Michael Simmons (RHUL) “Pre-layoff search” – PhD Seminar

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Abstract

Are workers able to foresee job loss? If so, how many and how far in advance? In this paper, I document the extent to which workers change their search behaviour before job loss in the UK. In particular, for low and high skill workers, search incidence increases by 17and 32 percentage points, respectively, during the quarter that precedes job loss, and this increased incidence is predominantly due to workers “thinking their job may end”. Equipped with this information, I build a search model of the labour market with stochastic human capital, where workers may receive information of job insecurity, and are able to respond by picking their search effort and savings. I show that that the dynamics of pre-layoff search pins down key parameters governing the changes in the average worker’s information set prior to unemployment. The model estimates reveal that, 50% and 67% of low and high skill workers, respectively, know of impending job loss on average about three months before becoming unemployed. As well as fitting the dynamics of pre-layoff search, the model is also able to replicate the level of involuntary job switching, and the costs of job loss for workers who immediately find new employment and for workers who do not. I decompose the difference sin the costs of job loss into the underlying forces at play. I find that the smaller costs of job loss for those managing to switch employers, relative to those who transition into unemployment, are predominantly due to workers avoiding skill loss in unemployment. Counterfactual analysis shows that if workers were unable to foresee job loss, the unemployment rate would rise by 20% and consumption would fall by over 1%. The results reveal that increasing search following the pre-layoff warning is far more valuable to the worker than to increase savings. Finally, I use the model to understand the implications for salient policies, designed to mitigate the costs of job loss.