In this paper, we develop methods for estimation and forecasting in large time-varying parameter vector autoregressive … dimension can change over time. For instance, we can have a large TVP-VAR as the forecasting model at some points in time, but a …, the parameter(s) of the shrinkage priors commonly-used with large VARs. These extensions are operationalized through the …

coefficients and the importance of the variables are allowed to change over time. We focus on forecasting and so the parsimony of … the model is important for good performance. A prior is developed which allows the shrinkage of the regression …. The new method is applied to two forecasting problems in econometrics: equity premium prediction and inflation forecasting …

principle components and other shrinkage techniques, including Bayesian model averaging and various bagging, boosting, least … prediction model specification methods, and that using “hybrid” combination factor/shrinkage methods often yields superior … 1990s, model averaging wins almost 1/2 of the time. Overall, combination factor/shrinkage methods “win” approximately 1 …