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When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage

Laurent Ferrara () and Anna Simoni

No 2019-04, Working Papers from Center for Research in Economics and Statistics

Abstract: Nowcasting GDP growth is extremely useful for policy-makers to assess macroe-conomic conditions in real-time. In this paper, we aim at nowcasting euro area GDP with a large database of Google search data. Our objective is to check whether this speci?c type of information can be useful to increase GDP nowcasting accuracy, and when, once we control for o?cial variables. In this respect, we estimate shrunk bridge regressions that integrate Google data optimally screened through a targeting method, and we empirically show that this approach provides some gain in pseudo-real-time nowcasting of euro area GDP quarterly growth. Especially, we get that Google data bring useful information for GDP nowcasting for the four ?rst weeks of the quarter when macroeconomic information is lacking. However, as soon as o?cial data become available, their relative nowcasting power vanishes. In addition, a true real-time anal-ysis con?rms that Google data constitute a reliable alternative when o?cial data are lacking.

Keywords: Nowcasting; Big data; Google search data; Sure Independence Screening; Ridge Regularization. (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-big and nep-mac
Date: 2019-02-21
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