We consider selecting a regression model, using a variant of Gets, when there are more variables than observations, in the special case that the variables are impulse dummies (indicators) for every observation. We show that the setting is unproblematic if tackled appropriately, and obtain the...

We consider selecting a regression model, using a variant of Gets, when there are more variables than observations, in the special case that the variables are impulse dummies (indicators) for every observation. We show that the setting is unproblematic if tackled appropriately, and obtain the...

In this paper, we extend the impulse saturation algorithm to a class of dynamic models. We show that the procedure is still correctly sized for stationary AR(1) processes, independently of the number of splits used for sample partitions. We derive theoretical power when there is an additive...

We develop a new automatically-computable test for super exogeneity, using a variant of general-to-specific modelling. Based on the recent developments in impulse saturation applied to marginal models under the null that no impulses matter, we select the significant impulses for testing in the...

OLS estimation of an impulse-indicator coefficient is inconsistent, but its variance can be consistently estimated. Although the ratio of the inconsistent estimator to its standard error has a t-distribution, that test is inconsistent: one solution is to form an index of indicators. We provide...

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...