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Forecasting the Spanish economy with an Augmented VAR-DSGE model

Author

Listed:
  • Gonzalo Fernandez-de-Córdoba

    (Universidad de Salamanca)

  • José L. Torres

    (Universidad de Málaga)

Abstract

During the past ten years Dynamic Stochastic General Equilibrium (DSGE) models have become an important tool in quantitative macroeconomics. However, DSGE models was not considered as a forecasting tool until very recently. The objective of this paper is twofold. First, we compare the forecasting ability of a canonical DSGE model for the Spanish economy with other standard econometric techniques. More precisely, we compare out-of-sample forecasts coming from different estimation methods of the DSGE model to the forecasts produced by a VAR and a Bayesian VAR. Second, we propose a new method for combining DSGE and VAR models (Augmented VAR-DSGE) through the expansion of the variable space where the VAR operates with artificial series obtained from a DSGE model. The results indicate that the out-of-sample forecasting performance of the proposed method outperforms all the considered alternatives.

Suggested Citation

  • Gonzalo Fernandez-de-Córdoba & José L. Torres, 2009. "Forecasting the Spanish economy with an Augmented VAR-DSGE model," Working Papers 2009-1, Universidad de Málaga, Department of Economic Theory, Málaga Economic Theory Research Center.
  • Handle: RePEc:mal:wpaper:2009-1
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    References listed on IDEAS

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    Cited by:

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    2. Bekiros, Stelios D. & Paccagnini, Alessia, 2014. "Bayesian forecasting with small and medium scale factor-augmented vector autoregressive DSGE models," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 298-323.
    3. Bekiros, Stelios D. & Paccagnini, Alessia, 2015. "Macroprudential Policy And Forecasting Using Hybrid Dsge Models With Financial Frictions And State Space Markov-Switching Tvp-Vars," Macroeconomic Dynamics, Cambridge University Press, vol. 19(7), pages 1565-1592, October.
    4. Luis E. Rojas, 2011. "Professional Forecasters: How to Understand and Exploit Them Through a DSGE Model," BORRADORES DE ECONOMIA 008945, BANCO DE LA REPÚBLICA.
    5. Stelios D. Bekiros & Alessia Paccagnini, 2016. "Policy‐Oriented Macroeconomic Forecasting with Hybrid DGSE and Time‐Varying Parameter VAR Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(7), pages 613-632, November.
    6. Lucian Liviu ALBU & Carlos MatéJIMÉNEZ & Mihaela SIMIONESCU, 2015. "The Assessment of Some Macroeconomic Forecasts for Spain using Aggregated Accuracy Indicators," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 30-47, June.
    7. Bentour, El Mostafa, 2015. "A ranking of VAR and structural models in forecasting," MPRA Paper 61502, University Library of Munich, Germany.
    8. Stelios D. Bekiros & Alessia Paccagnini, 2013. "Bayesian Forecasting with a Factor-Augmented Vector Autoregressive DSGE model," Working Paper series 22_13, Rimini Centre for Economic Analysis.
    9. Martínez-Martin, Jaime & Morris, Richard & Onorante, Luca & Piersanti, Fabio M., 2019. "Merging structural and reduced-form models for forecasting: opening the DSGE-VAR box," Working Paper Series 2335, European Central Bank.
    10. Stelios Bekiros & Alessia Paccagnini, 2014. "Forecasting the US Economy with a Factor-Augmented Vector Autoregressive DSGE model," Working Papers 2014-183, Department of Research, Ipag Business School.

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    More about this item

    Keywords

    DSGE models; forecasting; VAR; BVAR;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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