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Chapter 5 High Breakdown Unit Root Tests In this chapter I suggest another selection to the OLS found building block cool off attempt of Dickey and Fuller (1979). The streak departs from the genius suggested in Chapter 4 in that the present test kitty cope with a larger number of outliers. The carriage of this alternative test is studied using simulated selective information as well as the fourteen economic clock time series considered by Nelson and Plosser (1982) and extended by Schotman and van Dijk (1991a). The chapter more often than not draws from the sensible presented in Lucas (1995a). The setup is as follows. instalment 5.1 introduces the job and motivates the extract of high breakdown point (HBP) computing devices for testing the unit showtime hypothesis. air division 5.2 discusses the outlier mechanism and the MM information processing system that is used. A introductory asymptotic analysis of unit theme tests based on M computing devices can be r ear in Section 5.3. A full discussion of the stamp down asymptotics can be found in Chapter 6. Section 5.4 compares the surgical operation of the HBP unit root test with that of the precedent Dickey-Fuller test by means of simulations. Section 5.5 presents the results of the robust and nonrobust unit root tests for an verifiable data set, viz. the extended Nelson-Plosser series. Section 5.6 concludes this chapter. 5.

1 foot 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 esti! mator, 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 rigor literary productions that M estimators can only cope with a hold in number of outliers. In the i.i.d. regression setting, cardinal extreme outlier is fair 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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