Pitfalls in Higher Order Model Extensions of Basic Spatial Regression Methodology
By James Paul LeSage, R. Kelley Pace. 2011
114 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/71295971d1368abd0a13bd261164ce7c9e7578f5
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Solmaria Halleck Vega
- Nicolas Debarsy
- James Paul LeSage
- J. Paul Elhorst
- Luc Anselin
- Tobias Ruttenauer
- Jesús Crespo Cuaresma
- Peter H. Egger
Citations in the corpus
- Bayesian Model Averaging for Spatial Autoregressive Models Based on Convex Combinations of Different Types of Connectivity Matrices (2020, background): “For example, Pace et al. (2000) proposed a model for prices of homes sold that occur at irregular points in space and time, generalizing distance to include relative locations in time. Related work by Pace, Sirmans, and Slawson (2002) relied on generalized distances that considered the number of bed”
- The Slx Model (2015, background): “According to LeSage and Pace (2011) another distinction between the two is that global spillovers include feedback effects that arise as a result of impacts passing through neighboring units (e.g., from region i to j to k) and back to the unit that the change originated from (region i), whereas…”