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Macroeconomic forecasting in the EMU: Does disaggregate modeling improve forecast accuracy?

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  • Ruth, Karsten
Abstract
Accurate forecasts of aggregate European variables are crucial for conducting a union-wide monetary policy. This paper investigates empirically whether pooling forecasts from disaggregate models is a promising strategy for forecasting actual macroeconomic European variables. In contrast to previous studies we formulate an intermediate case of disaggregation with regard to forecast combination by pooling forecasts obtained from models which are separately specified and estimated for subgroups of actual EMU Member States. Moreover, by modeling different degrees of monetary autonomy across countries during the EMS-era we explicitly account for cross-country heterogeneity in advance of 1999. We find that policymakers might obtain more accurate forecasts of actual European macroeconomic variables by pooling subgroup-specific forecasts compared to forecasting with a single union-wide model.

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  • Ruth, Karsten, 2008. "Macroeconomic forecasting in the EMU: Does disaggregate modeling improve forecast accuracy?," Journal of Policy Modeling, Elsevier, vol. 30(3), pages 417-429.
    • Handle: RePEc:eee:jpolmo:v:30:y:2008:i:3:p:417-429
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    3. Mihaela Bratu (Simionescu), 2013. "How to Improve the SPF Forecasts?," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 9(2), pages 153-165, April.
    4. Gabe de Bondt & Arne Gieseck & Pablo Herrero & Zivile Zekaite, 2021. "Euro Area Income and Wealth Effects: Aggregation Issues," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(6), pages 1454-1474, December.
    5. BRATU SIMIONESCU, Mihaela, 2012. "Two Quantitative Forecasting Methods For Macroeconomic Indicators In Czech Republic," Annals of Spiru Haret University, Economic Series, Universitatea Spiru Haret, vol. 3(1), pages 71-87.
    6. Onorante, Luca & Pedregal, Diego J. & Pérez, Javier J. & Signorini, Sara, 2010. "The usefulness of infra-annual government cash budgetary data for fiscal forecasting in the euro area," Journal of Policy Modeling, Elsevier, vol. 32(1), pages 98-119, January.
    7. Mihaela BRATU (SIMIONESCU), 2012. "A Strategy To Improve The Gdp Index Forcasts In Romania Using Moving Average Models Of Historical Errors Of The Dobrescu Macromodel," Romanian Journal of Economics, Institute of National Economy, vol. 35(2(44)), pages 128-138, December.
    8. Bratu Mihaela, 2013. "An Evaluation Of Usa Unemployment Rate Forecasts In Terms Of Accuracy And Bias. Empirical Methods To Improve The Forecasts Accuracy," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 1, pages 170-180, February.
    9. Antipa, Pamfili & Barhoumi, Karim & Brunhes-Lesage, Véronique & Darné, Olivier, 2012. "Nowcasting German GDP: A comparison of bridge and factor models," Journal of Policy Modeling, Elsevier, vol. 34(6), pages 864-878.
    10. Mihaela Simionescu, 2014. "What Type Of Social Capital Is Engaged By The French Dairy Stockbreeders? A Characterization Through Their Professional Identities," Romanian Journal of Regional Science, Romanian Regional Science Association, vol. 8(1), pages 87-102, JUNE.
    11. Cesar Carrera & Alan Ledesma, 2015. "Aggregate Inflation Forecast with Bayesian Vector Autoregressive Models," Working Papers 50, Peruvian Economic Association.
    12. Constantin Mitru? & Mihaela Bratu (Simionescu), 2013. "The Indicators’ Inadequacy and the Predictions’ Accuracy," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 9(4), pages 430-442, August.
    13. Mihaela Simionescu, 2015. "The Improvement of Unemployment Rate Predictions Accuracy," Prague Economic Papers, Prague University of Economics and Business, vol. 2015(3), pages 274-286.

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