Time aggregation of mixed causal–noncausal models

Sean Telg

Economics Letters, 2024, vol. 244, issue C

Abstract: We study systematic and flow aggregation of mixed causal-noncausal autoregressive models. We show that aggregation preserves noncausality and generates a moving average component. Monte Carlo simulations demonstrate that backward- and forward-looking behavior can be identified empirically for sufficiently large samples.

Keywords: Systematic and flow aggregation; MAR models; Noncausality; Non-gaussianity (search for similar items in EconPapers)
JEL-codes: C18 C22 C53 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:244:y:2024:i:c:s0165176524005032

DOI: 10.1016/j.econlet.2024.112019

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