Showing 1 - 10 of 494
In this paper we reconsider large Bayesian Vector Autoregressions (BVAR) from the point of view of Bayesian Compressed Regression (BCR). First, we show that there are substantial gains in terms of out-of-sample forecasting by treating the problem as an error-in-variables formulation and...
Persistent link: https://www.econbiz.de/10014078868
We consider two problems concerning locating change points in a linear regression model. One involves jump discontinuities (change-point) in a regression model and the other involves regression lines connected at unknown points. We compare four methods for estimating single or multiple change...
Persistent link: https://www.econbiz.de/10013146197
The growing availability of financial and macroeconomic data sets including a large number of time series (hence the high dimensionality) calls for econometric methods providing a convenient and parsimonious representation of the covariance structure both in the time and the cross-sectional...
Persistent link: https://www.econbiz.de/10013112480
Persistent link: https://www.econbiz.de/10012991173
This paper proposes a variational Bayes algorithm for computationally efficient posterior and predictive inference in time-varying parameter (TVP) models. Within this context we specify a new dynamic variable/model selection strategy for TVP dynamic regression models in the presence of a large...
Persistent link: https://www.econbiz.de/10012851399
Bayesian regularization, a relatively new method for estimating model parameters, shrinks estimates towards the overall mean by shrinking the parameters. It has been proven to lower estimation and prediction variances from those of MLE for linear models, such as regression or GLM. It has a...
Persistent link: https://www.econbiz.de/10012851806
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
We simplify the implementation of some elliptical copula regression models through the normal representation. Both copula and marginal probability density functions are expressed as the scale mixtures of normals to facilitate the estimation procedure. With the fact that all elliptical...
Persistent link: https://www.econbiz.de/10014166990
We present the censored regression model with the error term following the asymmetric exponential power distribution. We propose three Markov chain Monte Carlo (MCMC) algorithms: the first one uses the probability integral transformation; the second one uses a combination of the probability...
Persistent link: https://www.econbiz.de/10014172697
We study the performance of Bayesian model averaging as a forecasting method for a large panel of time series and compare its performance to principal components regression (PCR). We show empirically that these forecasts are highly correlated implying similar mean-square forecast errors. Applied...
Persistent link: https://www.econbiz.de/10014039176