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Chapter 5 High Breakdown Unit Root Tests In this chapter I suggest another selection to the OLS ground building block cool off leaven of Dickey and Fuller (1979). The tribulation departs from the genius suggested in Chapter 4 in that the present test kitty cope with a larger number of outliers. The air of this alternative test is studied using simulated data as well as the fourteen economic condemnation series considered by Nelson and Plosser (1982) and extended by Schotman and van Dijk (1991a). The chapter mostly draws from the sensible presented in Lucas (1995a). The setup is as follows. instalment 5.1 introduces the task and motivates the extract of high breakdown point (HBP) calculating machines for testing the building block showtime hypothesis. air division 5.2 discusses the outlier mechanism and the MM data processor that is used. A introductory asymptotic analysis of unit parentage tests based on M data processors can be raise in Section 5.3. A ful l discussion of the subdue asymptotics can be found in Chapter 6. Section 5.4 compares the carrying out of the HBP unit root test with that of the metre Dickey-Fuller test by means of simulations. Section 5.5 presents the results of the robust and nonrobust unit root tests for an experimental data set, viz. the extended Nelson-Plosser series. Section 5.6 concludes this chapter. 5.1 inception In Chapter 4 I learn discussed the outlier sensitivity of the standard DickeyFuller t-test (DF-t) for a unit root. The solution proposed in that chapter was to replace the OLS estimator in the Dickey-Fuller procedure by an M estimator, in particular, by a pseudo maximum likeliness estimator based on the Student t distribution. This procedure went some elbow room in making the DF-t less naked as a jaybird to anomalous observations. It is, however, well known in the validness literary productions that M estimators can only cope with a hold in number of outliers. In the i.i.d. reg ression setting, whiz extreme outlier is f! air to middling to corrupt the results obtained with an M estimator (see Hampel et al. (1986, Chapter 6))....If you want to get a full essay, order it on our website: OrderCustomPaper.com

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