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Adaptive learning and survey data

Listed author(s):
  • Agnieszka Markiewicz
  • Andreas Pick

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 naïve 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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File URL: http://www.dnb.nl/en/binaries/Working%20Paper%20411_tcm47-302770.pdf
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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
Handle: RePEc:dnb:dnbwpp:411
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