Abstract
Out-of-sample forecasting tests of DSGE models against time-series benchmarks such as an unrestricted VAR are increasingly used to check a) the specification b) the forecasting capacity of these models. We carry out a Monte Carlo experiment on a widely-used DSGE model to investigate the power of these tests. We find that in specification testing they have weak power relative to an in-sample indirect inference test; this implies that a DSGE model may be badly mis-specified and still improve forecasts from an unrestricted VAR. In testing forecasting capacity they also have quite weak power, particularly on the lefthand tail. By contrast a model that passes an indirect inference test of specification will almost definitely also improve on VAR forecasts.
Item Type: |
Monograph
(Working Paper)
|
Date Type: |
Publication |
Status: |
Published |
Schools: |
Business (Including Economics) |
Subjects: |
H Social Sciences > HB Economic Theory |
Publisher: |
Cardiff University |
Date of First Compliant Deposit: |
30 March 2016 |
Last Modified: |
19 Apr 2020 13:43 |
URI: |
http://orca-mwe.cf.ac.uk/id/eprint/78013 |
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