Panel: The Impact of Health Insurance on Poverty and Inequality: Measurement Matters
(Health Policy)

Thursday, November 2, 2017: 3:30 PM-5:00 PM
Hong Kong (Hyatt Regency Chicago)

*Names in bold indicate Presenter

Panel Organizers:  Dahlia Remler, Baruch College, City University of New York; City University of New York
Panel Chairs:  Sherry Glied, New York University
Discussants:  Bhashkar Mazumder, Federal Reserve Bank of Chicago

The Impact of the Affordable Care Act on Health Inclusive Poverty
Dahlia K. Remler1,2, Sanders D. Korenman1,2 and Rosemary T. Hyson1,2, (1)Baruch College, City University of New York, (2)City University of New York

Early Medicaid Expansion Reduced Payday Borrowing in California
Heidi Allen1, Ashley Swanson2, Jialan Wang3 and Tal Gross1, (1)Columbia University, (2)University of Pennsylvania, (3)University of Illinois, Urbana-Champaign

Health Reform and the Health Insurance Coverage of Older Americans
Helen G Levy1, Thomas Buchmueller1 and Sayeh S Nikpay2, (1)University of Michigan, (2)Vanderbilt University

Health care and health insurance are very expensive, yet also basic needs. The United States has a complex and inconsistent system for meeting—and not meeting—these basic needs. Consequently, it is often difficult to measure the roles health care and insurance play in overall poverty, inequality and deprivation. New and innovative data, measures and analysis are essential for integrating health care and insurance into overall poverty, inequality and deprivation research. This panel includes papers taking different approaches to this issue.

The Supplemental Poverty Measure (SPM) was the first US Census Bureau poverty measure to reflect health care expenditures. The SPM is designed to measure material poverty and it addresses health care by deducting from resources all medical out-of-pocket expenditures (MOOP) on insurance premiums, medical care and over-the-counter medications. The Current Population Survey (CPS) began to measure these three kinds of MOOP in 2010. The CPS made significant revisions to how it gathers health insurance and MOOP variables in 2015. Brett O’Hara and Heide Jackson examine how monthly reporting of premiums improves the accuracy of premium MOOP and the SPM.

Sanders Korenman and Dahlia Remler (2016) developed a health inclusive poverty measure (HIPM), which treats basic health insurance as a need and counts health insurance benefits as resources available to meet that need. The HIPM is made possible by guaranteed issue and community rating regulations. A HIPM makes it possible to estimate the direct impacts of health insurance benefits on overall poverty and directly the effects to those of in-kind and cash benefits, such as TANF and SNAP, using the poverty accounting approach widely used with the SPM.  Korenman, Remler and Rosemary Harris apply the HIPM to account for the effects of health insurance and other benefits on poverty rates and gaps for the US under-65 population in 2014 under the Affordable Care Act (ACA).

Heidi Allen, Ashley Swanson, Jialan Wang and Tal Gross focus on a novel and important measure of financial hardship, the use of payday loans. They obtained the universe of loans from five large payday lenders with storefront sites across the country. Using a difference-in-difference approach and focusing on California’s early ACA Medicaid expansions, they found significant reductions in payday loan volume attributable to Medicaid.

Helen Levy, Thomas Buchmueller and Sayeh Nikpay also look at the effect of the Medicaid expansion, focusing on those aged 55 to 64. In addition to examining the effects on overall insurance coverage, they look at the effects on inequality in insurance coverage. The Medicaid expansion dramatically reduced the income and health status gradients in insurance coverage.

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