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Series:   Elements in the Economics of Emerging Markets

Exchange Rates in South America's Emerging Markets

Published online by Cambridge University Press:  22 June 2020

Luis Molinas Sosa  and
Caio Vigo Pereira
Luis Molinas Sosa
Affiliation:
Central Bank of Paraguay
Caio Vigo Pereira
Affiliation:
University of Kansas

Summary

Since Meese and Rogoff (1983) results showed that no model could outperform a random walk in predicting exchange rates. Many papers have tried to find a forecasting methodology that could beat the random walk, at least for certain forecasting periods. This Element compares the Purchasing Power Parity, the Uncovered Interest Rate, the Sticky Price, the Bayesian Model Averaging, and the Bayesian Vector Autoregression models to the random walk benchmark in forecasting exchange rates between most South American currencies and the US Dollar, and between the Paraguayan Guarani and the Brazilian Real and the Argentinian Peso. Forecasts are evaluated under the criteria of Root Mean Square Error, Direction of Change, and the Diebold-Mariano statistic. The results indicate that the two Bayesian models have greater forecasting power and that there is little evidence in favor of using the other three fundamentals models, except Purchasing Power Parity at longer forecasting horizons.
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Keywords

ForecastingExchange ratesBayesian model averagingBayesian vector autoregressionPurchasing power parityUncovered interest rateSticky price
Type
Element
Information
Series: Elements in the Economics of Emerging Markets
Online ISBN: 9781108893671
Publisher: Cambridge University Press
Print publication: 16 July 2020

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