Florian Heiss

Medicare prescription drug coverage: consumer information and preferences.

We investigate prescription drug use, and information and enrollment intentions for the new Medicare Part D drug insurance program, using a sample of Medicare-eligible subjects surveyed before open enrollment began for this program. We find that, despite the complexity of competing plans offered by private insurers under Part D, a majority of the Medicare population had information on this program and a substantial majority planned to enroll. We find that virtually all elderly, even those with no current prescription drug use, can expect to benefit from enrollment in a Part D Standard plan at the low premiums available in the current market. However, there is a significant risk that many eligible seniors, particularly low-income elderly with poor health or cognitive impairment, will make poor enrollment and plan choices.

Consumer-Directed Health Care: Can Consumers Look After Themselves?

SummaryIn health care systems today, including those of Switzerland and the United States, participants do not necessarily see the big picture of lifetime health costs and quality of life, and in many systems consumers and providers lack the incentives to manage preventative and chronic care to minimize lifetime private and social health costs. Resource allocation problems induced by asymmetric information and misaligned incentives are exacerbated if consumers fail to have the acuity or perspective needed to make choices consistent with their self-interest when faced with complex health care choices with ambiguous future consequences. This paper examines rationality of consumers’ health perceptions and choices using as a natural experiment the recent introduction in the United States of a highly subsidized market for prescription drug insurance, and draws lessons from this experiment on the practicality of “Consumer Directed Health Care” as an approach to achieving efficient allocation of health care resources by confronting consumers with the full marginal costs of the services they use.

Discrete Choice Methods with Simulation

Discrete Choice Methods with Simulation by Kenneth Train has been available in the second edition since 2009. The book is published by Cambridge University Press and is also available for download on the author’s homepage for private use. The second edition corrects some errors and contains two additional chapters, one on endogenous regressors and one on the expectation–maximization (EM) algorithm. As the title suggests, the book has two main topics. One concerns models of discrete (multinomial) choices that deal with the decision between a finite set of mutually exclusive alternatives such as the choice between brands of consumer goods, travel modes, or college majors. These models are important for fields such as marketing, transportation, environmental economics, education, labor, and industrial organization. The second major subject of the book is a simulation-based estimation with a focus on maximum simulated likelihood. These two topics are very compatible since multinomial choice models quite naturally lead to likelihood functions and other objective functions that are analytically infeasible to evaluate, requiring approximation methods such as a Monte Carlo simulation. As a consequence, much of the methodological work on simulation-based estimation was inspired by discrete choice models and much of the more recent empirical work studying discrete choices uses simulation-based estimation.