Welfare myths: The transmission of values and work among TANF families

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Social Science Research 37 (2008) 516–529

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Welfare myths: The transmission of valuesand work among TANF families

M.A. Lee a,*, Joachim Singelmann b, Anat Yom-Tov c

a Population Reference Bureau, Washington, DC 20009, USAb Department of Sociology, Louisiana State University, Baton Rouge, LA 70803, USA

c Department of Sociology, University of Wisconsin, Madison, WI 53705, USA

Available online 30 October 2007

Abstract

Both ‘‘welfare culture’’ arguments and structural explanations of poverty suggest that attitudes may have an effect onwork and welfare outcomes. However, most scholars only examine objective behaviors and characteristics despite the factthat values are an underlying mechanism in explanations of the transmission of welfare and work behavior. Using datafrom a survey of recent welfare recipients in Louisiana and structural equation methods, we analyze causal relationshipsamong family background, socioeconomic characteristics, attitudes, and two outcomes—TANF participation and employ-ment. We find some support for the intergenerational transmission of welfare but not through values; we find no evidencethat under the TANF system, values inhibit work.� 2007 Elsevier Inc. All rights reserved.

Keywords: Welfare; Culture of poverty; Inequality; Intergenerational mobility

1. Introduction

Prior to welfare reform in 1996, the American public viewed welfare as fostering a belief system incongruentwith work. Policy makers responded to public opinion with welfare reform and continue to do so with pro-posals mandating increased hours of work for recipients. Although there has been a rapid decline in caseloadsboth under Aid to Families with Dependent Children (AFDC) and Temporary Assistance for Needy Families(TANF) programs, some persons continue to remain on the welfare rolls and have not yet entered the laborforce. Many observers consider these hard-to-serve cases part of the cycle that welfare reform of 1996—thePersonal Responsibility and Work Opportunity Reconciliation Act (PRWORA)—was meant to break. Man-dated work and work-first programs aimed at ending this perceived welfare dependency and its intergenera-tional effects by creating a stronger work ethic in a new generation. However, questions remain as to whetherfailure to work and continued welfare use under TANF is the result of personal attitudes towards work or theresult of structural barriers to work.

0049-089X/$ - see front matter � 2007 Elsevier Inc. All rights reserved.doi:10.1016/j.ssresearch.2007.09.005

* Corresponding author.E-mail address: [email protected] (M.A. Lee).

mailto:[email protected]

M.A. Lee et al. / Social Science Research 37 (2008) 516–529 517

There is a long tradition of social science research discussing the relationship between social origin and suchoutcomes as welfare dependency and employment status. Two major perspectives have offered competingexplanations for this relationship: the culture of poverty explanation (including its specific application inthe welfare-culture critique), and the structural perspective. The poverty-culture perspective argues that chil-dren of poor families are socialized into a culture of poverty with a set of values and beliefs that prevents themfrom recognizing and taking advantage of opportunities. The structural perspective maintains that childrenwho grow up in poor families have less access to human capital, which makes them less competitive in thelabor market and, in turn, more likely also to end up poor. Thus, although both types of explanations hypoth-esize an effect of values on employment status, the causal path through which the effect occurs is different. Thepurpose of the present paper is to examine the competing claims of these two perspectives in order to furtherour understanding of the mechanisms underlying the relationship between social origin and current social sta-tus, thereby identifying opportunities for intervention policies. To that end, we directly test the mechanismsthrough which social origin and background affect welfare and employment status of poor women to adjudi-cate the competing arguments of the culture of poverty and structural perspectives.

2. Intergenerational transmission of welfare and work

The culture-of-poverty perspective and the structural perspective both suggest that attitudes and valuesmay have an effect on work and welfare outcomes. They also agree that disadvantaged social origin is directlyassociated with poverty and tangential labor-force participation. Where the two perspectives differ is in themechanisms—that is, in the relationship between social origin and welfare and employment status (cf. alsoSpilerman and Elesh, 1971).

2.1. Welfare culture framework

Scholars working with the culture-of-poverty framework have explained the persistence of poverty fromone generation to the next by noting that poverty, especially where it is concentrated, fosters a set of beliefsthat prevent poor families and their children from escaping poverty (Lewis, 1966). The culture-of-poverty the-ory provided the framework for the more recent welfare-culture critique (Moffitt, 1992; Moynihan, 1965; Mur-ray, 1984). This line of research argues that the structure of the pre-1996 welfare system strengthened the beliefsystem of the poor, limiting their perception of opportunities for work, and thereby contributed to the inter-generational transmission of dependency. Children raised in welfare households learn to use welfare and, thus,develop weak work ethics. Accordingly, they are socialized into a set of wrong values that weaken their laborforce attachment. Thus, this approach suggests that parents’ welfare use directly and indirectly results in theuse of welfare by their offspring.

