number of liabilities or the presence of specific liabilities influences the likelihood that a recipient is substantially employed (i.e., working at least 30 hours per week), and (3) simulating the changes in employment rates that could result from various strategies designed to address the employment liabilities of TANF recipients.

The Prevalence of Multiple Employment Liabilities

Previous studies on the characteristics of welfare recipients have found that they often have multiple employment liabilities and that the likelihood of employment decreases as the number of liabilities increases (Olson and Pavetti 1996; Danziger et al. 2000; Loprest and Zedlewski 1999). For example, a recipient with limited education but substantial work experience is likely to experience more success in finding employment than a recipient with limited education and no work experience. A recipient with limited education and poor health may have less success in finding a job than a recipient with only one of these liabilities; the first individual may need to find a job that does not require a high school diploma and that provides a work schedule that is flexible enough to accommodate the employee's medical needs. A recipient experiencing major depression who faces child care and transportation problems may be overwhelmed by the prospect of finding a job in the face of these obstacles, whereas a recipient who experiences major depression but no other liabilities may be able to manage her depression well enough to find and maintain employment.

In our analysis, we examine 16 employment liabilities. Broadly speaking, they fall into three categories: human capital liabilities, personal challenges, and logistical and situational challenges (Table IV.1). The category of human capital liabilities, newly introduced in this chapter, was established by identifying the employment assets lacking in TANF case heads.⁽¹⁾

• Multiple liabilities for employment are extremely common among TANF case heads and are significantly more common among those who are not substantially employed.

The majority of TANF case heads have 3 or more liabilities for employment (Figure IV.1).⁽²⁾ Only 4 percent do not have any liabilities, and 12 percent have only 1. Ten percent have 7 or more liabilities. The most liabilities for any one TANF recipient is 11.

TANF case heads who are not employed at least 30 hours per week have an average of 3.9 liabilities for employment, which is significantly higher than the average of 2.8 liabilities characteristic of substantially employed case heads (Table IV.2). On average, TANF recipients who are not substantially employed have significantly more liabilities--whether human capital, personal, or logistical and situational--than their counterparts who work at least 30 hours per week. Regardless of employment status, the presence of multiple human capital and logistical and situational liabilities is more pronounced than the presence of multiple personal liabilities. For instance, among TANF case heads not substantially employed, more than 40 percent have multiple human capital liabilities (46 percent) or multiple logistical and situational challenges (44 percent). In contrast, only 29 percent have multiple personal challenges (results not shown, see Appendix D, Table D-26).

• Multiple liabilities are especially common among TANF case heads facing personal challenges and transportation issues.

TANF case heads who have a mental health problem, are chemically dependent, have experienced severe domestic violence in the past year, show signs of a learning disability, have difficulty with English, or face a transportation problem always have other liabilities as well (Table IV.3). Among TANF case heads with at least one employment liability, only 10 percent have seven or more liabilities (Table IV.3). However, the likelihood of having seven or more liabilities is substantially higher for recipients with certain liabilities. For example, about 40 percent of TANF case heads who have difficulty with English, show signs of a learning disability, or are chemically dependent have a total of seven or more liabilities. About 30 percent of TANF case heads with a physical health problem, a mental health problem, a recent history of severe domestic violence, or a transportation problem have a total of seven or more employment liabilities. TANF case heads who have a child under age one in the household are the least likely to have a high number of liabilities; specifically, only 9 percent have seven or more liabilities.

Influence of Liabilities on Substantial Employment: Multivariate Analysis

This section presents the results of our multivariate analysis of the influence of various liabilities on the likelihood that a TANF recipient is working more than 30 hours per week. We initially investigated how the number of liabilities affects a recipient's employment status. We then investigated how the presence of specific liabilities affects a recipient's employment status. In these analyses, we considered background characteristics such as demographic traits, neighborhood and local labor market conditions, and the amount of time on TANF in the past 25 months.

As shown in Table IV.4, and consistent with previous studies, the greater the number of liabilities, the less likely a case head is to work 30 or more hours per week. The multivariate logit model predicts that a TANF recipient with no liabilities has a 58 percent probability of working 30 hours or more per week. Recipients with one or more liabilities have significantly lower probabilities of working. Specifically, the probability that a recipient with one liability works 30 or more hours per week is only 35 percent, nearly 23 percentage points lower than the probability for a recipient with no employment liabilities. Recipients with two or three liabilities have a slightly lower likelihood (33 percent) of working 30 or more hours per week than those with just one liability. For recipients with four to six liabilities, the likelihood of working 30 and more hours per week drops by an additional 10 percentage points to just 23 percent. And, for TANF recipients with seven or more liabilities, the probability of working 30 hours or more hours per week is extremely low, at just 7 percent.

Table IV.5 presents predicted probabilities based on a model that estimates the relative influence of each liability on the likelihood that a recipient works 30 or more hours per week, assuming that a TANF case head has "average" characteristics and only the liability under consideration. The model predicts that a TANF recipient with no liabilities has a 50 percent chance of working 30 hours or more per week.⁽³⁾

Only 4 of the 16 liabilities in the model are significantly related to a recipient's employment status: fewer than four quarters of recent work experience, a health problem, two or more arrests in the past six years, and a child care problem. Recipients with a child care problem have only a 30 percent chance of working 30 or more hours per week, which is 20 percentage points less than recipients with no employment liabilities. Similarly, recipients with a health problem, fewer than four quarters of recent work experience, or two or more arrests have a 32, 36, or 34 percent chance, respectively, of being employed 30 or more hours per week. Note that unobserved variables not included in this model (such as personal motivation or family support) could be significantly related to a recipient's employment status. While some of these unobserved variables could directly influence a recipient's employment status, they also might influence employment through other variables in the model. For example, personal motivation might influence whether a recipient has worked in the past, and it might be personal motivation rather than recent work experience that is exerting the observed influence on employment status.

Four liabilities that have a significant bivariate relationship with employment (Table III.7) did not show a significant relationship with employment in the multivariate analysis: mental health problems, transportation problems, pregnancy, and caring for a child under the age of one. Mental health and transportation problems are liabilities that occur in combination with many other liabilities, reducing their independent influence. Pregnancy and caring for a child under the age of one do not occur in combination as often as many other liabilities, although they do tend to occur more often among younger rather than older women.

The background characteristics in these models that significantly influence a recipient's employment status include age, race, county unemployment rate, and number of children. Consistent with the results of other studies, older recipients are significantly more likely to be working than are younger recipients. Recipients who are neither black nor white also are significantly more likely to be substantially employed than are white recipients. Possibly because of Illinois's generous earned-income disregard, which makes it easier for larger families to continue to receive assistance, families with three or more children are also significantly more likely to be substantially employed than are families with just one child. As expected, a higher county unemployment rate is associated with a significantly lower probability of being employed 30 or more hours per week.

Effects of Strategies to Address Employment Liabilities: Simulations

The model used to estimate the influence of employment liabilities can be used not only to examine the relative effect of each liability on employment status but also to simulate various strategies designed to increase work among TANF recipients. For example, the model can be used to examine how much the share of TANF recipients working 30 or more hours per week would increase if all child care problems were eliminated. The answer to this question depends on the proportion of recipients with a child care problem and the extent to which child care reduces the chance of working. The answer may also be influenced by the presence of other liabilities that may have independent effect on the likelihood of employment. In Table IV.6, we present the results of policy simulations that address one liability at a time. We then present simulations of strategies that address multiple liabilities, as in a policy or program that emphasizes development of human capital.

Under the current constellation of liabilities, about 28 percent of TANF case heads work 30 hours a week or more. Our simulation results suggest that no strategy that addresses just one specific liability would go far in increasing this rate. Eliminating the negative influence of limited work experience, possibly by placing recipients in transitional jobs or work experience programs, would increase the proportion of TANF recipients working 30 or more hours per week by 6 percentage points to 34 percent. Eliminating all child care problems would raise the proportion working by 4 percentage points to 32 percent.

Strategies that address multiple liabilities that may be related to one another would further increase the proportion of recipients working 30 or more hours per week. Still, these comprehensive strategies, even if successful, would raise the level of substantial employment to no more than two-fifths of the caseload. The comprehensive strategies that would go the furthest toward increasing work participation are those that address human capital liabilities and/or logistical challenges. A strategy that increases the level of work experience and eliminates the logistical challenges of child care and transportation would increase the proportion of the caseload working 30 or more hours per week by nearly 14 percentage points, to 41 percent. A strategy that eliminates all human capital liabilities (e.g., education and work experience) and addresses special learning needs (e.g., learning disabilities and language barriers) would increase the proportion to 36 percent. A strategy that eliminates all child care and transportation problems would raise the proportion of workers by about 6 percentage points. A strategy that focuses only on physical health and mental health problems and chemical dependence would raise the proportion of workers by only 3 percentage points. However, if these personal challenges contribute to the logistical and situational challenges faced by recipients, such a strategy could increase considerably the proportion of the caseload that is substantially employed.

The simulation results should be interpreted with caution. First, if the influence of unobserved variables (such as personal motivation) is reflected in observed variables (such as work experience), then the simulations overestimate the effects of a particular policy change, such as increasing work experience among TANF recipients. Second, because the results are based on cases that were on TANF at a point in time (and consequently may oversample long-term cases, as noted earlier), they do not capture the effects of strategies that are already successful at moving cases both into substantial employment and off of TANF.

Endnotes

1. The liabilities analyzed in this chapter differ slightly from those presented in Chapter III. For purposes of the multivariate analysis, the measure of work experience omits the study quarter, the fourth quarter of 2001. The liability is, therefore, defined as employed in less than four of the seven quarters preceding selection into the study. Three liabilities--perceived discrimination, a criminal conviction, and perceived problems within one's neighborhood--are excluded from the analysis presented in this chapter. We did not include convictions because, based on our initial analysis, arrests are the more important determinant of employment. Perceived discrimination was not included because it was not asked of recipients who were not working, and perceived problems in one's neighborhood were not included because many respondents did not respond to all the components of the question that were necessary in developing the summary measure.

2. For purposes of counting liabilities we grouped child care problems, pregnancy, and having a child under one year old in the household together as one.

3. This predicted probability is different than that for the model that includes the number of liabilities. The difference in the model specification results in a different set of coefficients used to produce the predicted probabilities.

Key Findings: Summary and Policy Relevance

In the six years since the passage of the Personal Responsibility and Work Opportunity Reconciliation Act of 1996, the dramatic decline in state welfare caseloads has drawn considerable attention from policymakers, program administrators, and researchers alike. Numerous studies have focused on understanding the characteristics and circumstances of families that have left TANF. Yet, many families are still on public assistance despite PRWORA's strong work requirements, its 60-month lifetime limit on the receipt of assistance, and the strong economy of the late 1990s. In this chapter, we summarize our key findings on the characteristics and circumstances of single-parent families currently on TANF in Illinois and discuss the relevance of the findings to TANF policy and administration.

Summary of Findings

What are the welfare and employment experiences of TANF recipients in Illinois?

Most single-parent TANF cases in Illinois are not long-term recipients of assistance. Nationally, close to half of all TANF cases have received assistance continuously for two or more years. But in Illinois, only 39 percent of TANF cases have continuously received assistance for that long. The median duration of the current welfare spell is 16 months. The relatively short time on welfare may be attributable to the state's particular combination of incentives and penalties that encourage work and self-sufficiency.

To promote work, Illinois provides a 67 percent earned-income disregard and stops the 60-month TANF clock for single-parent cases in which heads are working 30 or more hours per week. This means that a single-parent TANF case head with two children can earn up to $1,100 per month before she is ineligible for a cash grant. It also means that a case head who has received cash assistance for 36 months, for example, but has worked 30 hours per week for 20 of those months, would log not 36 but 16 months on her TANF benefits clock. As a result, most cases have no more than 24 elapsed months on their TANF clocks, and only 3 percent are at risk of reaching the 60-month lifetime limit on assistance within one year. In addition to these incentives to work, Illinois penalizes noncompliance with program requirements, including the work requirement. One-quarter of all single-parent TANF cases are under a sanction, and 9 percent of these cases are under a full-grant sanction.

Two out of every five TANF recipients are currently working for pay, but they do not work enough hours, earn sufficiently high wages, or remain in jobs long enough to achieve self-sufficiency. Compared with former TANF recipients across the nation, a smaller percentage of current TANF recipients in Illinois work full time, and their median rate of pay of $6.50 per hour is about 10 percent lower. About half of all recipients who held a job at any time worked in their most recent position for only five months or less. Only 6 percent of these jobs have the characteristics that are likely to lead to greater self-sufficiency in that they pay over $8.00 per hour, are not temporary or seasonal, involve daytime hours, and make paid leave (vacation and/or holidays) and health insurance available to qualified employees.

