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Economic predictions with big data: the illusion of sparsity

Author

Listed:
  • Giannone, Domenico
  • Lenza, Michele
  • Primiceri, Giorgio E.
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. JEL Classification: C11, C52, C53, C55

Suggested Citation

  • Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio E., 2021. "Economic predictions with big data: the illusion of sparsity," Working Paper Series 2542, European Central Bank.
    • Handle: RePEc:ecb:ecbwps:20212542
    Note: 411196
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    References listed on IDEAS

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    More about this item

    Keywords

    curse of dimensionality; model uncertainty; shrinkage; variable selection;
    All these keywords.

    JEL classification:

    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

    NEP fields

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