Causal Inference by Independent Component Analysis: Theory and Applications

Structural vector‐autoregressive models are potentially very useful tools for guiding both macro‐ and microeconomic policy. In this study, we present a recently developed method for estimating such models, which uses non‐normality to recover the causal structure underlying the observations. We show...

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Bibliographic Details
Published in:Oxford bulletin of economics and statistics 2013-10, Vol.75 (5), p.705-730
Main Authors: Moneta, Alessio, Entner, Doris, Hoyer, Patrik O., Coad, Alex
Format: Article
Language:English
Subjects:
C32
C52
Causality
D21
E52
Economic policy
L21
Macroeconomics
Microeconomics
Regression analysis
Studies
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Summary:Structural vector‐autoregressive models are potentially very useful tools for guiding both macro‐ and microeconomic policy. In this study, we present a recently developed method for estimating such models, which uses non‐normality to recover the causal structure underlying the observations. We show how the method can be applied to both microeconomic data (to study the processes of firm growth and firm performance) and macroeconomic data (to analyse the effects of monetary policy).
ISSN:0305-9049
1468-0084
DOI:10.1111/j.1468-0084.2012.00710.x