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Adaptive learning and survey data

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  • Agnieszka Markiewicz
  • Andreas Pick

Abstract

This paper investigates the ability of the adaptive learning approach to replicate the expectations of professional forecasters. For a range of macroeconomic and financial variables, we compare constant and decreasing gain learning models to simple, yet powerful benchmark models. We find that constant gain models provide a better fit for the expectations of professional forecasters. For macroeconomic series they usually perform significantly better than a na�ve random walk forecast. In contrast, we find it difficult to beat the no-change benchmark using the adaptive learning models to forecast financial variables.

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Bibliographic Info

Paper provided by Netherlands Central Bank, Research Department in its series DNB Working Papers with number 411.

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Date of creation: Jan 2014
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Handle: RePEc:dnb:dnbwpp:411

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Keywords: expectations; survey of professional forecasters; adaptive learning; bounded rationality;

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References

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  1. Adaptive Learning and Survey Data
    by Alessandro Cerboni in Knowledge Team on 2013-09-16 18:03:19
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Cited by:
  1. Berardi, Michele & Galimberti, Jaqueson K., 2014. "A note on the representative adaptive learning algorithm," Economics Letters, Elsevier, vol. 124(1), pages 104-107.

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