摘要：When researchers test a model that represents the effect an independent variable on another—dependent-- variable, many researchers commonly do not further investigate about the correctness of the causal direction of the model. Hypothesis testing of such model is generally done by assuring that the model coefficients are statistically significant assuming that the direction of the causality is indeed correct. Hence, the direction of the causality of these models is simply ex ante assumed, which means that the direction could be incorrectly stated. The effect of this mistake could be enormous, particularly if findings of the study, which adopt an incorrect causal order, are used for policy makingt. This study discusses two approaches in testing the causal ordering of a model, i.e., the Granger and Sim’s tests as well as SCDTs test of causality, which could be either used in an experimental or nonexperimental setting. Findings of two empirical researches written by Gudono (2006) and Chong and Chong (2002) are discussed and used as an illustration.
关键词：causal ordering; lagged- regression; the sequential Chi-Square Differences tests (SCDTs); Type I; Type II; and Type III errors)
