This research explores the medical care consumption and absenteeism decisions of employed individuals with acute illnesses in an effort to better understand health care behavior. Using data from the 1987 National Medical Expenditure Survey, the author estimates the structural parameters of an individual's discrete choice stochastic optimization problem, as opposed to employing conventional reduced form estimation methods that are prevalent in the health care literature. The estimates allow for predictions of the change in physician services use and illness-related absenteeism that arise with the introduction of new public policy initiatives involving health insurance and sick-leave coverage.

Some new tools for analyzing spurious regressions are presented. The theory utilizes the general representation of a stochastic process in terms of an orthonormal system and provides an extension of the Weierstrass theorem to include the approximation of continuous functions and stochastic processes by Wiener processes. The theory is applied to two classic examples of spurious regressions: regressions of stochastic trends on time polynomials and regressions among independent random walks. It is shown that such regressions reproduce in part and in whole the underlying orthonormal representations.