Notwithstanding the incentives for employment, the heads of many single-parent TANF cases in Illinois have limited attachment to the labor market. Three-fifths of them are not currently employed. One-fifth have not been employed during the past year, and three percent have never been employed.

What assets and liabilities do TANF recipients bring to the labor market?

The heads of single-parent TANF cases in Illinois have relatively weak educational backgrounds, but most bring other human capital assets to the labor market. Slightly more than half of these individuals have a high school diploma or a GED, compared to about three-fourths of TANF case heads in Michigan and Nebraska. However, about three in every four case heads in Illinois have made an effort during the past year to increase their human capital by participating in an employment-focused education or training program. About three-fourths of Illinois TANF case heads also have worked for pay during the past two years and are familiar with at least four common job tasks such as talking with customers in person or by telephone, doing arithmetic, or filling out forms. Some case heads have very substantial recent work experience: nearly half of them have been employed in at least four of the last eight calendar quarters.

Despite their assets, TANF recipients face a number of personal liabilities for employment, the most prevalent being poor physical and mental health. One-fifth of the heads of single-parent TANF cases in Illinois have a physical health problem, and one-quarter have a mental health problem. These rates are similar to those documented in studies of current and former TANF recipients in other states. Lower proportions of case heads have a history of multiple arrests (16 percent), have experienced severe domestic violence in the past year (13 percent), or are at risk for a learning disability (12 percent). And only a very small proportion is chemically dependent (3 percent) or has a language difficulty (2 percent).

Logistical and situational liabilities for employment are more prevalent than personal liabilities. The single most prevalent liability of this type is neighborhood problems. Over half (55 percent) of TANF recipients believe that their neighborhood is home to a serious problem related to crime, drugs, unemployment, or poor housing. One-fifth to one-third of recipients have each of the other logistical and situational liabilities measured in the study. These include an unstable housing situation characterized by multiple moves or an eviction in the past year. Despite the extensive public transit system in Cook County, where most Illinois TANF recipients live, it is not unusual for them to encounter transportation problems that interfere with their ability to work or participate in work-related activities. The situational liability with the lowest incidence is discrimination by a potential employer on the basis of race, gender, appearance, or welfare receipt. However, a full 20 percent of case heads who have ever worked for pay believe that a potential employer discriminated against them during the past year.

Family circumstances can also constitute logistical and situational liabilities for employment. About one-third of TANF case heads care for a family member or friend with a health or behavioral problem or a special need. Providing this care may limit the head's availability for work. Approximately the same proportion of heads is either pregnant or caring for an infant in her household, both of which may influence a parent's job performance and decisions about employment as well as an employer's decisions about hiring. Among single-parent case heads, one-third have had child-care problems during the past year that have interfered with their ability to participate in work or training.

What are the effects of the number and type of liabilities on employment?

Multiple liabilities for employment are extremely common among the heads of single-parent TANF cases in Illinois. Only 4 percent of case heads have none of the liabilities for employment measured in the study, and 12 percent have just one. On average, TANF case heads have 3.6 liabilities for employment, and those who are not substantially employed (not working 30 or more hours per week) are much more likely to have multiple liabilities than are those who are substantially employed. Among those not substantially employed, the presence of multiple human capital and multiple logistical and situational liabilities is more pronounced than the presence of multiple personal liabilities.⁽¹⁾

Findings from multivariate analyses indicate that few individual liabilities alone actually affect the likelihood that the head of a single-parent TANF case will be substantially employed when background characteristics and the presence of other liabilities are held constant. Rather, the presence of multiple liabilities decreases the probability that a case head will work 30 or more hours per week. Only 4 of the 16 individual liabilities examined in the study have a significant negative association with employment. Limited recent work experience, a physical health problem, multiple arrests, or a child care problem significantly reduce the likelihood of substantial employment. Consistent with studies of current and former TANF recipients, we found that as the number of liabilities increases, the probability of working decreases. TANF recipients without any liabilities have a 58 percent likelihood of working 30 or more hours per week. The probability drops to 35 percent for those with one liability, 33 percent for those with two or three liabilities, 23 percent for those with four to six liabilities, and to just 7 percent for those with seven or more liabilities.

Policy Relevance

Entry-level jobs held by TANF recipients who are attached to the labor market are unlikely to lead to self-sufficiency.

Illinois' efforts to promote employment among recipients have yielded some success; two out of every five heads of single-parent TANF cases in the state are working for pay. However, few of these individuals hold jobs with convenient hours, wages over $8.00 per hour, and fringe benefits. Recipients who do hold such jobs have longer terms of employment, on average, than recipients with other jobs. They are also more likely to believe that their jobs provide opportunities for advancement.

These findings suggest that increased efforts to improve the quality of the jobs secured by TANF recipients could improve job retention and advancement as well as place recipients on a more certain path to long-term self-sufficiency. This is a difficult task under even the best economic conditions.

Stopping the TANF clock can help promote work, but the criteria for doing so determines who benefits.

Illinois stops the 60-month TANF clock while recipients comply with program work requirements by working 30 or more hours per week or maintaining a 2.5 grade point average in a full-time postsecondary education program. Although this strategy has been advocated elsewhere by some researchers and policymakers, others believe that it might undermine the temporary nature of cash assistance as mandated by PRWORA. However, the proportion of long-term TANF recipients is lower in Illinois than it is nationwide, suggesting that stopping the clock can promote work without prolonging cash assistance.

In Illinois, the stop-the-clock policy rewards those who are meeting the full work requirement of 30 hours per week. Stopping the clock for compliance with broader program requirements--such as looking for work or participating in other work-related activities--is an option that could benefit those trying to build connections with the labor market and those at greatest risk of reaching the 60-month lifetime limit.

An increase in work participation rates will require innovative and integrated strategies.

In 2002, the federally mandated work participation rate was that 50 percent of the heads of single-parent TANF cases must work or participate in work-related activities for at least 30 hours per week. Today's policy debate on welfare reform centers on increasing the number of required weekly work hours, decreasing the types of activities that can be defined as "work," and increasing the proportion of families on the caseload that are working. Yet, even in Illinois, which has one of the nation's strongest work-incentive packages, only 30 percent of the heads of single-parent cases are working at least 30 hours per week.

The state's experience to date suggests that a narrowing of the definition of work and work-related activities would require states to adopt even more innovative strategies for moving recipients into work. However, the TANF caseload, at least in Illinois, is heterogeneous, and each case head brings a different set of liabilities to the labor market. Our evidence suggests that a strategy that focuses on just one or two liabilities would do little to raise the probability of substantial employment (30 or more hours per week) for the caseload as a whole. In addition, the policy simulations based on our multivariate analyses suggest that the most promising approaches are those that would address sets of multiple related liabilities. Our simulations suggest that, in Illinois, a strategy that would increase work experience while reducing the logistical challenges of child care and transportation would have the greatest impact on employment rates.

A strategy that focuses on the acquisition of work experience might include work experience or transitional job programs. Evidence on the effectiveness of work experience programs is mixed and suggests that the programs often do not meet the needs of individuals who face multiple liabilities for employment. Transitional job programs more closely mirror the working world by providing a paycheck while meeting the needs of hard-to-employ recipients through enhanced case management and job coaching. An advantage of both of these types of programs is that they can increase work participation rates among TANF recipients in the short term while giving them the work experience and skills development they need to find unsubsidized jobs in the long term. One disadvantage of transitional job programs is that they can be costly.

Future Research

In the coming months, additional studies of current TANF recipients in California, Colorado, Maryland, Missouri, South Carolina, and the District of Columbia will be released. These forthcoming studies, along with this study of TANF recipients in Illinois, are based on a common survey instrument. The data will therefore provide a unique opportunity to examine how the characteristics and employment assets and liabilities of current TANF recipients compare across the states.

In addition to this work, it would be useful to conduct a longitudinal study of new TANF entrants, who constituted a small share of our study population simply because of the study design and the dynamic nature of the TANF caseload. A longitudinal study of new TANF entrants would provide insight into the characteristics and needs of families as they come onto and continue to receive assistance. Ideally, such a study would include two surveys of household heads--one shortly after they begin receiving TANF and another several years later. A multivariate analysis of employment outcomes similar to that presented in Chapter IV of this report could identify the types of entrants who are at greatest risk for failing to achieve substantial employment. It could also identify the interventions that are most strongly associated with their success in the labor market. Targeting policy interventions to the new entrants most at-risk could reduce the proportion of TANF cases that reach time limits or become long-term recipients.

This study also suggests a need for a more extensive qualitative study of TANF recipients as the means to developing a deeper understanding of the factors that influence employment. While this study shows that current TANF recipients have many liabilities for employment, only a few exert a significant influence on a recipient's employment status. Research that delves further into recipients' experiences could identify not only the factors not captured in our survey that may influence the ability to find and maintain employment but also how multiple liabilities might interact to constrain the ability to work. Because the survey of TANF recipients in Illinois captured information on the most commonly cited liabilities to employment, it would be important for the suggested study to use innovative interviewing and case study techniques to identify the additional factors that might influence TANF recipients' employment status. For example, such an approach may be able to examine problem solving skills and functional capacity in order to assess the ease with which a person is able to carry out tasks of daily life.

This study was not designed to identify the effectiveness of various strategies for increasing employment among recipients deemed "hard to employ." However, obtaining such information should be part of the future research agenda on how to help more TANF recipients make the transition to employment. In the coming years, two studies funded by the U.S. Department of Health and Human Services will increase our knowledge about the effectiveness of various strategies to help TANF recipients find and maintain employment. The Employment Retention and Advancement Evaluation is examining the effectiveness of various strategies designed to help current and former TANF recipients stay employed and advance to better jobs. The Enhanced Services for the Hard-to-Employ Evaluation is examining the effectiveness of various strategies designed to help TANF recipients who face employment liabilities make the transition to employment.

Conclusion

This study has assessed the job readiness of the heads of single-parent families currently on TANF in Illinois by documenting the prevalence of specific labor market assets and liabilities and by analyzing their effects on employment. The study contributes to a small but growing body of research on current TANF recipients. The findings from this study and from other studies in progress should provide valuable information to policymakers and program administrators as they make welfare policy decisions and develop program strategies to improve employment outcomes for TANF recipients.

Endnote

1. For the purpose of analyzing effects on employment, we broadened the definition of liabilities to include the absence of human capital assets. So, for example, the absence of a high school diploma or GED is classified as a human capital liability.

References

Center on Budget and Policy Priorities. "Facts About the Earned Income Credit: A Tax Credit for People Who Work." Washington, DC: Center on Budget and Policy Priorities, 2001.

Danziger, Sandra, Mary Corcoran, Sheldon Danziger, Colleen Heflin, Ariel Kalil, Judith Levine, Daniel Rosen, Kristin Seefeldt, Kristine Siefert, Richard Tolman. "Barriers to the Employment of Welfare Recipients." Ann Arbor, MI: University of Michigan, Poverty Research and Training Center, February 2000.

Danziger, Sheldon. Comment on Sheila R. Zedlewski and Pamela Loprest, "TANF and the Most Disadvantaged Families." In The New World of Welfare, edited by Rebecca Balnk and Ron Haskins. Washington, DC: Brookings Institution Press, 2001.

Edin, Kathryn and Laura Lein. Making Ends Meet: How Single Mothers Survive Welfare and Low-Wage Work. New York: Russell Sage Foundation. 1997.

Illinois Department of Human Services. "TANF Policy Manual, Worker's Action Guide Section 25-03-05: Table of Monthly Allowances." Updated July 1, 2002.

______"TANF Policy Manual, Section 03-06-01: Months Counted in Illinois." Updated February 1, 2002.

______"TANF Policy Manual, Section 03-13-05: Sanction Levels." Updated January 25, 1999.

Kauff, Jacqueline, Fraker, Thomas, and Julita Milliner-Waddell. "Iowa Families That Left TANF: How Are They Faring Two Years Later?" Washington DC: Mathematica Policy Research, February 2002.

Lewis, Dan A., Kristen Shook Slack, Bong Joo Lee, Paul Kleppner, James Lewis, Stephanie Riger, and Robert Goerge. "Welfare Reform in Illinois: Is the moderate approach working?" Second annual report from the Illinois Families Study. Evanston, IL; The University Consortium on Welfare Reform, May 2002.

Loprest, Pamela. "How Are Families That Left Welfare Doing? A Comparison of Early and Recent Welfare Leavers." Washington, DC: Urban Institute, April 2001.

