Abstract
ABSTRACTThis study analyses the performance of the International Monetary Fund (IMF) World Economic Outlook output forecasts for the world and for both the advanced economies and the emerging and developing economies. With a focus on the forecast for the current year and the next year, we examine the durability of IMF forecasts, looking at how much time has to pass so that IMF forecasts can be improved by using leading indicators with monthly updates. Using a real-time data set for GDP and for indicators, we find that some simple single-indicator forecasts on the basis of data that are available at higher frequency can significantly outperform the IMF forecasts as soon as the publication of the IMF’s Outlook is only a few months old. In particular, there is an obvious gain using leading indicators from January to March for the forecast of the current year.
Highlights
We select appropriate key leading indicators for GDP forecasts of the three regional aggregates – (1) world, (2) advanced economies and (3) emerging and developing economies – and generate indicatorbased forecasts. Using these forecasts, we look at their prediction accuracy compared to the pure International Monetary Fund (IMF) forecasts taking into account 12 different forecast rounds per year
Both Purchasing Managers Index (PMI) and the OECD+6 leading indicator perform quite well up to month 15, and in particular they improve the forecast quality of world GDP compared to IMF World Economic Outlook (WEO) forecast up to forecast round 15
The study shows that simple indicator-based forecasts perform about well as the autumn forecast of the IMF for year’s output growth at the time the IMF’s outlook is published
Summary
The most important regular publication on the development and the outlook of the world economy is the World Economic Outlook (WEO) by the International Monetary Fund (IMF), which is published every spring and autumn. We select appropriate key leading indicators for GDP forecasts of the three regional aggregates – (1) world, (2) advanced economies and (3) emerging and developing economies – and generate indicatorbased forecasts. Using these forecasts, we look at their prediction accuracy compared to the pure IMF forecasts taking into account 12 different forecast rounds per year. Many studies have analysed the performance of IMF forecasts for selected countries, in particular the accuracy and unbiasedness of the WEO shortterm GDP forecasts (Pons 2000; Timmermann 2007; Dreher, Marchesi, and Vreeland 2008; Genberg and Martinez 2014). Only a few studies have analysed regional aggregates such as the world, industrial countries and developing countries, G7 (Artis 1996; Aldenhoff 2007; Jakaitiene and Dées 2012; Frenkel, Rülke, and Zimmermann 2013; Golinelli and Parigi 2014) or panels of IMFsupported programme countries (Atoyan and Conway 2011). In a recent study, Ferrara and Marsilli (2014) have analysed forecasts of world GDP as well but with focus on common factors from country-specific data
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