The discovery of long-run causal order: A preliminary investigation

Artikel

The relation between causal structure and cointegration and long-run weak exogeneity is explored using some ideas drawn from the literature on graphical causal modeling. It is assumed that the fundamental source of trending behavior is transmitted from exogenous (and typically latent) trending variables to a set of causally ordered variables that would not themselves display nonstationary behavior if the nonstationary exogenous causes were absent. The possibility of inferring the long-run causal structure among a set of time-series variables from an exhaustive examination of weak exogeneity in irreducibly cointegrated subsets of variables is explored and illustrated.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Journal: Econometrics ; ISSN: 2225-1146 ; Volume: 8 ; Year: 2020 ; Issue: 3 ; Pages: 1-24 ; Basel: MDPI

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models ; Model Construction and Estimation ; Methodological Issues: General
• Thema: causal search ; cointegrated vector autoregression (CVAR) ; graphical causal modeling ; irreducible cointegrating relations ; weak exogeneity

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Hoover, Kevin D.
• Ereignis: Veröffentlichung
• (wer): MDPI
• (wo): Basel
• (wann): 2020

Weitere Informationen

• DOI: doi:10.3390/econometrics8030031
• Handle: http://hdl.handle.net/10419/247579
• Letzte Aktualisierung: 10.03.2025, 11:44 MEZ