Determinants of AFDC Caseload Growth. a. Population Characteristics

07/01/1997

A general description of the methodology we use to capture the effects of population characteristics appears in Chapter Three. Recall that this requires the construction of "expected participation" variables, plus age adjustments to selected economic variables. We provide more details on the construction of expected participation variables here; details of the age-adjustments appear in later discussions of the variables to be adjusted. We also discuss the immigration variables here.

Expected Participation

The state-level population characteristic estimates needed for constructing the expected participation variables are available only on an annual basis. Hence, we have constructed an annual average monthly participation series for each program and then expanded the series to a quarterly series, using the methodology described in Chapter Three.

The following is a description of the construction of the expected Basic and UP caseload variables. Calculation of the expected total recipient and child recipient variables follows this same methodology (see the Appendix).

We employ three types of data to construct the expected caseload variables. The first type is AFDC participation by type of family (one-parent versus two-parent) and age of head for 1990, estimated using the 1990 Survey of Income and Program Participation (SIPP).(4) We use the SIPP data to compute initial national age-specific participation rates in the base period for the two programs. The rate for the Basic program in each specific age group is the proportion of women in an age group who head a one-parent AFDC family. The corresponding initial rate for the UP program is the number of men in the age group who are a parent in a two-parent AFDC family.(5)

The second type of data is national Current Population Estimates by age and sex in 1990 from the Bureau of the Census, and were used to control our initial participation rate estimates to national totals. For the Basic program, we multiply the initial age-specific participation rates by the number of women in the corresponding age group and then add across age groups to get implied estimates of the national Basic caseload in the base period. We then adjust all of the initial age-specific participation rates by the ratio of the actual caseload average monthly caseload for the period (from ACF statistics) to the estimated caseload. We repeat this process for the UP program, but using age-specific estimates for the number of men.

The third type of data is state Current Population Estimates by age and sex, from the Bureau of the Census, used with age-specific participation rates to construct the expected participation series for each state. For the Basic program, we multiply the age-specific participation rates for the base period by the number of women in the corresponding age group for each state and quarter and then add across age groups to obtain the value for the expected Basic caseload in that state for that quarter. We follow this same procedure for the UP program, but using the population estimates for men.

Immigration

We employ two measures of immigration in our models: the total number of immigrants by state and the number of aliens per thousand population legalized under the Immigration Reform and Control Act (IRCA) of 1986. We obtained fiscal year data for both series from the Immigration and Naturalization Service (INS). INS data for total immigrants cover the period from FY1978 through FY1994 while data for IRCA legalizations cover the period from FY1989 through FY1994; no IRCA legalizations occurred before FY1989. We interpolate quarterly values for each variable from the fiscal year series to obtain the series used in the models. We experimented with several variants of the IRCA variable including lagged and lagged moving average constructions. The final construction included in the models is the movement of the four previous quarters.