Premium Subsidies, Medicaid Expansion & the Mandate: Coverage - - PowerPoint PPT Presentation

Premium Subsidies, Medicaid Expansion & the Mandate:

Coverage Impacts of the Affordable Care Act

Ben Sommers & Molly Frean Harvard T.H. Chan School of Public Health Jonathan Gruber, MIT and NBER AcademyHealth Annual Research Meeting June 2016

Acknowledgments

• This project was supported by grant number

K02HS021291 from the Agency for Healthcare Research and Quality (AHRQ).

• I currently serve part-time as an advisor in the Office
• f the Assistant Secretary for Planning and

Evaluation, at the U.S. Department of Health and Human Services (HHS).

• This paper does not represent the views of HHS or

AHRQ.

Background

• ACA took a multi-pronged approach expanding

health insurance:

• Individual mandate & insurance market reforms
• Expanded Medicaid (income <138% poverty)
• Tax credits for private insurance purchased via

Exchanges (138-400% FPL)

Research To Date

• Ample evidence from time-series analyses of multiple data

sources – ACA implementation associated with dramatic drop in uninsured rate

• Analyses of Medicaid show large coverage gains for low-

income adults in expanding states, vs. non-expansion

• But no research to date has assessed the relative

contributions of the ACA’s key policy tools for the nation as a whole

Sources: Clemens-Cope et al. Urban Institute 2014; Black & Cohen NHIS 2015; Sommers et al. JAMA 2015; Wherry & Miller Annals Int Med 2016; Kaestner et al NBER 2015; Courtemanche et al. NBER 2016

Objective & Overview

• Objective: Provide the first comprehensive analysis of

ACA coverage impacts from the law’s key features:

1. Medicaid expansion 2. Premium subsidies 3. The individual mandate

• Overview: Difference-in-difference-in-difference

model comparing changes in coverage over time by income group and by geography

Methods: Data & Sample

• Household microdata from American Community

Survey (ACS) for 2012-2014

• Information on income, family structure,

demographics, and health insurance

• Level of analysis is the “health insurance unit” – adult,

his/her spouse, and dependent children

• All non-elderly adults, 0-64 years of age (>2 million
• bservations per year)
• Detailed within-state geography, but can’t go back

further than 2012

Policy Measures: Medicaid

• Medicaid eligibility from CMS, Kaiser Foundation, and

state sources

• Based on age, income, disability and family structure
• We distinguish between existing Medicaid eligibility as of

2013 and new Medicaid eligibility in 2014

• For secondary analyses, we also distinguish between:
• Non-expansion states as of 2014 (n=24)
• Early expander states, between 2011-2013 (n=6)
• 2014 expansion states (n=21)

Medicaid Eligibility: Children

Medicaid Eligibility: Adults

Policy Measures: Premiums

• Marketplace premiums by rating area from Robert

Wood Johnson Foundation - mapped onto 2,350 ACS “public use microdata areas” (PUMAs):

• Using 2nd-lowest cost silver plan in each rating area
• Age-specific using CMS age-rating curves
• Subsidy amount based on ACA provisions: family size,

family income (between 100/138% and 400% FPL)

• Compare state-based and federal marketplace states

Policy Measures: Premiums

% Subsidy per Family

Policy Measures: Mandate

• Exempt from Mandate (38%):
• Those below tax filing threshold (21% of sample)
• Those in Medicaid gap in non-expansion states (6%)
• Native Americans (1%)
• Affordability exemption, based on lowest cost bronze

plan > 8% of family income (10%)

• Mandate Penalty for Non-Exempt (62%):
• $95 per uninsured adult (half per child) or 1% of

taxable income, whichever is greater

• Capped at national average bronze premium

Policy Measures: Mandate

Simulated Policy Variables

PROBLEM– ‘Observed’ eligibility, mandate, subsidy subject to bias:

• Income and eligibility may change in response to ACA
• Family-level estimates of policy parameters - imprecisely measured

SOLUTION – Use “simulated” measure:

• Randomly select 200 families of each of three types – single adults,

adult couples, and adults with children

• Assign the same 200 families to each PUMA & income band, and

compute values for all key policy measures using this standardized

• Similar to previous work by Currie & Gruber on Medicaid in the

1990s

Results: Uninsured

Variable Coefficient Percent Subsidy * 2014

• 0.052***

Family Mandate Penalty * 2014 ($100s) 0.0001* Previously Medicaid-Eligible * 2014

• 0.040***

Newly Medicaid-Eligible * 2014

• 0.088***

Notes: ***p<0.01, **p<0.05, *p<0.10 Models include demographic controls, state and year fixed effects, with robust SE clustered at PUMA level.

