Similar Search Results

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

Point and density forecasts for the euro area using Bayesian VARs

Berg, Tim Oliver; Henzel, Steffen - 2014

Recent articles suggest that a Bayesian vector autoregression (BVAR) with shrinkage is a good forecast device even when the number of variables is large. In this paper we evaluate different variants of the BVAR with respect to their forecast accuracy for euro area real GDP growth and HICP...

Persistent link: https://www.econbiz.de/10010257225

Point and density forecasts for the Euro area using many predictors : are large BVARs really superior?

Berg, Tim Oliver; Henzel, Steffen - 2013

Forecast models with large cross-sections are often subject to overparameterization leading to unstable parameter estimates and hence inaccurate forecasts. Recent articles suggest that a large Bayesian vector autoregression (BVAR) with sufficient prior information dominates competing approaches....

Persistent link: https://www.econbiz.de/10010342246

Putting the New Keynesian DSGE model to the real-time forecasting test

Kolasa, Marcin; Rubaszek, Michał; Skrzypczyński, Paweł - 2009

. Nevertheless, their forecasting properties are still barely explored. We fill this gap by comparing the quality of real … priors from a DSGE model. We show that the analyzed DSGE model is relatively successful in forecasting the US economy in the … accurate short-term forecasts for interest rates. Conditional on experts' now casts, however, the forecasting power of the DSGE …

Persistent link: https://www.econbiz.de/10011605156

Inference in vector autoregressive models with an informative prior on the steady state

Villani, Mattias - 2005

Vector autoregressions have steadily gained in popularity since their introduction in econometrics 25 years ago. A drawback of the otherwise fairly well developed methodology is the inability to incorporate prior beliefs regarding the system's steady state in a satisfactory way. Such prior...

Persistent link: https://www.econbiz.de/10011585058

Forecasting inflation in Argentina

Garegnani, María Lorena; Gómez Aguirre, Maximiliano - 2018

In 2016 the Central Bank of Argentina began to announce inflation targets. In this context, providing authorities with good estimates of relevant macroeconomic variables is crucial for making pertinent corrections in order to reach the desired policy goals. This paper develops a group of models...

Persistent link: https://www.econbiz.de/10011882797

Improving inference and forecasting in VAR models using cross-sectional information

Prüser, Jan; Blagov, Boris - 2022

We propose a prior for VAR models that exploits the panel structure of macroeconomic time series while also providing shrinkage towards zero to address overfitting concerns. The prior is flexible as it detects shared dynamics of individual variables across endogenously determined groups of...

Persistent link: https://www.econbiz.de/10013359163

Bayesian forecast combination for VAR models

Andersson, Michael K.; Karlsson, Sune - 2007

problem to tackle with a traditional Bayesian approach. Our solution is to focus on the forecasting performance for the …

Persistent link: https://www.econbiz.de/10010320769

Bayesian forecast combination for VAR models

Andersson, Michael K. (contributor); … - 2007

problem to tackle with a traditional Bayesian approach. Our solution is to focus on the forecasting performance for the …

Persistent link: https://www.econbiz.de/10003581516

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

1
2
3
4
5
6
7
8
9
10
Next
Last