One test of the model is in its ability to match the vacancy rates, hiring rate, layoff rate, and part-time rate used by firms over the employment growth distribution. Figure 1.12 shows that the model is able to match the patterns of vacancies and hires across the growth distribution of firms. Similar to Kaas and Kircher (2015), the model matches the broad pattern that vacancies are posted by growing firms, though the vacancy rate is higher than it is in the data. This can be matched more closely through a higher Y in the recruitment cost function. The data may also not entirely account for the increased recruitment of rapidly growing firms if multiple hires result from a single vacancy.
Figure 1.13 shows the growth rate of hours per worker, the layoff rate, and the part-time rate of firms by monthly employment growth rate. The model produces a positive correlation of layoff rates and part-time share of employment for contracting firms. This result is consistent with the evidence in CPS flow data that workers in part-time employment have high separation rates to unemployment. While layoffs are only used in contracting firms, some workers separate from all firms due to exogenous quits. Part-time usage, however, is exclusively used by shrinking firms. The likelihood of separating to unemployment given a worker has been placed into part-time work is therefore high, as some workers in the firm will also be laid off at the end of the period.
Although the monthly average part-time rate is lower than the layoff rate for shrinking firms, this is not necessarily contrary to the fact that full-time workers are more likely to move to P T E than to unemployment in the CPS. From the firm’s individual policy function, Figure 1.9 in Section 1.4 showed that a contracting firm can use more part-time than separations in a period. While the layoff rate reflects total layoffs by a firm within the month, part-time percentage is an average of the weekly part-time utilization of a firm. The transitory nature of part-time usage and time-aggregation of total separations to a monthly rate can make the average parttime rate low in Figure 1.13, even if firms are moving more workers to part-time than using layoffs.
This short-term nature of part-time utilization in the model is also reflected in the growth-rate of weekly hours per worker for shrinking firms. While part-time usage and layoffs increase steadily for shrinking firms, the average monthly change in weekly hours per worker is relatively stable except at very negative growth-rates. This is due to fluctuations in part-time usage within a given month. If part-time usage were very persistent, it would be reflected in a steadier decline in the monthly growth rate of average weekly hours per worker.