Abstract
Performance sampling models of duration dependence in employee turnover and firm exit predict that hazard rates will initially be low, gradually rise to a maximum, and then fall. Some empirical duration distributions have bimodal hazard rates, however. In this paper, we present a generalization of the performance sampling model that can account for such deviations from unimodality. While the standard model of performance sampling assumes that the mean and the standard deviation of performance are constant over time, we allow them to change in time, to reflect the fact that tasks may change over time. We derive the hazard rate implied by this more general model and show that it can be bimodal. Using data on turnover in law firms, we show that the hazard rate predicted by these models fit data better than existing models.
| Original language | English |
|---|---|
| Pages (from-to) | 38-63 |
| Number of pages | 26 |
| Journal | Journal of Mathematical Sociology |
| Volume | 33 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 2009 |
| Externally published | Yes |
Keywords
- Duration dependence
- Hazard rates
- Learning
- Performance sampling
Fingerprint
Dive into the research topics of 'Performance sampling and bimodal duration dependence'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver