A comprehensive evaluation of macroeconomic forecasting methods

Carriero, Andrea and Galvão, Ana Beatriz and Kapetanios, George,(2019), A comprehensive evaluation of macroeconomic forecasting methods. , International Journal of Forecasting, UNSPECIFIED

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We employ datasets for seven developed economies and consider four classes of multivariate forecasting models in order to extend and enhance the empirical evidence in the macroeconomic forecasting literature. The evaluation considers forecasting horizons of between one quarter and two years ahead. We find that the structural model, a mediumsized DSGE model, provides accurate long-horizon US and UK inflation forecasts. We strike a balance between being comprehensive and producing clear messages by applying meta-analysis regressions to 2,976 relative accuracy comparisons that vary with the forecasting horizon, country, model class and specification, number of predictors, and evaluation period. For point and density forecasting of GDP growth and inflation, we find that models with large numbers of predictors do not outperform models with 13–14 hand-picked predictors. Factor-augmented models and equal-weighted combinations of single-predictor mixed-data sampling regressions are a better choice for dealing with large numbers of predictors than Bayesian VARs.
Keywords : Factor models BVAR models MIDAS models DSGE models Density forecasts Meta-analysis, UNSPECIFIED
Journal or Publication Title: International Journal of Forecasting
Volume: 35
Item Type: Article
Subjects: Ekonomi Pembangunan
Depositing User: Elok Inajati
Date Deposited: 30 Dec 2019 02:04
Last Modified: 30 Dec 2019 02:04
URI: https://repofeb.undip.ac.id/id/eprint/1130

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