Determinants of AFDC Caseload Growth. Notes


1. Each month's figure receives a weight equal to the ratio of the number of days in the month to the total number of days in the quarter in computing the average monthly caseload.

2. Initially, we had hoped to obtain separate average monthly benefit data for the Basic and UP programs, but ACF does not collect the data separately. For most quarters in the time series, quarterly data were available from ACF. When only monthly variables were available, quarterly data were computed by taking a weighted average of the AMB in each month of the quarter.

3. From 1980 through 1986, the second and fourth quarter values of the regional CPI are the average of the two bi-monthly values appearing in those quarters. For the first and third quarters, however, the value equals the one bi-monthly estimate in the quarter, February and August, respectively. From 1987 through 1995, is the average of the three monthly values in the given quarter.

4. We identify AFDC Basic units as those families or sub-families reporting having received AFDC benefits with a single reference person who has never been married, who is widowed, divorced, or separated, or whose spouse is absent. Based on conversations with individuals at ASPE, we also flag families headed by a married couples as AFDC Basic units if either parent has a disability or has held a job during the month in question. We classify all remaining families or sub-families receiving AFDC benefits as AFDC UP units.

5. Depending on the source for these initial rates, adjustments may also be made in order to obtain estimates that reflect average monthly caseloads.

6. We unsuccessfully attempted to produce state-level estimates of female headed households (FHHs). The plan required: 1) estimation of a nine-region pooled regression model for FHH using regional FHH estimates from the Current Population Survey (CPS) and vital statistics data aggregated to the regional level; 2) prediction of state values from the estimated model using state vital statistics data; and 3) controlling predicted state series to estimates from the 1980 and 1990 Censuses. However, these efforts failed to produce reliable estimates. The vital statistics variables proved to be very poor predictors of FHHs at the regional level. We attribute this to the erratic behavior of the FHH estimates over time within region. We expected that CPS-based FHH estimates at the regional level would be sufficiently reliable for our purpose, but this is apparently not so.

7. Monthly total unemployment by state were readily available from the BLS back to 1978. However, using this series would have limited the number of lags available for use in model. To obtain the maximum number of lags possible, we calculated and used the alternate total unemployment series described above. The correlation coefficient for the series available from the BLS and the calculated series was .93.

8. Although the value of MTBBR varies within a state over time, changes generally correspond to changes in federal requirements (OBRA-81 and DEFRA-84) and changes in the EITC. Thus, changes usually occur in the same quarter for most, if not all, states and are approximately equal across states. Overall, MTBBR follows a downward trend throughout the period.

9. A given family's maximum AFDC benefit may differ from the state's "typical" benefit as calculated by the ACF due to factors such as: locality, housing arrangements, family composition, or special needs.

10. More specifically, for each state we observed the quarter in which the nominal benefit changed after 1982. For most states, the quarter was the same every year, so we assumed that earlier changes were made in the same quarter in previous years. For states that did not follow a consistent pattern, with Florida being the most notable of these states, we assumed that changes before October 1982 occurred in the same quarter as the first change after October 1982. In addition, we cross-checked ACF data with semi-annual maximum monthly payment data from the Congressional Research Service. When a discrepancy appeared between the two series, an effort was made to explain the discrepancy and include the appropriate data.

11. We explored the use of effective benefit reduction rates estimated by Fraker, et al (1985) and McKinnish, et al (1995). Unfortunately, a series including all 50 states and the District of Columbia began in 1984 and only extended through 1991.

12. Technically, AFDC monthly benefits paid fall to zero as soon as the calculated benefit falls below $10; i.e., there is a notch in the disposable income schedule a few dollars below the earnings cut-off. Our measure smoothes over that notch.

13. The monthly standard allowance has varied over time as a result of federal legislation, in particular OBRA-81, DEFRA-84, and FSA-88.

14. A review of waivers implemented since 1991 appears in GAO (1996).

15. Merz, et al (1995) uses the term "therapeutic" for "medically necessary" and/or "elective" abortions.

16. The Appendix provides a more detailed explanation for the interpolation process used to create each quarterly series.