Nearest Neighbor Conditional Estimation for Harris Recurrent Markov Chains

Alessio Sancetta

Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge

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.

Keywords: Nonparametric Estimation; Quantile Estimation; Semiparametric Estimation; Sequential Forecasting; Tail Estimation; Time Series. (search for similar items in EconPapers)
Pages: 29
Date: 2007-07
New Economics Papers: this item is included in nep-ecm and nep-for
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Citations: View citations in EconPapers (2)

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Related works:
Journal Article: Nearest neighbor conditional estimation for Harris recurrent Markov chains (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:cam:camdae:0735

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