Paper by Andrew Caplin: “Economic data engineering deliberately designs novel forms of data to solve fundamental identification problems associated with economic models of choice. I outline three diverse applications: to the economics of information; to life-cycle employment, earnings, and spending; and to public policy analysis. In all three cases one and the same fundamental identification problem is driving data innovation: that of separately identifying appropriately rich preferences and beliefs. In addition to presenting these conceptually linked examples, I provide a general overview of the engineering process, outline important next steps, and highlight larger opportunities…(More)”.
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