Economic Predictions with Big Data: The Illusion of Sparsity
28 Pages Posted: 11 Sep 2017
Date Written: August 2017
We compare sparse and dense representations of predictive models in macroeconomics, microeconomics and finance. To deal with a large number of possible predictors, we specify a "spike-and-slab" prior that allows for both variable selection and shrinkage. The posterior distribution does not typically concentrate on a single sparse or dense model but on a wide set of models. A clearer pattern of sparsity can only emerge when models of very low dimension are strongly favored a priori.
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