2.2. Structural framework

Valentine (1968) was one of the earliest critics of the culture of poverty theory, arguing that there is neitheran identifiable set of self-defeating values nor is a specific cultural behavior responsible for poverty. However,his counter-argument for the importance of structural factors remained general and untested. But other schol-ars within the framework of the structural perspective (Blau and Duncan, 1967; Featherman and Hauser,1978; Sewell and Hauser, 1975) have shown that social origin and current socioeconomic status are highly cor-related because of the opportunity structure that is associated with social origin. Applying these relationshipsto welfare, this perspective argues that bad labor-market experiences shape attitudes. Isolated in neighbor-hoods where employment opportunities are few and limited, the very poor may believe that work will not helpthem improve their lot or that work is not available to them (Mead, 1992; Wilson, 1987; see also Beeghley,1989, and Schiller, 1970). According to this perspective, parents’ welfare use only indirectly affects welfareuse and work behavior of their children. It is the lack of opportunity among the poor that determines adultchildren’s characteristics, and these traits, such as education level, affect children’s work outcomes as adults.

A growing body of research has addressed the connection between background and individual behavior.However, in the study of welfare and work outcomes, most scholars examine behavioral or demographic

518 M.A. Lee et al. / Social Science Research 37 (2008) 516–529

characteristics despite the fact that both the welfare culture argument and structural explanations suggest thatvalues are an underlying mechanism in the transmission of welfare and work behavior (Cocoran, 1995; McL-anahan and Garfinkel, 1989; Wilson, 1987). For example, Rank and Cheng (1995) examined the two compet-ing frameworks for explaining the relationship between social origin and welfare use. Their findings lendsupport to the structural perspective in that parental socioeconomic status had a negative effect on welfareuse of their offspring, but parental use of welfare had no effect. However, Rank and Cheng (1995) did notinclude attitudes in their study. Yet, Bane and Ellwood (1994) have noted that objective behavior does notadequately explain women’s work behavior, and they encourage the incorporation of attitudes, values, andexpectations into analyses of work behavior.

Greenwell et al. (1998) did just that in an investigation of the transmission of welfare values on employmentamong new mothers. In order to advance our understanding of women’s employment and assess competingtheoretical models of intergenerational effects of welfare, these authors investigated two main sets of relation-ships—first, the relationship between family background and adolescent attitudes; second, the relationshipbetween adolescent attitudes and adult work behavior. They found that welfare background has a positiveeffect on willingness to accept public assistance. Their use of adolescent attitudes and adult work behaviorovercomes the statistical problems of endogeneity in earlier studies (McLanahan and Booth, 1989). The anal-yses, however, examine each set of relationships in separate regression equations, whereas the theoreticalexplanations from which their hypotheses are derived represent a set of integrated causal relationships.

The main arguments regarding the effect of parental background on employment and welfare participationtranslate into disagreement over how values/attitudes are developed and over the relative effects on publicassistance of welfare use by a person’s parents vs. the socioeconomic characteristics of that person when heis an adult. Murray (1984), in his extreme criticism of the welfare system, sees pre-reform work and marriagedisincentives as producing a rational set of values—which develop independently of parents’ use of welfare ortheir socioeconomic status—that includes negative attitudes toward work and positive attitudes towards wel-fare use. A more moderate criticism suggests that children of poor families grow up without access to educa-tion and job opportunity; this shapes their adult experiences in the labor market which, in turn, shape workattitudes and behavior (Biebly, 1992; Desai and Waite, 1991).

2.3. Modeling the expectations of the cultural and structural frameworks

Fig. 1 shows the causal explanations that dominate the literature on poverty. The upper triangle (arrows 1,4, 6) represents paths from the ‘‘welfare culture’’ argument. In this model values (attitudes) are assumed to be

Fig. 1. General schematic of causal paths represented in literature.


directly related to parental background. However, according to the structural argument represented by thelower triangle (arrows 2, 3, 5), attitudes and values are only indirectly related to parental background. Paren-tal background affects individuals’ labor market opportunities; these opportunities reproduce culture and val-ues that determine the probability of employment or TANF participation.

Both cultural and structural explanations suggest individuals may develop attitudes that increasechances of welfare participation and decrease odds of working. The structural argument is that ‘‘struc-ture’’ (opportunity) creates ‘‘culture’’ (values). The cultural argument is that the process of learning cul-ture, and thus parental background, produces dependency directly. Since some hypotheses are truewhether cultural or structural mechanisms are operating, an approach using a series of regressions thatare not statistically linked fails to effectively identify the causal paths associated with one set of mecha-nisms versus another.

