Causal inference by independent component analysis: Theory and applications

Alessio Moneta, Doris Entner, Patrik O. Hoyer, Alex Coad

研究成果: Article査読

61 被引用数 (Scopus)

抄録

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).

本文言語English
ページ(範囲)705-730
ページ数26
ジャーナルOxford Bulletin of Economics and Statistics
75
5
DOI
出版ステータスPublished - 2013 10
外部発表はい

ASJC Scopus subject areas

  • 統計学および確率
  • 社会科学(その他)
  • 経済学、計量経済学
  • 統計学、確率および不確実性

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