On the u-th Geometric Conditional Quantile

Yebin Cheng () and Jan G. Gooijer
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Yebin Cheng: Faculty of Economics and Econometrics, Universiteit van Amsterdam

No 04-072/4, Tinbergen Institute Discussion Papers from Tinbergen Institute

Abstract: Motivated by Chaudhuri's work (1996) on unconditional geometric quantiles, we explore the asymptotic properties of sample geometric conditional quantiles, defined through kernel functions, in high dimensional spaces. We establish a Bahadur type linear representation for the geometric conditional quantile estimator and obtain the convergence rate for the corresponding remainder term. From this, asymptotic normality on the estimated geometric conditional quantile is derived. Based on these results we propose confidence ellipsoids for multivariate conditional quantiles. The methodology is illustrated via data analysis and a Monte Carlo study.

Keywords: Asymptotic normality; Bahadur representation; geometric conditional quantile; confidence ellipsoids; kernel function (search for similar items in EconPapers)
JEL-codes: C14 (search for similar items in EconPapers)
Date: 2004-06-29
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:tin:wpaper:20040072

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