Regression Models with Data‐based Indicator Variables*
Texto Integral @ b-onFinancial support from the ESRC under a Professorial Research Fellowship, RES051270035, and from the Fundação para a Ciência e a Tecnologia (Lisboa), is gratefully acknowledged by the two authors, respectively, as are helpful comments from two anonymous referees and the Editors correcting a number of infelicities.
Abstract
Ordinary least squares 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 Monte Carlo evidence that including a plethora of indicators need not distort model selection, permitting the use of many dummies in a general‐to‐specific framework. Although White's (1980) heteroskedasticity test is incorrectly sized in that context, we suggest an easy alteration. Finally, a possible modification to impulse ‘intercept corrections’ is considered.
