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Selecting a Regression Saturated by Indicators.

Abstract:
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 finite-sample distribution of estimators of the mean and variance in a simple location-scale model under the null that no impulses matter. A Monte Carlo simulation confirms the null distribution, and shows power against an alternative of interest.

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Publisher:
Department of Economics (University of Copenhagen)
Series:
Discussion Papers
Publication date:
2007-01-01


Language:
English
UUID:
uuid:05fd3373-ad87-4fab-9e87-3aed60278e38
Local pid:
oai:economics.ouls.ox.ac.uk:12104
Deposit date:
2011-08-16
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