Discussion Paper
Economic Predictions with Big Data: The Illusion of Sparsity
Abstract: The availability of large data sets, combined with advances in the fields of statistics, machine learning, and econometrics, have generated interest in forecasting models that include many possible predictive variables. Are economic data sufficiently informative to warrant selecting a handful of the most useful predictors from this larger pool of variables? This post documents that they usually are not, based on applications in macroeconomics, microeconomics, and finance.
Keywords: Shrinkage; High Dimensional Data; Model Selection;
JEL Classification: E17;
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Bibliographic Information
Provider: Federal Reserve Bank of New York
Part of Series: Liberty Street Economics
Publication Date: 2018-05-21
Number: 20180521