Welfare Implications of the Affordable Care Act

Paper Session

Saturday, Jan. 7, 2017 2:30 PM – 4:30 PM

Hyatt Regency Chicago, Dusable
Hosted By: Econometric Society
  • Chair: Mark Duggan, Stanford University

The Effect of the Affordable Care Act on Health Insurance Coverage and Labor Market Outcomes

Mark Duggan
,
Stanford University
Emilie Jackson
,
Stanford University
Gopi Shah Goda
,
Stanford University

Abstract

The Affordable Care Act (ACA) includes several provisions designed to expand insurance coverage that also alter the tie between employment and health insurance. In this paper, we exploit proxies for expected treatment “intensity” of the ACA to estimate the effect of the ACA on health insurance coverage and labor market outcomes in the first two years after the implementation of the main features of the ACA. Our measures of treatment intensity take advantage of geographic variation in the income distribution and in the pre-ACA share uninsured, interacted with each state’s Medicaid expansion status. Our findings indicate that a substantial share of the increase in health insurance coverage since 2013 is due to the ACA and that areas in which a greater share of the population stood to benefit from the ACA’s provisions saw substantially larger increases in coverage. We find suggestive evidence of a small policy-induced increase in labor force exit and in part-time work, with this effect driven by those acquiring coverage through the ACA exchanges. However, we detect no corresponding change in employment.

Trade-Offs of Simplifying and Subsidizing Complex Choices: Early Evidence From the ACA Exchanges

Maria Polyakova
,
Stanford University
Stephen Ryan
,
University of Texas-Austin

Abstract

Using new data from the early years of the federally-facilitated Health Insurance Marketplaces (or ACA Exchanges), we explore which factors affect health insurance choices of the non-elderly population targeted by the ACA, and what implications these choices have on subsequent healthcare utilization. A growing literature has documented potential behavioral biases and high cost of decision-making in various insurance settings that rely on consumer choice - from retirement savings to prescription drug plans. A natural conclusion from this literature is that it may be optimal for policy-makers to introduce behavioral nudges (e.g. optimal defaults, framing) that could reduce the behavioral biases or decision-making costs. For example, ACA Exchanges use "metal level" classification of plans as a framing that reduces the complexity of comparisons across dozens of plans on the Exchanges. So far, we have little evidence on how such nudges work in practice, and whether they are strictly welfare-improving or may lead to unintended consequences. In this project we attempt to start closing this gap by exploring whether the metal tier framing and differential subsidization of metal tiers affects choices and subsequent healthcare utilization in the federally facilitated Health Insurance Marketplaces.

Consumption Responses to the Affordable Care Act: Evidence From Credit Card Data

Rebecca Diamond
,
Stanford University
Michael Dickstein
,
New York University
Timothy McQuade
,
Stanford University
Petra Persson
,
Stanford University

Abstract

This paper analyzes the dynamic consumption responses to the introduction of the Affordable Care Act (ACA). We use novel credit card and bank account microdata on over 8.5 million account holders from certain banks, which offers a detailed view of the consumption decisions of the banked population in the United States -- including at the tails of the income distribution. We first present model-free evidence on the take-up of subsidized health insurance made available through the ACA: We document (i) sharp increases in take-up during the enrollment periods, especially at the lower end of the income distribution; followed by (ii) a continuous drop-out as individuals cease to pay their premiums and lose coverage. We hypothesize that the drop-out is driven by newly insured individuals who, when starting to utilize health care, revise upwards their prior on the actual out-of-pocket costs of care (when covered by health insurance). To investigate these dynamics, we model insured individuals' decision whether to remain insured or drop coverage, allowing for patient learning through the arrival of health (cost) shocks. Our results suggest that patient learning about health care costs is a key driver of the drop-out decision. This emphasizes that efforts to expand coverage of health insurance must go beyond getting individuals to sign up; and in particular, must appropriately manage the insureds' expectations about the costs of care when covered.
JEL Classifications
  • A1 - General Economics