Determinants of AFDC Caseload Growth. 1. Basic Caseload


The model provides several insights into the cycles in caseload growth during the sample period:

  • For the nation as a whole, and in all states examined, we found that the slow growth of the 1979.4 - 1983.3 period was the net result of substantial offsetting forces: the growth and aging of the population and the double-dip recession on the positive side, and the substantial cuts in AFDC benefits resulting from OBRA81 on the negative side. The impact of the OBRA81 cuts is all the more impressive when it is recognized that the recession would have caused substantial additional caseload growth in its absence. We estimate that the total effect of these cuts was on the order of 20 percent. The size of the estimated impact from these cuts vary little across the four states we examined.
  • For the nation as a whole, and in all states, we found that the influence of population growth and aging declined substantially over the period. That is, slower growth and, eventually, a decline in the size of the population most at-risk for AFDC family headship was a strong force working against accelerating growth during this period, making the caseload growth in the latter part of the period all the more striking.
  • The Immigration Reform and Control Act of 1986 eventually led to substantial caseload growth in at least some states, including California and, to a lesser extent, Florida, as illegal residents were legalized. Even though newly legalized parents were not eligible for benefits immediately, their U.S. born children were if other eligibility criteria were satisfied.
  • Most of the growth not accounted for by the state variables and federal legislation dummies in the model occurred between 1984 and 1992. The divergence between the actual and predicted series for Florida from 1987 to 1992 is especially striking. Possible reasons for the missed growth during this period include:

Effects of federal legislation that are captured by the coefficients of the calendar dummies in the regression model, but not included in the predicted series. This almost surely explains part of the growth, but how much is difficult to determine. It would certainly not explain the very high growth not accounted for in Florida;

Overestimation of the impact of the recovery from 1983 to 1989, and underestimation of the impact of the recession of 1990-91. It could be that characteristics of the recessions that are not captured in the model's variables explain exceptionally high growth in some states (as per Don Winstead's comments on Florida);

Underestimation of the contribution of immigration. We have not looked at the effects of legal immigration after the three-year waiting period, nor have we modeled the effects of refugees, whom we understand are a high participant group;

Underestimation of the role of changes in household characteristics -- especially the growth in female headed households -- CBO (1993) attributed much of the Basic caseload growth in the 1989 - 1992 period to this factor in their time-series analysis. We could not satisfactorily measure female headed households at the state level, and found that vital statistics variables played a less substantial role in predicting growth during this period;

Increases in the cost of health care and reductions in access to health insurance -- substantial efforts to capture these factors in the model were not very successful. Given the evidence of the importance of these factors from micro data analyses, however, we still believe they may have been important. Don Winstead's comments concerning Medicaid outreach efforts in Florida suggest that unmeasured Medicaid factors could be an important factor in some states. In previous studies of SSI applications and awards, we have found substantial evidence of similar effects in other states for SSI, but also have not been able to quantify them (Lewin-VHI, 1995b, 1995c, and 1995d); and

Declines in job prospects for low-skilled workers that are not reflected in the unemployment rate and/or the trade employment variable. This explanation of the growth not accounted for by the model over the entire period was favored by several welfare researchers when preliminary findings from this project were presented at a recent conference.