NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH
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Amelie C. Wuppermann

Department of Economics
LMU Munich
Ludwigstr. 33
D-80539 Munich
Germany

E-Mail: EmailAddress: hidden: you can email any NBER-related person as first underscore last at nber dot org

NBER Working Papers and Publications

October 2016Inattention and Switching Costs as Sources of Inertia in Medicare Part D
with Florian Heiss, Daniel McFadden, Joachim Winter, Bo Zhou: w22765
The trend towards giving consumers choice about their health plans has invited research on how good they actually are at making these decisions. The introduction of Medicare Part D is an important example. Initial plan choices in this market were generally far from optimal. In this paper, we focus on plan choice in the years after initial enrollment. Due to changes in plan supply, consumer health status, and prescription drug needs, consumers' optimal plans change over time. However, in Medicare Part D only about 10% of consumers switch plans every year, and on average, plan choices worsen for those who do not switch. We develop a two-stage panel data model of plan choice whose stages correspond to two separate reasons for inertia: inattention and switching costs. The model allows for unob...
June 2015Measuring Disease Prevalence in Surveys: A Comparison of Diabetes Self-Reports, Biomarkers, and Linked Insurance Claims
with Florian Heiss, Daniel McFadden, Joachim Winter, Yaoyao Zhu
in Insights in the Economics of Aging, David A. Wise, editor
Reliable measures of disease prevalence are crucial for answering many empirical research questions in health economics, including the causal structures underlying the correlation between health and wealth. Much of the existing literature on the health-wealth nexus relies on survey data, for example those from the Health and Retirement Study (HRS). Such survey data typically contain self-reported measures of disease prevalence, which are known to suffer from reporting error. Two more recent developments—the collection of biomarkers and the linkage with data from administrative sources such as insurance claims—promise more reliable measures of disease prevalence. In this paper, we systematically compare these three measures of disease prevalence. This work extends an existing literature tha...
 
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