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is assessed in forecasting three major macroeconomic time series of the UK economy. Data-based restrictions of VAR … coefficients can help improve upon their unrestricted counterparts in forecasting, and in many cases they compare favorably to …
Persistent link: https://www.econbiz.de/10008764097
– 2010 I exhaustively evaluate the forecasting properties of Bayesian shrinkage in regressions with many predictors. Results …
Persistent link: https://www.econbiz.de/10009000949
This paper considers Bayesian variable selection in regressions with a large number of possibly highly correlated macroeconomic predictors. I show that by acknowledging the correlation structure in the predictors can improve forecasts over existing popular Bayesian variable selection algorithms.
Persistent link: https://www.econbiz.de/10010614521
In this paper we develop methods for estimation and forecasting in large time-varying parameter vector autoregressive … application involving forecasting inflation, real output, and interest rates demonstrates the feasibility and usefulness of our …
Persistent link: https://www.econbiz.de/10010540685
This paper compares the forecasting performance of different models which have been proposed for forecasting in the … macroeconomic time series, we demonstrate the presence of structural breaks and their importance for forecasting in the vast … majority of cases. We find no single forecasting model consistently works best in the presence of structural breaks. In many …
Persistent link: https://www.econbiz.de/10009142658
monetary policy analysis and macro-forecasting with the use of advanced Bayesian methods. …
Persistent link: https://www.econbiz.de/10010656010
Macroeconomic practitioners frequently work with multivariate time series models such as VARs, factor augmented VARs as well as time-varying parameter versions of these models (including variants with multivariate stochastic volatility). These models have a large number of parameters and, thus,...
Persistent link: https://www.econbiz.de/10008487526
We develop methods for Bayesian inference in vector error correction models which are subject to a variety of switches in regime (e.g. Markov switches in regime or structural breaks). An important aspect of our approach is that we allow both the cointegrating vectors and the number of...
Persistent link: https://www.econbiz.de/10009320949
This paper develops methods for Stochastic Search Variable Selection (currently popular with regression and Vector Autoregressive models) for Vector Error Correction models where there are many possible restrictions on the cointegration space. We show how this allows the researcher to begin with...
Persistent link: https://www.econbiz.de/10008487518
This paper proposes new dynamic component models of returns and realized covariance (RCOV) matrices based on time-varying Wishart distributions. Bayesian estimation and model comparison is conducted with a range of multivariate GARCH models and existing RCOV models from the literature. The main...
Persistent link: https://www.econbiz.de/10008800574