Macroeconometric forecasting using a cluster of dynamic factor models

Forecasting with dynamic factor models

The validity of previous findings that dynamic factor models are useful for macroeconomic forecasting is of great importance for subsequent studies which use these models not only as a starting point for further developments but also as a benchmark for the evaluation of the forecasting performance of these further developments. Reanalyzing a standard macroeconomic dataset, we do not find any ev...

Forecasting in Dynamic Factor Models Using Bayesian Model Averaging

This paper considers the problem of forecasting in dynamic factor models using Bayesian model averaging. Theoretical justi…cations for averaging across models, as opposed to selecting a single model, are given. Practical methods for implementing Bayesian model averaging with factor models are described. These methods involve algorithms which simulate from the space de…ned by all possible models...

Sufficient Forecasting Using Factor Models ∗

We consider forecasting a single time series when there is a large number of predictors and a possible nonlinear effect. The dimensionality was first reduced via a highdimensional factor model implemented by the principal component analysis. Using the extracted factors, we develop a link-free forecasting method, called the sufficient forecasting, which provides several sufficient predictive ind...

Wind Power Forecasting Using Dynamic Bayesian Models

Introduction Due to the cleanness and low cost of wind energy, wind farms are designed to produce as much energy as possible. Wind depends on external atmospheric conditions. For energy control centers is difficult to schedule wind power energy due to its intermittency.

Forecasting in Dynamic Factor Models Subject to Structural Instability