In this study, we use structural equation models to analyze the causal relationships for two outcomes—TANF participation and employment. We estimate those models to answer three questions. First, is therea direct effect of parental background on the probability of welfare participation and work (Fig. 1, arrow6)? Second, is there an indirect effect of family background and, if so, is the indirect effect through thedevelopment of attitudes towards achievement, or is it through economic opportunity (arrows 1 to 4vs. arrows 2 to 5)? Third, does opportunity/past achievement influence values, resulting in an effect offamily background through values via economic opportunity (arrows 2 to 3 to 4)? If the path throughvalues in the top triangle holds, then the welfare culture model applies. If the path through opportunityand then values holds, structural models are the better explanation. Both cultural and structural argu-ments support a path from parental background through opportunity influencing TANF participationand employment, but in the absence of a direct effect of parents’ welfare use, this path would representthe structural explanation. To telegraph our key finding upfront: we find some support for the intergen-erational transmission of welfare but not through values, and we do not find any evidence that, under theTANF system, values inhibit work.

3. Data

The analysis in this paper uses the Louisiana Welfare Survey, a stratified random sample of 1998–1999 wel-fare recipients in three Louisiana Office of Family Services districts in the city of New Orleans–Algiers, Gen-tilly, Midtown–and 12 parishes in northeastern Louisiana. All 13 parishes are part of the Lower MississippiDelta region as defined by the Lower Mississippi Delta Congressional Commission (note: the city of NewOrleans is synonymous with Orleans Parish). The initial survey population consisted of persons 18 years ofage or older, who as of March 1998, according to administrative records, received cash assistance paymentsgreater than ten dollars. We conducted interviews in persons and used telephone interviews only as a lastresort. We augmented the survey population with another sample drawn in February 1999. Comparison ofthe baseline interviews conducted with the initial sample and the supplement indicate no significant differencesin the characteristics of the two samples. We had a response rate of 60 percent (completed and partial inter-views as a proportion of the eligible sample) for the initial interviews and a cooperation rate of over 80 per-cent. These rates are comparable to results for the low-income population included in the Panel Study ofIncome Dynamics (PSID).

Our analysis uses respondents raised in single mother families or two-parent families (90.3% of all respon-dents, N = 855) and specifically excludes respondents raised in other living situations, e.g., grandparent andsingle father families. Single mothers were the primary recipient of Aid to Families with Dependent Children(AFDC) and still constitute the bulk of the active caseload under TANF. In Louisiana, two parent families didnot become eligible for welfare cash assistance until the mid-1990s. However, the 1996 PRWORA seeks topromote marriage as a long-term alternative to cash assistance, making two-parent families a policy-relevantgroup.

One drawback of our data is that our analyses are limited to the effects on persons already on welfare. Wecannot generalize to the larger population nor make inferences about the choice to ever use welfare or not.Nonetheless, in the post-reform welfare environment, inferences about how attitudes affect transitions fromwelfare to work can inform policy and program choices.


4. Variables

4.1. Dependent variables

Our two dependent variables are (1) continued receipt of cash assistance, i.e., TANF participation, and (2)being employed at the time of the survey. After 1996, most able-bodied recipients of TANF cash assistancehave been required to work and are subject to time limits. To control for TANF program effects in modelswith employment as the outcome, we included an indicator for whether the respondent is exempt from TANFwork requirements. Although non-exempt respondents may be required to fulfill work requirements throughvolunteer work, we do not consider forced volunteer work as employment because one relationship tested iswhether greater ‘‘willingness-to-work’’ as measured by attitude is associated with current employment status.Our definition of employment captures both formal and informal work, because we consider any respondentworking for money to be employed.

The use of categorical dependent variables in structural equation models is sometimes questioned.However, in our case these variables represent an underlying continuous probability of being employedor in TANF, fitting the structural equation models framework for capturing latent concepts. Analysesin this paper are estimated in the AMOS structural equations program using full information maxi-mum likelihood (FIML) estimation procedures. This software accommodates the use of categoricaldependent variables. We discuss this issue in more detail in the section on estimation proceduresbelow.

4.2. Parental background

Our main explanatory variables are indicators of mother’s background. These include whether therespondent’s mother has at least a high school education, whether she worked, whether the family inwhich the respondent was raised received AFDC, and respondent’s race as a proxy for mother’s race.Since husband’s and wife’s educational attainment are highly correlated, we substituted father’s educationwhere respondents could remember father’s education but not mother’s (Mare, 1991). We expect the chil-dren of more highly educated women to have higher education levels, more labor market experience, andfewer years on AFDC (we use age at first TANF/AFDC receipt net of current age as a proxy for totalyears on AFDC). We also expect them to be more likely to value work. Individuals with a disadvantagedbackground (e.g., those from black, single-parent, and non-working families) are less likely to hold strongwork values.

