Indirect inference is a simulation-based method for estimating the parameters of economic models.
[1][2] It is a computational method for determining acceptable macroeconomic model parameters in circumstances where the available data is too voluminous or unsuitable for formal modeling.
[3] Given a dataset of real observations and a generative model with parameters
Since a maximum likelihood estimation cannot be performed, indirect inference proposes to fit a (possibly misspecified) auxiliary model
to the observations, which will result in a set of auxiliary model parameters
This is done repeatedly for the output of the generative model for different
By using the auxiliary model as an intermediary, indirect inference allows for the estimation of the generative model's parameters even when the likelihood function is not easily accessible.
This method can be particularly useful in situations where traditional estimation techniques are not feasible or computationally prohibitive.