.png){kind=icon}
.png){kind=icon}
Return
INTERPRETING SPATIAL ECONOMETRIC ORIGIN-DESTINATION FLOW MODELS
.png){kind=icon}
PRE
AI
DOI：10.1111/jors.12114.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Spatial interaction or gravity models have been used to model flows that take many forms, for example population migration, commodity flows, traffic flows, all of which reflect movements between origin and destination regions. We focus on how to interpret estimates from spatial autoregressive extensions to the conventional regression-based gravity models that relax the assumption of independence between flows. These models proposed by LeSage and Pace (, ) define spatial dependence involving flows between regions. We show how to calculate partial derivative expressions for these models that can be used to quantify these various types of effect that arise from changes in the characteristics/explanatory variables of the model.
Keywords:
GRAVITY
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
2.7
Papers:
2.1K
Citations:
3.2K
