Big Data Econometrics: Now Casting and Early Estimates
Gianluigi Mazzi and
No 1882, BAFFI CAREFIN Working Papers from BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy
This paper aims at providing a primer on the use of big data in macroeconomic nowcasting and early estimation. We discuss: (i) a typology of big data characteristics relevant for macroeconomic nowcasting and early estimates, (ii) methods for features extraction from unstructured big data to usable time series, (iii) econometric methods that could be used for nowcasting with big data, (iv) some empirical nowcasting results for key target variables for four EU countries, and (v) ways to evaluate nowcasts and ash estimates. We conclude by providing a set of recommendations to assess the pros and cons of the use of big data in a specific empirical nowcasting context.
Keywords: Big Data; Nowcasting; Early Estimates; Econometric Methods (search for similar items in EconPapers)
JEL-codes: C32 C53 C55 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-big, nep-ecm, nep-eec and nep-ets
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Persistent link: https://EconPapers.repec.org/RePEc:baf:cbafwp:cbafwp1882
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