Determinants of AFDC Caseload Growth. E. SUMMARY OF THE FINDINGS

07/01/1997

1. The estimates we obtain for the effects of the business cycle on participation in the Basic program are substantial, and last longer than any we have found in the literature.

The relationship between the unemployment rate and the AFDC caseload is complex. Current changes in the unemployment rate have lingering effects on caseload growth for many quarters to come. Similarly, current AFDC caseload growth is affected not only by current changes in the unemployment rate, but also by unemployment rate changes from many quarters in the past.

The estimates imply that if the unemployment rate rises by one percentage point and then remains constant for a year, the AFDC Basic caseload by the end of that year will be 2.4 percent higher than it would be if the unemployment rate had not changed. This effect is somewhat larger than the four-quarter effects reported in any previous study.(9)

More significantly, our estimates indicate that a current increase in the unemployment rate affects caseload growth for the next 14 quarters (3.5 years). Previous studies have not found significant unemployment rate change effects after 4 quarters. It appears that we are able to detect these long lags in business cycle effects because we have used the information provided by the individual business cycle experiences of all states over two major cycles.

According to our estimates, if the unemployment rate were to rise by one percentage point and then remain constant for the next 14 quarters, the total increase in the Basic caseload over 14 quarters would be nearly six percent. Of course, this stylized scenario is unlikely. The unemployment rate typically increases by well over one percentage point in a recession, the increase is gradual and erratic, and the peak may be sustained or brief. Below, we describe the estimated effects of the two recessions in our sample period on the caseloads.

We estimate that the poor performance of the economy from 1980 to 1982 resulted in an average annual increase in the Basic caseload of 2.1 percent from 1980 through 1983, and that the sustained recovery that followed reduced the caseload at an average annual rate of 3.3 percent from 1984 through 1989. The impact of the business cycle during this period is not evident in the national caseload, which was essentially the same in 1983 as in 1970 and grew at an average annual rate of 1.0 percent from 1984 through 1989. The reason is that program changes substantially offset the business cycle effects (see below). We estimate that the less severe recession of 1990-91 resulted in average annual caseload growth of 1.5 percent from 1990 through 1993, about 23 percent of the actual average annual growth rate of 6.5 percent. Although the caseload grew by 0.4 percent in the last year of the sample, the recovery from the recession was already having a negative effect, estimated to be 0.8 percent in the last year.

The estimated business cycle effects for the UP caseload are also substantial, and longer lasting than those found previously. According to the estimates, a one percentage point increase in the unemployment rate would increase the UP caseload by 17.3 percent by the end of the year. The effects of a current change in the unemployment rate continue to affect the UP program for 14 quarters, similar to the effects on the Basic program. Based on the estimates, if the unemployment rate increases by one percentage point and then remains constant, the UP caseload would increase by 26 percent after 14 quarters. Cromwell (1986) obtained estimates of a similar magnitude, but after just four quarters. Other studies have found substantially smaller effects. The estimates of the combined effects of the unemployment rate and trade employment per capita are larger.

Again, this hypothetical scenario is unlikely, and we look to historical examples to demonstrate the actual effect of changes in the unemployment rate on the UP caseload. In the 19 states that had UP programs throughout the sample period, we estimate that the poor performance of the economy from 1980 to 1982 resulted in an average annual increase in the UP caseload of 15.3 percent from 1980 through 1983, or about 60 percent of the average annual increase of 25.1 percent. According to our estimates, the subsequent recovery from 1984 through 1989 reduced the caseload at an average annual rate of 16.6 percent, when the actual average annual decline was 7.9 percent. We estimate that the 1990-91 recession resulted in average annual caseload growth of 12.8 percent from 1990 through 1993, essentially all of the average annual growth of 13.1 percent. There was no change in the caseload in 1994, but our results indicate that the recovery was already having a small negative effect, estimated at 0.3 percent.

2. We obtain strong evidence of the effects of changes in three important program parameters--the maximum monthly benefit (MMB), the average tax and benefit reduction rate (ATBRR), and the gross income limit (GIL)--on participation.

We estimate that a ten percent real increase in the MMB (e.g., from $400 to $440) increases the Basic caseload by 2.7 percent and the UP caseload by 2.6 percent. We also estimate that a 10 percentage point reduction in the ATBRR increases the Basic caseload by 1.5 percent, but, somewhat surprisingly, has no impact on the UP caseload. Finally, we estimate that the increase in the GIL enacted under DEFRA84, from 150 percent of the state's need standard to 185 percent, increased both the Basic and UP caseloads by a little over one percent.

Our simulations indicate that the combined effects of program cuts related to OBRA81 reduced the Basic caseload at an average annual rate of 4.6 percent from 1980 through 1983 (mostly in the last two years of that period), more than offsetting the positive effect of the poor economy. The effect on the UP caseload was comparable.

3. The estimated contribution of growth and aging of the at-risk population to AFDC participation was high during the early 1980s (about two percent per year), but declined throughout the period studied.

The reason for the observed pattern is that the youngest members of the baby boom generation--those born in the early 1960s--were entering the age group at highest risk in the early 1980s, while smaller post-boom cohorts were entering that age group by the end of the decade. From 1980 through 1983, we estimate that this factor contributed an average of 2.0 percentage points to annual growth in the Basic caseload. This contribution gradually declined throughout the period and was actually negative by 1994, at 0.4 percent. Results for the UP program were comparable.

