Forecasting and stress testing with quantile vector autoregression

Sulkhan Chavleishvili and Simone Manganelli

No 2330, Working Paper Series from European Central Bank

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

Keywords: growth at risk; multivariate quantiles; regression quantiles; structural VAR (search for similar items in EconPapers)
Date: 2019-11
New Economics Papers: this item is included in nep-ets, nep-for, nep-mac, nep-ore and nep-rmg
Note: 196912
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Citations: View citations in EconPapers (41)

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Persistent link: https://EconPapers.repec.org/RePEc:ecb:ecbwps:20192330

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