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 estimat...

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 applied econometrics and social science methodology. I distinguish three broad phases in the development, which I refer to as preconditions, take off and maturity. For each of these phases I describe the main meth...

Analysis of strategic interaction among decision makers has recently become a major focus of economists and other social scientists. An example of such interaction includes interdependent choices of policy instruments by local or state governments. In this case, the optimal level of a jurisdiction's policy instrument depends on the levels chosen by other (perhaps neighboring) jurisdictions. Ano...

Spatial autocorrelation is a concept that helps to define the field of spatial analysis. It is central to studies using spatial statistics and spatial econometrics. In this paper, we trace the early development of the concept and explain the academic links that brought the concept to the fore in the late 1960s. In geography, the importance of the work of Michael F. Dacey, Andrew D. Cliff, and J...

It is now almost impossible to deal with spatial data without considering some explicit specification that captures possible spatial effects. One valuable feature of spatial econometrics models is their decomposition of marginal effects into spatial spillover effect and spatial externalities. Progress in interpreting spatial econometrics models has now been extended to the spatial-panel case. H...

Spatial autoregressive combined (SAC) model has been widely studied in the literature for analysis of spatial data various areas such as geography, economics, demography, regional sciences. This is a linear with scalar response, explanatory variables and which allows interactions dependent variable disturbances. In this work we extend modeling approach from to functional covariate. The paramete...