Editorial: Central bank forecasting
In: International journal of forecasting, Band 35, Heft 4, S. 1561-1563
ISSN: 0169-2070
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In: International journal of forecasting, Band 35, Heft 4, S. 1561-1563
ISSN: 0169-2070
In: ECB Working Paper No. 2132; ISBN: 978-92-899-3237-0
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In: International journal of forecasting, Band 31, Heft 4, S. 1096-1103
ISSN: 0169-2070
In: ECB Working Paper No. 1494
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In: NBER Working Paper No. w18467
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In: Journal of Econometrics, Band 146, Heft 2, S. 318-328
This paper considers Bayesian regression with normal and double-exponential priors as forecasting methods based on large panels of time series. We show that, empirically, these forecasts are highly correlated with principal component forecasts and that they perform equally well for a wide range of prior choices. Moreover, we study conditions for consistency of the forecast based on Bayesian regression as the cross-section and the sample size become large. This analysis serves as a guide to establish a criterion for setting the amount of shrinkage in a large cross-section.
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 conditioning information set. The marginal contribution is then split into what is due to timeliness of information and what is due to economic content. We find that the Federal Reserve Bank of Philadelphia surveys have a large marginal impact on the nowcast of both inflation variables and real variables and this effect is larger than that of the Employment Report. When we control for timeliness of the releases, the effect of hard data becomes sizeable. Prices and quantities affect the precision of the estimates of inflation while GDP is only affected by real variables and interest rates.
BASE
In: Bundesbank Series 1 Discussion Paper No. 2006,32
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In: International journal of forecasting, Band 37, Heft 3, S. 1173-1191
ISSN: 0169-2070
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Working paper
In: http://dx.doi.org/10.17016/FEDS.2015.066
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Working paper
In: International journal of forecasting, Band 30, Heft 3, S. 635-644
ISSN: 0169-2070
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In: The economic journal: the journal of the Royal Economic Society, Band 122, Heft 564, S. F467-F486
ISSN: 1468-0297