Estimating Earnings Losses Due to Mental Illness: A Quantile Regression Approach
Marcotte, Dave E.
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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.