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Does the foreign sector help forecast domestic variables in DSGE models?

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  • Marcin Kolasa

    (SGH Warsaw School of Economics and Narodowy Bank Polski)

  • Michał Rubaszek

    (SGH Warsaw School of Economics)

Abstract

This paper evaluates the forecasting performance of several small open economy DSGE models relative to a closed economy benchmark using a long span of data for Australia, Canada and the United Kingdom. We find that opening the model economy usually does not improve, and even deteriorates the quality of point and density forecasts for key domestic variables. We show that this result can be to a large extent attributed to an increase in forecast error due to a more sophisticated structure of the extended setup which is not compensated by better model specification. This claim is based on a Monte Carlo experiment, in which an open economy model fails to consistently beat its closed economy benchmark even if the former is the true data generating process.

Suggested Citation

  • Marcin Kolasa & Michał Rubaszek, 2018. "Does the foreign sector help forecast domestic variables in DSGE models?," NBP Working Papers 282, Narodowy Bank Polski.
    • Handle: RePEc:nbp:nbpmis:282
    Note: This project was financed by the National Science Centre grant No. 2012/07/E/HS4/01080. It benefited from suggestions by two anonymous referees as well as comments from participants to the International Symposium on Forecasting (Santander, June 2016), Ecomod Conference (Lisbon, July 2016), Narodowy Bank Polski Workshop on Forecasting (Warsaw,November 2016), ECB IPA Seminar (Frankfurt, January 2017) and ERFIN conference (Warsaw, September 2017).
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    Cited by:

    1. Van Nguyen, Phuong, 2020. "The Vietnamese business cycle in an estimated small open economy New Keynesian DSGE model," Dynare Working Papers 56, CEPREMAP.
    2. Rubaszek, Michał, 2021. "Forecasting crude oil prices with DSGE models," International Journal of Forecasting, Elsevier, vol. 37(2), pages 531-546.
    3. Van Nguyen, Phuong, 2020. "Evaluating the forecasting accuracy of the closed- and open economy New Keynesian DSGE models," Dynare Working Papers 59, CEPREMAP.
    4. Gelfer, Sacha, 2021. "Evaluating the forecasting power of an open-economy DSGE model when estimated in a data-Rich environment," Journal of Economic Dynamics and Control, Elsevier, vol. 129(C).
    5. Rachatar Nilavongse & Michał Rubaszek & Karsten Staehr & Gazi Salah Uddin, 2021. "Foreign and Domestic Uncertainty Shocks in Four Open Economies," Open Economies Review, Springer, vol. 32(5), pages 933-954, November.
    6. Ca’ Zorzi, Michele & Kolasa, Marcin & Rubaszek, Michał, 2017. "Exchange rate forecasting with DSGE models," Journal of International Economics, Elsevier, vol. 107(C), pages 127-146.
    7. Martin Feldkircher & Nico Hauzenberger, 2019. "How useful are time-varying parameter models for forecasting economic growth in CESEE?," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q1/19, pages 29-48.
    8. Sergii Kiiashko, 2018. "Applications for DSGE Models in Central Banking: Key Issues Explored During Research Workshop of the National Bank of Ukraine," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 246, pages 4-9.

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    More about this item

    Keywords

    Forecasting; DSGE models; New Open Economy Macroeconomics; Bayesian estimation;
    All these keywords.

    JEL classification:

    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics
    • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications

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