Template-Type: ReDIF-Paper 1.0
Author-Name: Emilio Blanco
Author-Name-First: Emilio
Author-Name-Last: Blanco
Author-Name: Laura D’Amato
Author-Name-First: Laura 
Author-Name-Last: D’Amato
Author-Name: Fiorella Dogliolo
Author-Name-First: Fiorella
Author-Name-Last: Dogliolo
Author-Name: Lorena Garegnani
Author-Name-First: Lorena
Author-Name-Last: Garegnani
Title: Nowcasting Macroeconomic Aggregates in Argentina: Comparing the predictive ability of different models
Abstract: Monetary policy making requires a correct and timely assessment of current macroeconomic conditions. While the main source of macroeconomic data is quarterly National Accounts, of- ten published with a significant lag, higher frequency business cycle indicators are increasingly available. Taking this into account, central banks have adopted nowcasting as a useful tool for having an immediate and more accurate perception of economic conditions. In this paper, we extend the use of nowcasting tools to produce early indicators of the evolution of two components of aggregate domestic demand: consumption and investment. The exercise uses a broad and restricted set of indicators to construct di↵erent dynamic factor models, as well as a pooling of models in the case of investment. Finally, we compare di↵erent approaches in a pseudo-real time out-of-sample exercise and evaluate their predictive performance.
Length:  19 pages
Creation-Date:  2020-11
File-URL: https://aaep.org.ar/works/works2020/DAmato2020.pdf
File-Format: Application/pdf
Number: 4335
Classification-JEL:  C22, C53, E37
Keywords: Nowcasting, dynamic factor models, forecast pooling
Handle: RePEc:aep:anales:4335