Causality has long been regarded among economists as a metaphysical minefield, best to be avoided. Yet, at the same time, the notion of cause and effect structures our ordinary lives and seems essential for understanding policy actions. Peter Adamset al.'s "Healthy, Wealthy, and Wise?" is welcome as an example of the relatively recent interest of microeconorm'sts in overcoming their metaphysical aversions in order to say something useful about cause and effect. Their study is carefully executed and aims to resolve a well-posed causal question. The authors' panel-data approach is closely analogous to the vector-autoregression (VAR) framework of macroeconomists. I want to pursue some of those analogies as they relate to causal inference. It is important to acknowledge that, because of the small number of periods, some of the technical issues in the estimation of panel data arc different from typical time-series data. The issues related to casual interpretation, however, do not depend on these differences.
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