Economic Predictions With Big Data: The Illusion of Sparsity

Domenico Giannone, Michele Lenza, Giorgio E. Primiceri

Econometrica · 2021 · Volume 89 · Issue 5

Abstract

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 prior that allows for both variable selection and shrinkage. The posterior distribution does not typically concentrate on a single sparse model, but on a wide set of models that often include many predictors.

Keywords

Variable selection, shrinkage, model uncertainty, high dimensional data

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