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ABSTRACT We argue that identification problems bedevil applied spatial economic research. Spatial econometrics usually solves these problems by deriving estimators assuming that functional forms are known and by using model comparison techniques to let the data choose between competing specifications. We argue that in many situations of interest this achieves, at best, only very weak identification. Worse, in many cases, such an approach will be uninformative about the causal economic processes at work, rendering much applied spatial econometric research “pointless,” unless the main aim is description of the data. We advocate an alternative approach based on the “experimentalist paradigm” which puts issues of identification and causality at center stage.