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Endogeneity in quantile regression models: a control function approach

Lee, S.; (2004) Endogeneity in quantile regression models: a control function approach. (cemmap Working Papers CWP08/). Institute for Fiscal Studies: London, UK. Green open access

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Abstract

This paper considers a linear triangular simultaneous equations model with conditional quantile restrictions. The paper adjusts for endogeneity by adopting a control function approach and presents a simple two-step estimator that exploits the partially linear structure of the model. The first step consists of estimation of the residuals of the reduced-form equation for the endogenous explanatory variable. The second step is series estimation of the primary equation with the reduced-form residual included nonparametrically as an additional explanatory variable. This paper imposes no functional form restrictions on the stochastic relationship between the reduced-form residual and the disturbance term in the primary equation conditional on observable explanatory variables. The paper presents regularity conditions for consistency and asymptotic normality of the two-step estimator. In addition, the paper provides some discussions on related estimation methods in the literature and on possible extensions and limitations of the estimation approach. Finally, the numerical performance and usefulness of the estimator are illustrated by the results of Monte Carlo experiments and two empirical examples, demand for fish and returns to schooling.

Type: Working / discussion paper
Title: Endogeneity in quantile regression models: a control function approach
Open access status: An open access version is available from UCL Discovery
Publisher version: http://www.cemmap.ac.uk/publications.php?publicati...
Language: English
Keywords: Endogeneity, partially linear regression, quantile regression, series estimation
UCL classification: UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Economics
URI: https://discovery.ucl.ac.uk/id/eprint/14694
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