Alternative methods for forecasting GDP

Chapitre d'ouvrage: An empirical forecast accuracy comparison of the non-parametric method, known as multivariate Nearest Neighbor method, with parametric VAR modelling is conducted on the euro area GDP. Using both methods for nowcasting and forecasting the GDP, through the estimation of economic indicators plugged in the bridge equations, we get more accurate forecasts when using nearest neighbor method. We prove also the asymptotic normality of the multivariate k-nearest neighbor regression estimator for dependent time series, providing confidence intervals for point forecast in time series.

Auteur(s)

Dominique Guegan, Patrick Rakotomarolahy

Éditeur(s)
  • Emerald Publishers
Éditeur(s) scientifique(s)
  • R. Barnett, F. Jawady
Collection
  • Series International Symposia in Economic Theory and Econometrics – n°21
Titre de l’ouvrage
  • Nonlinear Modeling of Economic and Financial Time-Series
Date de publication
  • 2010
Mots-clés
  • Forecast
  • Economic indicators
  • GDP
  • Euro area
  • VAR
  • Multivariate k nearest neighbor regression
  • Asymptotic normality
Pages
  • Chapiter 5 (29 p.)
Version
  • 1