4.3. Values

Among the values associated with the Protestant work ethic are the beliefs that the opportunity to getahead is available to all and that wealth is a product of effort and ability (Kluegel and Smith, 1986; Cor-razelli et al., 2001). Such beliefs should induce greater individual efforts to get and keep employment. Wemeasure values about achievement with a two-item scale based on questions where respondents were askedif they agreed or disagreed with each of the following statements: (1) ‘‘A person from a wealthy family has abetter chance of earning a lot of money than a person whose parents are poor;’’ and (2) ‘‘In America whatyou achieve largely depends on your family background.’’. Both questions had responses ranging fromstrongly agree to strongly disagree on a scale from 1 to 5. These questions have often been viewed in theliterature as an indicator of work ethic, with those believing in individual determination (disagreeing withthe above statements) having a strong work ethic. Weaker work ethics should lead to a lower probability ofemployment and a higher probability of TANF participation. Using factor analysis, we confirmed that thetwo items formed one factor that we call ‘‘attitudes toward social mobility’’ (ACHIEVE2). Respondentsthat agreed with one statement were very likely to strongly agree or agree with the other statement andmuch less likely to have discordant opinions across the two variables. Tests of association are highly signif-icant, and correlation of the two variables is 0.32 and the correlation between each variable and the latentfactor is 0.56.


4.4. Opportunity

We consider respondents’ education level, history of welfare participation, job experience and training,childbearing activity, physical limitations, and location to shape their labor market opportunities. Pastachievement affects employment opportunities because education, employment experience, and training con-tribute to human capital. There are more opportunities available to the more educated, more experienced, andmore skilled. In addition, factors that affect labor supply will limit the jobs respondents may take. For low-income women, household responsibilities such as child care may limit labor supply. Another factor that limitslabor supply and employer demand is a physical condition that prevents work or limits the number of hours ofwork. Vacancy rates in jobs for which respondents qualify may also differ between urban and rural areas andbetween the Delta and New Orleans.

In addition to affecting labor supply and employer demand, the factors discussed above may shape respon-dent values.Greater labor market attachment, higher skills, and more education are likely associated with stron-

ger work ethic. Non-metro and Delta respondents may have more traditional attitudes towards work thanNew Orleans inner-city respondents (Rank and Hirschl, 1993). Also, participants who have been on TANFlonger may not be as motivated to seek employment. Finally, TANF work requirements will increase respon-dents’ labor supply unless they are exempt from these. We expect persons with more education, more job expe-

rience and training, later entry into AFDC/TANF, no disability, and fewer children to have a higher probabilityof employment and lower probability of continued TANF participation.

Two possible determinants of welfare use and employment are absent in our model: having a criminalrecord and substance abuse. For example, Pager (2003:937) showed that ‘‘[a] criminal record presents a majorbarrier to employment;’’ this barrier is especially pronounced for blacks. And Delva et al. (2000) found a muchhigher incidence of drug use in welfare households than in other households. While they did not examine theconsequences of drug use for employment, drug use clearly lowers the likelihood of finding and holding on toa job. Unfortunately, the data set used for the present analysis does not have adequate information on either acriminal record or substance abuse. While the first wave of the panel survey did ask if the respondent has everbeen in jail, the number of persons responding in the affirmative was quite small. A bi-variate v2 test showedno significant association between a criminal record and employment status. The number of respondentsadmitting drug use was even smaller; there are too few admitted drug users in the panel survey to make evensimple statistics such as cross tabulations meaningful. While the absence of those two variables makes ourmodel less complete than desirable, we do note that the sample consists almost exclusively of women. Thelower crime rate and use of drugs among women when compared to men hopefully makes the omission ofthe two variables less consequential.

5. Analytic strategy and models

In order to test hypotheses about the intergenerational transmission of welfare and work, we conducted apath analysis using several structural equation models. We estimated a value model (ACHIEVE2) for each ofthe two dependent variables (employed and participating in TANF). In Fig. 2, we present an example of thepath diagram of the relationships hypothesized in our models. Each measure of parental background has adirect effect on: values (a latent construct observed in responses to attitude questions); five socioeconomicmeasures of opportunity (respondent’s years education, on-the-job training experiences, number of jobs since16, age at first AFDC, and number of children); and employment status. Each measure of opportunity has adirect effect on values and on employment status. Values have a direct causal effect only on employment statusand responses to attitude questions. Note that the values variable represents an unobserved latent construct;all other variables are observed indicators. As the causal path analyzed in each of the models is the same forboth outcome variables assessed, we only present the diagram for the model pertaining to employment.

