Determinants of AFDC Caseload Growth. 7. UP Results for 1991 - 1994

07/01/1997

FSA-88 mandated that all states have UP programs from October 1990 on. In this section we present estimates of the UP caseload model using data for the post-mandate period. Because the sample period is too short to use the Parks method, we use the alternative, weighted least squares (WLS) method.

The specification we report is somewhat different than the specification reported for the full-period model. We replicated that specification in our first set of post-mandate estimates, but found that the coefficients for the ratio of the ECO to the GIL were very insignificant. The evident reason for this is that the definition of the GIL was not changed during the subperiod. We also added two variables that had been dropped in the full period model because much of the cross-state variation in changes of these variables occurred in the subperiod: the IRCA immigrant variable and the Medicaid expansion variable. In addition, we added interactions between the seasonal dummies and a dummy for six-month UP programs that were introduced in some of the states affected by the mandate, on the expectation that the seasonal pattern for the caseload would differ from the seasonal pattern in states with 12-month programs.

We initially estimated models using changes for the full post-mandate sample, (1991.1 to 1994.3), but obtained results that made little sense. The coefficient for the 1990 year dummy (which estimates the annualized rate of growth from 1990.4 to 1991.1 that is not explained by changes in other variables) was extremely large, and the value for the 1991 coefficient was also very large. We traced the reason for this to the states that began their programs under the mandate. Because they started at zero in 1990.3, they experienced very rapid rates of growth for the first year. This is evident by comparing post-mandate estimates for the 19 states that had programs for the full period (Column 2 of Exhibit 5.4) to results obtained using just the 22 states that started their programs in 1990.4 (Column 4).(13) Dropping the first full year from the sample yields much more credible findings in the mandate states (Column 5), although year dummy coefficients continue to differ substantially from those for the full-period states (compare to Column 3). Hence, when pooling the data for all states, we added an interaction between each year dummy and a dummy for whether or not the state started its program under the mandate.

For the remainder of this section, we focus on the results using data for 49 states for the period 1992.1 through 1994.3 (Column 5) and compare them to estimates for the same model using the full period for the 19 states with UP programs for the full period (Column 1).(14)

The findings for the labor market variables are strong for the post-mandate period, although different in some respects from the full-period estimates. The long-run unemployment elasticity is 0.86 (compared to 0.97) and the long-run trade employment elasticity is -5.7 (compared -2.8). The large trade elasticity is primarily influenced by the data for the mandate states; using that sample alone, the elasticity is -10.3 (Column 5), compared to a post-mandate estimate of -1.7 for the 19 full-period states (Column 3). Hence, there is evidence of very strong business cycle effects, but there are differences in the findings for mandate and non-mandate states. We have not had an opportunity to explore these differences further.

The subperiod findings for the MMB and, especially, the ATBRR are puzzling. For the post-mandate estimates using just the 19 full-period states, the sign of the long-run MMB elasticity is opposite that expected and its magnitude is large. For the 22 mandate states, the sign is positive, as expected, but the coefficient is exceptionally large. When all states are combined, the estimate is credible. The problem may be inadequate independent variation in this variable over the subperiod, especially among the two subsets of states.

We did find significant results for the IRCA immigrant variable, but predominantly in the mandate states. Note that the IRCA coefficient is also significant in the full-period estimates for the 19 full-period states, whereas it was not when we used the Parks method for the full period. This change may be related to other changes in the specification, but it also may be due to the large weight given to California in these estimates.

We did not find evidence of an effect of the Medicaid expansion except marginally in the full-period estimates for the 19 full-period states. Recall, however, that we dropped this variable from the UP specification reported earlier because of its insignificance when we used the Parks method.