Loprest, Pamela and Sheila Zedlewski. "Current and Former Welfare Recipients: How Do They Differ?" Washington, DC: Urban Institute, November 1999.

Losby, Jan L., Jill R. Robinson, and John F. Else. "Long-Term Welfare Recipients' Barriers to Employment." Coralville, IA: Institute for Social and Economic Development, April 2002.

National Center for Health Statistics. "Early Release of Selected Estimates Based on Data From the January-June 2002 National Health Interview Survey." http://www.cdc.gov/nchs/about/major/nhis/released200212.htm. Released December 31, 2002.

Olson, Krista and LaDonna Pavetti. "Personal and Family Challenges to the Successful Transition from Welfare to Work." Washington, DC: Urban Institute, 1996.

Ponza, Michael, Alicia Meckstroth, and Jennifer Faerber, with Anne Bloomenthal, Bidisha Ghosh, Laura Kalb, Martha Kovac, and Michael Sinclair. "Employment Experiences and Challenges Among Urban and Rural Welfare Clients in Nebraska." Princeton, NJ: Mathematica Policy Research, August 2002.

Rangarajan, Anu and Amy Johnson. "Current and Former WFNJ Clients: How Are They and Their Children Faring 40 Months Later?" Washington DC: Mathematica Policy Research, January 2002.

Rangarajan, Anu, Peter Schochet and Dexter Chu. "Employment Experiences of Welfare Recipients Who Find Jobs: Is Targeting Possible?" Washington DC: Mathematica Policy Research, August 1998.

Richer, Elise, Savner, Steven and Mark Greenberg. "Frequently Asked Questions About Working Welfare Leavers." Washington, DC: Center for Law and Social Policy, November 2001.

Ross, Christine and Diane Paulsell. "Sustaining Employment Among Low-Income Parents: The Problems of Inflexible Jobs, Child Care, and Family Support." Washington DC: Mathematica Policy Research, December 1998a.

Ross, Christine and Diane Paulsell. "Sustaining Employment Among Low-Income Parents: The Role of Quality in Child Care." Washington DC: Mathematica Policy Research, December 1998b.

Strawn, Julie and Karin Martinson. "Steady Work and Better Jobs." New York, NY: Manpower Demonstration Research Corporation, June 2000.

Substance Abuse and Mental Health Services Administration. Results from the 2001 National Household Survey on Drug Abuse. "Prevalence and Treatment of Mental Health Problems." http://www.samsha.gov/oas/nhsda.htm. Updated September 4, 2002.

U.S. Census Bureau. Poverty Thresholds for 2001 by Size of Family and Number of Related Children Under 18 Years. Last Revised September 24, 2002.

Zedlewski, Sheila. "States' New TANF Policies: Is the Emphasis on Carrots or Sticks?" Policy and Practice, August 1998.

Zedlewski. Sheila and Donald Alderson. "Before and After Reform: How Have Families on Welfare Changed?" Washington, DC: Urban Institute, April 2001.

Appendix A: Survey and Data Weighting Methods

This appendix describes the methodology for the telephone survey of 416 TANF clients in Illinois and the procedures that were used to develop weights for the resultant data. Mathematica Policy Research (MPR) conducted the survey from November 2001 through February 2002.

Survey Methodology

In this section we present the methods that were used to design and conduct the client survey. We discuss the design of the survey sample, the survey instrument, data collection and processing, and the survey completion rates.

Sample Design

The sampling frame for this survey consisted of single-parent TANF cases in Illinois in November 2001. More specifically, the sampling frame consisted of TANF cases that, according to administrative records of the Illinois Department of Human Services (DHS):

1. Were classified as "single-parent"
2. Were authorized to receive a cash grant during the routine benefit issuance cycle for November 2001; however, 9 percent of the cases in the sampling frame received a $0 grant⁽¹⁾
3. Included the grantee as a case member, thus excluding "child-only" cases
4. Had a TANF status of "active" or "suspended" when the sampling frame was identified, thus excluding cases whose status had changed to "cancelled" after benefits were issued but before the sampling frame was identified⁽²⁾

These criteria were satisfied by 33,495 TANF cases. They constituted the sampling frame for the survey of families on TANF in Illinois.

We implemented a simple stratified sample design. There were just two strata, defined by whether a case was located in Cook County or "downstate" (all other counties). A key objective for this study by Illinois DHS was that the survey data support the description of the statewide TANF caseload, as opposed to supporting separate descriptions for Cook County and downstate. Consistent with that objective, the probability of selection of a case from the frame into the sample was designed to be uniform across the two strata. We selected 532 cases into the sample, of which 431 were located in Cook County and 101 were located downstate. We attempted to interview every case in the sample and succeeded in interviewing 416 (78 percent) of them.

Survey Instrument and Pretest

We developed the survey instrument in consultation with the Office of the Assistant Secretary for Planning and Evaluation (ASPE) in the U.S. Department of Health and Human Services under a separate task-order agreement. The instrument was designed for either paper and pencil administration or computer assisted telephone interviewing (CATI) and was designed to take 35 minutes. Several questions were taken from the Michigan Women's Employment Survey (WES, Wave 2) and MPR's Nebraska Client Barriers Survey. Specific scales covering the topics of learning disabilities, mental health and depression, alcohol and drug abuse, and domestic violence were taken from Washington State's Learning Disabilities screener, the Composite International Diagnostic Interview (CIDI), and the Conflict Tactics Scale, respectively. In addition, we developed a series of questions to assess job readiness skills in collaboration with researchers at the University of Colorado.

We drafted the survey instrument between August and October of 2001 and pretested it in early November. The pretest interviews were conducted with the heads of ten TANF cases in Illinois who had received a cash benefit in October. Those interviews averaged 40 minutes in length. The goals of the pretest were to: (1) identify ways to improve the administration procedures, (2) measure the length of the survey, (3) test the flow and sequencing of questions, (4) clarify question wording for the interviewees, and (5) clarify instructions for the interviewers. Based on information obtained from the pretests through debriefings with the interviewers and through the monitoring of interviews by supervisory staff, we made minor modifications to the newly developed job readiness questions.

Data Collection

Survey data collection began on November 19, 2001 and continued through March 3, 2002--a field period of 16 weeks. At the outset, our target interview completion rate was 75 percent and we exceeded that goal by three percentage points. The interviews averaged 42 minutes in length, all interviews were conducted by telephone using a hard-copy survey instrument, and no in-person follow-up was employed on this study.

Immediately prior to the commencement of interviewing, we held an eight-hour interviewer training session spread over two days, November 14^th and 15^th 2001, led by the survey director. In attendance were the survey director's assistant, the telephone supervisor, the locating supervisor, the telephone interviewers, and the quality control monitors.

We contacted sample members by mail and by telephone to participate in the survey. DHS administrative records were the source of the initial addresses and telephone numbers. We mailed advance letters to all sample members prior to the first telephone contact. The letters introduced the study, identified the study sponsor and MPR, and invited the sample members to call our toll-free telephone number and participate in the survey at their earliest convenience. The letter explained that participation was voluntary and that the identities and responses of all participants would be kept confidential. It offered sample members $35 if they would call and complete the survey within two weeks of receiving the letter. Otherwise they would receive $20 for completing the survey after that.

Our next step was to call the sample members. We timed the first telephone calls to begin after sample members received the advance letter. This resulted in a number of completed interviews and also helped us to identify the sample members with either no phone number or for whom the number from DHS records was incorrect and would require additional searching efforts. In addition, the advance letters served to identify cases that required additional searching. Some of the advance letters were returned to us if the addresses that we had obtained from DHS records were out of date. Advance letters that were returned with forwarding addresses marked on the envelopes were remailed to the new addresses. Advance letters that were returned without a forwarding address required additional searching.

Our principal searching effort consisted of running identifying information (name, date of birth, last known address and phone number) for sample members through a database owned by Lexis-Nexis, a personal database search company. That generated some new addresses and phone numbers to which we then sent letters or called. We also obtained updated contact information for some sample members through a search of DHS records that we conducted approximately halfway through the field period.

Throughout the 16-week field period we continued mailing letters and postcards to sample members with whom we had not completed interviews. The format and content of the letters and postcards changed every few weeks, as well as the size and appearance of the envelope and method of mailing (first-class mail versus priority mail). This was done to spark the sample members' interest in reading the items sent. However, the most salient information remained the same in each version of the letter or postcard.

A small number of sample members initially refused to participate in the survey. For these cases, we waited approximately one month from the telephone contact in which the refusal occurred and then mailed them a specially crafted letter. The letter reiterated the importance of the study and of their participation. It again invited them to call our toll-free telephone number to participate and reminded them that we would pay them $35 if they completed the interview. We waited until we were confident that a sample member had received the letter, and then a specially trained "refusal-conversion" interviewer called to attempt to gain his or her cooperation. If the result of these steps was a second refusal, we ceased attempts to contact the sample member until the end of the field period. At that time, we sent out a final mailing to all sample members who had not completed an interview to alert them that the study was ending and to offer an increased incentive of $50 for participating.

Data Preparation

As interviews were completed, they were reviewed for completeness, consistency, and accuracy. Based on guidelines developed by MPR, interviewers called back respondents to obtain information or to clarify contradictory answers. Reviewers back-coded "other-specify" responses to prelisted choices where appropriate, or assigned new codes if responses were common enough to warrant the additions. They also assigned numeric codes to open-ended questions and to industry and occupation responses using standard coding manuals.⁽³⁾

After the completed interviews had been reviewed and coded, they were sent through the data entry process. A customized data entry program restricted entries to values that were consistent with the skip patterns in the survey instrument and were within allowable ranges. The data were entered two times by different people to verify that they had been entered correctly. After data entry was verified, frequencies for all data elements were produced and reviewed for inconsistencies and out-of-range values. Questionable data were reconciled based on review of the source data and, in some cases, on callbacks to sample members. Following this process, a final data file was produced and turned over to MPR's Research Division for further processing and analysis.

Sample Disposition and Survey Response Rate

We completed interviews with the TANF grantees in 416 of the 532 sampled cases, for an overall survey response rate of 78 percent. Of the completed interviews, 335 were with TANF clients from Cook County and 81 were with clients from downstate. Only two percent of the sample members refused to participate in the survey and only one sample member failed to complete an interview after starting. Table A.1 shows the final survey disposition of all cases in the sample by Cook County, downstate, and combined.

Two factors accounted for almost 90 percent of nonresponse to this survey. Nearly half of the nonresponse occurred because sample members could not be located (10.5 percent of all sample members). These were sample members whose addresses and phone numbers, as provided by Illinois DHS, were incorrect and we were unable to locate them by other means, such as searching through various databases for contact information and using the forwarding addresses provided by the U.S. Postal Service on letters returned to us after we had mailed them to sample members. Forty percent of nonresponse (8.6 percent of all sample members) occurred because the sample members were never available to participate in the survey. We believe that our contact information for these sample members was good, but they did not call us in response to our letters, did not answer the telephone in response to our calls, and were not available to take our calls when another household member answered the telephone.

A language barrier--lack of proficiency with English or Spanish--resulted in only one case of nonresponse to the survey (0.2 percent of all sample members). There were very few Spanish-only members of the survey sample and we chose to interview them in their native language so they could be included in the study. We conducted three interviews in Spanish, all with the same interviewer, who is a native Spanish speaker. That interviewer participated in the initial interviewer training session and completed roughly 40 interviews in English prior to conducting interviews in Spanish. She translated the instrument on her own and used the same translation for all three interviews. A native Spanish speaker monitored these interviews.

Comparison of Survey Respondents and Nonrespondents

In a survey that achieves less than a 100 percent response rate there is a risk that respondents may be systematically different from nonrespondents. Such differences would imply that the respondents should not be regarded as a random subsample of the full survey sample. If the survey data are not adjusted to mitigate these differences, such as by weighting the survey respondents, it may be inappropriate to draw inferences about the sampling frame from statistics computed on the basis of the survey data.

To assess whether the sample members who responded to the survey are different from those who did not respond, we regressed each of 12 characteristics of the case or case head (i.e., the TANF grantee) on a 0/1 variable that indicates the sample member's response status: 1 for respondents and 0 for nonrespondents.⁽⁴⁾ The regression coefficient on the indicator variable is the difference between the two groups in a characteristic. We conducted a t-test to determine whether the estimate of the coefficient is significantly different from zero for each of the 12 characteristics. The results of that analysis are presented in Table A.2.

