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Forecasting economic activity with mixed frequency Bayesian VARs
Brave, Scott A.; Butters, R. Andrew; Justiniano, Alejandro - 2016
Mixed frequency Bayesian vector autoregressions (MF-BVARs) allow forecasters to incorporate a large number of mixed frequency indicators into forecasts of economic activity. This paper evaluates the forecast performance of MF-BVARs relative to surveys of professional forecasters and investigates...
Persistent link: https://www.econbiz.de/10011776834
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Nowcasting GDP in Real-Time: A Density Combination Approach
Aastveit, Knut Are; Gerdrup, Karsten R.; Jore, Anne Sofie; … - 2011
In this paper we use U.S. real-time vintage data and produce combined density nowcasts for quarterly GDP growth from a system of three commonly used model classes. The density nowcasts are combined in two steps. First, a wide selection of individual models within each model class are combined...
Persistent link: https://www.econbiz.de/10012143776
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GDPNow: A model for GDP "nowcasting"
Higgins, Patrick - 2014
This paper documents GDPNow, a "nowcasting" model for gross domestic product (GDP) growth that synthesizes the "bridge …
Persistent link: https://www.econbiz.de/10010397673
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A Survey of Econometric Methods for Mixed-Frequency Data
Foroni, Claudia; Marcellino, Massimiliano - 2013
The development of models for variables sampled at different frequencies has attracted substantial interest in the recent econometric literature. In this paper we provide an overview of the most common techniques, including bridge equations, MIxed DAta Sampling (MIDAS) models, mixed frequency...
Persistent link: https://www.econbiz.de/10012143818
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Density Forecasts with Midas Models
Aastveit, Knut Are; Foroni, Claudia; Ravazzolo, Francesco - 2014
In this paper we derive a general parametric bootstrapping approach to compute density forecasts for various types of mixed-data sampling (MIDAS) regressions. We consider both classical and unrestricted MIDAS regressions with and without an autoregressive component. First, we compare the...
Persistent link: https://www.econbiz.de/10012143848
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Nowcasting Using News Topics. Big Data Versus Big Bank
Thorsrud, Leif Anders - 2016
and thereby shape aggregate economic fluctuations. Traditional nowcasting approches have to a relatively little degree …
Persistent link: https://www.econbiz.de/10012143898
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Using survey information for improving the density nowcasting of US GDP with a focus on predictive performance during Covid-19 pandemic
Çakmaklı, Cem; Demircan, Hamza - 2020
We provide a methodology that efficiently combines the statistical models of nowcasting with the survey information for … improving the (density) nowcasting of US real GDP. Specifically, we use the conventional dynamic factor model together with a … over the baseline model for nowcasting GDP. While the mean survey predictions deliver valuable information during extreme …
Persistent link: https://www.econbiz.de/10012628449
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Information in the revision process of real-time datasets
Corradi, Valentina; Fernandez, Andres; Swanson, Norman R. - 2011
Rationality of early release data is typically tested using linear regressions. Thus, failure to reject the null does not rule out the possibility of nonlinear dependence. This paper proposes two tests that have power against generic nonlinear alternatives. A Monte Carlo study shows that the...
Persistent link: https://www.econbiz.de/10010282830
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Real-time datasets really do make a difference: Definitional change, data release, and forecasting
Fernandez, Andres; Swanson, Norman - 2011
In this paper, we empirically assess the extent to which early release inefficiency and definitional change affect prediction precision. In particular, we carry out a series of ex-ante prediction experiments in order to examine: the marginal predictive content of the revision process, the...
Persistent link: https://www.econbiz.de/10010282871
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Combining Forecast Densities from VARs with Uncertain Instabilities
Jore, Anne Sofie; Mitchell, James; Vahey, Shaun P. - 2008
Clark and McCracken (2008) argue that combining real-time point forecasts from VARs of output, prices and interest rates improves point forecast accuracy in the presence of uncertain model instabilities. In this paper, we generalize their approach to consider forecast density combinations and...
Persistent link: https://www.econbiz.de/10012143681