Studies of Welfare Populations: Data Collection and Research Issues. Welfare Histories of the Caseload in July 1995

06/01/2002

Table 13-1 provides the distribution of the total number of months of AFDC benefit receipt for the full caseload overall and separately by the number of spells of receipt during the time frame. (To abbreviate, we call this total-time-on, or TTO.) Column 1 shows TTO for the entire caseload. This column shows that a majority of the caseload in July 1995 received benefits for more than 2 years and that a large portion (nearly 38 percent) received benefits for at least 5 of the 6 years in the preexit period. This is not surprising given that at any point in time, the caseload will be made up disproportionately of long-term beneficiaries. (See Bane and Ellwood, 1994, for a discussion of welfare dynamics.)

The bottom row of Table 13-1shows the overall distribution of the number of spells of the caseload in July 1995. The majority of cases had only one spell (57.2 percent) and just over a quarter had 2 spells (25.8 percent). The fraction of those with three or more spells is quite small; as only 14 percent fell into this category. Moffitt (this volume: Chapter 14) found that of those who were ever on AFDC of the 10 years of NLSY data used in the study, 48 percent had only one spell of receipt and only 8 percent had 4 or more spells. Thus, both of these studies show a small amount of turnover in the caseload. Table 13-1 also reports the distribution of TTO by the number of spells of benefit receipt. Of those who had only one spell, 46 percent had a long spell of more than 5 years. The rest of those with only one spell are distributed fairly evenly across the TTO scale. For those with 2 spells, a smaller fraction received welfare for more than 5 years (34 percent). Those with two spells are, however, more concentrated in the categories of 2-6 years of benefit receipt than those with only one spell. Finally, those with three spells of receipt are concentrated primarily in the range of 2-5 years of benefit receipt. Two-thirds, 67 percent, of those with at least 3 spells received benefits for a total of 2-5 years.

TABLE 13-1
Distribution of Total-Time-On AFDC in Months Between 7/89 to 7/95
by Number of Spells of AFDC Receipt Over Entire Period (percent distribution)
Total-Time-On(months) All Number of Spells
0 1 2 3+
0 3.1 3.1 -- -- --
1-6 4.8 -- 7.9 1.3 0
7-12 6.7 -- 8.9 5.5 1.7
-13-15 5.7 -- 5.4 7.3 5.2
19-24 6.3 -- 5.6 7.7 7.8
25-36 11.2 -- 8.6 13.7 19.6
37-48 11.9 -- 9.3 13.6 22.2
49-60 12.6 -- 8.4 16.5 25.6
61+ 37.7 -- 46 34.4 17.9
Total percent with number of spells   3.1 57.2 25.8 13.9
Note: Total number of observations = 48,216.  Maximum number of months = 71

Table 13-2 is a slight variation on Table 13-1. Instead of reporting the total number of months of benefit receipt, Table 13-2 reports the average spell length (ASL) of benefit receipt.(7) The first column gives the overall distribution of ASL. There is a cluster (26 percent) of the caseload with an ASL of more than 5 years. However, the majority of the caseload have ASLs of between half a year and 3 years.

The distribution of ASL for those with one spell is the same as in Table 13-1. For those with two spells of benefit receipt, more than half have ASLs of 2 to 3 years. For those with three spells, 11 percent have an ASL of less than half a year. An additional 35 percent have ASLs of less than a year. Thus, 45 percent of cases have short spells of benefit receipt on a relatively infrequent basis. However, 55 percent of those with three spells have ASLs of 1 to 2 years.

TABLE 13-2
Distribution of Average AFDC Receipt Spell Length in Months
Between 7/89 to 7/95 by Number of Spells of AFDC Receipt Over Entire Period (percent distribution)
Average Spell Lenth (months) All Number of Spells
0 1 2 3+
0 3.1 3.1 -- -- --
1-6 7.7 -- 7.9 6.8 10.4
7-12 13.8 -- 8.9 15 35.1
13-18 10.8 -- 5.4 13.7 30.2
19-24 10.1 -- 5.6 13.6 24.4
25-36 18.1 -- 8.6 51 0
37-48 5.3 -- 9.3 0 0
49-60 4.8 -- 8.4 0 0
61+ 26.3 -- 46 0 0
Total percent with number of spells   3.1 57.2 25.8 13.9

To capture the two concepts of average spell length and total number of spells in a less cumbersome way, three categories of welfare recipients were created: cyclers (more than two spells), short-termers (fewer than two spells and TTO of less than 2 years), and long-termers (fewer than two spells and TTO of 2 or more years). Table 13-3 illustrates the distribution of the caseload in July 1995 across these three categories. More than half the sample (55 percent) are long-term welfare users. Nearly a third (31 percent) are short-term users, and nearly 14 percent of the sample are cyclers.

TABLE 13-3
Long-termer, Short-termer and Cycler Status (percent distribution)
  Overall Leaver Stayer
Long-termer 55.3 42.9 66.7
Short-termer 30.8 39.1 23.1
Cycler 13.9 18 10.2

Moffitt (this volume: Chapter 14) found about one-third of the women ever on AFDC were cyclers, between 37 and 58 percent were long-termers, and between 23 and 44 percent were short-termers, depending on how these two concepts were defined. Using Maryland administrative data on the AFDC/TANF caseload from 1985-1998 and linked UI data, Stevens (2000) disaggregated the AFDC/TANF caseload from Baltimore City into four birth cohorts and observed each of the cohorts for a ten-year period. He also divided the caseload into the long-termer, short-termer, and cycler distinctions and found more short-term welfare recipients than long-term welfare recipients. About 50 percent of those on welfare during the time span were short-termers while about one-third were long-termers, which is almost exactly the reverse of findings from the Wisconsin data. In another study that used the Maryland data and similar definitions of dependence, but that examined 11 birth cohorts of women, the percent of the caseload that was short-termers ranged between 44-67 percentage, the percent that was longer-termers ranged from 35 to 47 percent, and the percent that were cyclers ranged from 3-19 percent (Moffitt and Stevens, 2001). Except for two birth cohorts, the percent of short-termers was always greater than the percentage of long-termers. The results of the Maryland studies that show more short-termers than long-termers in the caseload compared to results from the Wisconsin data that show more long-termers illustrate the point about compositional factors of different caseloads at different times. Given these different compositions, we might expect Maryland leavers to have better postexit outcomes than Wisconsin leavers who have greater welfare dependency, with all, else being equal.

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