Read "Notes on Linear RE models.pdf".
I document some widely used methods in solving and estimating linear rational expectation models. I start presenting different solution methods and explaining how we can use these algorithms to solve simple models. Then, I make a brief review of Bayesian statistics. After that, I explain in a general way the usefulness of the Kalman Filter and give some useful examples. Finally, I present a simple sampler algorithm used in the estimation of linear rational expectation models and expose the way we implement it in a small open economy model using Peruvian data.
Folders:
- Estimation: Contains codes for bayesian estimation and Sims' code for solving linear RE models.
- Solution: Contains own codes for solving linear RE models.
Files:
- main_sol.m: replicates the applications of the "solution codes".
- main_KF.m: replicates the applications of the Kalman Filter.
- main.m: replicates the estimation of a SOE model using Peruvian data.
Alex Carrasco / [email protected]