Structural estimation of labor adjustment costs suffers from a myriad of specification errors, largely due to data constraints. The literature usually assumes that adjustment decisions are made at the firm level, that adjustment happens at the frequency at which a firm is observed (typically annually or quarterly), and that adjustment costs are incurred on net changes in employment. This paper builds and estimates a dynamic optimization model of labor adjustment of establishments using data that permit 1) specifying any desired adjustment frequency (including daily adjustment), 2) using the micro unit of an establishment, 3) estimating the model based on net and on gross employment flows and 4) allowing for simultaneous hirings and separations. Results for adjustment costs depend crucially on the model specification. Only a monthly adjustment model yields positive cost parameters, while estimates from quarterly and annual adjustment models imply negative adjustment costs (that is adjustment implies a gain rather than a loss). Estimating the model on net employment changes imply hiring and separation costs of more than four annual median salaries, while the model on gross changes implies costs on the order of two annual median salaries. Adjustment costs differ significantly between small and large establishments. However, a static specification of the model performs equally well as the dynamic model with respect to out-of-sample predictions
