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Economic Predictions with Big Data: The Illusion Of Sparsity

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  • 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 "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.

Suggested Citation

  • Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio E, 2017. "Economic Predictions with Big Data: The Illusion Of Sparsity," CEPR Discussion Papers 12256, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:12256
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    1. Fernández, Raquel & Martin, Alberto, 2014. "The Long and the Short of It: Sovereign Debt Crises and Debt Maturity," CEPR Discussion Papers 10322, C.E.P.R. Discussion Papers.
    2. Sturzenegger, Federico & Zettelmeyer, Jeromin, 2008. "Haircuts: Estimating investor losses in sovereign debt restructurings, 1998-2005," Journal of International Money and Finance, Elsevier, vol. 27(5), pages 780-805, September.
    3. Tamon Asonuma & Christoph Trebesch, 2016. "Sovereign Debt Restructurings: Preemptive Or Post-Default," Journal of the European Economic Association, European Economic Association, vol. 14(1), pages 175-214, February.
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