Constrained inference in multiple regression with structural changes
-
Fuqi Chen
und
Sévérien Nkurunziza
Abstract
In this paper, we study an inference problem for the regression coefficients in some multivariate regression models with multiple change-points occurring at unknown times, when the regression coefficients may satisfy some restrictions. The hypothesized restriction is more general than that given in recent literature. Under a weaker assumption than that given in recent literature, we derive the joint asymptotic normality of the restricted and unrestricted estimators. Finally, we construct a test for the hypothesized restriction and derive its asymptotic power.
Funding source: Natural Sciences and Engineering Research Council of Canada
The authors would like to thank the anonymous referees for useful comments and suggestions.
© 2014 by De Gruyter
Artikel in diesem Heft
- Frontmatter
- Law-invariant risk measures: Extension properties and qualitative robustness
- Constrained inference in multiple regression with structural changes
- Stochastic dominance with respect to a capacity and risk measures
- Change point test for tail index of scale-shifted processes
- Optimal risk allocation for convex risk functionals in general risk domains
Artikel in diesem Heft
- Frontmatter
- Law-invariant risk measures: Extension properties and qualitative robustness
- Constrained inference in multiple regression with structural changes
- Stochastic dominance with respect to a capacity and risk measures
- Change point test for tail index of scale-shifted processes
- Optimal risk allocation for convex risk functionals in general risk domains
