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Small sample performance of indirect inference on DSGE models

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Using Monte Carlo experiments, we examine the performance of indirect inference tests of DSGE models in small samples, using various models in widespread use. We compare these with tests based on direct inference (using the Likelihood Ratio). We find that both tests have power so that a substantially false model will tend to be rejected by both,but that the power of the indirect inference test is by far the greater, necessitating re-estimation to ensure that the model is tested in its fullest sense. We also find that the small-sample bias with indirect estimation is around half of that with maximum likelihood estimation.

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Paper provided by Cardiff University, Cardiff Business School, Economics Section in its series Cardiff Economics Working Papers with number E2015/2.

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Length: 41 pages
Date of creation: Jan 2015
Handle: RePEc:cdf:wpaper:2015/2
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