Economic predictions with big data: The illusion of sparsity - Domenico Giannone; Michele Lenza; Giorgio E. Primiceri (European Central Bank (ECB), 2021)
We compare sparse and dense representations of predictive models in macroeconomics, microeconomics and ftnance. 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: C11; C52; C53; C55; 330; Variable Selection; Shrinkage; Model uncertainty; Curse of dimensionality