Population Growth and Aging
We did not include a variable for population growth and aging in the AMB equation.
|Average Monthly Benefit Regression Results|
|Sample: 51 states, 1980.2 - 1993.3|
|Dependent Variable is Change in ln(average monthly benefit)|
|Variables c||Lag||Coefficient||T-statistic b|
|(PDL: L = 14) a||100xa1||-0.338||-6.6|
|long run elasticity||-0.030|
|ln(trade employment per cap.)||a0||0.127||14.7|
|(PDL: L = 10) a||10xa1||-0.615||-24.9|
|long run elasticity||-0.406|
|ln(maximum monthly benefit)||current||0.663||73.0|
|average tax and benefit||current||-0.133||-8.8|
|reduction rate||1st lag||-0.142||-9.4|
|AFDC earnings cut off||current||-0.026||-3.7|
|relative to gross income limit||1st lag||-0.003||-0.5|
|6-month UP program||current||0.035||4.6|
|12-month UP program||current||0.013||4.5|
|UP started in 1990.4||current||-0.038||-5.8|
|family cap||1st lag||0.055||3.5|
|IRCA immigrants per 100||1st lag||*||0.007||1.4|
|ln(% insured unemployed)||1st lag||0.032||8.0|
|abortion: parental consent/notice.||1st lag||-0.015||-6.8|
|Medicaid restricted||1st lag||-0.016||-7.5|
a For the polynomial distributed lag (PDL) variables, the coefficient of the variable lagged j periods is a0 + a1 j + a2 j2 for j = 0, 1, 2, ... L. Other variables are lagged the number of periods indicated.
b. T-statistics in bold are at least 2.0 in absolute value.
c. All explanatory variables except quarter and year dummies are changes. Quarter and year dummies are equal to .25 in the quarters/years indicated so that coefficients can be interpreted as annualized rates of growth.
d Variables are moving averages of previous four quarters.
Only one of the vital statistics variables, out-of-wedlock births, appears in the final AMB specification and it has a significant, positive coefficient. More out-of-wedlock births among existing AFDC families would be expected to increase AMB, but families entering the caseload as the result of a first out-of-wedlock birth would presumably receive lower than average benefits.
The IRCA legalizations variable appears in the final specification with a positive, but insignificant, coefficient. The positive coefficient seems at odds with the hypothesis that the large coefficients on this variable in the Basic participation models reflects child-only families; presumably such families would receive lower than average benefits unless the average number of children in such families is substantially larger than average.