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, enhancing the estimation method by taking a similarity approach, and adjusting the forecasts to put them back on track by a …
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, enhancing the estimation method by taking a similarity approach, and adjusting the forecasts to put them back on track by a …
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The COVID-19 pandemic has led to enormous data movements that strongly affect parameters and forecasts from standard VARs. To address these issues, we propose VAR models with outlier-augmented stochastic volatility (SV) that combine transitory and persistent changes in volatility. The resulting...
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Based on evidence gathered from a newly built large macroeconomic data set for the UK, labeled UK-MD and comparable to similar datasets for the US and Canada, it seems the most promising avenue for forecasting during the pandemic is to allow for general forms of nonlinearity by using machine...
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