Who is leaving and why? the dynamics of high-quality human capital outflows.

Abstract

This study proposes a unified, dynamic framework based on Turnover Event Theory (TET) to evaluate the effects of dismissals, layoff announcements, and voluntary turnover on subsequent work unit voluntary turnover. Applying our approach to 1,620 retail stores over 22 months, we show that modeling exit events as a dynamic and interdependent system adds to our ability to predict subsequent human capital outflow. Dismissals had the weakest total effect on subsequent voluntary turnover, layoff announcements had the strongest and most immediate effects, and voluntary turnovers had moderate but lasting effects. We also find that these three exit reasons each exhibit a distinct pattern of subsequent turnover intensity and longevity. Based on the characteristics of work units in our setting, our results correspond to a cumulative worker-level average effect of 0.17 quits following dismissals, 0.23 quits following quits, and 2.2 quits following a layoff. We find that these “multiplier” effects are concentrated among workers of similar performance: high-performer exits beget high-performer quits, just as low-performer exits beget low-performer quits. Our findings suggest analyses offering individual-level estimates of turnover will generally underestimate the broader, work-unit level consequences of individual exit events on similar workers.

We developed an integrative and comparative model that, both theoretically and empirically, evaluates the relative magnitude and duration of changes in subsequent voluntary turnover rates following the flow of human capital in and out of work units due to staffing events (hiring, dismissals, layoffs, and voluntary turnover). This model encapsulates the endogenous, co-evolving, and dynamic nature of human capital flows due to various staffing events, and assesses the ways in which these dynamics could be engineered through