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Pooling of Forecasts; does it Improve the Nowcast of Swedish GDP?
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
2015 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Even slight improvements in forecast accuracy can have a huge economic impact. Especially, when considering the steady increase of interconnections in the global financial markets, and the ever growing pressure of quick decisions. Empirically, combinations of forecasts from several plausible models usually outperform the forecast of the best fitted model in the presence of model uncertainty. Can the accuracy of the nowcast of Swedish GDP be improved by combining the forecasts of multiple economic models? Different specifications of mixed data sampling (MIDAS) regressions are fitted and used to produce nowcasts of current quarter GDP. The performance of the pooling and the single model selection is evaluated by pseudo out-of-sample forecast MSE. Simple pooling schemes of the forecasts significantly outperforms the benchmark, while very few of the best fitted models achieve significantly improved accuracy over the benchmark. Overall, the pooling of forecasts also produces more stable and lower mean square forecast errors than the other model specifications.

Place, publisher, year, edition, pages
2015. , 23 p.
Keyword [en]
Forecast, Nowcast, MIDAS, Factor models, Pooling
National Category
Economics and Business Probability Theory and Statistics
URN: urn:nbn:se:uu:diva-256074OAI: diva2:824672
External cooperation
Educational program
Master Programme in Statistics
Available from: 2015-06-24 Created: 2015-06-22 Last updated: 2015-06-24Bibliographically approved

Open Access in DiVA