An Automatic Test of Super Exogeneity

We develop a new automatically-computable test for super exogeneity, using a variant of general-to-specific modeling. Based on the recent developments of impulse saturation applied to marginal models under the null that no impulses matter, we select the significant impulses for testing in the conditional. Since zero-mean changes are relatively undetectable in both VARs and conditional equations, we focus on location shifts, although we also discuss variance changes. The approximate analytical non-centrality of the test is derived for a failure of weak exogeneity when there is a shift in the marginal process. Monte Carlo simulations confirm the empirical accuracy of the nominal significance levels under the null, and show rejections for this failure of super exogeneity. An empirical application to UK M1 delivers new results for this much-studied data set.

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