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Chapter 8 Alternative Methods for Forecasting GDP

Nonlinear Modeling of Economic and Financial Time-Series

ISBN: 978-0-85724-489-5, eISBN: 978-0-85724-490-1

Publication date: 31 December 2010

Abstract

Purpose – The purpose of this chapter is twofold: to forecast gross domestic product (GDP) using nonparametric method, known as multivariate k-nearest neighbors method, and to provide asymptotic properties for this method.

Methodology/approach – We consider monthly and quarterly macroeconomic variables, and to match the quarterly GDP, we estimate the missing monthly economic variables using multivariate k-nearest neighbors method and parametric vector autoregressive (VAR) modeling. Then linking these monthly macroeconomic variables through the use of bridge equations, we can produce nowcasting and forecasting of GDP.

Findings – Using multivariate k-nearest neighbors method, we provide a forecast of the euro area monthly economic indicator and quarterly GDP, which is better than that obtained with a competitive linear VAR modeling. We also provide the asymptotic normality of this k-nearest neighbors regression estimator for dependent time series, as a confidence interval for point forecast in time series.

Originality/value of chapter – We provide a new theoretical result for nonparametric method and propose a novel methodology for forecasting using macroeconomic data.

Keywords

Citation

Guégan, D. and Rakotomarolahy, P. (2010), "Chapter 8 Alternative Methods for Forecasting GDP", Jawadi, F. and Barnett, W.A. (Ed.) Nonlinear Modeling of Economic and Financial Time-Series (International Symposia in Economic Theory and Econometrics, Vol. 20), Emerald Group Publishing Limited, Leeds, pp. 161-185. https://doi.org/10.1108/S1571-0386(2010)0000020013

Publisher

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Emerald Group Publishing Limited

Copyright © 2010, Emerald Group Publishing Limited