ECON 7300
Last Updated
- Schedule of Classes - December 1, 2024 7:42PM EST
- Course Catalog - December 1, 2024 7:07PM EST
Classes
ECON 7300
Course Description
Course information provided by the Courses of Study 2024-2025.
The course introduces students to Bayesian time series methods. Students will learn how to make likelihood-based inference about unobserved quantities, e.g. model parameters, policy impacts or future outcomes, conditional on the observed data. Applications include structural vector autoregressions, state space models and linearized dynamic stochastic general equilibrium macro models. Student will become familiar with numerical posterior simulation techniques such as Gibbs sampling and the Metropolis-Hasting algorithm. The course is useful for any students interested in empirical work that involves time series and/or structural likelihood-based estimation.
When Offered Spring.
Course Attribute (EC-SAP)
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