Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/195432 
Erscheinungsjahr: 
2017
Quellenangabe: 
[Journal:] Econometrics [ISSN:] 2225-1146 [Volume:] 5 [Issue:] 4 [Publisher:] MDPI [Place:] Basel [Year:] 2017 [Pages:] 1-22
Verlag: 
MDPI, Basel
Zusammenfassung: 
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.
Schlagwörter: 
inflation
seasonal adjustment filters
mixed causal-noncausal models
JEL: 
C22
E37
Persistent Identifier der Erstveröffentlichung: 
Creative-Commons-Lizenz: 
cc-by Logo
Dokumentart: 
Article

Datei(en):
Datei
Größe
883.69 kB





Publikationen in EconStor sind urheberrechtlich geschützt.