How Well Have Rural and Small Metropolitan Labor Markets Absorbed Welfare Recipients?. Estimating Welfare Recipients in Labor Force


To estimate the number of welfare recipients in the labor force, we collected caseload information from all regions and estimated labor force participation from a combination of caseload employment reports, state estimates produced by DHHS, and a study of TANF leavers from the National Survey of Americas Families (NSAF).

The change in welfare caseloads over time is due to two effects: the change in the number of welfare recipients who enter the welfare rolls (inflow) and the change in the number of welfare recipients who leave the rolls (outflow).

Change in Inflow

Changes in inflow can be caused by the economy and by welfare reform. For example, potential welfare recipients who might have entered the rolls under previous economic conditions (e.g., the 1991 recession) may be less likely to apply if they can find jobs easily in a strong economy. Potential welfare recipients might also be diverted from welfare due to welfare reforms, such as time limits, stringent work requirements, and state welfare diversion programs that either require an applicant to look for work before being approved for benefits or offer a one-time lump sum payment to help potential clients to avoid welfare altogether. These potential recipients might instead rely on family support for income or enter the labor market.

Change in Outflow

Changes in outflow also are due to the economy and welfare reform. For example, in a strong economy, more recipients might leave welfare due to better job opportunities in the labor market. Welfare reform policies also play a role. More recipients might leave welfare due to time limits and stringent work requirements. Recipients who leave may rely on family support for income or might enter the labor market. Some might have been working off the books while on welfare and could continue to rely on their shadow labor market activities for income after they leave the rolls.

For this analysis, we are measuring the change in stock between two points in time and not focusing on changes in flows. Therefore, our analysis assumes there is no net effect on the labor market when a person leaves welfare, but is replaced by another person who enters welfare.

Our analysis uses the number of welfare recipients who are newly employed. That is, our estimates include those who were not in the labor force initially (e.g., in a given month in 1993), but who entered at a later point in time (e.g., in a given month in 1996). The number of welfare recipients entering the labor market is estimated using the following equation:

(vi) (C0 C1) *(L1 W0) + C1 * (W1 W0)


C0 = Caseload at time(0)
C1 = Caseload at time(1)
W0 = Percent of caseload in labor force at time(0)
W1 = Percent of caseload in labor force at time(1)
L1 = Percent of leavers in labor force at time(1)

Note that C0 C1 represents the change as a result of welfare recipients leaving (net of those arriving) and others diverted from entering the rolls. While the formula appears to assume that welfare leavers and welfare stayers  those who continued to be on the rolls at time(1)  had equal labor force participation rates at time(0), this is not a necessary condition. We can assume that welfare leavers had a higher rate of labor force participation in the initial period than did stayers and still get the same results.(41)

Exhibit 4.4 presents each regions monthly caseload, for each relevant year, along with estimates of the percentage of welfare recipients and welfare leavers who were in the labor force. These estimates came from the following sources:

  • The state welfare agencies supplied the average monthly caseload estimates for the specific study regions.
  • A few of the state welfare agencies (Alabama, Missouri, New York, and Wisconsin) were able to estimate the percent of the caseload employed in the study regions. For Mississippi, Oregon, South Carolina, Tennessee, and Vermont regions, we used the state average, reported by DHHS.
  • The Urban Institute analyzed the NSAF, which surveyed families between February and November 1997. Approximately 61 percent of the families that had been on welfare at some point since 1995 and had left and remained off welfare at the survey date were employed.(42) Similar rates were found in the studies of welfare leavers funded by ASPE.
  • We estimated that a smaller percent of leavers (50 percent) were employed between 1993 and 1996. We know of no study that has estimated this percentage for this pre-PRWORA time period.

As this exhibit shows, New York, Vermont, and Wisconsin welfare recipients were more likely to be in the labor force while on welfare. These states offer relatively high cash grants that enable individuals with earnings to remain eligible for welfare. The Southern states, on the other hand, offer lower grants and have a lower share of the welfare population employed.

