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

Forecasting current quarter GDP is a permanent task inside the central banks. Many models are known and proposed to solve this problem. Thanks to new results on the asymptotic normality of the multivariate k-nearest neighbor regression estimate, we propose an interesting and new approach to solve in particular the forecasting of economic indicators, included GDP modelling. Considering dependent mixing data sets, we prove the asymptotic normality of multivariate k-nearest neighbor regression estimate under weak conditions, providing confidence intervals for point forecasts. We introduce an application for economic indicators of euro area, and compare our method with other classical ARMA-GARCH modelling.