What Do Longitudinal Data on Millions of Hospital Visits Tell Us About the Value of Public Health Insurance as a Safety Net for the Young and Privately Insured?

Working Paper: NBER ID: w20887

Authors: Amanda E. Kowalski

Abstract: Young people with private health insurance sometimes transition to the public health insurance safety net after they get sick, but popular sources of cross-sectional data obscure how frequently these transitions occur. We use longitudinal data on almost all hospital visits in New York from 1995 to 2011. We show that young privately insured individuals with diagnoses that require more hospital visits in subsequent years are more likely to transition to public insurance. If we ignore the longitudinal transitions in our data, we obscure over 80% of the value of public health insurance to the young and privately insured.

Keywords: public health insurance; young individuals; safety net; longitudinal data

JEL Codes: I13


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
Severity of health conditions (I12)Transition to public health insurance (I13)
Multiple hospital visits (I19)Transition to public health insurance (I13)
Ignoring longitudinal transitions (J62)Underestimation of public health insurance value (I13)
Hospital costs over time (I11)Transition to public health insurance (I13)

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