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Causal Inference by Independent Component Analysis: Theory and Applications* |
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| Authors: | Alessio Moneta Doris Entner Patrik O. Hoyer Alex Coad |
| Affiliation: | 1. Institute of Economics, Scuola Superiore Sant'Anna, Piazza Martiri della Libertà 33, 56127 Pisa, Italy (e‐mail: amoneta@sssup.it);2. Helsinki Institute for Information Technology & Department of Computer Science, University of Helsinki, Helsinki, Finland (e‐mails: doris.entner@helsinki.fi;3. patrik.hoyer@helsinki.fi);4. SPRU, University of Sussex, Brighton, UK and Department of Business and Management, Aalborg University, Aalborg, Denmark (e-mail: a.coad@sussex.ac.uk) |
| Abstract: | 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). |
| Keywords: | C32 C52 D21 E52 L21 |