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Original Articles

Pitfalls in using Granger causality tests to find an engine of growth

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Pages 411-414 | Published online: 07 Oct 2010
 

Abstract

This paper discusses the reliability of using a Granger causality test to find an engine of growth. The paper first focuses on growth models' cointegration implications since causality must exist in an error-correction model. As a complementary, Monte Carlo experiments with independently generated I(1) variables also indicate a significant probability for rejecting the Granger non-causality null. Given the persistency and cointegration of variables in growth models, rejecting the non-causality null may reflect a spurious causal relationship, rather than confirm a theoretical causality.

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