A Structural Approach for Testing Causality

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International Econometric Review
Volume:3 Issue:2
A Structural Approach for Testing Causality

A Structural Approach for Testing Causality

Authors : Zahid ASGHAR

Pages : 1-12

View : 11 | Download : 10

Publication Date : 2011-09-01

Article Type : Research Paper

Abstract :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 insert ignore into journalissuearticles values(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 insert ignore into journalissuearticles values(1991);, Hoover insert ignore into journalissuearticles values(2001);, and Keane insert ignore into journalissuearticles values(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.
Keywords : Structural Causality, Granger Causality, Extra statistical Information, Export led Growth

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