Dynamic Factor Models in Forecasting Latvia's Gross Domestic Product

Working Paper 2/2008

Abstract
The study aims at evaluating how useful the application of models using large panels of data in forecasting Latvia's GDP is. Two factor models have been used: the Stock-Watson factor model and the generalised dynamic factor model. The forecast findings by the two models have been compared with the results obtained by the benchmark autoregressive model. The results suggest that compared with simpler autoregressive models both the Stock-Watson factor model and the generalised dynamic factor model ensure forecast improvement, which, however, has not been statistically significant if statistical tests are used.

Keywords: forecasting, factor models, large cross section

JEL codes: C32, C33, C53