Template-type: ReDIF-Paper 1.0
Author-Name: Dario Buono
Author-Name: George Kapetanios
Author-Name: Massimiliano Marcellino
Author-Name: Gianluigi Mazzi
Author-Name: Fotis Papailias
Title: Big Data Econometrics: Now Casting and Early Estimates
Abstract: 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.
Classification-JEL:C32, C53, C55
Keywords: Big Data, Nowcasting, Early Estimates, Econometric Methods
Length: 53 pages 
Number: 1882
Creation-Date: 2018
File-URL: https://repec.unibocconi.it/baffic/baf/papers/cbafwp1882.pdf
File-Format: application/pdf
File-Size: 479
Handle: RePEc:baf:cbafwp:cbafwp1882