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Forecasting and stress testing with quantile vector autoregression

Author

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  • Chavleishvili, Sulkhan
  • Manganelli, Simone

Abstract

A quantile vector autoregressive (VAR) model, unlike standard VAR, models the interaction among the endogenous variables at any quantile. Forecasts of multivariate quantiles are obtained by factorizing the joint distribution in a recursive structure. VAR identification strategies that impose restrictions on the joint distribution can be readily extended to quantile VAR. The model is estimated using real and financial variables for the euro area. The dynamic properties of the system change across quantiles. This is relevant for stress testing exercises, whose goal is to forecast the tail behavior of the economy when hit by large financial and real shocks. JEL Classification: C32, C53, E17, E32, E44

Suggested Citation

  • Chavleishvili, Sulkhan & Manganelli, Simone, 2019. "Forecasting and stress testing with quantile vector autoregression," Working Paper Series 2330, European Central Bank.
  • Handle: RePEc:ecb:ecbwps:20192330
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    References listed on IDEAS

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    More about this item

    Keywords

    growth at risk; multivariate quantiles; regression quantiles; structural VAR;
    All these keywords.

    JEL classification:

    • 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
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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