Skip navigation
User training | Reference and search service

Library catalog

Content aggregators
Please use this identifier to cite or link to this item:

Title: Linear instrumental variables model averaging estimation
Authors: Martins, L. F.
Gabriel, V. J.
Keywords: Instrumental variables
Model selection
Model averaging
Model screening
Returns to education
Issue Date: 2014
Publisher: Elsevier
Abstract: Model averaging (MA) estimators in the linear instrumental variables regression framework are considered. The obtaining of weights for averaging across individual estimates by direct smoothing of selection criteria arising from the estimation stage is proposed. This is particularly relevant in applications in which there is a large number of candidate instruments and, therefore, a considerable number of instrument sets arising from different combinations of the available instruments. The asymptotic properties of the estimator are derived under homoskedastic and heteroskedastic errors. A simple Monte Carlo study contrasts the performance of MA procedures with existing instrument selection procedures, showing that MA estimators compare very favorably in many relevant setups. Finally, this method is illustrated with an empirical application to returns to education.
Description: WOS:000328869000053 (Nº de Acesso Web of Science)
Peer reviewed: Sim
ISSN: 0167-9473
Publisher version: The definitive version is available at:
Appears in Collections:BRU-RI - Artigos em revistas científicas internacionais com arbitragem científica

Files in This Item:
File Description SizeFormat 
publisher_version_1_s2_0_S0167947313001813_main.pdf453.62 kBAdobe PDFView/Open    Request a copy

FacebookTwitterDeliciousLinkedInDiggGoogle BookmarksMySpace
Formato BibTex MendeleyEndnote Currículo DeGóis 

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