ACA policies and market outcomes: rating regions, age-rating, and APTC HIX 5.0 Penn-LDI September 2017 Pietro Tebaldi University of Chicago Financial support from the Kapnick Foundation through a grant to the Stanford Institute for Economics Policy Research and from the Becker-Friedman Institute Healthcare Initiative is gratefully acknowledged

What did we learn from the early years? Combination of Data on plans, choices, and models of ACA regulations teach lessons on the effect of specific rules on policy relevant outcomes Who gets covered? How much does it cost?

Three questions with some answers How do insurers respond when we change rating regions? Dickstein, Duggan, Orsini, Tebaldi (2015) What is the effect of constraints on age-rating? Ericson, Starc (2015); Orsini, Tebaldi (2017) How does the design of APTC affect enrollment and spending? Jaffe, Shepard (2017); Tebaldi (2017)

How does rating region determination affect market outcomes? Rating region defines a market: group of counties (zip codes) defining level at which regulations apply and decisions of buyers and sellers take place Critical design decision: how to bundle counties? Tradeoffs: Larger markets increase size of enrollment pools, which also have a more homogeneous composition Larger markets force insurers to have a broader network of medical providers covered by their plan

States behaved very differently

Our analysis Compare carriers and premiums in Rural counties that were bundled with nearby urban counties Rural counties that were not bundled with nearby urban counties

Main results: When a small, rural county is bundled in a rating region with a large, urban county: One extra carrier on average Silver premium (for 45 year olds) is ≈$300/year lower Should we then have very large regions? No: larger regions (in land area) and heterogeneous regions (e.g. large within region variation in population density or racial composition) present – ceteris paribus – less insurers and higher premiums We should think of optimal region determination as a function of Markets of medical providers Population composition and geographic distribution

WHAT IS THE EFFECT OF THE CONSTRAINTS ON AGE-RATING?

Subsidies + age-rating adjustments Premium Public Spending in APTC Premium received by insurer absent constraint on age-rating Premium received by insurer under constraint on age-rating Price ceiling = premium paid by subsidized buyer maximum affordable amount Age of buyer For APTC beneficiaries (≈85%) no transfer from Y to O; change in public spending

Second implication of age-rating adjustments Positive relationship between price of 21-y.o. and share of over 50 uninsured in a region Relatively older markets have higher premium for young buyers 3:1 Constrained premium in “old market” Premium Constrained premium in “young market” Unconstrained premium 3:1 5:1 Age of buyer

Difference in pre-APTC monthly premium for 21 year olds between counties with above average % 50-64 uninsured and below average % 50-64 uninsured

Effect of age-rating constraints imposed under ACA on APTC spending (federally facilitated marketplaces) Smaller impact on coverage: ≈3% enrollment reduction among under 50 below 400% FPL ≈6% enrollment reduction among under 50 above 400% FPL

SHOULD MAXIMUM AFFORDABLE AMOUNTS VARY WITH AGE?

Over 50 vs young invincible in Covered California enrollment data Relatively older buyers are more willing to pay for health insurance

% drop in participation if APTC are $100/year lower

Age-adjustments to APTC Public Spending Premium received by insurer Premium Premium Premium received by insurer Public Spending Price ceiling = premium paid by buyer Age adjusted price ceiling Age of buyer Age of buyer subsidize more young invincible and achieve lower cost, lower (gross) premium for all buyers can also lower maximum affordable amount for older buyers  lower spending, more participation from all groups, higher total profits

Equilibrium calculations with estimates from Covered California Increase APTC of under 45 by $50/month , decrease APTC of over 45 by $25/month All buyers face lower net-of-APTC premiums

Wrapping up Observational data and economic models teach us how specific rules in ACA marketplaces are critical to policy-relevant outcomes How we draw rating regions matters Age-rating constraints impact both, participation and spending Age adjustments to maximum affordable amounts can make all buyers better off without extra spending Many open questions: How important is active purchasing? How would insurers adjust entry/networks/generosity if we were to change APTC? Can re-insurance / risk-adjustment play a complementary role to APTC?