Exact computation of GMM estimators for instrumental variable quantile regression models

Le-Yu Chen, Sokbae Lee

We show that the generalized method of moments (GMM) estimation problem in instrumental variable quantile regression (IVQR) models can be equivalently formulated as a mixed integer quadratic programming problem. This enables exact computation of the GMM estimators for the IVQR models. We illustrate the usefulness of our algorithm via Monte Carlo experiments and an application to demand for fish.

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Year of publication:	22 November 2017
Authors:	Chen, Le-yu ; Lee, Sokbae
Publisher:	London : Cemmap, Centre for Microdata Methods and Practice, The Institute for Fiscal Studies, Department of Economics, UCL
Subject:	generalized method of moments \| instrumental variable \| quantile regression \| endogeneity \| mixed integer optimization \| Regressionsanalyse \| Regression analysis \| Momentenmethode \| Method of moments \| IV-Schätzung \| Instrumental variables \| Schätztheorie \| Estimation theory

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Extent:	1 Online-Ressource (circa 26 Seiten)
Series:	CEMMAP working papers / Centre for Microdata Methods and Practice. - London : [Verlag nicht ermittelbar], ISSN 1753-9196, ZDB-ID 2106928-1. - Vol. CWP 17, 52
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Arbeitspapier ; Working Paper ; Graue Literatur ; Non-commercial literature
Language:	English
Other identifiers:	hdl:10419/189786 [Handle]
Classification:	C21 - Cross-Sectional Models; Spatial Models ; c26 ; C61 - Optimization Techniques; Programming Models; Dynamic Analysis ; C63 - Computational Techniques
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10011775368