Do seasonal adjustments induce noncausal dynamics in inflation rates?

Artikel

This paper investigates the effect of seasonal adjustment filters on the identification of mixed causal-noncausal autoregressive models. By means of Monte Carlo simulations, we find that standard seasonal filters induce spurious autoregressive dynamics on white noise series, a phenomenon already documented in the literature. Using a symmetric argument, we show that those filters also generate a spurious noncausal component in the seasonally adjusted series, but preserve (although amplify) the existence of causal and noncausal relationships. This result has has important implications for modelling economic time series driven by expectation relationships. We consider inflation data on the G7 countries to illustrate these results.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Journal: Econometrics ; ISSN: 2225-1146 ; Volume: 5 ; Year: 2017 ; Issue: 4 ; Pages: 1-22 ; Basel: MDPI

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes ; Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications
• Thema: inflation ; seasonal adjustment filters ; mixed causal-noncausal models

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Hecq, Alain ; Telg, Sean ; Lieb, Lenard
• Ereignis: Veröffentlichung
• (wer): MDPI
• (wo): Basel
• (wann): 2017

Weitere Informationen

• DOI: doi:10.3390/econometrics5040048
• Handle: http://hdl.handle.net/10419/195432
• Letzte Aktualisierung: 10.03.2025, 11:44 MEZ