Pitfalls in using Granger causality tests to find an engine of growth
AbstractThis 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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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Applied Economics Letters.
Volume (Year): 9 (2002)
Issue (Month): 6 ()
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- Tang, Chor Foon, 2009. "Does causality technique matter to savings-growth nexus in Malaysia?," MPRA Paper 38535, University Library of Munich, Germany.
- R. Scott Hacker & Abdulnasser Hatemi-J, 2006. "Tests for causality between integrated variables using asymptotic and bootstrap distributions: theory and application," Applied Economics, Taylor & Francis Journals, vol. 38(13), pages 1489-1500.
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