Artikel

A Structural Approach for Testing Causality

The ever present possibility of confounding factors creates difficulties in identifying causal effects on the basis of observational data. A large number of approaches to resolve this difficulty have been proposed; see Zaman (2010) for a recent survey. One involves using a "natural experiment" where nature acts like an experimenter in changing the setting of a key variable, allowing us to differentiate between "treatment" and "control" observations. This idea has been used by Hendry and Ericsson (1991), Hoover (2001), and Keane (2010) in rather complex settings. This paper presents an elementary version of this structural approach for detecting causality in the simplest possible setting. The structural method is able to detect contemporaneous causality. We illustrate the uses of this technique on a simulated data set, and also apply it to the export-led growth hypothesis for India and energy-growth data for Shanghai.

Sprache
Englisch

Erschienen in
Journal: International Econometric Review (IER) ; ISSN: 1308-8815 ; Volume: 3 ; Year: 2011 ; Issue: 2 ; Pages: 1-12 ; Ankara: Econometric Research Association (ERA)

Klassifikation
Wirtschaft
Econometric Modeling: Other
Thema
Structural Causality
Granger Causality
Extra-statistical Information
Export led Growth

Ereignis
Geistige Schöpfung
(wer)
Asghar, Zahid
Ereignis
Veröffentlichung
(wer)
Econometric Research Association (ERA)
(wo)
Ankara
(wann)
2011

Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Asghar, Zahid
  • Econometric Research Association (ERA)

Entstanden

  • 2011

Ähnliche Objekte (12)