If a newly unemployed parent in a potential AFDC family receives unemployment insurance (UI) benefits, the family is less likely to qualify for AFDC benefits than otherwise. We expect, therefore, that the impact of increases in the unemployment rate on AFDC caseloads would be inversely related to the share of unemployed persons who receive UI benefits. We also expect an inverse relationship between the share of unemployed persons with UI benefits and average monthly AFDC payments because UI benefits paid to AFDC family members reduce the size of AFDC benefits dollar for dollar. Because UI benefits are time limited (six months under normal circumstances in almost all states), the strength of these inverse relationships is likely to diminish substantially after two quarters. Extensions of UI benefit periods during severe recessions (usually an additional quarter) may increase the number of quarters over which the relationships are observed -- from one or two to three or four.
While the direction of the effects of an exogenous increase in UI benefits on AFDC participation and AMB seems clear, there is an important reason why we might not obtain findings that are consistent with expectations. UI program changes may mirror AFDC program changes in states. For instance, states that administratively tighten award of UI benefits out of fiscal necessity are likely to do the same for AFDC benefits. If such changes in the AFDC program are not captured in the AFDC program variables, changes UI program variables may proxy for them. Thus, tightening of UI benefits might be associated in the data with reductions in AFDC participation, rather than the hypothesized increase.
Like AFDC, the UI program is a state-federal program. Each state's program must comply with federal regulations and reporting requirements, but states have substantial latitude within those requirements concerning benefit eligibility and levels. Ideally, we would capture the essential program characteristics of state UI programs in one or two explanatory variables. We explored this approach during our work on participation in SSA's disability programs and found it infeasible, both because of the complexity of state programs and because of limitations on data availability. Hence, we adopted a simpler approach: we include the logarithm of the insured unemployment rate divided by the total unemployment rate as an explanatory variable in both the participation and average monthly benefit equations. Like the unemployment rate, the insured unemployment rate is available from the BLS, monthly. We use the average of each quarter's three months to construct the variable. We experimented with both current and lagged values of the constructed variable.
Because the UI measure is based on actual participation, it is especially susceptible to the problem discussed above -- reductions in the share of unemployed persons who are covered by UI may reflect administrative tightening or other factors that have a common effect on both AFDC and UI, inducing a positive relationship between the UI measure and AFDC participation.