
doi: 10.1068/a230421
Shift-share analysis continues to be popular among geographers, regional scientists, and planners despite widespread criticism of the method. In this paper, it is argued that insufficient attention has been paid to model-based approaches to shift—share analysis. It is shown that conventional shift—share and stochastic shift—share yield identical conclusions. Stochastic shift—share is easily extended dynamically and along the lines suggested by Arcelus. Thus, in the stochastic models several of the most persistent criticisms of the technique are addressed by allowing for testing of hypotheses, while preserving the practicality of the conventional accounting approach. It is suggested that stochastic shift—share should be used whenever practical.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 41 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