Table A.2 shows significant differences between survey respondents and nonrespondents in only three of the twelve selected characteristics. Cases with grantees who were 28 years old or less were more likely to participate in the survey than were cases with older grantees. Consistent with that difference, respondent cases tended to have fewer children and to have been on TANF for fewer consecutive months than nonrespondent cases.

To reduce the bias that systematic differences between survey respondents and nonrespondents might introduce to inferences based on the survey data, we developed survey weights that directly correct for the age difference. The development of the weights is described in the next section. We expected the weights to indirectly mitigate differences in age-related characteristics, such as the number of children on the case and the duration of the current TANF spell. Those expectations were realized, as discussed in the final section of this appendix.

Data Weighting Procedure

We computed weights for the survey respondents using three factors, as summarized in Table A.3 and discussed below. The product of these three factors for a given survey respondent is the final sampling weight for that case.

Component 1: Sample Weight

The sample weight for each case in the survey sample accounts for the number of cases it represents in the sampling frame, based on the sample selection procedure. As indicated earlier, we designed a stratified sample in which the theoretical sampling rate was constant across the two strata, Cook County and downstate. Because we had to select whole cases, we actually sampled Cook County cases at a very slightly higher rate than downstate cases. The sample weight is the inverse of the actual probability of selection. For sampled cases in Cook County and downstate, respectively, its value is 62.93 and 63.09.

Component 2: Survey Response Adjustment

This component compensates for the reduction in the sample due to cases that could not be interviewed for the reasons given in Table A.1. It is the inverse of the survey response rate. Because the response rate was slightly lower in Cook County than downstate, the value of this component is slightly higher in Cook County (1.28) than downstate (1.25).

Component 3: Post-Stratification Adjustment

This component of the survey weights is based on a post-stratification of the survey respondents into five cells as shown in Table A.4. This factor causes the sum of the weighted survey respondents to equal the number of cases in the sampling frame in each cell. The five cells were defined by three variables that were extracted from the Illinois DHS administrative data system in November 2001: residence in Cook County or downstate, the grantee's age less than or equal to 28 years or greater than 28 years, and a zero or positive TANF benefit amount. While in principle, these variables could be used to define eight cells, the infrequency of zero-benefit cases led us to consolidate them in a single cell. The values of the post-stratification adjustment factor range from 0.86 to 1.25. In general, the larger values are for cells containing cases with older grantees, which had a lower survey response rate than cases with younger grantees.

Final Survey Weights

The final weights for the survey respondents are the product of the three components discussed above. There is a unique weight for each of six cells, ranging in value from 69.17 to 98.24.⁽⁵⁾

Assessment of the Weighted Survey Respondents

We assessed the representativeness of the weighted sample of survey respondents by comparing them with the entire 33,495 cases in the sampling frame. The comparisons were based on the same 12 characteristics that we used to test for differences between survey respondents and nonrespondents. Those include demographic characteristics of grantees and cases as of November 2001, the TANF benefit amount in November 2001, and employment and earnings in 2000 and 2001. Characteristics that were expressed as percentages in the comparison of survey respondents and nonrespondents are expressed as case counts in this analysis. Thus, we are comparing the weighted count of survey respondents that possess the selected characteristic with the count of cases in the sampling frame that possess the characteristic. The results of the tests are presented in Table A.5.

Table A.5 shows a high degree of correspondence between the weighted survey respondents and all of the cases in the sampling frame. For ten of the twelve characteristics considered the weighted count of survey respondents differs from the count of all cases in the sampling frame by 2 percent or less. Most notably, the difference with respect to the grantee characteristic, "age 28 or younger," is just one percent. Recall that this is the characteristic on which survey respondents and nonrespondents differ most sharply. The survey weights virtually eliminate the effect of nonrandomness in survey response along this dimension.

The survey weights mitigate, but fall short of eliminating, the effects of nonrandomness in survey response with respect to two characteristics of TANF cases: the number of children per case and the duration of the current spell on TANF. For both of these characteristics the error rate in the sample of weighted respondents is 5 percent relative to all cases in the sampling frame. These error rates, while not trivial, are less than half of the relative difference in these characteristics between survey respondents and nonrespondents.

To summarize, the weighted survey respondents resemble very closely the cases in the sampling frame. This correspondence is a consequence of a high survey response rate, the general absence of large systematic differences between survey respondents and nonrespondents, and the survey weights. Consequently, we can be confident in drawing inferences about the sampling frame from statistics computed on the basis of the survey data.

Endnotes

1. The routine TANF benefit issuance cycle for November 2001 extended from October 19 to November 8. The sampling frame was identified upon the completion of benefit issuance on November 8. Four factors accounted for 95 percent of the zero benefit cases: recoupment of prior overpayments, failure to cooperate with eligibility determination, participation in Illinois' Work First program, and sanctioning.

2. A case whose November TANF benefit was processed prior to November 8, 2001, may have closed by the time the sampling frame was identified following completion of routine benefit processing on November 8. We excluded cases such as this (recent TANF leavers) from the sampling frame in order to maximize the proportion of survey respondents that were current TANF recipients when interviewed.

3. For coding industry responses we used the 1987 Standard Industrial Classification Manual. For coding occupation responses we used the 2000 Standard Occupational Classification Manual.

4. The characteristics were obtained from TANF administrative records for November 2001 maintained by the Illinois DHS and from Unemployment Insurance earnings records for the years 2000 and 2001 maintained by the Illinois Department of Employment Security.

5. The six cells and their associated survey weights are: 1) zero TANF benefit, Cook County, 95.96; 2) zero TANF benefit, downstate, 93.48; 3) positive TANF benefit, Cook County, less than or equal to age 28, 69.17; 4) positive TANF benefit, Cook County, greater than age 28, 93.60; 5) positive TANF benefit, downstate, less than or equal to age 28, 70.38; 6) positive TANF benefit, downstate greater than age 28, 98.24.

Appendix B: Measures of Employment Assets and Liabilities

We used data collected in the 2001-02 survey of Illinois TANF cases, Unemployment Insurance earnings records, and administrative data from the Illinois Criminal Justice Information Authority to create 3 measures of assets and 13 measures of liabilities that TANF case heads bring to employment that are discussed throughout this report. These measures are defined as follows:

Assets

1. High school diploma, GED, or more: Completed high school, its equivalent, or education beyond the high school level.

2. Substantial recent work experience. Positive Unemployment Insurance earnings in at least four of the seven quarters immediately preceding the quarter in which the study population and survey sample were selected. The seven quarters examined were all four quarters in 2000 and the first three quarters of 2001.

3. Performed at least four common job tasks. Has performed at least four of the following common job tasks on a daily or weekly basis, (1) talk with customers face-to-face, (2) talk with customers over the phone, (3) read instructions or reports, (4) write letters or memos, (5) work with a computer, such as word processing or data entry, (6) work with another electronic machine such as a cash register, bar code scanner, or calculator, (7) do arithmetic, including making change, (8) fill out forms, and (9) keep a close watch over gauges, dials, or instruments of any kind. The questions and scoring methods for this measure were adopted from the Women's Employment Study of the Poverty Research and Training Center, University of Michigan.

Liabilities

1. Physical health problem. Self-reported fair or poor general health and a physical functioning score in the lowest quartile based on national norms adjusted for age and gender. Physical functioning was determined following the methodology of the Physical Functioning Scale of the SF-36 Health Survey that asks about ease in performing vigorous physical activities such as running or lifting heavy objects, moderate physical activities such as moving a table or pushing a vacuum cleaner, and daily physical activities such as carrying groceries, walking, and climbing stairs (see Ware et. al 2000).

2. Mental health problem. Experienced psychological distress in the past 30 days and/or probable major depression in the past year. Psychological distress was measured using the K6 Psychological Distress Symptom Scale that asks the frequency of feelings such as depression, hopelessness, restlessness, worthlessness, and nervousness. Individuals who scored 13 or more points on the K6 scale, which ranges from 0 to 24, were classified as experiencing distress. This validated scale has been used in the 2002 National Health Interview Survey and the 2001 National Household Survey on Drug Abuse (see National Center for Health Statistics 2002; Substance Abuse and Mental Health Services Administration 2002 for scoring instructions and estimates). The probability of major depression was determined following the methodology of the Composite International Diagnostic Interview Short Form (CIDI-SF). Under this methodology, individuals with three or more of seven symptoms of major depression were classified as being at probable risk of major depression (see Nelson et. al 1998). Individuals who volunteered that they were on medication or anti-depressants also were classified as being at probable risk of major depression.

3. Multiple arrests. Arrested on two or more occasions for any felony or misdemeanor charge from November 1996 through September 2002 based on administrative data from the Illinois Criminal Justice Information Authority.

4. Severe physical domestic violence in past year. Experienced severe physical violence--hitting, beating, choking, using or threatening use of a weapon, or forcing sexual activity--from a domestic partner in the past year. This measure is based on a modified version of the Conflict Tactics Scale used in the Women's Employment Study of the Poverty Research and Training Center, University of Michigan.

5. Chemical dependence. Assessed as having probable alcohol dependence and/or probable drug dependence. The probability of having alcohol or drug dependence was determined following the methodology of the Composite International Diagnostic Interview Short Form (CIDI-SF). Under this methodology, individuals with three or more of seven symptoms of dependence were classified as being at probable risk of dependence (see Nelson et. al 1998).

6. Signs of a learning disability. A total score of 12 or more out of a possible 30 points on the Washington State Learning Disabilities Screener.

7. Difficulty with English: Self-reported difficulty speaking, reading, or writing English because it is not her native language.

8. Child or other family member or friend with a health problem or special need. Self-report on having a child with health, behavioral, or other special needs and/or caring for an elderly, disabled, or sick family member or friend.

9. Child under one year old. Self-report on presence of a child under the age of one in the household.

10. Pregnant. Self-report on pregnancy.

11. Child care problem. Self-report on having a child care problem that inhibits ability to take a job, to keep a job, or attend education or training activities. This summary measure was developed from a direct question about child care problems asked of case heads with children under the age of 15 and from two additional questions in which respondents could volunteer that child care was a reason for leaving her most recent job or for never having worked for pay.

12. Transportation problem. Self-report on having a transportation problem that inhibits ability to take a job, keep a job, or attend education or training activities.

13. Unstable housing. Moved two or more times and/or was evicted in the past year.

References

National Center for Health Statistics. "Early Release of Selected Estimates Based on Data From the January-June 2002 National Health Interview Survey." http://www.cdc.gov/nchs/about/major/nhis/released200212.htm. Released December 31, 2002.

Nelson, C.B., Kessler, R.C., Mroczek, D. "Scoring the World Health Organization Composite International Diagnostic Interview Short Form." http://www.who.int/msa/cidi.

Substance Abuse and Mental Health Services Administration. Results from the 2001 National Household Survey on Drug Abuse. "Prevalence and Treatment of Mental Health Problems." http://www.samhsa.gov/oas/nhsda.htm. Updated September 4, 2002.

Substance Abuse and Mental Health Services Administration. Results from the 2001 National Household Survey on Drug Abuse. "Substance Dependence, Abuse, and Treatment.." http://www.samhsa.gov/oas/nhsda.htm. Updated September 4, 2002.

Ware, J.E., Snow, K.K., Kosinski, M. SF-36 Health Survey: Manual and Interpretation Guide. Lincoln, RI: QualityMetric Incorporated, 1993, 2000.

Appendix C: Detailed Administrative Data Tables

Table C.1 Demographic Characteristics of the Heads of Single-Parent TANF Cases in Illinois

Table C.1
Demographic Characteristics of the Heads of Single-Parent TANF Cases in Illinois

Measure	Percentage, Unless Indicated Otherwise
Gender
Female	98
Male	2
Age in Years
Less than 20	8
20 to 24	27
25 to 29	21
30 to 34	17
35 to 39	13
40 to 49	12
50 or more	2
Median age	28.5 years
Ethnicity/Race
Non-Hispanic, white	12
Non-Hispanic, African American	82
Non-Hispanic, other races	1
Hispanic, any race	6
Marital Status
Never married	84
Married, spouse present	4
Married, spouse absent but not legally separated	6
Legally separated, divorced, or widowed	6
Institutionalized	1
Education
Less than high school diploma/GED	49
High school diploma/GED	40
More than high school diploma/GED	11
Number of TANF Cases	33,495
Source: Administrative data on the TANF caseload maintained by the Illinois Department of Human Services. Population: TANF cases in Illinois that: (1) were eligible for a cash grant in November 2001, (2) were classified by DHS as "single-parent," and (3) included the grantee (i.e., the person to whom the benefit was issued) as a member of the case (thus excluding "child-only" cases). Some of the cases (9 percent) in the study population did not receive a positive cash grant despite being classified as "eligible" for a cash grant (see Table C.4 for reasons).