6. Estimation methods

We developed multiple-indicator multiple-cause (MIMIC) structural equation models using the AMOSgraphic interface. Reduced form estimates of direct and total effects were estimated for each model. We

Fig. 2. Example of path diagram for a full model.


assume correlations among independent variables within each model. Indirect effects were estimated based onthe AMOS estimated parameters and covariance matrix. Although AMOS is designed to handle continuousvariables, the program may also be used to estimate effects on observed categorical variables used to representan underlying continuous phenomenon (Byrne, 2001). Observed TANF participation and employment repre-sent the underlying probability of employment/non-employment and of TANF participation (Table 1). Someof our 1998–1999 welfare participants were exempt from work requirements, others were not employed butlooking for work, and some were working and receiving TANF at the same time. Similarly TANF participa-tion may reflect different degrees of dependence on cash assistance. Recipients may both formally work andreceive cash assistance, while some may work informally even if exempt from work requirements. Others nei-ther receive TANF nor do they work.

Because more than 5% of our data had some missing information, we used the AMOS full informationmaximum likelihood procedures (FIML) to estimate models. In relatively large samples, this procedure pro-duces unbiased estimates if values are missing at random and the least biased estimates of missing valuescannot be ignored (Arbuckle, 1996; Byrne, 2001). Multivariate non-normality, required to produce correctv2 measures of model fit and coefficient standard errors in both generalized least squares and maximum like-lihood estimation, proved to be another problem in our sample. Although Bollen (1989:426–27, 439–47) rec-ommends distribution-free procedures to handle non-normality, Yuan and Bentler (1994) found that thesample size must be at least 2000 to obtain satisfactory results. With the number of variables and FIML pro-cedures, using bootstrap methods to derive empirical standard errors proved impractical with our data.Although we could impute missing values and then apply the bootstrap methods, imputation further exacer-bates the problems of using maximum likelihood estimation with non-normal data—a downward bias instandard errors. Other methods of adjusting the inflated model v2 and the deflated standard errors (e.g., Sator-ra–Bentler scaled v2) are not available in AMOS 4.01. Variable transformations also did not produce

Table 1Sample characteristics (N = 855)

Definition Mean or proportion S.E.

Outcomes

TANF participation On TANF = 1 0.78Employment Working = 1 0.33

Values

Achievement/perception about mobility Person from wealthy family has a better chance. . . 2.78 1.219What you achieve depends on family 3.14 1.089

Socioeconomic characteristics

Children Number of biological children 1.97 1.382Adult AFDC receipt Age at which first began receipt of AFDC 22.70 8.516Respondent’s education Number of years of education 8.18 5.548Labor market attachment Number of previous jobs 3.96 4.741Job training Number job training experiences 0.74 0.949

Background characteristics

Welfare family Grew up in a family that received AFDC 0.37Mother works Respondent’s mother worked 0.56Mother’s education Mother has equivalent of high school education or above 0.60Family type Single mother versus two parents 0.42Race Black = 1 0.98

Controls

Age 18 to 25 0.3326 to 54 (reference category) 0.6155 or older 0.07

Exemption from work Exempt from TANF work requirements 0.32Disability Physically unable to work or must limit hours 0.23Place of residence Delta metropolitan 0.16

Delta non-metropolitan (reference category) 0.32New Orleans 0.52

Notes: Sample includes only respondents who grew up in either single-mother or two parent families. If mother’s characteristic unknown,father’s characteristic was used as a substitute. Analyses not included in this paper used other measures of values based on attitudes aboutgovernment assistance and/or the role of luck vs. hard working in achieving success. As models using other measures of values had apoorer fit to the data, these are not included but results are available from the authors.


multivariate normality in our sample. Because of these problems, we may find significant effects for coefficientsin the models when these are not, in fact, significant. Thus, in the models presented, rejection of a path (insig-

nificant coefficients with p > 0.05) is a more powerful finding than failure to reject the path (significant coeffi-

cients with p < 0.05).

Because of our large sample size and multivariate non-normality, we do not use the model v2 to examinemodel fit. We use CFI as a measure of comparative model fit, RMSEA as a measure of model fit to the pop-ulation covariance matrix, and AIC (Akaike’s information criterion) and BCC (Browne–Cudeck criterion) tocompare non-nested models. The best fitting models for both TANF participation and employment measurevalues based on attitudes towards social mobility (Achieve2 in Table 2). These models have smaller RMSEAand lower AIC and BCC than other models. In the next sections, we present a brief overview of results from allmodels (Appendices A1 to A3) and use trimmed results from Achieve2 models to discuss the intergenerationaltransmission of welfare and work.