4. Legalizations of illegal aliens under the Immigration Reform and Control Act (IRCA) of 1986 appear to have contributed substantially to Basic caseload growth in some states during the period from 1988 to 1993.

Even though individuals legalized under IRCA were not eligible for benefits during a five-year waiting period, many of their children were born in the United States and had been eligible all along, but were apparently not enrolled because of deportation fears. It appears that many "child-only" cases were opened when parents became legal aliens. We estimate that IRCA legalizations contributed about five percentage points to average annual growth in California's Basic caseload from 1990 to 1993, and about 1.5 percentage points to growth in the national Basic caseload.

5. Declines in marriage and increases in non-marital births contributed noticeably to Basic caseload growth throughout the period examined.

These "vital statistic" variables account for average annual growth in the Basic caseload of 0.5 percentage points from 1980 to 1994 which is a little more than one-quarter of the total average annual growth in the Basic caseload of just under 2 percent. We did not find a statistically significant effect for the UP caseload, but this is not surprising because UP cases are two-parent families.

We expected to find that omitting these variables from the models would increase the estimated effects of the labor market and AFDC benefit variables on participation, based on the hypothesis that changes in the latter have an impact on the former. Changes in estimated effects were in the anticipated direction, but proved to be trivial. Thus, it would appear that other major factors are behind the decline in marriage and the growth in non-marital births.

We had originally hoped to develop state-level estimates of female-headed households for use in our models, but our efforts were not successful. Vital statistics variables--marriages, divorces, and non-marital births--were substituted instead. It may be that better measures of female-headed households would lead to stronger estimated effects for this factor, but we do not know.

5. Many other factors we examined were not found to have statistically significant, substantial estimated effects.

We were especially surprised that the Medicaid variables used in the analysis yielded very weak findings, given strong findings that appear in the literature. According to our estimates, the Medicaid expansions for women and children who were not on AFDC had a small positive effect on AFDC caseloads in states where the share of children in AFDC was previously small, and a small negative effect in states where the share of children in AFDC was previously large. We did not find a statistically significant effect for changes in the estimated value of Medicaid benefits.

The following findings are not very strong, and are subject to interpretation. It should be kept in mind that we examined a large number of possible explanatory variables, and any such examination is bound to yield a few "statistically significant" effects by random chance alone.

  • States that implemented "family caps"--limits on payments for children born to existing AFDC mothers--under 1115 Waivers experienced statistically significant reductions in their Basic caseloads according to some models we estimated, but not in their UP caseloads. These results are weak and it is not clear what conclusions should be drawn;
  • States that imposed restrictions on Medicaid funding of abortions or required parental consent or notification for minors experienced statistically significant reductions in their Basic caseloads according to some models we estimated, but not in their UP caseloads. For abortion restrictions to have a negative impact on the Basic caseload, they would presumably have to reduce fertility among the target population by more than any increase they cause in the number of pregnancies ending in live births. While the findings for the Basic caseload would be consistent with such an effect and are intriguing, they are not rigorous enough to support it on their own. Again, these results are not conclusive;
  • Administrative tightening of eligibility requirements for the Social Security Administration's disability programs (Social Security Disability Insurance and Supplemental Security Income) in 1977-78 had a statistically significant, positive impact on the Basic caseload a year later, but not on the UP caseload. As with the other factors described here, it is difficult to know to what extent these findings may be due to chance, or influenced by the effects of omitted variables;
  • The share of unemployed persons who are covered by unemployment insurance has statistically significant, positive coefficients in the Basic participation equations. The sign is contrary to what might be expected, and may reflect factors that have been omitted from the model and that have positive effects on both participation and the share of unemployed persons who are insured; and
  • The number of children receiving SSI benefits also has significant, positive coefficients in the Basic participation equations. The explanation of the counter-intuitive sign of this coefficient may be similar to that for the coefficient of the insured unemployment variable.

Other factors we tried that did not yield statistically significant findings are: average weekly wages in the trade industry; average weekly wages in manufacturing; total employment per capita; manufacturing employment per capita; dummy variables for other types of 1115 waivers (in addition to family caps); dummies for child support and paternity establishment laws; the ratio of employed men to the number of women of childbearing age; dummies for the existence and type of UP program (Basic participation equations only); a measure of cuts in state general assistance programs; SSI benefit levels, including state supplements; and the number of SSI children in the Zebley class.(10)

In many years, the changes in the state explanatory variables in the models account for most of the observed changes in the caseload, but there are important exceptions. We included "year effects"--dummy variables for each year to capture the average effects of omitted, or poorly measured, factors on the Basic and UP caseloads. For both caseloads, the coefficients are positive in most years and are statistically significant from 1985 to 1991, indicating that factors other than those captured in the state explanatory variables played a substantial role in determining caseload growth. For the UP caseload, the dummy coefficients are also positive and significant in 1980 and 1981. Possible reasons for these positive year effects include:

  • Effects of federal legislation that applies equally to all states;
  • Overestimation of the impact of the recovery from 1983 to 1989, and underestimation of the impact of the recession of 1990-91;
  • Effects of the relative decline in wages for low-skill work;
  • Underestimation of the contribution of immigration;
  • Underestimation of the role of changes in household characteristics;
  • Increases in the cost of health care and reductions in access to health insurance that were not captured with our Medicaid variables; and
  • Declines in job prospects for low-skilled workers that are not reflected in the unemployment rate and/or the trade employment variable.