Exact computation of GMM estimators for instrumental variable quantile regression models

No CWP52/17, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract: 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.

Keywords: generalized method of moments; instrumental variable; quantile regression; endogeneity; mixed integer optimization (search for similar items in EconPapers)
JEL-codes: C21 C26 C61 C63 (search for similar items in EconPapers)
Date: 2017-11-22
New Economics Papers: this item is included in nep-ecm and nep-ore
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Citations: View citations in EconPapers (11)

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Related works:
Journal Article: Exact computation of GMM estimators for instrumental variable quantile regression models (2018)
Working Paper: Exact computation of GMM estimators for instrumental variable quantile regression models (2017)
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