Table C.2 Number and Age of Children on Single-Parent TANF Cases in Illinois

Table C.2
Number and Age of Children on Single-Parent TANF Cases in Illinois

Measure	Percentage, Unless Indicated Otherwise
Number of Children on Case
0a	2
1	29
2	28
3	20
4 or more	21
Median number of children	2 children
Age of Youngest Child on Case
Not applicable (no child on case)a	2
Less than 1 year	27
1 to 5 years	42
6 to 14 years	26
15 years or older	3
Median age of youngest child	2.7 years
Age of Oldest Child on Case
Not applicable (no child on case)a	2
Less than 1 year	8
1 to 5 years	28
6 to 14 years	45
15 to 17 years	14
18 years or older	2
Median age of oldest child	8.6 years
Number of TANF Cases	33,495
Source: Administrative data on the TANF caseload maintained by the Illinois Department of Human Services. Population: TANF cases in Illinois that: (1) were eligible for a cash grant in November 2001, (2) were classified by DHS as "single-parent," and (3) included the grantee (i.e., the person to whom the benefit was issued) as a member of the case (thus excluding "child-only" cases). Some of the cases (9 percent) in the study population did not receive a positive cash grant despite being classified as "eligible" for a cash grant (see Table C.4 for reasons). a A family in which all of the minor children receive SSI may be eligible for TANF. For such a family, the TANF case would consist of only the adult member(s), which for this study's population would be the single parent.

Table C.3 Characteristics of the Communities of Single-Parent TANF Cases in Illinois

Table C.3
Characteristics of the Communities of Single-Parent TANF Cases in Illinois

Measure	Percentage, Unless Indicated Otherwise
Location
Cook County	81
Downstate (all other counties)	19
County Unemployment Rate for 2001
2 to 3.9 percent	2
4 to 5.9 percent	90
6 to 7.9 percent	7
8 to 9.9 percent	1
Median unemployment rate	5.9
Percentage of ZIP Code Population That Is Non-Hispanic, White
Less than 10 percent	47
10 to 19.9 percent	22
20 to 79.9 percent	22
80 to 89.9 percent	4
90 percent or more	5
Median percentage white	10.3
Percentage of ZIP Code Pop. That Is Non-Hispanic, African-American
Less than 10 percent	13
10 to 19.9 percent	9
20 to 79.9 percent	32
80 to 89.9 percent	10
90 percent or more	36
Median percentage African-American	70.6
Percentage of ZIP Code Population That Is Hispanic, Any Race
Less than 10 percent	66
10 to 49.9 percent	26
50 percent or more	8
Median percentage Hispanic	3.1
Number of TANF Cases	33,495
Sources: Data on the TANF caseload from the Illinois Department of Human Services; unemployment data from the Bureau of Labor Statistics, U.S. Department of Labor; data on race and ethnicity for 5-digit ZIP codes from the 2000 Census, Bureau of the Census, U.S. Department of Commerce. Population: TANF cases in Illinois that: (1) were eligible for a cash grant in November 2001, (2) were classified by DHS as "single-parent," and (3) included the grantee (i.e., the person to whom the benefit was issued) as a member of the case (thus excluding "child-only" cases). Some of the cases (9 percent) in the study population did not receive a positive cash grant despite being classified as "eligible" for a cash grant (see Table C.4 for reasons).

Table C.4 TANF and Food Stamp Benefit Amounts Received by Single-Parent TANF Cases in Illinois

Table C.4
TANF and Food Stamp Benefit Amounts Received by Single-Parent TANF Cases In Illinois

Measure	Percentage Unless Indicated Otherwise
TANF Benefit Amount in November 2001
$0	9
$1 to $99	10
$100 to $199	16
$200 to $299	36
$300 to $399	18
$400 to $499	9
$500 or more	2
Median TANF benefit for all cases	$278
Median TANF benefit for cases with a positive benefit	$278
If $0 TANF Benefit in November 2001, Reason
Recoupment of prior overpayments	8
Failed to cooperate w/ elig. determination for cash assist.	34
In Work First program	26
Sanction	28
Other	5
Food Stamp Benefit Amount in November 2001
$0	12
$1 to $99	1
$100 to $199	8
$200 to $299	30
$300 to $399	24
$400 to $499	15
$500 to $599	6
$600 or more	4
Median Food Stamp benefit for all cases	$292
Median Food Stamp benefit for cases with a positive benefit	$320
Number of TANF Cases	33,495
Source: Administrative data on the TANF caseload maintained by the Illinois Department of Human Services. Population: TANF cases in Illinois that: (1) were eligible for a cash grant in November 2001, (2) were classified by DHS as "single-parent," and (3) included the grantee (i.e., the person to whom the benefit was issued) as a member of the case (thus excluding "child-only" cases). Some of the cases (9 percent) in the study population did not receive a positive cash grant despite being classified as "eligible" for a cash grant for reasons given in this table.

Table C.5 Programmatic Status of Single-Parent TANF Cases in Illinois

Table C.5
Programmatic Status of Single-Parent TANF Cases in Illinois

Measure	Percentage Unless Indicated Otherwise
Current Status of 60-month TANF "Clock"
Running	74
Stopped	26
Elapsed Time on 60-Month TANF "Clock"
0 to 12 months	32
13 to 24 months	26
25 to 36 months	23
37 to 48 months	16
49 to 60 months	3
Median elapsed time on TANF "clock"	20 months
TANF Sanctiona
Not sanctioned	74
Sanctioned for non-participation in required activity	23
Sanctioned for non-cooperation w/ child support enforcement	3
Number of TANF Cases	33,495
Source: Administrative data on the TANF caseload maintained by the Illinois Department of Human Services. Population: TANF cases in Illinois that: (1) were eligible for a cash grant in November 2001, (2) were classified by DHS as "single-parent," and (3) included the grantee (i.e., the person to whom the benefit was issued) as a member of the case (thus excluding "child-only" cases). Some of the cases (9 percent) in the study population did not receive a positive cash grant despite being classified as "eligible" for a cash grant (see Table C.4 for reasons). a A sanction entails the loss of either the full cash grant or one-half of the grant, depending on the sanction level.

Table C.6 Duration and Consistency of TANF Receipt by Single-Parent TANF Cases in Illinois

Table C.6
Duration and Consistency of TANF Receipt by Single-Parent TANF Cases in Illinois

Measure	Percentage, Unless Indicated Otherwise
Duration of Current TANF Spell
1 to 6 months	26
7 to 12 months	16
13 to 18 months	11
19 to 24 months	7
25 months or more	39
Median duration of current TANF spell	16 months
Percentage of Last 25 Months Received TANF
1 to 24.9 percent	16
25 to 49.9 percent	14
50 to 74.9 percent	13
75 to 99.9 percent	18
100 percent	39
Median percentage of last 25 months received TANF	88 percent
Number of TANF Cases	33,495
Source: Administrative data on the TANF caseload maintained by the Illinois Department of Human Services. Population: TANF cases in Illinois that: (1) were eligible for a cash grant in November 2001, (2) were classified by DHS as "single-parent," and (3) included the grantee (i.e., the person to whom the benefit was issued) as a member of the case (thus excluding "child-only" cases). Some of the cases (9 percent) in the study population did not receive a positive cash grant despite being classified as "eligible" for a cash grant (see Table C.4 for reasons).

Table C.7 Past Employment and Earnings by the Heads of Single-Parent TANF Cases in Illinois

Table C.7
Past Employment and Earnings by the Heads of Single-Parent TANF Cases in Illinois

Measure	Percentage, Unless Indicated Otherwise
UI-Covered Employment and Earnings in 2000
Employed in at Least One Quarter	66
Employed in All Four Quarters	24
Earnings Over Entire Year
$0 (not employed in 2000)	34
$1 to $999	16
$1,000 to $4,999	26
$5,000 to $9,999	15
$10,000 to $19,999	8
$20,000 or more	1
Median earnings for all case heads	$1,001
Median earnings for case heads employed at least 1 qtr.	$3,164
UI-Covered Employment and Earnings in 2001
Employed in at Least One Quarter	61
Employed in the Fourth Quartera	40
Employed in All Four Quarters	20
Earnings Over Entire Year
$0 (not employed in 2001)	39
$1 to $999	16
$1,000 to $4,999	24
$5,000 to $9,999	13
$10,000 to $19,999	7
$20,000 or more	1
Median earnings for all case heads	$608
Median earnings for case heads employed at least 1 qtr.	$2,913
UI-Covered Employment and Earnings in 2000-2001
Employed in at Least One Quarter	77
Employed in At Least Four Quarters	45
Employed in All Eight Quarters	12
Annualized Earnings Over the Two Years
$0 (not employed in 2001-2002)	23
$1 to $999	23
$1,000 to $4,999	32
$5,000 to $9,999	15
$10,000 to $19,999	7
$20,000 or more	1
Median earnings for all case heads	$1,291
Median earnings for case heads employed at least 1 qtr.	$2,424
Number of TANF Cases	33,477b
Source: Unemployment Insurance earnings records maintained by the Illinois Department of Employment Security. Population: TANF cases in Illinois that: (1) were eligible for a cash grant in November 2001, (2) were classified by DHS as "single-parent," and (3) included the grantee (i.e., the person to whom the benefit was issued) as a member of the case (thus excluding "child-only" cases). Some of the cases (9 percent) in the study population did not receive a positive cash grant despite being classified as "eligible" for a cash grant (see Table C.4 for reasons). a The fourth quarter of 2001 includes the month (November 2001) when TANF participants were selected into this study. b Missing Social Security numbers precluded a search for UI earnings records for the heads of 18 cases in the study's population.

Appendix D: Detailed Survey Data Tables

Table D.1 Employment Experiences of TANF Case Heads (Percentages, Unless Stated Otherwise)

Table D.1
Employment Experiences of TANF Case Heads
(Percentages, Unless Stated Otherwise)

	All Cases
Current Employment Status
Employed	39
Not employed; worked for pay during the past year	35
Not employed; worked for pay more than a year ago	22
Not employed; never worked for pay	3
Number of Months Worked for Pay During the Past Year
0	26
1 to 3	15
4 to 6	25
7 to 9	12
10 to 11	5
12	17
Number of Months Worked If Employed in Past Year
Average	6.9
Median	6.0
Number of Jobs Held During the Past Year
0	26
1	44
2	24
3 or more	6
Number of Jobs Held If Employed in Past Year
Average	1.5
Median	1.0
Proportion of Time Employed Since Age 18
About 75 percent or more	54
About 50 percent	22
About 25 percent or less	21
Not at all	3
Sample Size	416
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between employed and not employed case heads.

Table D.2 Characteristics of Current or Most Recent Job Held by TANF Case Headsa (Percentages, Unless Stated Otherwise)

Table D.2
Characteristics of Current or Most Recent Job Held by TANF Case Heads^a
(Percentages, Unless Stated Otherwise)

	Currently Employed	Previously Employed	Ever Employed
Length of Employment on Job
Average number of months	14.3	10.2**	11.9
Median number of months	6.0	5.0	5.0
Hours Worked Per Week
Less than 20	9	8	8
20 to 34	36	30	33
35 or more	55	61	59
Average hours worked per week	32.3	34.9**	34.2
Median hours worked per week	35.0	40.0	35.0
Temporary or Seasonal Job	22	32**	28
Shift or Time of Day Worked
Regular day time shift	54	57	56
Morning or afternoon shift	11	9	9
Evening or night shift	20	24	22
Irregular, split, or rotating shift	14	9	11
Other	2	2	2
Industry		***
Manufacturing	3	9	7
Retail	27	31	29
Transit/transportation	3	2	2
Personal servicesb	14	7	9
Business services/utilities	9	15	13
Recreation/amusement	3	2	2
Health services	20	10	14
Social/educ./other non-profit or public services	18	11	14
Hotels and other lodging services	3	4	3
Other	2	10	7
Occupation
Administrative support/clerical	16	16	16
Sales	14	19	17
Health services	15	9	12
Food services	15	13	14
Grounds maintenance/cleaning services	10	10	10
Personal services	11	9	10
Other services	9	7	8
Technical	1	2	2
Production/manufacturing	4	5	4
Other	5	9	8
Sample Size	157	244	401
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between currently and previously employed case heads. */**/*** Difference between cases with a currently/previously employed head is statistically significant at the .10/.05/.01 level. a Statistics in this table are on the characteristics of the current or most recent jobs held by case heads who ever worked for pay. b Personal services include laundry and cleaning services, beauty shops, and other services performed within a private household.

