Determinants of AFDC Caseload Growth. 1. Basic Caseload


1979.4 - 1983.3 Subperiod

For this four-year subperiod, average annual growth of the Basic caseload was essentially zero, but zero growth was the net effect of very large, offsetting changes (Exhibit 6.1, top section). According to our estimates, the labor market variables account for average annual caseload growth of 2.1 percentage points per year and AFDC benefit reductions account for a decline of 4.6 percentage points per year. This probably understates the impact of benefit reductions associated with OBRA81 because the estimated effects of the benefit reductions do not include any effects of OBRA81 that are captured by the calendar year dummies for 1981 and 1982; after adjusting for seasonal factors, the coefficients of these dummies imply reductions of 2.8 and 1.0 percentage points that might also be attributable to OBRA81. In total, the findings imply that OBRA81 reduced the Basic caseload by approximately 20 percent, after controlling for other factors.

Another important, but less widely recognized, feature of this period is that the population in the age group most at-risk for participating in AFDC was growing at a rapid rate as the tail-end of the baby boom generation -- those born in the early 1960s -- was entering the age group; those born in the year usually recognized as the last baby boom year, 1964, turned 16 in 1980. According to our estimates, this growth contributed 2.0 percentage points per year to average annual caseload growth during the period. Changes in the vital statistics variables and in other variables in the model made modest contributions to growth.

1983.4 - 1989.3 Subperiod

During this subperiod the caseload grew at an average annual rate of 1.0 percent. According to our estimates, economic growth reduced the annual growth rate of the caseload by approximately 3.3 percentage points. The AFDC benefit changes captured by the state-level variables made a positive contribution of 0.2 percentage points per year. The effect of AFDC program changes are likely understated in the simulations, however, because the state-level variables do not fully reflect changes mandated by DEFRA84 and other federal legislation that

partially reversed some of the changes of OBRA81. Growth accounted for by population growth and aging declined from 2.0 percentage points in the previous period to 0.5 percentage points as the smaller post-baby boom cohort began entering the at-risk age group. The vital statistics variables contributed 0.7 percentage points per year. The state level factors in the model accounted for nearly all the growth during this period.

Overall, the model predicts an average annual decline of 1.8 percent per year. Given actual average growth of 1.0 percent, growth of 2.8 percentage points was due to other factors not captured in the model.

Exhibit 6.1
Decomposition of National Caseload and Average Monthly Benefit Series
  Average Annual Growth Rate Annual Growth Rate Accounted for by:
Program, Period, and Model Actual Accounted for by Model Not Accounted for by Model Population Growth and Aging Vital Statistics Variables Labor Market Variables AFDC Benefits Other Variables
1979.4 - 1983.3 0.0% -0.1% 0.1% 2.0% 0.3% 2.1% -4.6% 0.2%
1983.4 - 1989.3 1.0% -1.8% 2.8% 0.5% 0.7% -3.3% 0.2% 0.1%
1989.4 - 1993.3 6.5% 3.8% 2.7% 0.1% 0.5% 1.5% 0.1% 1.7%
1993.4 - 1994.3 0.4% 0.8% -0.3% -0.4% 0.5% -0.8% 1.3% 0.2%
1979.4 - 1994.3 2.2% 0.4% 1.8% 0.8% 0.5% -0.4% -1.0% 0.5%
Unemployed Parent 1                
1979.4 - 1983.3 25.1% 12.2% 12.9% 1.7% n.a. 15.3% -4.9% n.a.
1983.4 - 1989.3 -7.9% -15.4% 7.5% 1.2% n.a. -16.6% 0.6% n.a.
1989.4 - 1993.3 13.1% 13.0% 0.1% 0.7% n.a. 12.8% -0.4% n.a.
1993.4 - 1994.3 0.0% -1.7% 1.7% -0.3% n.a. -0.3% -1.1% n.a.
1979.4 - 1994.3 7.0% 0.9% 6.1% 1.4% n.a. 0.9% -1.4% n.a.
Average Monthly Benefit                
1980.4 - 1983.3 -3.3% 0.8% -4.1% n.a. 0.2% -0.2% 1.1% -0.3%
1983.4 - 1989.3 -0.2% 0.5% -0.7% n.a. 0.5% 0.1% -0.1% 0.0%
1989.4 - 1993.3 -4.1% -1.7% -2.3% n.a. 0.3% -0.3% -1.9% 0.2%
1980.4 - 1993.3 -2.0% 0.0% -1.9% n.a. 0.4% -0.1% -0.3% 0.0%
1. The UP caseload model does not include the vital statistic variables and the AMB model does not include a variable for population growth and aging. The UP caseload simulations are for the 19 states with UP programs throughout the sample period only.

