Quantiles for Fractions and Other Mixed Data
This paper studies the estimation of quantile regression for fractional data, focusing on the case where there are mass-points at zero or/and one. More generally, we propose a simple strategy for the estimation of the conditional quantiles of data from mixed distributions, which combines standard results on the estimation of censored and Box-Cox quantile regressions. The implementation of the proposed method is illustrated using a well-known dataset.
|Date of creation:||29 Jul 2008|
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"Quantiles for counts,"
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CWP22/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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NBER Working Papers
10428, National Bureau of Economic Research, Inc.
- Joshua Angrist & Victor Chernozhukov & Iván Fernández-Val, 2006. "Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure," Econometrica, Econometric Society, vol. 74(2), pages 539-563, 03.
- Taisuke Otsu, 2009. "RESET for quantile regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer, vol. 18(2), pages 381-391, August.
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