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Would DSGE Models Have Predicted the Great Recession in Austria?

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  • Fritz Breuss

    (WU – Wirtschaftsuniversität Wien (Vienna University of Economics and Business)
    WIFO – Austrian Institute of Economic Research)

Abstract

Dynamic stochastic general equilibrium (DSGE) models are the common workhorse of modern macroeconomic theory. Whereas story-telling and policy analysis were in the forefront of applications since its inception, the forecasting perspective of DSGE models is only recently topical. In this study, we perform a post-mortem analysis of the predictive power of DSGE models in the case of Austria’s Great Recession in 2009. For this purpose, eight DSGE models with different characteristics (small and large models; closed and open economy models; one and two-country models) were used. The initial hypothesis was that DSGE models are inferior in ex-ante forecasting a crisis. Surprisingly however, it turned out that not all but those models which implemented features of the causes of the global financial crisis (like financial frictions or interbank credit flows) could not only detect the turning point of the Austrian business cycle early in 2008 but they also succeeded in forecasting the following severe recession in 2009. In comparison, non-DSGE methods like the ex-ante forecast with the Global Economic (Macro) Model of Oxford Economics and WIFO’s expert forecasts performed comparable or better than most DSGE models in the crisis.

Suggested Citation

  • Fritz Breuss, 2018. "Would DSGE Models Have Predicted the Great Recession in Austria?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 105-126, April.
  • Handle: RePEc:spr:jbuscr:v:14:y:2018:i:1:d:10.1007_s41549-018-0025-1
    DOI: 10.1007/s41549-018-0025-1
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    Cited by:

    1. Fritz Breuss, 2018. "100 Jahre österreichische Wirtschaft," WIFO Working Papers 570, WIFO.
    2. Peymankar, Mahboobeh & Davari, Morteza & Ranjbar, Mohammad, 2021. "Maximizing the expected net present value in a project with uncertain cash flows," European Journal of Operational Research, Elsevier, vol. 294(2), pages 442-452.
    3. Fritz Breuss, 2021. "25 Years of Austria's EU Membership. Quantifying the Economic Benefits With a DSGE Model," WIFO Working Papers 603, WIFO.
    4. Gunther Tichy, 2020. "Zur Prognostizierbarkeit von Krisen," WIFO Monatsberichte (monthly reports), WIFO, vol. 93(3), pages 193-206, March.

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    More about this item

    Keywords

    DSGE models; Business cycles; Forecasting; Open-economy macroeconomics;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • 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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