7. Results

All models indicated intergenerational transmission of work and welfare use through opportunities/expe-rience. In particular, models show that adult children of more educated parents have higher education which,in turn, increases the likelihood of employment. Also, children from welfare families enter welfare at an earlierage; but under the TANF welfare regime, it is older participants who are more likely to remain on welfare.We find little support for the intergenerational transmission of work or welfare use through values. Mother’s

Table 2Comparison of FIML model

Employment models TANF models

Full Trimmed Full Trimmed

Achieve2 RMSEA 0.033 0.024 0.036 0.028PCLOSE 0.999 1.000 0.992 1.000CFI 0.997 0.997 0.997 0.997Hoelter N .05 595 717 557 656AIC 413.300 372.234 382.160 350.169BCC 420.680 377.894 388.600 355.084

Notes: Models differ with respect to the measurement of values and correlations assumed in order to identify the model. Trimmed modelsconstrain to zero exogenous variables with significance p < .10 in the full model. RSMEA measures fit of model covariance to populationcovariance, with values less than .05 being acceptable. PCLOSE greater than .90 fails to reject hypothesis that RSMEA = 0. CFI comparesthe model to one in which none of the variables are correlated, .95 or higher is desirable. Hoelter N .05 gives the sample size at which amodel v2 of .05 is achieved. AIC and BCC decrease with better model fit. Analyses not included in this paper used other measures of valuesbased on attitudes about government assistance and/or the role of luck vs. hard working in achieving success. As models using othermeasures of values had a poorer fit to the data, these are not included, but results are available from the authors.

1.7

-0.3

9.20.1

-12.98.5

26.6 -2.6

0.2-34.7 -1.9

0.2 -3.7

2.4

-36.7 0.6-24.9

3.6

ACHIEVEMENTATTITUDES

PAST NUMBER OF JOBS

AGE FIRST AFDC/TANF

NUMBER OF CHILDREN

WELFARE FAMILY*

BLACK*

EMPLOYMENT

AGE25*

DISABILITY*

EXEMPT*

MOTHER'SEDUCATION*

JOB TRAINING

MOTHER WORKS*

EDUCATION

Fig. 3. Direct effects from trimmed employment model. Note: Effects given by standardized coefficients · 10 from trimmed model. Onlypaths significant at the 0.05 level or better shown. *Indicates exogenous variables (single parent family, labor market area, age greater than55 trimmed from model). Variables shown with no arrows and trimmed variables had effects constrained to zero.


welfare use or work has no direct effect on values (Figs. 3 and 4 and Appendix A1). Neither model shows asignificant effect of values on employment or TANF participation. Also, family background variables do notdirectly influence respondents’ values (Appendix A1). In all models, coming from a welfare family directlyincreases chances of continued TANF use (Appendix A3, B � 0.08). This would seem to support the intergen-erational transmission of welfare expected in the ‘‘welfare culture’’ model, except that there is no effect of par-ents’ use of welfare on values, the underlying mechanism assumed in the cultural model.

Figs. 3 and 4 represent path diagrams of our best fitting (trimmed) model for each dependent variable. InFig. 3, we look at structural equation results for employment and include only direct effects that are significantat the .05-level after trimming the model. Parental background influences work through education and num-ber of children. The adult children of mothers who work have higher education levels themselves (std.

0.711.24

-2-0.77

1.29-1.22

-1.470.92

0.872

1.18

0.79 1.03 1.98

0.71

0.224

0.84

ACHIEVEMENTATTITUDES

NUMBER OF CHILDREN

PAST NUMBER OF JOBS

EDUCATION

ON THE JOB TRAINING

MOTHER WORK*

BLACK*TANF

AGE25*

MOTHER'SEDUCATION*

AGE FIRST AFDC

WELFARE FAMILY*

Fig. 4. Direct effect from trimmed TANF model. Note: Effects given by standardized coefficients · 10 from trimmed model. Only pathssignificant at the 0.05 level or better shown. *Indicates exogenous variables (single parent family, labor market area, age greater than 55trimmed from model). Variables shown with no arrows and trimmed variables had effects constrained to zero.


coeff. = 0.920); a higher education level increases the chance of working (std. coeff. = 0.010). Similarly, theadult children of mothers with higher education also have more education (std. coeff. = 0.266) and a betterchance of working (std. coeff. = 0.010). As adults, children raised in welfare families tend to have more chil-dren and, as a result, are less likely to work (std. coeff. = 0.036 and �0.030, respectively). There is no directeffect of mother’s working or welfare background on adult children’s working. There are also no indirecteffects of mother’s characteristics on the outcome variables through achievement attitudes.

