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Forecast Pooling for European Macroeconomic Variables *
Author(s) -
Marcellino Massimiliano
Publication year - 2004
Publication title -
oxford bulletin of economics and statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.131
H-Index - 73
eISSN - 1468-0084
pISSN - 0305-9049
DOI - 10.1111/j.1468-0084.2004.00071.x
Subject(s) - pooling , inflation (cosmology) , econometrics , economics , industrial production , unemployment , series (stratigraphy) , variable (mathematics) , linear model , statistics , mathematics , macroeconomics , computer science , physics , artificial intelligence , biology , theoretical physics , paleontology , mathematical analysis
We compare alternative forecast pooling methods and 58 forecasts from linear, time‐varying and non‐linear models, using a very large dataset of about 500 macroeconomic variables for the countries in the European Monetary Union. On average, combination methods work well but single non‐linear models can outperform them for several series. The performance of pooled forecasts, and of non‐linear models, improves when focusing on a subset of unstable series, but the gains are minor. Finally, on average over the EMU countries, the pooled forecasts behave well for industrial production growth, unemployment and inflation, but they are often beaten by non‐linear models for each country and variable.