Determinants of AFDC Caseload Growth. 1. California


Basic Caseload

The Basic caseload in California grew at an average annual rate of 3.9 percent over the entire period, almost twice as fast as the national rate. The model predicts average annual growth of 3.3 percent (top section of Exhibit 6.3). According to the model, the main contributors to growth were population growth and aging (1.7 percentage points per year), and the "other" variables -- primarily legalizations under IRCA (1.7 percentage points per year). Changes in the vital statistics and labor market variables made smaller positive contributions, while reductions in AFDC benefits had a substantial offsetting effect (-1.1 percentage points per year).

In most ways, the simulations indicate that California's experience over this period mirrors the experience of the rest of the country, but with differences in the magnitudes of the various effects. The most significant differences are:

  • Population growth and aging played a significantly greater role in California -- over twice as large as for the country as a whole. This factor alone accounts for 0.9 percentage points of the 1.7 percentage point difference between California's average caseload growth rate and that for the entire country. Another interesting feature is that the decline in this factor's influence over time is much greater in California; in fact, in the last year of the sample period this factor contributed -0.8 percentage points to caseload growth, compared to -0.4 percentage points in the country as a whole, presumably reflecting a reversal of cross-state migration patterns.
  • The estimated contribution of the labor market variables to growth in California's Basic caseload during the 1989.4 to 1993.3 period is over twice as large as their contribution to growth in the national caseload (3.4 percentage points per year vs. 1.5 nationally). This reflects the fact that California's recession was deeper and longer than that for the country as a whole.
  • The estimated contribution of the "other" variables -- primarily the IRCA immigration variable -- to growth in California's Basic caseload is much greater than for the country as whole. The difference in growth attributed to this factor over the whole period (1.2 percentage points per year), together with the difference for the population and aging factor, more than accounts for the difference between caseload growth in California and in the country as a whole. In the four years from 1989.4 to 1993.3, when most legalizations occurred, the average annual contribution of the other factors to growth in California's Basic caseload was 5.5 percentage points. According to Werner Schink, this finding is consistent with the large numbers of "child-only" cases opened in California during this period, although we have not had an opportunity to compare the magnitude of such openings to the predictions of the model.
Exhibit 6.3
Decomposition of California 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 2.1% 0.8% 1.2% 3.2% 0.2% 1.8% -4.5% 0.2%
1983.4 - 1989.3 2.8% 0.6% 2.2% 1.9% 0.8% -2.7% 0.2% 0.4%
1989.4 - 1993.3 7.5% 9.7% -2.2% 0.4% 0.7% 3.4% -0.3% 5.5%
1993.4 - 1994.3 3.2% 4.1% -0.9% -0.8% 1.1% 2.2% 1.1% 0.4%
1979.4 - 1994.3 3.9% 3.3% 0.6% 1.7% 0.6% 0.5% -1.1% 1.7%
Unemployed Parent 1                
1979.4 - 1983.3 23.1% 10.1% 13.0% 3.6% n.a. 11.1% -4.6% n.a.
1983.4 - 1989.3 -3.1% -10.7% 7.6% 2.7% n.a. -13.6% 0.2% n.a.
1989.4 - 1993.3 19.2% 18.8% 0.4% 1.0% n.a. 18.7% -0.8% n.a.
1993.4 - 1994.3 9.1% 5.2% 3.9% -0.5% n.a. 7.2% -1.6% n.a.
1979.4 - 1994.3 10.6% 3.8% 6.9% 2.3% n.a. 3.0% -1.5% n.a.
Average Monthly Benefit                
1980.4 - 1983.3 -2.2% 2.6% -4.8% n.a. 0.4% -0.2% 2.4% 0.0%
1983.4 - 1989.3 1.0% 1.2% -0.2% n.a. 0.6% 0.1% 0.4% 0.0%
1989.4 - 1993.3 -6.6% -3.0% -3.6% n.a. 0.5% -0.4% -3.7% -0.7%
1980.4 - 1993.3 -2.1% 0.2% -2.3% n.a. 0.5% -0.1% -0.4% 0.2%
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 contributions and timing of labor market factors and IRCA immigration to growth in California's Basic caseload are illustrated in Exhibit 6.4 (top panel), where we also compare predicted and actual caseload growth for the whole period. The model's state-level factors and federal legislation dummies predict caseload growth that is slower than actual growth over the period from the beginning of the sample through 1989, with the greatest divergence in growth rates occurring from 1984 on -- just as for the national caseload. From 1989 to 1992 the series move closely together. After 1992 predicted growth exceeds actual growth.

UP Caseload

Over the entire sample period, California's UP caseload also grew at a rate substantially faster than that for the nation -- 10.6 percent per year vs. 7.0 percent nationally (Exhibit 6.3, middle section).(5) As with the national caseload, the periods of greatest growth in the California UP caseload were 1979.4 - 1983.3 and 1989.4 - 1993.3; growth during the latter subperiod was especially strong in California (19.2 percent per year). Just as with the national caseload, the model predicts less than half of the growth of the California caseload in the earlier subperiod, predicts a larger decline than actually occurred in the following subperiod, but predicts most of the growth in the 1989.4 - 1993.3 subperiod. The labor market variables dominate the predicted series.

Werner Schink offered the following additional information about the history of the California caseload and suggestions for further analysis:

  • About 90 percent of refugees in California have been continuously on welfare since entering the country. Refugees are not captured in the model and, although relatively small in number, could help explain substantial caseload growth in California;
  • Two thirds of AFDC recipients in California score in the lowest decile on the Armed Forces Qualifying Test and 90 percent are in the lowest quarter. Measures of labor market strength that are more focused on low-skill jobs might improve the model's performance;
  • About two thirds of UP cases in California eventually transition to Basic. The model's specification does not reflect this; and
  • In California, it would be helpful to build separate models by racial/ethnic groups because their experiences are very different.


Exhibit 6.4

Actual and Predicted Caseloads for California, 1979.4 - 1994.3

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Michael Wiseman also reviewed our findings for California and compared them to his own findings in a recent time-series analysis of openings and closings. According to Wiseman, his model tracks the California caseload better than our model, as we would expect (see Chapter 2). The primary reason apparently is better measures of demographic variables than are available in other states.(6)

Average Monthly Benefits

The results of the AMB simulation for California (Exhibit 6.3, bottom section) are very similar to those for the country as a whole: actual AMB declines at an average annual rate of 2.1 percent, but the model predicts a small increase; the average rate of decline was 2.2 percent in the first three-year subperiod, but the benefit variables predict a 2.4 percentage points annual increase (again, not reflecting the effects of OBRA81 captured by the year dummies); and recent changes in benefits account for at least part of the decline in AMB during the last four-year subperiod. The AMB decline in the last subperiod was substantially larger in California than in the country as a whole (6.6 percentage points per year vs. 4.1 percentage points) and changes in the benefit variables account for more (3.7 percentage points per year vs. 1.9 percentage points).