A Practical Approach to Testing Calibration Strategies

A calibration strategy tries to match target moments using a model’s parameters. We propose tests for determining whether this is possible. The tests use moments at random parameter draws to assess whether the target moments are similar to the computed ones (evidence of existence) or appear to be outliers (evidence of non-existence). Our experiments show the tests are effective at detecting both existence and non-existence in a non-linear model. Multiple calibration strategies can be quickly tested using just one set of simulated data. Applying our approach to indirect inference allows for the testing of many auxiliary model specifications simultaneously. Code is provided.

Publication Date:
Jan 03 2018
Date Submitted:
Jul 01 2019
Computational Economics
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 Record created 2019-07-01, last modified 2019-08-05

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