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Brief Description:
Brief Description:
This course consists of two parts. The first part introduces tools for solving and estimating linearized, full-information, dynamic stochastic general equilibrium (DSGE) models. Students will develop tools in matlab to solve and estimate medium-scale DSGE models using several approaches. Part two of the course explores alternatives to the full-information, rational expectations paradigm.
This course consists of two parts. The first part introduces tools for solving and estimating linearized, full-information, dynamic stochastic general equilibrium (DSGE) models. Students will develop tools in matlab to solve and estimate medium-scale DSGE models using several approaches. Part two of the course explores alternatives to the full-information, rational expectations paradigm.
Course Syllabus:
Course Syllabus:
Linked here. The syllabus includes an updated list of readings.
Linked here. The syllabus includes an updated list of readings.
Office Hours:
Office Hours:
Wednesdays: 1:30pm to 3:30pm. Please sign up here for office hours!
Wednesdays: 1:30pm to 3:30pm. Please sign up here for office hours!
Problem Sets:
Problem Sets:
Other Resources
Other Resources
RBC example 1: linearization using Matlab's symbolic toolbox
RBC example 1: linearization using Matlab's symbolic toolbox
RBC example 2: linearization using Matlab's symbolic toolbox
RBC example 2: linearization using Matlab's symbolic toolbox
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