Developing spatial econometrics functions in R can not only enable analysts to advance our own techniques using convenient interpreted language features. Placing spatial econometrics and more generally spatial statistics in the context of an extensible data analysis environment also exposes similarities and differences between traditions of analysis. These can be fruitful, as is explored here i...

One can have an impact on a field in a variety of ways such as papers published in prestigious journals, through service to associations, and through students. Certainly, James LeSage has published extensively in a variety of fields including economics and econometrics, regional science, spatial econometrics and statistics. He has helped organize sessions and performed other conference-related ...

This paper reviews a number of conceptual issues pertaining to the implementation of an explicit " spatial " perspective in applied econometrics. It provides an overview of the motivation for including spatial effects in regression models, both from a theory-driven as well as from a data-driven perspective. Considerable attention is paid to the inferential framework necessary to carry out estim...

Many theories in political science predict the spatial clustering of similar behaviors among neighboring units of observation. This spatial autocorrelation poses implications for both inference and modeling that are distinct from the more familiar serial dependence in time series analysis. In this paper, I examine how political scientists can diagnose and model the spatial dependence that is pr...