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Bayesian demographic modeling and forecasting : an application to U.S. mortality
Reichmuth, Wolfgang H. (contributor);  … - 2008
We present a new way to model age-specific demographic variables with the example of age-specific mortality in the U … jointly with the latent variables underlying mortality of all age classes. In contrast to previous models, a similar … forecasts for particular age classes. A structural analysis of the relationship between age-specific mortality and covariates is …
Persistent link: https://www.econbiz.de/10003770767
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Modeling and forecasting age-specific mortality : a Bayesian approach
Reichmuth, Wolfgang H. (contributor);  … - 2008
We present a new way to model age-specific demographic variables, using the example of age-specific mortality in the … their dynamics jointly with the latent variables underlying mortality of all age classes. In contrast to previous models, a … for particular age classes. A structural analysis of the relationship between age-specific mortality and covariates is …
Persistent link: https://www.econbiz.de/10003770768
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Large vector autoregressions with asymmetric priors
Carriero, Andrea; Clark, Todd E.; Marcellino, Massimiliano - 2015 - This draft: November 2015
We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors and time varying volatilities, even when the cross sectional dimension of the system N is particularly large. The algorithm is based on a simple triangularisation which allows to...
Persistent link: https://www.econbiz.de/10011389735
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Forecast accuracy of a BVAR under alternative specifications of the zero lower bound
Berg, Tim Oliver - 2015
This paper discusses how the forecast accuracy of a Bayesian vector autoregression (BVAR) is affected by introducing the zero lower bound on the federal funds rate. As a benchmark I adopt a common BVAR specification, including 18 variables, estimated shrinkage, and no nonlinearity. Then I...
Persistent link: https://www.econbiz.de/10011306293
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Forecasting with instabilities : an application to DSGE models with financial frictions
Cardani, Roberta; Paccagnini, Alessia; Villa, Stefania - 2015
This paper examines whether the presence of parameter instabilities in dynamic stochastic general equilibrium (DSGE) models affects their forecasting performance. We apply this analysis to medium-scale DSGE models with and without financial frictions for the US economy. Over the forecast period...
Persistent link: https://www.econbiz.de/10011349997
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Money growth and inflation : evidence from a Markov Switching Bayesian VAR
Amisano, Gianni; Colavecchio, Roberta - 2013
We contribute to the empirical debate on the role of money in monetary policy by analysing the features of the relationship between money growth and inflation in a Bayesian Markov Switching framework for a set of four countries, the US, the UK, the Euro area and Japan, over an estimation period...
Persistent link: https://www.econbiz.de/10010425829
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Marginalized predictive likelihood comparisons of linear Gaussian state-space models with applications to DSGE, DSGEVAR, and VAR models
Warne, Anders; Coenen, Günter; Christoffel, Kai - 2014
The predictive likelihood is of particular relevance in a Bayesian setting when the purpose is to rank models in a forecast comparison exercise. This paper discusses how the predictive likelihood can be estimated for any subset of the observable variables in linear Gaussian state-space models...
Persistent link: https://www.econbiz.de/10010412361
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Forecasting Using a Large Number of Predictors : Is Bayesian Regression a Valid Alternative to Principal Components?
De Mol, Christine - 2016
Persistent link: https://www.econbiz.de/10012991173
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Forecasting Using a Large Number of Predictors : Is Bayesian Regression a Valid Alternative to Principal Components?
De Mol, Christine; Giannone, Domenico; Reichlin, Lucrezia - 2021
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...
Persistent link: https://www.econbiz.de/10013317338
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Nowcasting in a pandemic using non-parametric mixed frequency VARs
Huber, Florian; Koop, Gary; Onorante, Luca; Pfarrhofer, … - 2021
This paper develops Bayesian econometric methods for posterior inference in non-parametric mixed frequency VARs using additive regression trees. We argue that regression tree models are ideally suited for macroeconomic nowcasting in the face of extreme observations, for instance those produced...
Persistent link: https://www.econbiz.de/10012405305