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Forecasting Inflation with Forecast Combinations: Using Neural Networks in Policy

  • P. McNelis
  • P. McAdam
Part of the New Economic Windows book series (NEW)

Abstract

Forecasting is a key activity for policy makers. Given the possible complexity of the processes underlying policy targets, such as inflation, output gaps, or employment, and the difficulty of forecasting in real time, recourse is often taken to simple models. A dominant feature of such models is their linearity. However, recent evidence suggests that simple, though non-linear, models may be at least as competitive as linear ones for forecasting macro variables.

Keywords

Monetary Policy Forecast Error Consumer Price Index Phillips Curve Producer Price Index 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Italia 2007

Authors and Affiliations

  • P. McNelis
    • 1
  • P. McAdam
    • 2
  1. 1.Fordham UniversityUSA
  2. 2.DG-ResearchEuropean Central BankFrankfurt am Main

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