Discussion paper

DP12256 Economic Predictions with Big Data: The Illusion Of Sparsity

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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Citation

Giannone, D, M Lenza and G Primiceri (2017), ‘DP12256 Economic Predictions with Big Data: The Illusion Of Sparsity‘, CEPR Discussion Paper No. 12256. CEPR Press, Paris & London. https://cepr.org/publications/dp12256