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The Multivariate k-Nearest Neighbor Model for Dependent Variables : One-Sided Estimation and Forecasting

  • Dominique Guegan


    (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics)

  • Patrick Rakotomarolahy


    (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS)

This article gives the asymptotic properties of multivariate k-nearest neighbor regression estimators for dependent variables belonging to Rd, d > 1. The results derived here permit to provide consistent forecasts, and confidence intervals for time series An illustration of the method is given through the estimation of economic indicators used to compute the GDP with the bridge equations. An empirical forecast accuracy comparison is provided by comparing this non-parametric method with a parametric one based on ARIMA modelling that we consider as a benchmark because it is still often used in Central Banks to nowcast and forecast the GDP.

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Paper provided by HAL in its series Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) with number halshs-00423871.

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Date of creation: Dec 2009
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Publication status: Published in Documents de travail du Centre d'Economie de la Sorbonne 2009.50 - ISSN : 1955-611X. 2009
Handle: RePEc:hal:cesptp:halshs-00423871
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