Table D.3 Compensation on Current or Most Recent Job Held by TANF Case Heada (Percentages, Unless Stated Otherwise)

Table D.3
Compensation on Current or Most Recent Job Held by TANF Case Head^a
(Percentages, Unless Stated Otherwise)

	Currently Employed	Previously Employed	Ever Employed
Hourly Wageb
Less than $5.15	21	20	20
$5.15 to 6.00	26	24	25
$6.01 to 7.00	24	19	21
$7.01 to 8.00	13	13	13
$8.01 to 9.00	7	10	9
$9.01 to 10.00	5	7	6
More than $10.00	4	8	6
Average hourly wage	$6.37	$7.64**	$7.12
Median hourly wage	$6.31	$6.50	$6.50
Fringe Benefits Available
Paid sick leave	32	31	31
Paid vacation	43	37	40
Paid holidays	46	38	41
Health insurance	34	34	34
Retirement plan	25	20	22
Opportunity for Advancement (Self-assessment)
Great deal	16	16	16
Some	28	25	26
A little	20	25	23
None	36	34	34
Sample Size	157	244	401
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between currently and previously employed case heads. */**/*** Difference between cases with a currently/previously employed head is statistically significant at the .10/.05/.01 level. a Statistics in this table are on the characteristics of the current or most recent jobs held by case heads who ever worked for pay. b This estimate includes both case heads who are paid on an hourly basis and those who are paid a salary where the hourly wage was calculated.

Table D.4 Principal Reasons for Not Working and for Leaving Most Recent Job (Percentages)

Table D.4
Principal Reasons for Not Working and for Leaving Most Recent Job^a
(Percentages)

	Cases w/ Heads Not Currently Employed
Principal Reason Currently Not Working For Pay
Physical, mental health, or substance abuse problem	14
Pregnancy or newborn care	17
Prefer/need to stay home with children	7
Other family responsibilities	4
Child care problem	11
Transportation problem	3
In school/training	10
Lack education/work experience	11
No jobs available/wages too low	13
Other	10
Principal Reason for Leaving Most Recent Job
Not satisfied with hours/benefits/salary	8
Problems on the job (with boss or too stressful)	7
Pregnancy/maternity leave	19
Own health problems	11
Family or personal problems	6
Child care or transportation problems	7
Improved opportunities (school or another job)	3
Temporary or short term assignment ended	14
Fired or laid off	14
Other	11
Sample Size	244
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. a Tabulated for cases on which the head was not currently employed, but had been employed in the past.

Table D.5 Perceived Discrimination by Potential Employer During the past Year (Percentages)

Table D.5
Perceived Discrimination by Potential Employer During the past Year^a
(Percentages)

	Currently Employed	Previously Employed	All
Perceived Discrimination Based On:
Race or ethnic origin	6	9	7
Gender	3	7	5
Having been on welfare	12	10	11
Appearance or other physical characteristicsb	8	11	10
Any of the above	19	22	20
Sample Size	157	244	401
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between employed and not employed case heads. */**/*** Difference between cases with/without an employed head is statistically significant at the .10/.05/.01 level. a Statistics in this table are based on experiences by case heads who have ever worked for pay. b Includes dental problem, weight, eyesight or hearing, or anything else about appearance.

Table D.6 Performance of Job Tasks among TANF Cases (Percentages)

Table D.6
Performance of Job Tasks among TANF Cases
(Percentages)

	Regularlya	Monthly	Ever
Job Tasks Performed:
Talk with customers face to face	80	2	82
Talk with customers over the phone	51	4	55
Read instructions or reports	53	8	61
Write letters or memos	30	6	36
Work with a computer	37	5	42
Work with another electronic machine	67	3	70
Do arithmetic	60	4	64
Fill out forms	55	6	61
Keep watch over gauges or instruments	40	5	46
Performed at Least Four Job Tasks	67	1	72
Sample Size			416
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between employed and not employed case heads. a Regularly is defined as having performed the job skill at least weekly.

Table D.7 Participation in Education, Training, and Job Preparation Programs among TANF Cases During the past Year (Percentages)

Table D.7
Participation in Education, Training, and Job Preparation Programs among TANF Cases During the past Year
(Percentages)

	Employed	Not Employed	All
Education or Training Programs	46	50	49
GED classes or preparing for GED exam	16	23*	21
Specialized training program	34	29	31
College classes	15	12	13
Job Preparation Programs	48	60**	55
Job readiness training	33	33	33
Job search program or job club	45	54*	51
Work Experience Program	13	29***	23
Any of the Above	67	78**	74
Sample Size	157	259	416
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between employed and not employed case heads. */**/*** Difference between cases with/without an employed head is statistically significant at the .10/.05/.01 level.

Table D.8 Basic Understanding of Work Norms among TANF Cases (Percentages)

Table D.8
Basic Understanding of Work Norms among TANF Cases
(Percentages)

	Employed	Not Employed	All
Understands Problem and Able to Identify Viable Solutions:
Arriving at Work Late Due to Unreliable Babysitter	43	50	47
Not Performing Well on Smaller Job Tasks (e.g. filing)	41	46	44
Losing Temper over Criticism from Co-Worker	86	88	87
Approaching New Tasks That Are Unfamiliar	47	56*	53
Making Mistakes Due to Stress of Job	47	51	50
Good Overall Understanding of at Least 3 Work Normsa	56	64	61
Sample Size	157	259	416
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between employed and not employed case heads. */**/*** Difference between cases with/without an employed head is statistically significant at the .10/.05/.01 level. a For each of the five scenarios, the survey asked respondents to gauge their understanding of the problem and then provide a solution. Those who demonstrated a sense of the problem and could identify a viable solution were considered to have a good understanding of the underlying work norm.

Table D.9 Characteristics of the Heads of Single-parent TANF Cases in Illinois (Percentages, Unless Stated Otherwise)

Table D.9
Characteristics of the Heads of Single-parent TANF Cases in Illinois
(Percentages, Unless Stated Otherwise)

	Employed	Not Employed	All
Gender
Female	99	99	99
Male	1	1	1
Age		***
Younger than 25 years	21	45	36
25 to 34 years	41	31	35
35 years or older	38	24	30
Average age (years)	31.8	28.1***	29.5
Median age (years)	31.0	25.0	28.0
Marital Status
Never married	65	72	69
Married or living with partner	15	12	13
Separated, divorced, or widowed	20	16	17
Highest Education Completed
Less than high school diploma/GED	40	47	44
High school diploma/GED	27	28	28
More than high school diploma/GED	33	25	28
Sample Size	157	259	416
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between employed and not employed case heads. */**/*** Difference between cases with/without an employed head is statistically significant at the .10/.05/.01 level.

Table D.10 Household Composition of Single-parent TANF Cases in Illinois (Percentages, Unless Stated Otherwise)

Table D.10
Household Composition of Single-parent TANF Cases in Illinois
(Percentages, Unless Stated Otherwise)

	Employed	Not Employed	All
Household Composition
Adults only, no children	0	1	1
Single parent, children	61	50	55
Single parent, other adults, childrena	32	38	36
Single parent, partner, childrenb	4	4	4
Two married adults, childrenb	3	6	4
Average number of persons in HH	4.6	4.5	4.5
Median number of persons in HH	4.0	4.0	4.0
Number of Children Less than Age 18 in Household
0	0	1	1
1	17	29	24
2	30	27	28
3	26	20	22
4	11	9	10
5 or more	16	14	15
Average number of children < 18 in HH	2.9	2.6*	2.7
Median number of children < 18 in HH	3.0	2.0	2.0
Number of Children Less than Age 6 in Household		***
0	36	19	26
1	36	46	42
2	21	25	24
3 or more	6	10	9
Average number of children < 6 in HH	1.0	1.3**	1.2
Median number of children < 6 in HH	1.0	1.0	1.0
Age of Youngest Child		***
Less than 1 year	21	33	29
1 to 5 years	42	48	46
6 to 14 years	32	18	23
15 years or older	4	1	2
Average age of youngest child	4.8	3.0***	3.8
Median age of youngest child	3.0	1.0	2.0
Have Own Children Less than Age 18 Living Outside Household	5	7	6
Sample Size	157	259	416
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between employed and not employed case heads. */**/*** Difference between cases with/without an employed head is statistically significant at the .10/.05/.01 level. a "Other adults" is exclusive of a spouse or partner. b Other adults may also have been present in the household.

Table D.11housing Characteristics (Percentages)

Table D.11
Housing Characteristics
(Percentages)

	Employed	Not Employed	All
Number of Bedrooms
1	7	9	9
2	35	38	37
3	34	34	34
4 or more	24	18	20
Housing Assistance
Live in public housing	17	15	16
Receive rent subsidy	28	26	27
None	56	59	58
Number of Moves in Past 12 Months
0	61	48	53
1	26	25	25
2 or more	13	27	21
Evicted in Past Year	5	6	5
Unstable Housinga	16	27**	23
Sample Size	157	259	416
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) to test for differences between employed and not employed recipients. */**/*** Difference between cases with/without an employed head is statistically significant at the .10/.05/.01 level. a Defined as having been evicted or moving two or more times in the past 12 months.

Table D.12 Children's Health and Special Needsa (Percentages, Unless Stated Otherwise)

Table D.12
Children's Health and Special Needs^a
(Percentages, Unless Stated Otherwise)

	All Cases
Type of Problem / Special Needb
Asthma	34
Medical problems	42
Learning problems	35
Behavior problems	24
Depression / mental health problems	2
Other	6
Age of Child with Problems / Special Needsb
5 and under	41
6 to 12	49
13 to 17	26
Child Receives SSI Benefits	27
Child is Limited in Activities	53
Number of Children Limited in Activities
0	47
1	45
2	7
3	1
Sample Size	120
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between employed and not employed case heads. a Tabulated for cases with at least one child with health, behavioral, or special needs. b Percentages do not add to 100 percent due to cases with multiple children with health, behavioral, or special needs.

Table D.13 Earnings of TANF Cases (Percentages, Unless Stated Otherwise)

Table D.13
Earnings of TANF Cases
(Percentages, Unless Stated Otherwise)

	All Cases
Case Head Worked for Pay in Past Month	40
Monthly Earnings of Case Heada
Less than $400	28
$400 to $799	42
$800 to $1199	23
$1200 or more	7
Average monthly earnings	$616
Median monthly earnings	$600
Other Adults in the Household Worked for Pay in Past Month	21
Sample Size	416
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between currently and previously employed case heads. a Tabulated for cases who reported working for pay in past month (n=160).

Table D.14 Income Sources and Amounts among TANF Householdsa (Percentages, Unless Stated Otherwise)

Table D.14
Income Sources and Amounts among TANF Households^a
(Percentages, Unless Stated Otherwise)

	Percentage with Income from Sourceb	Income in Past Monthb
		Cases with Income from Selected Source	All Clientsc
Earnings by All Household Members	54	$817	$407
Public Assistance
TANF benefits	86	$273	$235
Food stamp benefits	93	$317	$293
SSI or disability insurance	15	$559	$ 79
Child Support Over Past 12 Months
Received any	10	--	--
Received regularlyd	48	--	--
Other Sourcese	13	$244	$ 32
All Sources	--	--	$1065
Sample Size			416
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between currently and previously employed case heads. a Income sources and amounts refer to the month prior to the survey. b Categories include income received by any member of the household. c Figures for "all clients" includes clients who received or who did not receive the income source in the past month. Those who did not receive the income source had values of $0 in the calculation of the average. d Tabulated only for cases that received child support in past 12 months (n=41). e Other income includes child support, unemployment benefits, alimony payments, and money from friends or relatives. Separate figures for monthly child support payments were not gathered in the survey.

Table D.15 Monthly Household Income of TANF Cases and Income Relative to Poverty Levels (Percentages, Unless Stated Otherwise)

Table D.15
Monthly Household Income of TANF Cases and Income Relative to Poverty Levels
(Percentages, Unless Stated Otherwise)

	All Cases
Total Monthly Household Incomea
Less than $500	14
$500 to 999	41
$1,000 to 1,499	27
$1,500 to 1,999	10
$2,000 or more	8
Average income	$1065
Median income	$934
Total Monthly Household Income Relative to Poverty Levelb
Less than 0.50	65
0.50 to 0.99	29
1.00 to 1.49	4
1.50 to 1.99	2
2.00 or more	0
Average income to poverty level	.48
Median income to poverty level	.39
Sample Size	416
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between currently and previously employed case heads. a Based on reported household income for month prior to the survey. b Poverty threshold level for 2001 as established by the U.S. Bureau of the Census. The analysis of monthly household income relative to the poverty level excludes food stamps. Income from food stamps is included in the monthly household income figures presented.

