In many instances in empirical spatial analysis, the method of choice is a regression
analysis, whereby a variable of interest (the dependent variable) is related in a linear way to …

Every house is different. It is important that house price indexes take account of these quality
differences. Hedonic methods which express house prices as a function of a vector of …

Importance Treatment with methadone or buprenorphine is the current standard of care for
opioid use disorder. Given the paucity of research identifying which patients will respond …

Spatial Data Science introduces fundamental aspects of spatial data that every data scientist
should know before they start working with spatial data. These aspects include how …

Spatial data contain locational information as well as attribute information. It is increasingly
recognized that most data sets are spatial in that the attribute being measured is typically …

Spatial econometrics deals with spatial dependence and spatial heterogeneity, critical
aspects of the data used by regional scientists. These characteristics may cause standard …

Recent advances in the implementation of spatial econometrics model estimation
techniques have made it desirable to compare results, which should correspond between …

In this paper, I give a personal view on the development of the field of spatial econometrics
during the past 30 years. I argue that it has moved from the margins to the mainstream of …

Autoregressive models for spatial interaction have been proposed by several authors
(Whittle [15] and Mead [11], for example). In the past, computational difficulties with the ML …

Based on a large number of Monte Carlo simulation experiments on a regular lattice, we
compare the properties of Moran's I and Lagrange multiplier tests for spatial dependence …