Working Paper: NBER ID: w10297
Authors: Russell W. Cooper; John C. Haltiwanger; Jonathan Willis
Abstract: This paper studies the dynamics of labor demand at the plant and aggregate levels. The correlation of hours and employment growth is negative at the plant level and positive in aggregate time series. Further, hours and employment growth are about equally volatile at the plant level while hours growth is much less volatile than employment growth in the aggregate data. Given these differences, we specify and estimate the parameters of a plant-level dynamic optimization problem using simulated method of moments to match plant-level observations. Our findings indicate that non-convex adjustment costs are critical for explaining plant-level moments on hours and employment. Aggregation generates time series implications which are broadly consistent with observation. Further, we find that a model with quadratic adjustment costs alone can also broadly match the aggregate facts.
Keywords: No keywords provided
JEL Codes: E240; J230; C330
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| non-convex adjustment costs (D24) | labor demand dynamics (J23) |
| non-convex adjustment costs (D24) | negative correlation between hours and employment growth (J29) |
| non-convex adjustment costs (D24) | positive correlation between hours and employment growth (aggregate) (E24) |
| quadratic adjustment costs (C51) | match aggregate employment facts (J68) |