In Fig. 4, we look at the model for continued TANF participation. Here, we find that welfare background,race, and mother’s educational level indirectly influence TANF participation through the effect of the age atwhich respondents first started using welfare as adults. Adults raised in welfare households, blacks, and thosewith more highly educated mothers, tend to have begun welfare use at an earlier age (negative coefficients).However, beginning TANF at a later age is positively associated with continued TANF participation inour sample (std. coeff. = 0.129). This may be because our sample includes child-only cases where work require-ments and time limits are not in effect. In these cases, the adult payees (not parents) having custodial care ofqualified children are older than parents that are adult recipients. In this model, adult children whose familyused welfare have a stronger tendency to continue using TANF as adults (std. coeff. = 0.071).

8. Discussion

Although the effect of values is considered in both cultural and structural explanations for the intergener-ational transmission of welfare use and work behavior, few researchers include attitudinal measures in studiesof these phenomena. In addition, most research to date has tested individual hypotheses instead of sets of cau-sal relationships, yielding results that do not necessarily distinguish cultural explanations from structuralexplanations of welfare dependence. In our study, we also look at the effect of parental welfare use and socio-economic status on individuals’ welfare use and work. By incorporating attitudinal measures and a structuralequation methodology, we are able to test for the effect of underlying mechanisms assumed in structural andcultural arguments.

We find a direct effect of mothers’ welfare use on adult children’s TANF participation but not on attitudes.Together these effects suggest that there is intergenerational transmission of welfare use but not necessarily a‘‘welfare culture’’. The ‘‘welfare culture’’ argument largely rests on the poor having different attitudes than thegeneral population and raising their children with these attitudes. But the values expressed by the respondentsin our panel survey do not differ from values held by the general population, as can be shown with data from


the General Social Survey (GSS for 1984–1996).1 In our models, net of education, past labor market experi-ence, and number of children, mothers’ welfare use is not associated with differences in values. We find no evi-dence of the mechanism through which the ‘‘welfare culture’’ purportedly transmits welfare use. This isconsistent with results in Wilson’s (1996) study of inner city poverty and employment where he finds no dif-ference between the values of poor respondents in his study neighborhoods and values reported for nationalsamples. On the other hand, the indirect effect of mothers’ background on attitudes via respondents’ educa-tion, labor market experience, and household structure support hypotheses about how opportunity affects val-ues—i.e., the structural determination of culture.

Our results are consistent with earlier AFDC research showing an association between parents’ and adultchildren’s welfare use, but they appear to differ from Rank and Cheng (1995) who do not find parents’ welfareuse to be a significant determinant of adult children’s welfare use after controlling for adult children’s socio-economic status. However, the indirect effects in our TANF model (Fig. 4) show results similar to Rank andCheng’s (1995). We find, as do they, that net of parents’ welfare use, parents’ lower economic status is stronglyassociated with adult children’s lower education and more children. Several indicators of adult children’ssocioeconomic status are strongly associated with entering AFDC at an earlier age. Our TANF model resultsonly partially support Rank and Cheng’s conclusion that it is parents’ economic background but not theirwelfare use that drives adult children’s welfare participation. Net of other socioeconomic indicators, a welfarebackground increases the likelihood of adult children’s welfare use, possibly because these children haveknowledge of how public assistance works. This kind of cultural capital is consistent with Lewis’ (1966) ori-ginal presentation of the culture of poverty. It does not, however, represent the rejection of work assumed inthe ‘‘welfare culture’’ values argument.

Our employment model lends more support to Rank and Cheng’s (1995) conclusions and is also consistentwith Greenwell et al.’s (1998) results regarding the relationship of values and work. Greenwell et al. look atattitudes and work behavior among new mothers using the National Longitudinal Survey of Youth. Theypoint to the positive association of welfare background with willingness to use welfare as evidence of a ‘‘wel-fare culture’’. This ‘‘welfare culture’’, however, does not translate into behavior because adolescent willingnessto use welfare does not affect whether new mothers work years later. In our analysis, we find no direct rela-tionship between values and whether respondents work. Being required to work under new TANF regulationsand higher education increases the probability of respondents’ working.

In summary, our analysis of TANF participation and employment among recent welfare recipients in Lou-isiana provides little support for the existence of a ‘‘welfare culture.’’ We do, however, find evidence of thestructural determination of attitudes, welfare participation, and employment. Parental background affectssocioeconomic characteristics of adult children which, in turn, determines welfare use and work behavior.These results suggest that changes in welfare requirements since 1996 have reduced and will continue torestrain participation among poor families except in the child-only cases. Any reduction in welfare participa-tion among the children of recent welfare participants is unlikely to be the result of changed attitudes towardswelfare and work. It is more likely that the strategic use of public assistance by poor people will evolve, as newregulations change the opportunities available.

