"The Distribution of Earnings Losses: Evidence from Displaced Worker Su" by Mallika Garg
 

Graduate Research and Discovery Symposium (GRADS)

Document Type

Poster

Publication Date

Spring 2015

Abstract

Workers that lose their jobs because their employer closed a plant or division, moved or abolished their position, or simply had insufficient work for them are reported to experience huge losses in earnings, post-displacement. Empirical studies using ordinary regression techniques have estimated these losses to average between 10% - 40%. However, around this mean loss is a distribution with considerable variation, variation that for the most part has been unremarked on. Using Displaced Workers Survey data from 1994-2010, I find that the mean loss in weekly earnings of displaced workers stands at 18%, while the median loss is only 6.5%. At the 25th percentile of the earnings-change distribution, the loss amounts to 35% and at the 75th percentile there’s a gain of around 9.5%. In light of such variation in losses, I argue that classical regression models with their estimates of conditional-mean loss fail to provide a complete picture of the post-displacement earnings experience of workers. I apply quantile regression technique to this problem and use regression curves corresponding to various points on the earnings-change distribution to provide more insight into these losses.

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