Francesca Monti
King's College
will give a presentation on
Nowcasting with large Bayesian vector autoregressions
Abstrct
Monitoring economic conditions in real time,or nowcasting, is among the key tasks routinelyperformed by economists. Nowcasting entails some key challenges, which also characterisemodern Big Data analytics, often referred to as the three “Vs”: the large number of timeseries continuously released (Volume), the complexity of the data covering various sectors ofthe economy, published in an asynchronous way and with different frequencies and precision(Variety), and the need to incorporate new information within minutes of their release (Ve-locity). In this paper, we explore alternative routes to bring Bayesian Vector Autoregressive(BVAR) models up to these challenges. We find that BVARs are able to effectively handlethe three Vs and produce, in real time, accurate probabilistic predictions of US economicactivity and, in addition, a meaningful narrative by means of scenario analysis.
Joint with Jacopo Cimadomo, Domenico Giannone, Michele Lenza and Andrej Sokol
Meeting ID: 984 7226 7504
Access code: 305594