Course
Masterclass: An introduction to applied Bayesian Econometrics
Description
Bayesian methods provide an alternative way to estimate a model's parameters by incorporating prior beliefs. Although conceptually straightforward, Bayesian methods have sparingly been used in applied research due to the mathematics involved. However, specialized statistical softwares have recently been developed that automate calculations, thus relieving the researcher from tedious algebraic manipulations and long-lasting coding procedures.
This masterclass aims at shedding light on the basics of Bayesian econometrics, with particular attention being paid on the application of the methods. It does so by using the R software and a specialized Bayesian statistical software called JAGS, which stands for Just Another Gibbs Sampler.
Lecture | Introduction | - Introduction to Bayesian Econometrics |
- Classical vs Bayesian estimation | ||
- Priors & Simulation | ||
Linear regression | - Introduction to the linear model | |
- Likelihood, priors & posterior | ||
- Application to a production function | ||
Practicum | Estimation of a linear model in R and JAGS | |