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This paper formalizes the process of updating the nowcast and forecast on output and inflation as new releases of data become available. The marginal contribution of a particular release for the value of the signal and its precision is evaluated by computing "news" on the basis of an evolving...
Persistent link: https://www.econbiz.de/10011604679
, produces a degree of forecasting accuracy of the federal funds rate similar to that of the markets, and, for output and …
Persistent link: https://www.econbiz.de/10005497952
This paper formalizes the process of updating the nowcast and forecast on output and inflation as new releases of data become available. The marginal contribution of a particular release for the value of the signal and its precision is evaluated by computing 'news' on the basis of an evolving...
Persistent link: https://www.econbiz.de/10005124339
predictive accuracy in now-casting and forecasting. Our empirical results show that both the monthly version of the DSGE and the …
Persistent link: https://www.econbiz.de/10011399325
Monitoring economic conditions in real time, or nowcasting, is among the key tasks routinely performed by economists. Nowcasting entails some key challenges, which also characterise modern Big Data analytics, often referred to as the three "Vs": the large number of time series continuously...
Persistent link: https://www.econbiz.de/10012259379
This paper considers Bayesian regression with normal and doubleexponential priors as forecasting methods based on large …
Persistent link: https://www.econbiz.de/10010295821
This paper considers Bayesian regression with normal and doubleexponential priors as forecasting methods based on large …
Persistent link: https://www.econbiz.de/10011604746
We compare sparse and dense representations of predictive models in macroeconomics, microeconomics, and finance. To deal with a large number of possible predictors, we specify a prior that allows for both variable selection and shrinkage. The posterior distribution does not typically concentrate...
Persistent link: https://www.econbiz.de/10012921051
We define nowcasting as the prediction of the present, the very near future and the very recent past. Crucial in this process is to use timely monthly information in order to nowcast key economic variables, such as e.g. GDP, that are typically collected at low frequency and published with long...
Persistent link: https://www.econbiz.de/10013135504
This paper describes an algorithm to compute the distribution of conditional forecasts, i.e. projections of a set of variables of interest on future paths of some other variables, in dynamic systems. The algorithm is based on Kalman filtering methods and is computationally viable for large...
Persistent link: https://www.econbiz.de/10013047977