Regression Models with Data-based Indicator Variables
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 tdistribution, 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 improvement. Finally, a possible modification to impulse ‘intercept corrections’ is considered.
References listed on IDEAS
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- Doornik, Jurgen A & Hendry, David F & Nielsen, Bent, 1998.
" Inference in Cointegrating Models: UK M1 Revisited,"
Journal of Economic Surveys,
Wiley Blackwell, vol. 12(5), pages 533-572, December.
- Jurgen A. Doornik & David F. Hendry & Bent Nielsen, 1998. "Inference in Cointegrating Models: UK M1 Revisited," Journal of Economic Surveys, Wiley Blackwell, vol. 12(5), pages 533-572, December.
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- Hendry, David F, 1980. "Econometrics-Alchemy or Science?," Economica, London School of Economics and Political Science, vol. 47(188), pages 387-406, November.
- Messer, Karen & White, Halbert, 1984. "A Note on Computing the Heteroskedasticity Consistent Covariance Matrix Using Instrumental Variable Techniques," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 46(2), pages 181-184, May. Full references (including those not matched with items on IDEAS)
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