Structural estimation resources

[rickecon]

@uta-bolt had a good question about structural estimation.

Estimation/Method of simulated moments: Are we only going to use models with calibrated parameters, or can we maybe have a problem set on estimating parameters with the method of simulated moments or so? I guess for one parameter it's not too hard, but for multiple parameters things seem more tricky.

In the past two years, we have had a one-week module on structural estimation, including notebooks and exercises on maximum likelihood estimation, generalized method of moments estimation, and simulated method of moments estimation. We took that module out this year because some of those topics will be covered in next week's Dynamic Structural Economics Summer School, mostly with regard to estimating dynamic discrete choice models.

I have some updated Jupyter notebooks on Maximum Likelihood Estimation, Generalized Method of Moments, and Simulated Method of Moments on my Notebooks GitHub repository. I also have some nice problem sets for these notebooks associated with my Structural Estimation class I teach at the University of Chicago.

[rickecon]

My most recent course on structural estimation at the University of Chicago is here. In particular, I recommend reading the Michael Keane (2010) and John Rust (2010) papers.