林向愷Lee, Hsiu-YunHsiu-YunLeeWu, Jyh-LinJyh-LinWu2010-06-262018-06-282010-06-262018-06-282000http://ntur.lib.ntu.edu.tw//handle/246246/186316This 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.172096 bytesapplication/pdfen-US[SDGs]SDG8economic growth; Granger causality test; growth determination; testing methodjournal article10.1080/13504850110088132http://ntur.lib.ntu.edu.tw/bitstream/246246/186316/1/14.pdf