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Identification of Noncausal Models by Quantile Autoregressions

Alain Hecq () and Li Sun

Papers from arXiv.org

Abstract: We propose a model selection criterion to detect purely causal from purely noncausal models in the framework of quantile autoregressions (QAR). We also present asymptotics for the i.i.d. case with regularly varying distributed innovations in QAR. This new modelling perspective is appealing for investigating the presence of bubbles in economic and financial time series, and is an alternative to approximate maximum likelihood methods. We illustrate our analysis using hyperinflation episodes in Latin American countries.

New Economics Papers: this item is included in nep-ecm and nep-ets
Date: 2019-04
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