Causality in Time Series - ClopiNet

JMLR: Workshop and Conference Proceedings 12:95–114, 2011Causality in Time SeriesCausal Search in Structural Vector Autoregressive ModelsAlessio MonetaMax Planck Institute of EconomicsJena, GermanyNadine ChlaßFriedrich Schiller University of Jena, GermanyDoris EntnerHelsinki Institute for Information Technology, FinlandPatrik HoyerHelsinki Institute for Information Technology, Finlandmoneta@econ.mpg.denadine.chlass@uni-jena.dedoris.entner@cs.helsinki.fipatrk.hoyer@helsinki.fiEditors: Florin Popescu and Isabelle GuyonAbstractThis paper reviews a class of methods to perform causal inference in the framework ofa structural vector autoregressive model. We consider three different settings. In thefirst setting the underlying system is linear with normal disturbances and the structuralmodel is identified by exploiting the information incorporated in the partial correlationsof the estimated residuals. Zero partial correlations are used as input of a searchalgorithm formalized via graphical causal models. In the second, semi-parametric,setting the underlying system is linear with non-Gaussian disturbances. In this casethe structural vector autoregressive model is identified through a search procedurebased on independent component analysis. Finally, we explore the possibility ofcausal search in a nonparametric setting by studying the performance of conditionalindependence tests based on kernel density estimations.Keywords: Causal inference, econometric time series, SVAR, graphical causal models,independent component analysis, conditional independence tests1. Introduction1.1. Causal inference in econometricsApplied economic research is pervaded by questions about causes and effects. Forexample, what is the effect of a monetary policy intervention? Is energy consumptioncausing growth or the other way around? Or does causality run in both directions? Areeconomic fluctuations mainly caused by monetary, productivity, or demand shocks?Does foreign aid improve living standards in poor countries? Does firms’ expenditurein R&D causally influence their profits? Are recent rises in oil prices in part caused byspeculation? These are seemingly heterogeneous questions, but they all require someknowledge of the causal process by which variables came to take the values we observe.c○ 2011 A. Moneta, N. Chlaß, D. Entner & P. Hoyer.