CHIPRA Mandated Evaluation of Express Lane Eligibility: First Year Findings. b. Findings on Other Variables

12/01/2012

According to the results in the main models, the log transformation of the child population has a positive and statistically significant effect on enrollment as expected (Table IV.3). These results imply that a 1 percent increase in a state’s total child population would yield a 0.86 percent increase in quarterly Medicaid/CHIP enrollment and a 1.21 percent increase in Medicaid enrollment on average, holding all else constant. The coefficient on the unemployment variable is 0.007 in the Medicaid/CHIP enrollment model and 0.005 in the Medicaid-only model, but is statistically insignificant.


Table IV.4. Estimated ELE Effects for Alternative Models, 2007-2011 Quarterly SEDS Data

  Dependent Variable (log transformed)
  Total Medicaid/CHIP Enrollment Medicaid Enrollment Only
Main Regression Model 0.0420* (0.024) 0.0562** (0.026)
Alternative Specification of Control Variables
(1) State and quarter fixed effects only (unadjusted model)
0.0349 (0.028) 0.0406 (0.025)
(2) Unadjusted model+policy variables 0.0471* (0.024) 0.0587** (0.026)
(3) Unadjusted model +unemployment rate and child population 0.0346 (0.028) 0.0401 (0.025)
(4) Policy index instead of dummy variables 0.0478* (0.0280) 0.0518** (0.025)
Alternative Specification of Comparison States
(5) Include all 41 non-ELE states as comparison states
0.0335 (0.022) 0.0422 (0.026)
(6) 10% significance threshold for dropping comparison state 0.0360 (0.022) 0.0595** (0.026)
(7) 1% significance threshold for dropping comparison state 0.0377 (0.024) 0.0565** (0.025)
(8) Excluding states based on joint test 0.0244 (0.026) 0.0551* (0.029)
(9) Excluding outlier comparison states 0.0425** (0.020) 0.0726*** (0.023)
(10) Excluding top 5 and bottom 5 comparison states in terms of ELE effect 0.0364* (0.020) 0.0552** (0.024)
(11) Excluding top 10 and bottom 10 comparison states in terms of ELE effect 0.0277 (0.018) 0.0506* (0.025)

Source: CMS Statistical Enrollment Data System (SEDS) as of March 30, 2012, verified and provided by CMS.

Notes: (1) Robust standard errors clustered at the state level are in parentheses. (2) *p<.1, **p<.05, ***p<.01. (3) All models include state and quarter fixed effects (coefficients not shown). All other right-hand side variables are the same as those in the Table 3 main results. (4) Total enrollment includes children who were ever enrolled in Medicaid or CHIP during the fiscal quarter. Medicaid enrollment only includes children who were ever enrolled in Title XIX (Medicaid) or Title XXI Medicaid expansion CHIP programs during the fiscal quarter

CHIP = Children’s Health Insurance Program; CMS = Centers for Medicare & Medicaid Services; ELE = Express Lane Eligibility; SEDS = Statistical Enrollment Data System.


The results in Table IV.5 suggest that the ELE effect on Medicaid/CHIP and Medicaid enrollment varies across states. When we re-estimate each of the main models excluding one ELE state at a time, we find that the coefficient on the ELE variable is smaller in magnitude (compared with the main effect) when Iowa, Maryland, New Jersey, and Oregon are excluded, suggesting that the ELE effect might have been stronger in these four states. The ELE effect is no longer statistically significant at conventional levels when any one of these four states are individually removed from the Medicaid/CHIP model, whereas in the Medicaid model, only the exclusion of Oregon eliminates the statistical significance associated with the ELE coefficient (p-value = .12). However, the ELE effect in the Medicaid model remains statistically significant when Oregon is removed from some of the alternative model specifications that alter the composition of comparison states, such as alternatives 9 and 10. Altogether, this suggests that no single state’s experience drives the average effect in the Medicaid model.

Similarly, the ELE coefficients are positive and statistically significant in both the Medicaid-only and combined Medicaid/CHIP models, with magnitudes exceeding the average effect, when Iowa, Maryland, New Jersey, and Oregon are included in the sample one at a time. We also find a smaller but statistically significant effect for Alabama in the Medicaid-only model. In contrast, there is no evidence in favor of a positive ELE effect on enrollment when the other ELE states are included one at a time. These results hold when we use the main model comparison states and the comparison states specific to each ELE state. We also grouped states by type of ELE program (for example, ELE through income tax returns and ELE through the Supplemental Nutrition Assistance Program [SNAP]), but found inconsistent results across model specifications (results not shown).

The results in Table IV.6 suggest that ELE implementation had a sustained impact on Medicaid enrollment over the period of analysis. We explored this by including a continuous variable that measures the number of quarters since ELE was implemented in the state, along with an interaction term with the ELE dummy variable. We find that the interaction is positive and statistically significant at the 10 percent level in the Medicaid enrollment model only. This result suggests that the ELE effect on enrollment could be stronger the longer states have had ELE in place. However, given the limited number of post-ELE implementation quarters, the sensitivity of this result across model specifications, and the discontinuous nature of ELE implementation in some states, we will provide more confident estimates of the pattern of ELE effects over time in our subsequent analyses, described next.


Table IV.5. Estimated ELE Effect for Models on Different Subsets of ELE States, 2007-2011 Quarterly SEDS Data

  Dependent Variable (log transformed)
  Total Medicaid/CHIP Enrollment Medicaid Enrollment Only
Main Regression Model 0.0420* (0.024) 0.0562** (0.026)
Models Excluding Individual States:
Alabama 0.0509* (0.028) 0.0625** (0.030)
Georgia 0.0527** (0.024) 0.0642** (0.027)
Iowa 0.0295 (0.024) 0.0480* (0.028)
Louisiana 0.0554** (0.026) 0.0739*** (0.024)
Maryland 0.0325 (0.024) 0.0515* (0.026)
New Jersey 0.0382 (0.026) 0.0514* (0.027)
Oregon 0.0390 (0.024) 0.0344 (0.022)
South Carolina 0.0494* (0.026) 0.0636** (0.026)

Source: CMS Statistical Enrollment Data System (SEDS) as of March 30, 2012, verified and provided by CMS.

Notes: (1) Robust standard errors clustered at the state level are in parentheses. (2) *p<.1, **p<.05, ***p<.01. (3) All models include state and quarter fixed effects (coefficients not shown). All other right-hand side variables are the same as those in the Table 3 main results. (4) Total enrollment includes children who were ever enrolled in Medicaid or CHIP during the fiscal quarter. Medicaid enrollment only includes children who were ever enrolled in Title XIX (Medicaid) or TItle XXI Medicaid expansion CHIP programs during the fiscal quarter. (5) The Medicaid/CHIP models include 660 and the Medicaid model includes 820 state-quarter observations

CMS = Centers for Medicare & Medicaid Services; SEDS = Statistical Enrollment Data System

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