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Macroeconomic data are subject to revision over time as later vintages are released, yet the usual way of generating real-time out-of-sample forecasts from models effectively makes no allowance for this form of data uncertainty. We analyse a simple method which has been used in the context of...
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The Covid-19 crisis has shown how high-frequency data can help tracking economic turning points in real-time. Our paper investigates whether high-frequency data can also improve the nowcasting performances for world GDP growth on quarterly or annual basis. To this end, we select a large dataset...
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The small open hypothesis suggests that small open economies are crucially affected by foreign economic activity. This study compares the predictive content of traditional financial variables and foreign economic activity for forecasting GDP growth in seven European small open economies during...
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Quarterly GDP figures usually are published with a delay of some weeks. A common way to generate GDP series of higher frequency, i.e. to nowcast GDP, is to use available indicators to calculate a single index by means of a common factor derived from a dynamic factor model (DFM). This paper deals...
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. For this purpose, we develop a novel long-run forecast framework based on enodogenous growth theory with human and fixed …
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