Table D.16 Child Care Use and Problems (Percentages)

Table D.16
Child Care Use and Problems
(Percentages)

	Cases With Child Under Age 6a	Cases With Child Between Age 6 and 12	Cases With Child Under Age 13
Used Child Care During the Past Yearb	47	52	48
Received Child Care Subsidyc	62	66	63
Child Care Problems Interfered w/ Work/School/Training	32	23	31
Specific child care problems for cases with problemsd
Cost	13	25	15
Not available when needed	30	27	30
Too far from home or work	4	0	4
Provider unavailable or unreliable	43	10***	38
Worry about child neglect or abuse	8	0	7
Sick or disabled child	12	27	15
Subsidy late, so lost provider	4	0	3
Other	19	23	20
Sample Size	311	71	382
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between employed and not employed case heads. */**/*** Difference between cases based on child's age (under 6 and between 6 and 12) is statistically significant at the .10/.05/.01 level. a TANF clients with a child younger than 6 years of age and a child between 6 and 12 years of age are classified as having a child in the younger age category but not in the older age category. b The measure of child care use does not include care provided by a child's parent. c Tabulated only for cases that used child care other than that provided by a parent (sample size = 190). d Tabulated only for cases that experienced problems with child care that interfered with work, school, or training (sample size = 120). Percentages sum to more than 100 because some cases experienced multiple problems.

Table D.17 Other Personal and Family Issues That May Be Barriers to Employment (Percentages)

Table D.17
Other Personal and Family Issues That May Be Barriers to Employment
(Percentages)

	Employed	Not Employed	All
Possible Presence of a Learning Disabilitya	10	13	12
Child with Health or Behavioral Problem or Special Need	33	29	30
Caring for an Elderly, Sick or Disabled Family Member or Friend	8	14*	12
Difficulty with English Because it is Not Native Language	3	2	2
Criminal Conviction	19	17	18
Multiple Arrestsb	11	20**	16
Sample Size	157	259	416
Source: MPR's 2001-02 survey of Illinois TANF cases and administrative data from the Illinois Criminal Justice Information Authority. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between employed and not employed case heads. */**/*** Difference between cases with/without an employed head is statistically significant at the .10/.05/.01 level. a The possible presence of a learning disability was determined following the methodology of the Washington State Learning Needs Screening Tool. b Has had two or more arrests since 1996.

Table D.18 Physical Health (Percentages, Unless Otherwise Stated)

Table D.18
Physical Health
(Percentages, Unless Otherwise Stated)

	Employed	Not Employed	All
Overall Health (Self-Assessment)
Excellent	22	23	23
Very good	20	16	18
Good	38	31	34
Fair	15	20	18
Poor	5	10	8
Pregnanta	3	11***	8
Younger than 25 years	--	--	12
25 to 34 years	--	--	8
35 years or older	--	--	3
Presence of Chronic Health or Medical Conditionb	22	31*	27
Arthritis	4	4	4
Asthma/Emphysema	9	13	12
Back problem	2	5	4
High blood pressure	1	5**	3
Nerves/Anxiety/Stress	2	5	4
Physical Functioningc		**
First quartile of the U.S. population	40	51	47
Second quartile of the U.S. population	22	12	16
Third or fourth quartile of the U.S. population	38	37	38
Below average for the U.S. population	30	40**	36
Physical Health Problemd	16	24**	21
Sample Size	157	259	416
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between employed and not employed case heads. */**/*** Difference between cases with/without an employed head is statistically significant at the .10/.05/.01 level. -- Sample sizes too small for subgroup analysis. a Tabulated only for cases with female heads (sample size = 413). b Not all categories are shown. c Physical functioning was determined following the methodology of the Physical Functioning Scale of the SF-36 Health Survey, incorporating norms based on age and gender. d Following the methodology of the University of Michigan's Women's Employment Study, a case head was defined to have a physical health problem if overall health was poor or fair and physical functioning was in the lowest quartile.

Table D.19 Mental Health (Percentages, Unless Stated Otherwise)

Table D.19
Mental Health
(Percentages, Unless Stated Otherwise)

	Employed	Not Employed	All
Experienced Psychological Distress in Past 30 Daysa	6	15***	12
Experienced Major Depression in Past Yearb	86	72***	77
Characteristics of Depressive Spells Over Past 12 Mos.c
Cumulative duration (in weeks)	--	--	17.6
Timing of most recent spell (months in past)	--	--	2.7
Consulted doctor or other professional	--	--	58
Took medication or used drugs or alcohol	--	--	48
Caused at least some interference with activities	--	--	78
Mental Health Problemd	15	31***	25
Sample Size	157	259	416
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between employed and not employed case heads. */**/*** Difference between cases with/without an employed head is statistically significant at the .10/.05/.01 level. -- Sample sizes too small for subgroup analysis. a Categories of nonspecific psychological distress were assigned on the basis of the K6 psychological distress scale, with a range of 0 to 24, and on normative data from the 2002 National Health Interview Survey and the 2001 National Household Survey on Drug Abuse. Individuals with scores of 13 or greater are classified as experiencing psychological distress. b The probability of major depression was determined following the methodology of the Composite International Diagnostic Interview Short Form (CIDI-SF). Under this methodology, individuals with three or more of seven symptoms of major depression are classified as being at probable risk of major depression. Individuals who volunteer that they are on medication, such as anti-depressants also are classified as being at probable risk of major depression. c Tabulated for the 95 cases in which the head had at least three of the seven symptoms of major depression in the CIDI-SF. d Defined as having a high level of nonspecific psychological distress or probable major depression.

Table D.20 Chemical Dependence (Percentages)

Table D.20
Chemical Dependence
(Percentages)

	Employed	Not Employed	All
Alcohol Dependencea
No alcohol dependence	99	98	98
Probable alcohol dependence	1	2	2
Drug Dependenceb
No drug dependence	99	98	98
Probable drug dependence	1	2	2
Any Chemical Dependencec	2	4	3
Sample Size	157	259	416
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between employed and not employed case heads. */**/*** Difference between cases with/without an employed head is statistically significant at the .10/.05/.01 level. a The probability of alcohol dependence was determined following the methodology of the Composite International Diagnostic Interview Short Form (CIDI-SF). Under this methodology, individuals with three or more of seven symptoms of alcohol dependence are classified as being at probable risk of alcohol dependence. b The probability of drug dependence was determined following the methodology of the Composite International Diagnostic Interview Short Form (CIDI-SF). Under this methodology, individuals with three or more of seven symptoms of drug dependence are classified as being at probable risk of drug dependence. c Probable alcohol or drug dependence.

Table D.21 Domestic Violence (Percentages)

Table D.21
Domestic Violence^a
(Percentages)

	Employed	Not Employed	All
Experienced Physical Violence from Partner
Moderate Physical Violenceb		**
In past year	15	17	16
In lifetime, but not past year	24	14	18
Never	61	68	65
Severe Physical Violencec		**
In past yeard	11	14	13
In lifetime, but not past year	23	13	17
Never	66	72	70
Any Physical Violence		**
In past year	15	19	17
In lifetime, but not past year	26	15	19
Never	58	66	63
Experienced Threats from Partner
Physical Threatse		***
In past year	12	13	13
In lifetime, but not past year	31	17	22
Never	57	70	65
Coercive Threatsf		*
In past year	10	11	11
In lifetime, but not past year	19	11	14
Never	71	78	75
Any Threats		**
In past year	15	17	16
In lifetime, but not past year	30	17	22
Never	55	65	62
Ever Experienced Violence/Threats from Partner	50	40**	44
Sample Size	156	257	413
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between employed and not employed case heads. */**/*** Difference between cases with/without an employed head is statistically significant at the .10/.05/.01 level. a Tabulated only for cases with female heads, based on a modified version of the Conflict Tactics Scale used in the University of Michigan's Women's Employment Study. b Moderate physical violence: pushing, grabbing, shoving, slapping, kicking, or biting. c Severe physical violence: hitting, beating, choking, using or threatening use of a weapon, or forcing sexual activity. d Any severe physical violence in past year was used to signify a barrier to employment in the Women's Employment Study of the University of Michigan. Severe physical violence includes hitting, beating, choking, using or threatening use of a weapon, or forcing sexual activity. e Physical threats: threatening to hit with a fist or object, or throwing anything that could harm. f Coercive threats: threatening to take children away, to harm individual or friends, to report to child protective services or welfare agency, harassing at work or school, or coercing into doing illegal things .

Table D.22 Transportation Use and Problems (Percentages, Unless Stated Otherwise)

Table D.22
Transportation Use and Problems
(Percentages, Unless Stated Otherwise)

	Employed	Not Employed	All
Primary Mode of Transportation to Work or Work-Related Activitya		**
Drives self	30	16	22
Gets a ride	11	10	10
Bus or public transportation	52	67	61
Walks	5	5	5
Other	3	3	3
Length of Commute to Work or Work-Related Activity (in Minutes)a
Average	51.9	55.1	53.7
Median	45.0	45.0	45.0
Does Not Have a Valid Driver's License	43	56**	51
Does Not Own or Have Access to a Car	51	69***	62
Self-Reported Transportation Problemb	14	26***	21
Sample Size	157	259	416
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between employed and not employed case heads. */**/*** Difference between cases with/without an employed head is statistically significant at the .10/.05/.01 level. a Tabulated only for cases in which the head worked or attended a work-related activity (sample size = 381 ) b Case head indicated that a transportation problem prevented him/her from participating in work, education or training during the past year.

Table D.23 Perceived Neighborhood Characteristics (Percentages)

Table D.23
Perceived Neighborhood Characteristics^a
(Percentages)

	Employed	Not Employed	All
Unemployment Among Neighborhood Residents
Not a problem	37	34	35
Somewhat of a problem	26	29	28
Big Problem	37	37	37
Drug Users or Pushers in Neighborhood
Not a problem	33	31	32
Somewhat of a problem	24	27	26
Big Problem	43	42	42
Crime, Assaults, or Burglaries in Neighborhood
Not a problem	49	44	46
Somewhat of a problem	31	29	30
Big Problem	20	27	24
Run-down Buildings and Yards in Neighborhood
Not a problem	60	61	61
Somewhat of a problem	23	22	22
Big Problem	16	17	17
At Least One Neighborhood Characteristic is Perceived to Be a Big Problem	53	56	55
No Safe Area for Children to Play in Neighborhood	34	37	36
Sample Size	157	259	416
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between employed and not employed case heads. */**/*** Difference between cases with/without an employed head is statistically significant at the .10/.05/.01 level. a Statistics in this table are analyzed from the self-assessments of TANF case heads. The case head was asked how much of a problem, if any, each category posed in their neighborhood.

Table D.24 Summary of Potential Assets and Liabilities for Employment (Percentages, Unless Stated Otherwise)

Table D.24
Summary of Potential Assets and Liabilities for Employment
(Percentages, Unless Stated Otherwise)

	Employed	Not Employed	All
Potential Assets for Employment
High school / GED or more	60	53	56
Substantial work experiencea	86	70***	76
Performed four or more common job tasks	76	69	72
Potential Liabilities for Employment
Personal and Family Challenges
Physical health problemb	16	24**	21
Child or other family member or friend with a health problem or special needc	36	33	35
Pregnantd	3	11***	8
Mental health probleme	15	31***	25
Chemical dependencef	2	4	3
Severe physical domestic violence in past yeard	11	14	13
Possible presence of learning disability	10	13	12
Criminal conviction	19	17	18
Multiple arrestsg	11	20**	16
Difficulty with English	3	2	2
Logistical and Situational Challenges
Transportationh	14	26***	21
Child careh	19	40***	31
Unstable housingi	16	27**	23
Any perceived discrimination by potential employerj	19	22	20
Perceived problem neighborhood characteristicsk	53	56	55
Sample Size	157	259	416
Source: MPR's 2001-02 survey of Illinois TANF cases and administrative data from the Illinois Criminal Justice Information Agency. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between employed and not employed case heads. */**/*** Difference between cases with/without an employed head is statistically significant at the .10/.05/.01 level. a Worked for pay 50 percent or more of time since turning age 18. b Poor or fair overall health and physical functioning in the lowest quartile. c Cases with a child with health, behavioral, or special need or those caring for an elderly, disabled, or sick family member or friend. d Tabulated only for females (sample size = 413). e High level of nonspecific psychological distress or probable major depression. f Probable alcohol or drug dependence. g Has had two or more arrests since 1996. h Self-reported problems that prevented case head from participating in work, education, or training during the past year. i Having been evicted or moving two or more times in the past 12 months. j Tabulated only for cases who have worked for pay (n = 401). k At least one neighborhood characteristic is perceived by case head to be a big problem.

