Explanations for the Decline in Health Insurance Coverage Michael Chernew, Michigan and NBER David Cutler, Harvard and NBER Patricia Keenan, Harvard This work was funded by the Economic Research Initiative on the Uninsured, the National Institutes on Aging, and the Alfred P. Sloan Foundation.

Research Questions What impact will rising premiums have on coverage in the future? What role did rising premiums for health insurance play in declining coverage rates over the 1990s?

Basic Fact Despite strong economic growth, and expanding public coverage, the rate of health insurance coverage fell during the 1990s. –13.7% of non-elderly uninsured (1987) –15.8% of non-elderly uninsured (2000)

Reasons for Decline Demographic or labor market changes Changing value of alternatives (charity care) Equilibrium unraveling –Increase in working spouses Regulatory changes Changing Load –Taxes Rising premiums –1% increase in premium  drop of 300,000 (Lewin)

‘Load’ as a Measure of Price Textbook models: –‘Price’ is the load (difference between premium and expected payout) –Rising premiums Have no ‘price’ effect May lead to greater coverage if correspond to greater risk Most elasticity estimates are ‘load’ or ‘co-premium based’

Why Premiums May Matter Higher premiums may include greater moral hazard cost –Contracting imperfect Higher premiums may increase incentives for low risk to opt out and market to unravel Higher premiums may increase relative appeal of charity care –Particularly if better technology (which drives up premiums) is also partially available via charity care

Approach Control for: –Individual traits –Taxes –Working spouses –Medicaid expansion –Immigration –State insurance regulation –MSA unemployment –MSA demographics –Managed care enrollment Relate decline in coverage between and to increases in premiums − Probit model using individual level data

Market Data Health Care CostsPremiums Employer Survey (KPMG 1988, 1989, 1998; KFF/HRET 1999) Hedonic price regression yields MSA estimates Medicare Part B expenses (CMS) State health care spending (CMS) TaxesNBER TAXSIM program: Gruber Method RegulationsRate reform/guaranteed issue: Kosali Simon Medicaid Coverage NGA and Reagan Baughman: Similar to Cutler/Gruber Method Immigrants1990 Census (ARF) and March CPS Managed CareInterStudy and Loren Baker Charity CareAHA: 1990 beds in public or teaching hospitals per capita % working spouses March CPS

Individual Data Insurance Coverage Demographics and employment characteristics for individuals and family head –Time interactions Income deciles (Gruber approach) –Income deciles interacted with marital status of family head –Income deciles interacted with marital status and time Child age dummies, mean medical care spending by child age (Cutler /Gruber 1996).

Base Results Any Cov. Private Public private premiums (1000s) marginal tax rate insurance reforms % working women unemployment rate % foreign born Medicaid eligibility charity care availability Effect of $645 spending *** ** * *** *** * *** * *** Controls for individual level traits and MSA demographics included but not displayed.

Endogeneity and Attenuation bias Noise in premium measure Uninsured may cause rising costs –Selection effects –Cost shifting Instrument with Medicare and State per capita costs –F-stat: –Partial R-squared:.75

Any Cov. Any Cov. Any Cov. Probit LPM LPM - IV private premiums (1000s) tax price insurance reforms % working women unemployment rate % foreign born Medicaid eligibility charity care availability Effect of $645 spending *** ** * *** *** * * *** Instruments for private premiums are Medicare Part B and state nonelderly medical spending. Controls for individual level traits and MSA demographics included but not displayed. Base Results - IV

Premium Results by Subgroup Any Cov. Private Public Base SAMPLE: Age Age Income < 30K Income > 30K < = High School > High School *** ** *** *** ** *** Controls for all covariates in base model.

Interpretation 1% increase in premiums leads to 150,000 more uninsured –Half of Lewin effect 1% cost growth above GDP leads to 1.8M more uninsured 2% cost growth above GDP leads to 3.8M more uninsured Mean premium increase ($645) accounts for: –1.7 percentage points decline in coverage –~54% of mean decline Effects greatest for young and low income

Conclusions Health care cost increases are related to drop in coverage. It is reasonable to assume that coverage rates will continue the long-term decline. –Subsidy and pro-competition strategies may be short term fixes Suggests a fundamental challenge to policy makers –Individuals desire access to new medical technologies –Costs of coverage may become increasingly less affordable

Explaining Tax Results Results are not robust to specification changes Very little variation in taxes rates over time –Fixed effects absorb much of this variation –Counter-intuitive results likely noise We don’t focus on groups most likely to be affected –Private coverage –Workers Workers own employment-based coverage results are consistent with literature

Sensitivity of ‘Any Coverage’ to Cost Measure private premiums (1000s) Medicare Part B (1000s) marginal tax rate insurance reforms % working women unemployment rate % foreign born Medicaid eligibility charity care availability Effect of $645 spending Number of MSAs *** ** * *** ** * ** *** Controls for individual level traits and MSA demographics included but not displayed. Private premiums Medicare Pt. B

Other findings Medicaid expansions increase coverage 1 percentage point Some variables reduce private, but not public, coverage –Working women –Premiums Demographic forces offset –Income vs. other demographics

Focus on ‘Any Coverage’ Advantage –Broadest measure of coverage trends Disadvantage –Effects may differ in sub-markets Private –Workers –Own ESI Public

Model Coverage i,m,t = X i,m,t B t + Z m,t +  m +  t + e i,m,t Standard errors assume clustering by MSA*time