Autori:
Proietti, Tommaso,
Ricchi, Ottavio,
Tegami, Cristian,
Tinti, Cristina,
Giovannelli, Alessandro,
Citton, AmbraTitolo:
Nowcasting GDP and its components in a data-rich environment:the merits of the indirect approachPeriodico:
Ministero dell'Economia e delle Finanze. Dipartimento del Tesoro. Working paperAnno:
2020 - Fascicolo:
2 - Pagina iniziale:
3 - Pagina finale:
40The national accounts provide a coherent and exaustive description of the current state of the economy, but are available at the quarterly frequency and are released with a nonignorable
publication lag. The paper proposes and illustrates a method for nowcasting and forecasting the sixteen main components of Gross Domestic Product (GDP) by output and expenditure type at the monthly frequency, using a high-dimensional set of monthly economic indicators spanning the space of the common macroeconomic and financial factors. The projection on the common
space is carried out by combining the individual nowcasts and forecasts arising from all possible bivariate models of the unobserved monthly GDP component and the observed monthly
indicator. We discuss several pooling strategies and we select the one showing the best predictive performance according to a pseudo real time forecasting experiment. Monthly GDP can be indirectly estimated by the contemporaneous aggregation of the value added of the
different industries and of the expenditure components. This enables the comparative assessment of the indirect nowcasts and forecasts vis-à-vis the direct approach and a growth accounting exercise.
Our approach meets the challenges posed by the dimensionality, since it can handle a large
number of time series with a complexity that increases linearly with the cross-sectional
dimension, while retaining the essential heterogeneity of the information about the
macroeconomy. The application to the Italian case leads to several interesting discoveries
concerning the time-varying predictive content of the information carried by the monthly indicators.
SICI: 1972-411X(2020)2<3:NGAICI>2.0.ZU;2-
Testo completo:
http://www.dt.mef.gov.it/modules/documenti_it/analisi_progammazione/working_papers/WP_2.pdfEsportazione dati in Refworks (solo per utenti abilitati)
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