Causal Inference With Spatial Econometric Models: Challenges and Applications for Epidemiologic Research

Abstract

Spatial econometric models have become very popular in recent years and have started to make their appearance in geospatial studies of health outcomes. Although explicit or implicit causal claims are widely made using these models, this article demonstrates with the use of causal graphs why causal vocabulary should be avoided. The article first introduces spatial causal inference from an epidemiologic perspective and then presents the challenges in the application of these specifications using this framework. Further implications and modeling options are discussed.