Interpretation

• Each additional 10% subsidy reduces uninsured by 5.2

percentage points, or roughly 1.5 million persons

• Mandate effect negligible (and wrong-signed): $100 increase

in average mandate penalty (~20% of baseline) raises uninsured by 0.01 percentage points

• Big effect in 2014 of Medicaid eligibility
• 8.8% reduction in uninsured among newly-eligible
• 4.0% reduction in uninsured among previously eligible

Decomposing the ACA’s Policy Effects

Variable (* 2014) Reduced Form ß Population Mean Implied Percentage Point Change % of ACA- Related Change Percent Subsidy

• 0.052

0.162

• 0.85%

37% Family Mandate Penalty 0.0001 4.58 0.05% N/A Previously Medicaid- Eligible

• 0.040

0.248

• 1.00%

44% Newly Medicaid-Eligible

• 0.088

0.049

• 0.43%

19% Note: Our parameterized policies overall explain a ~2.3 percentage-point drop in uninsured rate in 2014, compared to ~3.4 point drop in raw data.

Results: Type of Coverage

Variable (* 2014) Uninsured Medicaid / “State- Subsidized Coverage” ESI Non-Group Percent Subsidy

• 0.052***

0.018*** 0.009*** 0.029*** Family Mandate Penalty 0.0001* 0.0003***

• 0.0002
• 0.0003***

Previously Medicaid- Eligible

• 0.040***

0.038*** 0.005** 0.003* Newly Medicaid-Eligible

• 0.088***

0.092*** 0.002 0.002 Notes: ***p<0.01, **p<0.05, *p<0.10 Models include demographic controls, state and year fixed effects, with robust SE clustered at PUMA level.

Results: Type of Coverage

Variable (* 2014) Uninsured Medicaid / “State- Subsidized Coverage” ESI Non-Group Percent Subsidy

• 0.052***

0.018*** 0.009*** 0.029*** Family Mandate Penalty 0.0001* 0.0003***

• 0.0002
• 0.0003***

Previously Medicaid- Eligible

• 0.040***

0.038*** 0.005** 0.003* Newly Medicaid-Eligible

• 0.088***

0.092*** 0.002 0.002 Notes: ***p<0.01, **p<0.05, *p<0.10 Models include demographic controls, state and year fixed effects, with robust SE clustered at PUMA level.

Results: Type of Coverage

Variable (* 2014) Uninsured Medicaid / “State- Subsidized Coverage” ESI Non-Group Percent Subsidy

• 0.052***

0.018*** 0.009*** 0.029*** Family Mandate Penalty 0.0001* 0.0003***

• 0.0002
• 0.0003***

Previously Medicaid- Eligible

• 0.040***

0.038*** 0.005** 0.003* Newly Medicaid-Eligible

• 0.088***

0.092*** 0.002 0.002 Notes: ***p<0.01, **p<0.05, *p<0.10 Models include demographic controls, state and year fixed effects, with robust SE clustered at PUMA level.

State Subgroups

• Premium subsidy effects were twice as large in states

with state-based Exchanges than federal healthcare.gov

• PercentSubsidy ß=-0.080 vs. -0.044, both p<0.001
• Pre-ACA Medicaid effect was 3x as large in early

expansion states than in 2014 expanders and non- expanders:

• PreviousMcaidElig ß=-0.063 vs. -0.028 & -0.021, all

p<0.001

Policy Implications

• 40% of ACA coverage gains due to Marketplace premium

subsidies

• State Marketplaces had much higher take-up rates than

federal (outreach, functionality, politics?)

• Mandate – no specific effects of penalty details, but this

misses general “taste for compliance” (Saltzman et al 2015)

• Effect may be larger in future years as penalties increase

Policy Implications

• 60% of ACA is Medicaid effect, can be roughly divided

into thirds:

1. New Medicaid expansion in 2014

• Note that 7 additional states have expanded since then

2. Woodwork or welcome mat effect, which occurred in all states regardless of expansion status

• Streamlined application, navigators, and publicity (all states)

3. Early expansion effect – building on 6 states’ early efforts

• ‘Priming the pump,’ takes time for awareness to spread
• No crowd-out from Medicaid once we model premium

subsidies

Questions?

Ben Sommers bsommers@hsph.harvard.edu