Journal
ECONOMICS LETTERS
Volume 91, Issue 3, Pages 380-388Publisher
ELSEVIER SCIENCE SA
DOI: 10.1016/j.econlet.2005.12.016
Keywords
causality in information; information-theoretic statistics; nonlinearity; fast double bootstrap test
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This paper introduces a nonparametric characterization of causality relying on information-theoretic statistics and proposes a causality testing procedure robust to the presence of potential nonlinearities. Monte Carlo simulations suggest that the test performs well in a nonlinear context. (c) 2006 Elsevier B.V. All rights reserved.
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