About this document
Parametrizing DSGE Models: Methods Explained by jessezheng742247 is a document available to read on EtoBox.
The document discusses methods for parametrizing DSGE models, focusing on estimation techniques such as Maximum Likelihood and Bayesian estimation. It outlines alternatives like calibration and moment matching, emphasizing the importance of selecting appropriate parameters based on real-world data features. Additionally, it introduces the Kalman filter for estimating unobserved states in time-series models, which is crucial for effective model forecasting.
- Author
- jessezheng742247
- Language
- EN