Exhibit 4.4
Monthly Caseloads and Participation in Labor Force
1993 1996 1998
  Monthly Caseload Caseload in Labor Force (%) Monthly Caseload Caseload in Labor Force (%) Leavers in Labor Force (%) Monthly Caseload Caseload in Labor Force (%) Leavers in Labor Force (%)

Decatur and Florence, Alabama

1,577 1.0 1,167 1.1 50.0 645 8.7 61.0

Rural Mississippi

45,384 9.1 36,565 8.1 50.0 19,096 7.6 61.0

Joplin, Missouri

2,081 4.5 1,906 4.6 50.0 1,271 10.1 61.0

Southeast Missouri

12,674 4.6 10,817 8.6 50.0 7,972 14.1 61.0

Jamestown, New York

3,154 17.0 2,516 24.0 50.0 1,975 27.0 61.0

North Country, New York

6,656 9.0 5,749 15.8 50.0 4,145 20.9 61.0

Medford-Ashland, Oregon

2,540 12.7 1,820 11.8 50.0 896 3.8 61.0

Central Oregon

1,342 12.7 1,026 11.8 50.0 635 3.8 61.0

Florence, South Carolina

2,619 6.8 2,469 9.8 50.0 1,665 16.8 61.0


10,081 12.0 9,210 23.1 50.0 7,591 22.7 61.0

Eau Claire, Wisconsin

2,037 28.2 1,116 27.9 50.0 302 13.6 61.0

Wausau, Wisconsin

1,162 22.5 785 23.1 50.0 234 15.8 61.0

United States

4,963,000 7.8 4,628,000 10.3 50.0 3,305,000 15.6 61.0
Source: Lewin calculations using data provided by state welfare agencies and DHHS.


(32) Technically, there are two supply curves behind the supply curve drawn, one for each of the population groups. The sum of labor supplied at a given wage from the two groups corresponds to total labor supplied at that wage on the supply curve shown. The shift in the labor supply curve for the welfare target group corresponds to the shift in the total labor supply curve. [Back To Text]

(33) The derivation of these equations can be found in Freeman (1977). They hold only approximately, except for infinitesimally small shifts. A simple way to derive them is to begin with the assumption that the demand and supply curves are linear in natural logarithms (i.e., assume that the wage and employment axes in Exhibit 4.1 are natural log scales). For small changes, changes in logs are equivalent to percentage changes in levels. The slope of the supply curve on the log scales is the inverse of the supply elasticity and the slope of the demand curve is the negative of the inverse of the demand elasticity. Given these slopes, Equations (i) and (ii) can be derived via the use of geometry. If percentage changes in the equation are replaced by changes in logarithms, and if the demand and supply curves are linear in the logarithms, the equations apply exactly. [Back To Text]

(34) We obtained data for all of our metropolitan regions from the BLS and for nonmetropolitan regions from State Employment Security Agencies (SESA) for 1993, 1996, and 1998. [Back To Text]

(35) Leete, L. & N. Bania (1999) [Back To Text]

(36) Lerman, R., P. Loprest, & C. Ratcliffe (1999). [Back To Text]

(37) Bartik, T. J. (1999). Displacement and Wage Effects of Welfare Reform. W.E. Upjohn Institute for Employment Research. Kalamazoo, MI. [Back To Text]

(38) Mishel, L. & J. Schmitt (1995). Cutting Wages By Cutting Welfare. Economic Policy Institute. Washington, DC. [Back To Text]

(39) Holzer, H. J. (1996). Employer Demand, AFDC Recipients, and Labor Market Policy. Institute for Research on Poverty Discussion Paper No. 1115-96. Michigan State University. East Lansing, MI. [Back To Text]

(40) Bernstein, J. (1997). Welfare Reform and the Low-Wage Labor Market: Employment, Wages, and Wage Policies. Economic Policy Institute Technical Paper #226. Washington, DC. [Back To Text]

(41) If we assume there are two groups  leavers (C0  C1) and stayers (C1)  and each group has an average employment rate at time(0) of WL0 and WS0, respectively, then the following equation measures the increase in total employed from time(0) to time(1):

(vii) (C0  C1) * (L1  WL0) + C1 * (W1  WS0).

The following identity also holds:

(viii) ( C0  C1) * WL0 + C1 * WS0 = W0 * C0 {total employed at time(0)}

Substituting the right-hand side of Eq. (viii) in Eq. (vii), yields the following:

(C0  C1) * L1 + C1 * W1  W0 * C0, which is equal to Eq. (vi)  [Back To Text]

(42) Loprest, P. (1999). Families Who Left Welfare: Who Are They and How Are They Doing? Washington, DC: The Urban Institute. [Back To Text]