Exhibit 5.4

Regression Results for Post-mandate Unemployed Parent Caseload Models a
Weighted Least Squares
Dependent Variable is change in ln(participation/expected participation)
  19 States with UP Programs 22 States with  
    for the Full Sample Mandated UP Programs 49 States
Explanatory   1979.4- 1991.1- 1992.1- 1991.1- 1992.1- 1991.1- 1992.1-
Variables b   1994.3 1994.3 1994.3 1994.3 1994.3 1994.3 1994.3
ln(unemployment rate) a0 0.092 -0.026 0.002 -0.026 0.006 -0.012 0.027
(PDL: L = 14)   (6.06) (-0.85) (0.05) (-0.28) (0.07) (-0.45) (1.04)
  100xa1 -0.422 0.793 0.634 1.652 1.082 0.756 0.371
    (-2.47) (2.45) (1.77) (1.61) (1.31) (2.74) (1.40)
  1000xa2 0.013 0.038 0.055 -0.052 0.004 0.006 0.029
    (1.46) (2.63) (3.04) (-0.93) (0.09) (0.44) (2.22)
  long-run elasticity 0.973 0.489 0.716 1.343 1.249 0.666 0.856
ln(trade employment per cap.) a0 -0.839 -1.862 -1.199 -3.912 -3.479 -2.816 -1.994
(PDL: L = 6)   (-5.85) (-6.00) (-3.11) (-6.29) (-6.76) (-12.03) (-8.61)
  a1 0.144 0.394 0.317 0.757 0.669 0.542 0.394
    (4.58) (5.18) (3.37) (5.24) (6.05) (9.78) (7.52)
  long-run elasticity -2.849 -4.76 -1.736 -11.487 -10.304 -8.33 -5.684
ln(maximum monthly benefit) current 0.235 0.287 -0.080 0.048 1.429 0.448 0.789
    (2.38) (0.81) (-0.17) (0.05) (1.58) (1.42) (2.40)
  1st lag 0.141 -1.305 -1.112 -1.933 1.170 -0.769 0.111
    (1.31) (-3.43) (-2.39) (-1.67) (1.30) (-2.24) (0.31)
  2nd lag 0.040 -0.183 -0.493 2.616 0.019 1.351 0.106
    (0.41) (-0.52) (-1.19) (2.88) (0.03) (4.45) (0.36)
  long-run elasticity 0.416 -1.201 -1.685 0.730 2.618 1.030 1.006
average tax and benefit current 0.216 -0.083 0.044 0.194 -0.206 -0.177 -0.223
reduction rate   (2.59) (-0.64) (0.29) (0.39) (-0.56) (-1.49) (-1.98)
  1st lag -0.211 -0.107 -0.034 1.190 1.180 0.141 0.134
    (-2.56) (-0.66) (-0.18) (2.11) (2.78) (0.99) (1.06)
  2nd lag -0.166 -0.043 0.047 1.358 1.337 0.283 0.292
    (-2.82) (-0.29) (0.28) (2.65) (3.53) (2.19) (2.50)
  long-run effect -0.160 -0.233 0.057 2.742 2.311 0.246 0.203
OBRA81 current -0.064            
    (-3.23)            
  1st lag -0.005            
    (-0.26)            
  long-run effect -0.069            
DEFRA84 current 0.011            
    (0.85)            
IRCA immigrants per 100c 1st lag 0.326 0.365 0.040 2.109 1.647 1.035 0.458
    (2.40) (1.94) (0.17) (2.31) (1.77) (4.56) (1.97)
Medicaid expansion current -0.192 -0.151 -0.139 1.149 -0.408 -0.133 -0.082
    (-1.97) (-1.21) (-1.04) (0.80) (-0.32) (-0.98) (-0.67)
Seasonal Dummies Spring -0.220 0.006 -0.109 0.029 0.093 0.062 -0.045
    (-8.79) (0.11) (-1.52) (0.12) (0.54) (1.14) (-0.82)
  Summer -0.341 -0.011 -0.116 -0.040 0.030 0.073 -0.061
    (-10.71) (-0.16) (-1.22) (-0.18) (0.19) (1.16) (-0.98)
  Fall -0.140 0.147 0.002 -0.143 -0.159 0.210 0.069
    (-5.15) (2.72) (0.02) (-0.73) (-1.11) (4.17) (1.31)
interaction of dummy for states Spring       -0.240 -0.192 -0.170 -0.240
with six-month UP programs and         (-1.55) (-1.74) (-1.69) (-3.12)
seasonal dummies Summer       -0.343 -0.079 -0.392 -0.169
          (-2.14) (-0.66) (-3.71) (-2.08)
  Fall       0.484 0.668 0.188 0.392
          (3.07) (6.00) (1.88) (5.09)
interaction of dummy for states with 1991           4.954  
UP programs mandated under             (36.66)  
FSA-88 and year dummies 1992           0.701 0.501
              (7.73) (6.18)
  1993           0.368 0.300
              (4.06) (5.30)
  1994           0.014 -0.053
              (0.16) (-0.93)
  1995           0.026 -0.061
              (0.25) (-0.95)
Calendar Year Dummies 1979 0.653            
    (13.25)            
  1980 0.496            
    (12.46)            
  1981 0.338            
    (7.56)            
  1982 0.159            
    (4.00)            
  1983 0.197            
    (5.96)            
  1984 0.170            
    (4.76)            
  1985 0.223            
    (6.63)            
  1986 0.230            
    (6.71)            
  1987 0.156            
    (4.84)            
  1988 0.199            
    (6.16)            
  1989 0.289            
    (8.25)            
  1990 0.298 0.319   5.330   0.314  
    (8.24) (4.27)   (24.36)   (4.59)  
  1991 0.141 -0.013 -0.026 0.706 0.151 -0.068 -0.159
    (3.76) (-0.22) (-0.36) (4.14) (0.95) (-1.34) (-2.77)
  1992 0.158 -0.063 -0.002 0.413 0.407 -0.042 0.019
    (4.26) (-1.24) (-0.04) (2.56) (3.59) (-0.90) (0.41)
  1993 0.225 -0.084 -0.012 0.113 -0.027 -0.050 -0.005
    (6.00) (-1.41) (-0.16) (0.59) (-0.17) (-0.92) (-0.08)
  1994 0.134 -0.187 -0.111 0.519 0.346 -0.006 0.052
    (3.31) (-2.81) (-1.29) (2.26) (1.88) (-0.11) (0.83)
Auto-Regression Correction 1st Lag 0.233 0.257 0.266 0.227 0.340 0.271 0.324
    (7.76) (4.27) (3.71) (4.02) (4.87) (7.45) (7.50)
                 

a. T-statistics in bold are at least 2.0 in absolute value.

b. 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.lagged the number of periods indicated. For the polynomial distributed lag (PDL) variables, the coefficient of the variable lagged j periods is ao + a1 j + a2j2 for j=0, 1, 2, ...L. Other variables are lagged the number of periods indicated.

c. Variable is amoving average of previous four quarters.