Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/211098
Authors: 
Grant, Nicky L.
Smith, Richard J.
Year of Publication: 
2019
Series/Report no.: 
cemmap working paper No. CWP05/19
Abstract: 
The particular concern of this paper is the construction of a confidence region with pointwise asymptotically correct size for the true value of a parameter of interest based on the generalized Anderson-Rubin (GAR) statistic when the moment variance matrix is singular. The large sample behaviour of the GAR statistic is analysed using a Laurent series expansion around the points of moment variance singularity. Under a condition termed first order moment singularity the GAR statistic is shown to possess a limiting chi-square distribution on parameter sequences converging to the true parameter value. Violation, however, of this condition renders the GAR statistic unbounded asymptotically. The paper details an appropriate discretisation of the parameter space to implement a feasible GAR-based confidence region that contains the true parameter value with pointwise asymptotically correct size. Simulation evidence is provided that demonstrates the efficacy of the GAR-based approach to moment-based inference described in this paper.
Subjects: 
Laurent series expansion
moment indicator
parameter sequences
singular moment matrix
JEL: 
C13
C31
C51
C52
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.