How did DSGE model forecasts perform before, during and after the financial crisis, and what type of off-model information can improve the forecast accuracy? We tackle these questions by assessing the real-time forecast performance of a large DSGE model relative to statistical and judgmental benchmarks over the period from 2000 to 2013. The forecasting performances of all methods deteriorate substantially following the financial crisis. That is particularly evident for the DSGE model’s GDP forecasts, but augmenting the model with a measure of survey expectations made its GDP forecasts more accurate, which supports the idea that timely off-model information is particularly useful in times of financial distress.
Boneva, L., Fawcett, N., Masolo, R. M., Waldron, M., Forecasting the UK economy: Alternative forecasting methodologies and the role of off-model information, <<INTERNATIONAL JOURNAL OF FORECASTING>>, 2019; 35 (1): 100-120. [doi:10.1016/j.ijforecast.2018.06.005] [https://hdl.handle.net/10807/227840]
Forecasting the UK economy: Alternative forecasting methodologies and the role of off-model information
Masolo, Riccardo Maria
Formal Analysis
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2019
Abstract
How did DSGE model forecasts perform before, during and after the financial crisis, and what type of off-model information can improve the forecast accuracy? We tackle these questions by assessing the real-time forecast performance of a large DSGE model relative to statistical and judgmental benchmarks over the period from 2000 to 2013. The forecasting performances of all methods deteriorate substantially following the financial crisis. That is particularly evident for the DSGE model’s GDP forecasts, but augmenting the model with a measure of survey expectations made its GDP forecasts more accurate, which supports the idea that timely off-model information is particularly useful in times of financial distress.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.