GMM

Hi! This is a sandbox for studying GMM!! I will upload coding files implementing GMM estimations described in Hansen's Econometrics and some seminal papers!! Also I am going to upload simulation codings to explrore/discover some useful features of GMM!!

File description

3-1 GMM class

Problem Set 1

'ps1.m' and 'ps1_1.m' are the main code files. They are implementing the Toy Example monte carlo simulations with different correlation parameter \rho, misspecification parameter \delta and sample size n.

Problem Set 2

'ps2.m', 'ps2_with_GMMboot...', 'ps2_with_repAEsubsample.m' are essentially the same code files, but using self-defined functions 'GMMbootstrap.m' and 'repAEsubsample.m' respectively. I separated these function files to improve computation speed. 'VarMR.m' and 'VarMR.cpp' are codes to implement M-R variance with improved performance(but failed - I leave them for future work) 'pums80.mat' is the data file for the replication of Angrist,Evans(1998). 'ps2n1000/2000/5000.mat', 'ps2r100b10000n100.mat' are the simulation results with n = 1000,2000,5000 , r = 100, b = 10000, n = 100 respectively. 'untitled.m' : I don't know for what this is.

Term paper codes and files

'termpaper.m' is the main code implementing Monte Carlo simulation for the Toy Example introduced in Lee(2014,JoE) with averaging Gmm estimator. 'termpaper_sim_result.mat' is a simulation result(but this result is wrong because I used wrong weight \omega).