Computer Code

Link to Victor Aguirregabiria's Code in GitHub for Econometrics and Computational Methods in Economics, with examples of programs that call the procedures.

Link to Christopher Ferrall's GitHub repository of papers with empirical applications of Dynamic Discrete Choice Structural models. It includes code and data.

Link to Jason Blevin and Minhae Kim's Matlab Code for the replication of Aguirregabiria and Mira (ECMA, 2007).

Link to Eric Schulman's Python code for the implementation of the Nested Pseudo Likelihood method in Aguirregabiria and Mira (ECMA, 2020).

Link to Patrick Mogesen's Julia code for the solution of Rust's bus engine replacement model using Gaussian Quadrature

Link to Jaap Abbring and Tobias Klein's Matlab code on Econometric Methods for Dynamic Discrete Choice models.

COMPANION WEB PAGE OF THE PAPER

“DYNAMIC DISCRETE CHOICE STRUCTURAL MODELS: A SURVEY”

BY VICTOR AGUIRREGABIRIA AND PEDRO MIRA

COMPUTER CODE

This web page contains computer code which implements methods for the estimation of discrete choice dynamic programming models (single agent models, competitive equilibrium models and dynamic games). These methods are reviewed (with more or less detail) in the survey paper “Dynamic Discrete Choice Structural Models: A Survey,” by Victor Aguirregabiria and Pedro Mira.

The computer programs included below have been generously provided by the authors of the methodological papers that first proposed each method. The authors have contributed ZIP files with programs and documentation (readme files), and in some case with datasets. We have just posted these ZIP files on this webpage.