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Uniform Convergence Rates For Kernel Estimation With Dependent Data

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Author Info
Hansen, Bruce E.

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Abstract

This paper presents a set of rate of uniform consistency results for kernel estimators of density functions and regressions functions. We generalize the existing literature by allowing for stationary strong mixing multivariate data with infinite support, kernels with unbounded support, and general bandwidth sequences. These results are useful for semiparametric estimation based on a first-stage nonparametric estimator.

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File URL: http://journals.cambridge.org/abstract_S0266466608080304
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Publisher Info
Article provided by Cambridge University Press in its journal Econometric Theory.

Volume (Year): 24 (2008)
Issue (Month): 03 (June)
Pages: 726-748
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:cup:etheor:v:24:y:2008:i:03:p:726-748_08

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  1. Dennis Kristensen, 2008. "Uniform Convergence Rates of Kernel Estimators with Heterogenous, Dependent Data," CREATES Research Papers 2008-37, School of Economics and Management, University of Aarhus. [Downloadable!]
    Other versions:
  2. Kyungchul Song, 2009. "Efficient Estimation of Average Treatment Effects under Treatment-Based Sampling," PIER Working Paper Archive 09-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania. [Downloadable!]
  3. Debopam Bhattacharya & Pascaline Dupas, 2008. "Inferring Welfare Maximizing Treatment Assignment under Budget Constraints," NBER Working Papers 14447, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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This page was last updated on 2009-11-24.

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