Table D.25 Self-reported Problems That Prevented Case Heads from Working (Percentages)

Table D.25
Self-reported Problems That Prevented Case Heads from Working
(Percentages)

Problem that Prevented Case Head from Participating in Work, Education, or Training During Past Year	Employed	Not Employed	All
Child's Health or Behavioral Problem or Special Need	11	13	12
Physical Health Problem	21	28	25
Mental Health Problem	3	10***	7
Alcohol or Drug Problem	0	1	1
Problem in Relationship with Spouse or Partnera	6	8	7
Transportation Problem	14	26***	21
Child Care Problemb	19	36***	29
Housing Problem	5	16***	12
Other Problemc	8	9	9
Any of the Above Problems	50	68***	61
Sample Size	157	259	416
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between employed and not employed case heads. */**/*** Difference between cases with/without an employed head is statistically significant at the .10/.05/.01 level. a Tabulated only for cases with female heads (sample size = 413). b Tabulated only for cases with children under age 15 (sample size = 400). c Caring for an elderly, disabled, or sick family member or friend; difficulty with English because it is not native language; criminal record.

Table D.26 Number of Potential Liabilities for Employment

Table D.26
Number of Potential Liabilities for Employment

	Employed At Least 30 Hours Per Week	Not Employed At Least 30 Hours Per Week	All
Number of Human Capital Deficitsa		**
0	29	18	21
1	40	36	37
2	25	32	30
3	6	14	12
Average	1.09	1.41***	1.31
Median	1.0	1.0	1.0
Number of Personal Challengesb		**
0	54	42	45
1	34	28	30
2	10	19	17
3	1	7	5
4 or more	1	3	3
Average	.61	1.02***	.89
Median	0	1.0	1.0
Number of Logistical and Situational Challengesc		**
0	32	20	24
1	40	36	37
2	19	26	24
3	9	13	12
4	0	5	3
Average	1.04	1.45***	1.33
Median	1.0	1.0	1.0
Number of All Potential Liabilities for Employment		***
0	9	2	4
1	16	11	12
2	21	14	16
3	24	19	21
4	13	18	17
5	9	14	13
6	5	8	7
7 or more	3	13	10
Average	2.76	3.90***	3.55
Median	3.0	4.0	3.0
Sample Size	157	259	416
Source: MPR's 2001-02 survey of Illinois TANF cases. Notes: The survey data have been weighted to be representative of all single-parent TANF recipients in Illinois. Survey item nonresponse may cause the sample sizes for specific variables to be smaller than those shown. Rounding may cause percentages to sum to something other than 100. We conducted two-tailed t-tests (for continuous variables) and chi-square tests (for categorical variables) for differences between employed and not employed case heads. */**/*** Difference between cases with/without an employed head is statistically significant at the .10/.05/.01 level. a Human capital deficits include: (1) no high school diploma or GED, (2) employed less than four quarters of the past seven, and (3) never performed at least four of nine common job tasks. b Personal challenges include: (1) current physical health problem, (2) mental health problem in the past year, (3) multiple arrests in past six years, (4) severe physical domestic violence in past year, (5) chemical dependence in the past year, (6) signs of a learning disability, and (7) difficulty with English. c Logistical and situational challenges include: (1) child or other family member or friend currently experiencing a health or behavioral problem or special need, (2) child care problem in the past year, currently pregnant, or currently have a child under age one in the household, (3) transportation problem in the past year, and (4) unstable housing in the past year.

Appendix E: Methodology for Multivariate Analysis

To examine the affect of liabilities on employment in a multivariate context, we use a logit models to estimate whether the number or specific liabilities affects whether a TANF case head is employed 30 hours or more per week. The analysis sample includes the 372 survey respondents who had no missing data on employment status, selected background characteristics, or any of the 16 liability measures. A list of variables included in the models and their means and standard deviations are presented in Table E-1. The logit estimation results are presented in Tables E-2 and E-3.

First, we estimate equations (1) and (2) to determine whether the number of liabilities affects employment status. These equations express employment status as a function of the number of employment liabilities and a set of background characteristics, including a measure of prior welfare receipt. We specify the number of barriers as a series of seven dummy variables in equation (1) and as a series of three dummy variables in equation (2).

where:

EMP30_i =1 if working 30 or more hours per week; 0 otherwise
N1_ji =1 if the number of liabilities is j; 0 otherwise; j 1,…, 6
N1_7i =1 if the number of liabilities is 7 or more; 0 otherwise
X_ki =set of background control variables,^{(1) k = 1,…, K}
U_i =random disturbance term
=parameters to be estimated
i = index for survey respondents, i = 1,…, 372

where:

EMP30_i =1 if working 30 or more hours per week; 0 otherwise
N2_1i =1 if the number of liabilities is 1, 2, or 3; 0 otherwise
N2_2i =1 if the number of liabilities is 4, 5, or 6; 0 otherwise
N2_3i = 1 if the number of liabilities is 7 or more; 0 otherwise
X_ki =set of background control variables, k = 1,…, K
U_i =random disturbance term
=parameters to be estimated
i = index for survey respondents, i = 1,…, 372

Next, we estimate equation (3) to determine how each individual liability affects employment status. This equation expresses employment as a function of 14 employment liabilities, prior welfare receipt, and the same set of background characteristics as in the previous two equations.

where:

EMP30_i =1 if working 30 or more hours per week; 0 otherwise
L_ji =1 if specific liability j is present; 0 otherwise; j 1,…, 16
X_ki =set of background control variables, k = 1,…, K
U_i =random disturbance term
=parameters to be estimated
i = index for survey respondents, i = 1,…, 372

Finally, for comparison purposes, we estimate equation (4) to determine how the background characteristics alone affect employment.

where:

EMP30_i =1 if working 30 or more hours per week; 0 otherwise
X_ki =set of background control variables, k = 1,…, K
U_i =random disturbance term
=parameters to be estimated
i = index for survey respondents, i = 1,…, 404

Table E.1
Variable Descriptions

Variable	Mean	Standard Deviation
Dependent Variable
Case head works 30 or more hours per week	.30	.46
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
Two to three	.37	.48
Four to six	.36	.48
Seven or more	.10	.30
Background Characteristics
Age 25-34	.34	.48
Age 34 and over	.30	.46
African American	.82	.38
Non-African American, Non-White	.07	.26
Never married	.82	.39
Separated, divorced, or widowed	.14	.35
County unemployment rate	5.80	.50
80% or more of zip code is non-Hispanic African American	.48	.50
Percentage of past 25 months received TANF	69.64	32.47
Percentage of past 25 months received TANF squared	5901.21	3959.92
Have child between age one and five	.61	.49
Have two children	.28	.45
Have three children	.47	.50
Source: 2001-02 survey of Illinois TANF cases, N=416.

Table E.2
Effects of Multiple Liabilities on the Probability that a TANF Case Head Works 30 or More Hours Per Week

	Model 1				Model 2
	Coefficient	Std Error	t	P>|t|	Coefficient	Std Error	t	P>|t|
Number of Liabilities
One	-1.09	0.66	-1.65	0.10	-1.09	0.66	-1.66	0.10
Two	-1.00	0.65	-1.54	0.12
Three	-1.38	0.63	-2.17	0.03
Four	-1.75	0.67	-2.63	0.01
Five	-1.72	0.71	-2.41	0.02
Six	-1.76	0.75	-2.35	0.02
Seven or more	-3.26	0.90	-3.61	0.00
Grouped Liabilities
Two to three					-1.21	0.61	-1.98	0.05
Four to six					-1.74	0.62	-2.82	0.01
Seven or more					-3.25	0.90	-3.62	0.00
Background Characteristics
Age 25-34	0.79	0.35	2.25	0.03	0.78	0.35	2.24	0.03
Age 34 and over	1.12	0.39	2.84	0.01	1.08	0.39	2.80	0.01
African American	-0.27	0.49	-0.54	0.59	-0.28	0.50	-0.57	0.57
Non-African American, Non- White	1.09	0.62	1.76	0.08	1.04	0.61	1.70	0.09
Never married	-0.20	0.63	-0.32	0.75	-0.17	0.64	-0.27	0.79
Separated, divorced, widowed	0.12	0.70	0.18	0.86	0.18	0.70	0.25	0.80
County unemployment rate	-0.44	0.24	-1.86	0.06	-0.43	0.24	-1.82	0.07
80 percent or more of zip code is non-Hispanic African American	0.28	0.29	0.96	0.34	0.27	0.29	0.95	0.35
Percentage of past 25 months received TANF	0.01	0.02	0.24	0.81	0.01	0.02	0.24	0.81
Percentage of past 25 months received TANF squared	0.00	0.00	0.02	0.98	0.00	0.00	0.03	0.98
Have child between age one and five	-0.21	0.34	-0.61	0.54	-0.21	0.34	-0.63	0.53
Have two children	0.31	0.39	0.80	0.42	0.33	0.39	0.84	0.40
Have three children	0.69	0.36	1.93	0.06	0.71	0.36	1.97	0.05
Constant	1.90	1.65	1.15	0.25	1.83	1.64	1.12	0.27
F-Statistic	2.43				2.75
Prob > F	0.0006				0.0003
Number of Observations	375				375
Source: Results of multinomial logit models predicting the probability of working 30+ hours per week using data from 2001-02 survey of Illinois TANF cases.

Table E.3
Effects of Specific Liabilities on the Probability that a TANF Case
Head Works 30 or More Hours Per Week

	Model 3				Model 4
	Coefficient	Std Error	t	P>|t|	Coefficient	Std Error	t	P>|t|
Human Capital Liabilities
No high school diploma or GED	-0.17	0.29	-0.59	0.56
Limited work experience	-0.70	0.29	-2.46	0.01
Performed fewer than four common job tasks	-0.11	0.32	-0.36	0.72
Personal Challenges
Physical health problem	-0.90	0.43	-2.12	0.03
Mental health problem	-0.13	0.39	-0.34	0.73
Chemical dependence	-0.13	0.95	-0.14	0.89
Severe physical domestic violence in past year	0.58	0.42	1.37	0.17
Signs of a learning disability	0.23	0.47	0.49	0.63
Multiple arrests	-0.80	0.45	-1.79	0.07
Difficulty with English	-0.69	0.89	-0.78	0.44
Logistical and Situational Challenges
Child/family member/friend w/ health problem or special need	0.14	0.31	0.43	0.67
Pregnant	-0.59	0.46	-1.28	0.20
Child under age one in household	-0.18	0.35	-0.51	0.61
Transportation	-0.46	0.39	-1.18	0.24
Child care	-1.00	0.38	-2.66	0.01
Unstable housing	-0.05	0.39	-0.13	0.90
Background Characteristics
Age 25-34	0.61	0.39	1.58	0.11	0.83	0.32	2.56	0.01
Age 34 and over	0.97	0.42	2.30	0.02	0.97	0.36	2.70	0.01
African American	0.16	0.51	0.32	0.75	-0.13	0.46	-0.27	0.79
Non-African American, Non-White	1.58	0.66	2.42	0.02	0.62	0.57	1.09	0.28
Never married	-0.49	0.78	-0.62	0.54	-0.25	0.58	-0.43	0.67
Separated, divorced, widowed	-0.18	0.82	-0.22	0.82	0.09	0.63	0.14	0.89
County unemployment rate	-0.48	0.25	-1.97	0.05	-0.46	0.27	-1.75	0.08
80 percent or more of zip code is non-Hispanic African American	0.06	0.31	0.21	0.84	0.14	0.27	0.51	0.61
Percentage of past 25 months received TANF	0.02	0.02	0.75	0.45	0.01	0.02	0.53	0.60
Percentage of past 25 months received TANF squared	0.00	0.00	-0.37	0.71	0.00	0.00	-0.04	0.97
Have child between age one and five	-0.23	0.31	-0.73	0.47
Have child under age five					-0.33	0.30	-1.09	0.28
Have two children	0.41	0.41	1.00	0.32	0.32	0.37	0.87	0.39
Have three children	0.56	0.39	1.45	0.15	0.66	0.35	1.87	0.06
Constant	1.46	1.64	0.89	0.37	0.40	1.71	0.24	0.81
F-Statistic	2.40				2.98
Prob > F	0.0001				0.0004
Number of Observations	374				404
Source: Results of multinomial logit models predicting the probability of working 30+ hours per week using data from 2001-02 survey of Illinois TANF cases

Endnote

1. 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).