ABSTRACT
To combat adverse selection, governments increasingly base payments to health plans and providers on enrollees' scores from risk-adjustment formulae. In 2004, Medicare began to risk-adjust capitation payments to private Medicare Advantage (MA) plans to reduce selection-driven overpayments. But because the variance of medical costs increases with the predicted mean, incentivizing enrollment of individuals with higher scores can increase the scope for enrolling "overpriced" individuals with costs significantly below the formula's prediction. Indeed, after risk adjustment, MA plans enrolled individuals with higher scores but lower costs conditional on their score. We find no evidence that overpayments were on net reduced.
Subject(s)
Insurance Selection Bias , Medicare Part C/economics , Risk Adjustment/economics , Capitation Fee , Humans , United StatesABSTRACT
Most existing work on the demand for health insurance focuses on employees' decisions to enroll in employer-provided plans. Yet any attempt to achieve universal coverage must focus on the uninsured, the vast majority of whom are not offered employer-sponsored insurance. In the summer of 2008, we conducted a survey experiment to assess the willingness to pay for a health plan among a large sample of uninsured Americans. The experiment yields price elasticities of around one, substantially greater than those found in most previous studies. We use these results to estimate coverage expansion under the Affordable Care Act, with and without an individual mandate. We estimate that 35 million uninsured individuals would gain coverage and find limited evidence of adverse selection.
Subject(s)
Insurance Coverage , Insurance, Health , Medically Uninsured , Policy Making , Adolescent , Adult , Female , Humans , Intention , Male , Medicaid/statistics & numerical data , Medically Uninsured/statistics & numerical data , Middle Aged , Needs Assessment/statistics & numerical data , Patient Protection and Affordable Care Act , Surveys and Questionnaires , United States , Young AdultABSTRACT
Breastfeeding is negatively correlated with future fertility because nursing temporarily reduces fecundity and because mothers usually wean on becoming pregnant again. We model breastfeeding under son-biased fertility preferences and show that breastfeeding duration increases with birth order, especially near target family size; is lowest for daughters and children without older brothers because their parents try again for a son; and exhibits the largest gender gap near target family size, when gender is most predictive of subsequent fertility. Data from India confirm each prediction. Moreover, child survival exhibits similar patterns, especially in settings where the alternatives to breastmilk are unsanitary.
