Abstract
Central banks, statistical agencies, and international organizations such as the IMF and OECD typically use information about the exchange rate some weeks before the publication date as the basis for their exchange rate forecasts. This paper tests if exchange rate forecasts can be made more accurate by utilizing information about exchange rate movements closer to the publication date. To this end, we apply recent tests of equal predictability and encompassing for path forecasts. We find that the date on which the exchange rate forecast is based is crucial. Using exchange rate forecasts made by Statistics Norway over the period 2001–2018, we find that the random walk, when based on the exchange rate 1 day ahead of the publication deadline, encompasses the predicted path by Statistics Norway. However, when using the exchange rate 15 days before the publication deadline, the random walk path and the predicted exchange rate path by Statistics Norway have equal predictability.
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Notes
- 1.
We can also include a small sample correction for the heteroskedasticity. In this application, we apply the HC3 correction [16], which we operationalize by defining \(\tilde {d}_t = \frac {1}{1-h_t}\left ( {\mathbf {e}}^{A \prime }_{t,H|t} - {\mathbf {e}}^{B \prime }_{t,H|t} \right ) \hat {\Omega }_{(\hat {\alpha })}^{-1} \hat {\varepsilon }_t\), where \(h_t = D_t^{\prime }\left ( \sum _{j=1}^{T} D_{j} D_{j}^{\prime } \right )^{-1}D_t\) with \(D_t = {\mathbf {e}}^{A}_{t,H|t} - {\mathbf {e}}^{B}_{t,H|t}\).
- 2.
There are two exceptions: First, in the publication of the forecast made the first quarter in 2001, Statistics Norway only published a forecast for I-44 for the years 2001 and 2002. In our analysis, we assume that the forecasted value of I-44 for 2003 in the forecast published in the first quarter of 2001 is equal to the forecasted value for 2002, i.e., no change in the I-44 from 2002 to 2003 on a year-to-year basis. Second, Statistics Norway did not publish forecasts in the third quarter of 2013. In this analysis, we have set this forecast equal to the forecast made in the second quarter of that year. For the forecast based on the random walk, we have also used the exchange rate equal to the exchange rate in the market relative to the time the second quarter forecast from Statistics Norway was made.
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Acknowledgements
Thanks to Pål Boug, Thomas von Brasch, Terje Skjerpen, participants at the 22nd Dynamic Econometric Conference in 2019 and the 42nd Annual Meeting of the Norwegian Association of Economists in 2020, the referees for and participants at the 7th International Conference on Time Series and Forecasting in 2021 for valuable comments, and the referees for this book chapter. Also, thanks to Trym Kristian Økland for collecting and organizing the data. An earlier version of this paper is available as a working paper from Statistics Norway [13].
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Hungnes, H. (2023). Predicting the Exchange Rate Path: The Importance of Using Up-to-Date Observations in the Forecasts. In: Valenzuela, O., Rojas, F., Herrera, L.J., Pomares, H., Rojas, I. (eds) Theory and Applications of Time Series Analysis and Forecasting. ITISE 2021. Contributions to Statistics. Springer, Cham. https://doi.org/10.1007/978-3-031-14197-3_13
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