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Nearest Neighbor Conditional Estimation for Harris Recurrent Markov Chains

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Author Info
Sancetta, A.

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Abstract

This paper is concerned with consistent nearest neighbor time series estimation for data generated by a Harris recurrent Markov chain. The goal is to validate nearest neighbor estimation in this general time series context, using simple and weak conditions. The framework considered covers, in a unified manner, a wide variety of statistical quantities, e.g. autoregression function, conditional quantiles, conditional tail estimators and, more generally, extremum estimators. The focus is theoretical, but examples are given to highlight applications.

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File URL: http://www.econ.cam.ac.uk/dae/repec/cam/pdf/cwpe0735.pdf
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Publisher Info
Paper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 0735.

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Length: 29
Date of creation: Jul 2007
Date of revision:
Handle: RePEc:cam:camdae:0735

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Related research
Keywords: Nonparametric Estimation; Quantile Estimation; Semiparametric Estimation; Sequential Forecasting; Tail Estimation; Time Series.;

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Rychlik, Tomasz, 1994. "Distributions and expectations of order statistics for possibly dependent random variables," Journal of Multivariate Analysis, Elsevier, vol. 48(1), pages 31-42, January. [Downloadable!] (restricted)
  2. Joel L. Horowitz, 2003. "Bootstrap Methods for Markov Processes," Econometrica, Econometric Society, vol. 71(4), pages 1049-1082, 07. [Downloadable!] (restricted)
  3. Nze, Patrick Ango & Doukhan, Paul, 2004. "Weak Dependence: Models And Applications To Econometrics," Econometric Theory, Cambridge University Press, vol. 20(06), pages 995-1045, December. [Downloadable!]
  4. Granger, Clive W. J. & Jeon, Yongil, 2004. "Thick modeling," Economic Modelling, Elsevier, vol. 21(2), pages 323-343, March. [Downloadable!] (restricted)
  5. Ole E. Barndorff-Nielsen & Shephard, 2002. "Econometric analysis of realized volatility and its use in estimating stochastic volatility models," Journal Of The Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 253-280. [Downloadable!] (restricted)
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  6. Timmermann, Allan, 2006. "Forecast Combinations," Handbook of Economic Forecasting, Elsevier. [Downloadable!] (restricted)
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