Labour Market Matters - December 2012

It is well-documented that workers displaced from long-tenure jobs tend to have difficulty finding new employment, and face even greater difficulty finding a job without suffering a substantial loss in earnings. Workers with significant prior tenure typically undergo substantial earnings losses, with mean losses of 25-35 percent for those with at least five years’ tenure. Such earnings losses have been found to be persistent even five years after the displacement. Earnings losses suffered by displaced long-tenure workers tend to be large and may be permanent. Policies to address problems faced by displaced long-tenure workers tend to be centred on education, training and skill development. A report by CLSRN affiliate Stephen Jones (McMaster University) entitled “The Effectiveness of Training for Displaced Workers with Long Prior Job Tenure†(CLSRN Working Paper no. 92)* cautions that research shows returns to training for displaced workers that are low, being significantly less than the returns to formal schooling which lie in the 6-9% range. On a cost-benefit basis, the body of evidence does not show that training pays off for most of the displaced population. How does a firm’s decision to engage in employee training react to economic fluctuations? During downturns, lower productivity (a “negative productivity shock†) can be associated with increased training, as the opportunity cost to train workers is lower. However, increased productivity (a “positive productivity shock†) can be related to the adoption of new technologies that may require training, which can create increased return to skill. Currently, there is little evidence to prove which of the two scenarios holds more accurately over the other. In a paper entitled “The Impact of Aggregate and Sectoral Fluctuations on Training Decisions†(CLSRN Working Paper no. 45) CLSRN affiliates Vincenzo Caponi (Ryerson University), Cevat Burc Kayahan (Acadia University), and Miana Plesca (University of Guelph) examine how the firm-level decision to train depends on aggregate and sectoral output fluctuations, and find that more training tends to happen during downturns, and that training is generally higher in sectors that are doing relatively better than others.