The aim of the proposed research is to develop a more complete understanding of the relationships between labor market outcomes and affective disorders and develop more accurate estimates of the labor market losses associated with such illnesses.  Affective disorders are among the most common and debilitating forms of mental illness.  In the proposed research, we draw on research in economics, psychi-atry, and public health to hypothesize that existing estimates of the labor market loses suffered by workers as a consequence of affective disorders are too low.  We believe that the relationship between affective disorders and labor market outcomes is complex.  In fact, we hypothesize that important but unobservable individual and job factors which enhance productivity and earning tend to be associated with observed cases of affective disorders in the labor market.  The complicated relationship between affective disorders and labor market outcomes can arise for two reasons.  First, after onset the afflicted face a more complicated decision about labor force participation.  Those observed working are more likely to be those who would perform successfully in the labor market or have other job-related factors which help compensate them for the costs associated with their illness.  Second, clinical work has identified various personality traits and lifestyle stressors as important predictors of affective disorders.  Many of these factors may also enhance a worker's productivity and earnings, so standard estimates of subsequent earn-ing losses ascribe to affective disorders the positive effects of these often unmeasurable traits and thereby underestimate the true earning losses.  We propose two ways to identify how important these factors are in the estimation of labor market losses due to affective disorders and to correct for the bias they cause: (1) We will use panel data with appropriate estimation techniques to control for unobservable individual characteristics that are constant over time; and (2) we will develop instrumental variables that serve as proxies for affective disorders but are uncorrelated with important unobservable characteristics.  This research will at once provide more accurate estimates of the earning losses due to mental illness and identify estimation problems for which future researchers need to account.  This is vital information for researchers and policy-makers seeking to better understand and address the problems associated with mental illness.