A potential limitation of this study is the sampling on the dependent variable, i.e., the restriction of the sam-ple to recent or current TANF participants. One might argue that while the value differences among therespondents have no direct effect on differences in employment and TANF participation, the TANF popula-tion as a whole subscribes to a set of work values that differ from those of the general population. However, aswe noted above, there is no statistically significant difference in the values expressed by the respondents in ourstudy and those held by respondents in the GSS. Moreover, successful welfare policies depend on our knowl-edge of what works among the potential welfare population. Our models based on data for current and recentTANF recipients precisely aim at providing such information.

Another limitation to the generalizability of this study to other states is the omission of child care. The linkbetween childcare and employment has been well established. Press et al. (2006) found that concerns withquality of childcare had the effect of increasing the level of depressive symptoms among women which, in turn,

1 Tabulations not shown but available from the authors.


could lead to detachment from employment. In another study of low-income women, Press et al. (2003) foundclear evidence for a positive effect of child-care subsidies on employment (not only finding a job but also keep-ing it). Similarly, Shlay et al. (2004) recognize the importance of child care for finding and keeping employ-ment and studied the reasons why many poor women do not use available subsidies for child care. Themodels did not include child care as a variable because the data used for this study did not have the appro-priate information required for the models. However, bi-variate analyses of the information available did notshow any relationship between child-care use and employment. This does not come as a surprise, because inLouisiana, TANF participants could have relatives paid by the state to be child care providers. Thus, theabsence of child-care information in this study of current and recent Louisiana TANF participants shouldnot affect our results in meaningful ways.

More than ten years have now passed since the Welfare Reform Act of 1996. In early 2006, Congress finallypassed a revision of this Act, increasing the number of hours that a woman has to work to be eligible forTANF receipt. The findings reported above are relevant for any further changes in welfare legislation. Withrespect to the intergenerational transmission of work, if the relationships found in this study hold for futuregenerations, then limiting welfare assistance will increase work in the children of recent welfare recipients’ onlyto the extent that it reduces their fertility as adults. According to our employment model, a more powerfulmeans of promoting work in the next generation is to improve the education levels of their mothers and toincrease opportunities for their mother’s to work. The strong association of mother’s work and higher educa-tion with children’s higher education produces a powerful indirect effect on children’s employment. In addi-tion, the positive direct effect of human capital on respondents’ employment suggests that investment ineducation, job training, and job readiness would result in even more women on TANF obtaining employment.By failing to support education or job creation for current and former welfare recipients, Louisiana risks per-petuation of labor force detachment among the poor in our study areas.

Appendix A1

Standardized direct and indirect effects on values, full models for employment out

ACHIEVE2 coeff.

Direct effects

Family background
Welfare family �0.046 Mother works 0.020 Mother’s education �0.010 Family type �0.045 Race 0.003
Socioeconomic characteristics
Adult AFDC receipt �0.031 Labor market attachment 0.130**
Children
0.083*
Respondent’s education
0.099**
Job training
�0.035
Controls
New Orleans 0.089*
Delta metropolitan
0.087*
Exemption from work
�0.013 Disability �0.035 Age 18 to 25 0.204**
Age 55 or older
�0.035
(continued on next page)


Appendix A1 (continued)

ACHIEVE2 coeff.

Indirect effectsa

Family background
Welfare family 0.013*
Mother works
0.016**
Mother’s education
0.036**
Family type
�0.015*
Race
�0.003**
Notes: Results are similar for TANF outcome.a Standard errors not estimated for indirect effects; significance assigned according to significance of socioeconomic variable direct

effect—see path diagrams in Appendix A2.* Significant at the .05 level.

** Significant at the .01 level.

Appendix A2

Path diagram of significant indirect effects, TANF and employment in full model.

+

+

-

-

+-

-

+

+

-

ACHIEVE2Past Number Jobs**

Mother works*

Black**

Mother H.S.Educ.**

Welfare Family**

Single Family*

Number Children* ACHIEVE2

ACHIEVE2Years of Education**

Mother works*

Mother H.S.Educ**

Appendix A3

Direct effects of values and family welfare background on TANF and employment status, full models

Employment
TANF
Coeff.
Coeff./S.E Coeff. Coeff./S.E
Direct
�0.009 �0.251 0.084 2.368*
Indirect thru Achieve2
0.015 0.591 �0.029 �1.176 * Significant at the 0.05 level.


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Documents

Welfare myths: The transmission of values and work among TANF families