Testing the Information Matrix Equality with Robust Estimators



Figure 1: Asymmetric contamination: non-centraiity parameter

Note: right panel uses 104 as measurement unit on vertical axis

Figure 2: Symmetric contamination: non-centraiity parameter

Note: right panel uses 104 as measurement unit on vertical axis

We see in both figures that the non-centrality parameter corresponding to
the ML estimator is uniformly smaller than those corresponding to the other
estimators, as shown. The non-centrality parameter associated with the
MAD estimator is discontinuous at
x = Φ-1(3/4) = 0.6745, where also ρc( )
is discontinuous. Figure 3 gives the power curves of 5%-level IM tests with
level
e contamination at x = 10, a clear outlier relative to the N (0, 1) distri-

13



More intriguing information

1. The name is absent
2. The name is absent
3. The name is absent
4. The name is absent
5. Job quality and labour market performance
6. The Role of area-yield crop insurance program face to the Mid-term Review of Common Agricultural Policy
7. The name is absent
8. Shifting Identities and Blurring Boundaries: The Emergence of Third Space Professionals in UK Higher Education
9. The name is absent
10. Work Rich, Time Poor? Time-Use of Women and Men in Ireland
11. ANTI-COMPETITIVE FINANCIAL CONTRACTING: THE DESIGN OF FINANCIAL CLAIMS.
12. Three Policies to Improve Productivity Growth in Canada
13. An Empirical Analysis of the Curvature Factor of the Term Structure of Interest Rates
14. Evidence on the Determinants of Foreign Direct Investment: The Case of Three European Regions
15. Errors in recorded security prices and the turn-of-the year effect
16. The name is absent
17. The name is absent
18. CGE modelling of the resources boom in Indonesia and Australia using TERM
19. Disentangling the Sources of Pro-social Behavior in the Workplace: A Field Experiment
20. Nach der Einführung von Arbeitslosengeld II: deutlich mehr Verlierer als Gewinner unter den Hilfeempfängern