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Qual Var Revisited: Good Forecast, Bad Story

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  • Makram El-Shagi
  • Gregor Von Schweinitz

Abstract

Due to the recent financial crisis, the interest in econometric models that allow to incorporate binary variables (such as the occurrence of a crisis) experienced a huge surge. This paper evaluates the performance of the Qual VAR, originally proposed by Dueker (2005). The Qual VAR is a VAR model including a latent variable that governs the behavior of an observable binary variable. While we find that the Qual VAR performs reasonable well in forecasting (outperforming a probit benchmark), there are substantial identification problems even in a simple VAR specification. Typically, identification in economic applications is far more difficult than in our simple benchmark. Therefore, when the economic interpretation of the dynamic behavior of the latent variable and the chain of causality matter, use of the Qual VAR is inadvisable.

Suggested Citation

  • Makram El-Shagi & Gregor Von Schweinitz, 2016. "Qual Var Revisited: Good Forecast, Bad Story," Journal of Applied Economics, Taylor & Francis Journals, vol. 19(2), pages 293-321, November.
    • Handle: RePEc:taf:recsxx:v:19:y:2016:i:2:p:293-321
    DOI: 10.1016/S1514-0326(16)30012-5
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    Cited by:

    1. Michael W. McCracken & Joseph T. McGillicuddy & Michael T. Owyang, 2022. "Binary Conditional Forecasts," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1246-1258, June.
    2. Aßhoff, Sina & Belke, Ansgar & Osowski, Thomas, 2021. "Unconventional monetary policy and inflation expectations in the Euro area," Economic Modelling, Elsevier, vol. 102(C).
    3. Löscher, Anne & Kaltenbrunner, Annina, 2025. "Climate risks, balance-of-payments constraints and central banking in emerging economies – Insights from Nigeria," Emerging Markets Review, Elsevier, vol. 65(C).

    More about this item

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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