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Regression Models with Data‐based Indicator Variables*

2005/09/27 by David F. Hendry, Carlos Santos
Economics, Econometrics and Finance · Mathematics · #Advanced Statistical Methods and Models #Fiscal Policy and Economic Growth #Monetary Policy and Economic Impact

paper · doi:10.1111/j.1468-0084.2005.00132.x

openalex publication_date 2005/09/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29

Abstract

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.

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