Chapter 8 Alternative Methods for Forecasting GDP

Dominique Guégan and Patrick Rakotomarolahy

A chapter in Nonlinear Modeling of Economic and Financial Time-Series, 2010, pp 161-185 from Emerald Group Publishing Limited

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: economic indicators; euro area GDP; VAR; asymptotic normality; forecast (search for similar items in EconPapers)
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:eme:isetez:s1571-0386(2010)0000020013

DOI: 10.1108/S1571-0386(2010)0000020013

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