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Understanding the effect of measurement error on quantile regressions

Author:
Chesher, Andrew
Source:
Journal of econometrics 2017 v.200 no.2 pp. 223-237
ISSN:
0304-4076
Subject:
econometric models, economic analysis, economic theory, regression analysis, variance
Abstract:
The impact of measurement error in explanatory variables on quantile regression functions is investigated using a small variance approximation. The approximation shows how the error contaminated and error free quantile regression functions are related. A key factor is the distribution of the error free explanatory variable. Exact calculations probe the accuracy of the approximation. The order of the approximation error is unchanged if the density of the error free explanatory variable is replaced by the density of the error contaminated explanatory variable which is easily estimated. It is then possible to use the approximation to investigate the sensitivity of estimates to varying amounts of measurement error.
Agid:
6107866