A Practical Approach to Testing Calibration Strategies
CAEPR Working Paper 2016-004
20 Pages Posted: 27 Sep 2016 Last revised: 4 Jan 2018
Date Written: January 3, 2018
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.
Keywords: Calibration, GMM, Indirect Inference, Existence, Misspeciﬁcation, Outlier Detection, Data Mining
JEL Classification: C13, C51, C52, C80, F34
Suggested Citation: Suggested Citation