This paper assesses the OECD’s projections for GDP growth and inflation during the global financial crisis and recovery, focussing on lessons that can be learned. The projections repeatedly over-estimated growth, failing to anticipate the extent of the slowdown and later the weak pace of the...

Uncertainty is inherent to forecasting and assessing the uncertainty surrounding a point forecast is as important as the forecast itself. Following Cornec (2010), a method to assess the uncertainty around the indicator models used at OECD to forecast GDP growth of the six largest member...

This paper presents the results from a new model for projecting growth of OECD and major non-OECD economies over the next 50 years as well as imbalances that arise. A baseline scenario assuming gradual structural reform and fiscal consolidation to stabilise government-debt-to GDP ratios is...

The downturn in fixed investment among advanced economies from the onset of the global crisis was unusually severe, widespread and long-lasting relative to comparable episodes in the past. As a result, investment gaps are large in many countries, not only in relation to past norms but also...

Fan charts were pioneered by the Bank of England and Riksbank and provide a visually appealing means to convey the uncertainty surrounding a forecast. This paper describes a method for parameterising fan charts around GDP growth forecasts by which the degree of uncertainty is based on past...

Financial conditions indices (FCIs) have been developed to summarise financial conditions and also supplement more traditional macroeconomic forecasting. They capture market expectations but also quantitative and survey information. This paper seeks to provide up to date financial conditions...

This paper firstly describes the role of models in producing OECD global macroeconomic forecasts; secondly, reviews the OECD's forecasting track record; and finally, considers the relationship between forecast performance and models. OECD forecasts are not directly generated from a single global...

The present paper develops Adaptive Trees, a new machine learning approach specifically designed for economic forecasting. Economic forecasting is made difficult by economic complexity, which implies non-linearities (multiple interactions and discontinuities) and unknown structural changes (the...

Forecasts of GDP growth are typically over-optimistic for horizons beyond the current year, particularly because they fail to predict the occurrence or severity of future downturns. Macroeconomic forecasters have also long been under pressure to convey the uncertainty surrounding their...