1989.4 - 1993.3 Subperiod

This four-year period is one of very rapid growth in the Basic caseload, at an average rate of 6.5 percent per year. According to the model, the deteriorating economy accounts for 1.5 percentage points of that growth, and the vital statistics variables account for another 0.5 percentage points. The variables in the "other" category contributed a substantial amount (1.7 points per years); this is primarily attributable to the IRCA immigration variable. AFDC benefit changes captured in the state-level variables contributed just 0.1 percentage points to growth. Again, this neglects any effects of federal legislation that might be picked up by the year dummies. The contribution of population growth and aging continues to decline, to 0.1 percentage points per year. The estimated effects of all state-level factors in the model account for 3.8 percentage points of annual growth, combined, leaving 2.7 percentage points attributable to other factors that could not be measured in the model .

1993.4 - 1994.3 Subperiod

Caseload growth decelerated sharply in the last year of the sample period, to just 0.4 percent. The model also predicts decelerated growth, although not as low as actual growth--0.8% compared to 0.4%. Two factors account for the slow growth: an improving economy contributes -0.8 percentage points and a decline in the size of the at-risk population contributes -0.4 percentage points. These factors are offset by growth attributable to the vital statistics variables of 0.5 percentage points and by the AFDC benefit variables of 1.3 percentage points. The latter growth is attributed to the effect that the expansion of the EITC had on the average tax and benefit reduction rate. Additional factors that could not be measured by the model caused slight declines in the caseload, accounting for the difference between 0.4% and 0.8%

Full Period Findings

The average annual growth rate of the Basic caseload over the period was 2.2 percent. Of this growth, 0.4% per year is attributable to state level factors in the model. Thus, 1.8 percentage points per year of growth are due to factors outside of the model. This disguises the fact, however, the state-level factors and the two federal legislation dummies (OBRA81 and DEFRA84) in the model substantially help explain the large cycles in growth during the period. It also hides the fact that some factors in the models made substantial positive contributions to growth over the period and others made offsetting negative contributions.

Positive contributions come from three identified sources. First, population growth and aging contributed an average of 0.8 percentage points per year. Second, declines in marriage and increases in out-of-wedlock births (the vital statistics variables) contributed average growth of 0.5 percentage points per year. Third, other variables -- especially the IRCA immigration variable -- account for average growth of 0.5 percentage points per year.

Offsetting the factors contributing to positive growth were improvements in the labor market and reductions in benefits. According to the model, these latter factors reduced growth by an average of 0.4 and 1.0 percentage points per year, respectively.

Most of the difference in growth between the predicted and actual series occurs between 1983.4 and 1991.4. This is evident in Exhibit 6.2 (top panel) where we plot the two series. As in Exhibit 1.1, we have graphed logarithms of the caseload, so the slope of each series plot represents the growth rate. The predicted series is normalized to equal the actual series in 1989.4. That is, we use 1989.4 as the base period for the predictions and predict forward and backward from that quarter We have also plotted series showing the contributions of the labor market variables and the IRCA variable.(3) It seems likely that the cause of the substantial divergence in the actual and predicted series is the result of several factors not captured in the state-level variables. We discuss this issue further in Section D, after examining the other simulations.