Causal Inference by Independent Component Analysis with Applications to Micro- and Macroeconomic Data

Alessio Moneta (), Doris Entner (), Patrik Hoyer () and Alex Coad ()
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Doris Entner: Helsinki Institute for Information Technology
Patrik Hoyer: Helsinki Institute for Information Technology and Massachusetts Institute of Technology

No 2010-031, Jena Economics Research Papers from Friedrich-Schiller-University Jena

Abstract: Structural vector-autoregressive models are potentially very useful tools for guiding both macro- and microeconomic policy. In this paper, we present a recently developed method for exploiting non-Gaussianity in the data for estimating such models, with the aim of capturing the causal structure underlying the data, and show how the method can be applied to both microeconomic data (processes of firm growth and firm performance) as well as macroeconomic data (effects of monetary policy).

Keywords: Causality; Structural VAR; Independent Components Analysis; Non-Gaussianity; Firm Growth; Monetary Policy (search for similar items in EconPapers)
JEL-codes: C32 C52 D21 E52 L21 (search for similar items in EconPapers)
Date: 2010-05-11
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:jrp:jrpwrp:2010-031

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