Cointegration as an explanation for the Meese–Rogoff puzzle

Imad Ahmed Moosa, John Jude Vaz

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3 Citations (Scopus)

Abstract

Some economists suggest that the failure of exchange-rate models to outperform the random walk in exchange rate forecasting out of sample can be attributed to failure to take into account cointegration when it is present. We attempt to find out if cointegration matters for forecasting accuracy by examining the relation between the stationarity and size of the forecasting error. Results based on three macroeconomic models of exchange rates do not provide strong support for the proposition that cointegration matters for forecasting accuracy. The simulation results show that while stationary errors tend to be smaller than non-stationary errors, this is not a universal rule. Irrespective of the presence or absence of cointegration, none of the three models can outperform the random walk in out-of-sample forecasting, which means that cointegration cannot solve the Meese–Rogoff puzzle.
Original languageEnglish
Pages (from-to)4201-4209
Number of pages9
JournalApplied Economics
Volume48
Issue number44
DOIs
Publication statusPublished - Mar 2016

Keywords

  • Exchange rates
  • Directional accuracy
  • Forecasting
  • Currency trading

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