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Forecasting economic variables with nonlinear models

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Author Info
Teräsvirta, Timo () (Dept. of Economic Statistics, Stockholm School of Economics)

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Abstract

This article is concerned with forecasting from nonlinear conditional mean models. First, a number of often applied nonlinear conditional mean models are introduced and their main properties discussed. The next section is devoted to techniques of building nonlinear models. Ways of computing multi-step ahead forecasts from nonlinear models are surveyed. Tests of forecast accuracy in the case where the models generating the forecasts are nested are discussed. There is a numerical example, showing that even when a stationary nonlinear process generates the observations, future obervations may in some situations be better forecast by a linear model with a unit root. Finally, some empirical studies that compare forecasts from linear and nonlinear models are discussed.

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Publisher Info
Paper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 598.

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Length: 55 pages
Date of creation: 31 May 2005
Date of revision: 29 Dec 2005
Publication status: Published in Handbook of Economic Forecasting, Elliott, Graham, Granger, Clive W.J., Timmermann, Allan (eds.), 2006, pages 413-457, Elsevier.
Handle: RePEc:hhs:hastef:0598

Note: This paper has been prepared for Graham Elliott, Clive W.J. Granger and Allan Timmermann (eds.). Handbook of Economic Forecasting. Amsterdam: Elsevier. This version replaces the previous faulty one (references missing).
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Related research
Keywords: Forecast accuracy; forecast comparison; hidden Markov model; neural network; nonlinear modelling; recursive forecast; smooth transition regression; switching regression;

Other versions of this item:

Find related papers by JEL classification:
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications

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Full references

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Andrés González & Kirstin Hubrich & Timo Teräsvirta, 2009. "Forecasting inflation with gradual regime shifts and exogenous information," CREATES Research Papers 2009-03, School of Economics and Management, University of Aarhus. [Downloadable!]
  2. Giancarlo Bruno, 2008. "Forecasting Using Functional Coefficients Autoregressive Models," ISAE Working Papers 98, ISAE - Institute for Studies and Economic Analyses - (Rome, ITALY). [Downloadable!]
  3. David Peel & Ivan Paya & E Pavlidis, 2009. "Forecasting the Real Exchange Rate using a Long Span of Data. A Rematch: Linear vs Nonlinear," Working Papers 006075, Lancaster University Management School, Economics Department. [Downloadable!]
  4. Gloria González-Rivera & Tae-Hwy Lee, 2007. "Nonlinear Time Series in Financial Forecasting," Working Papers 200803, University of California at Riverside, Department of Economics, revised Feb 2008. [Downloadable!]
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