Document Type



In this paper, we examine the effects of mental illness on earnings by recognizing that effects may vary across the distribution of earnings. Using data from the National Comorbidity Survey, we employ a quantile regression estimator to identify the effects at key points in the earnings distribution. We find that earnings effects vary importantly across the distribution. While average effects are often not large, mental illness more commonly imposes earnings losses at the lower tail of the earnings distribution, especially for women. Consequently, mental illness can have larger negative impacts on economic outcomes than previously estimated, even if those effects are not uniform.

Publication Date


Original Citation

Wilcox-Gök and Dave E.Marcotte."Estimating Earnings Losses Due to Mental Illness: A Quantile Regression Approach." Journal of Mental Health Policy and Economics Volume 6, Number 3, 2003, 123-134


Department of Economics

Legacy Department

Department of Economics


This research was supported by the National Institute of Mental Health (R01-MH56463-01).




John Wiley and Sons



To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.