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Macroeconometrics

Bayesian Macroeconometrics

Learn Advanced Techniques for Economic Modeling, Policy Analysis, and Forecasting.

20h (10 days)

Online

English

Program date: February 16 - 27, 2026

Early bird deadline: January 19, 2026

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Macroeconometrics

Bayesian Macroeconometrics

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Who is this Course for?

Bayesian Macroeconometrics

Course Overview

BSE Bayesian Macroeconometrics course offers a comprehensive introduction to modern Bayesian time series methods, with a strong focus on Bayesian Vector Autoregressions (BVARs) featuring time-varying coefficients and stochastic volatility. The course is designed for those who want to go beyond traditional VAR models and apply cutting-edge tools for macroeconomic modeling, forecasting, and policy analysis.

The program begins by building a solid foundation in Bayesian inference, covering key concepts such as priors, likelihoods, posterior distributions, and the MCMC algorithm, including Gibbs sampling and the Metropolis-Hastings algorithm, as well as hierarchical modeling techniques.

Participants will then apply these methods directly to macroeconomic time series data. Topics include estimating large-scale BVARs, producing density forecasts and fan charts, and incorporating informative priors from DSGE and factor models to improve forecast accuracy and interpretability.

The course combines in-depth lectures with hands-on MATLAB sessions, allowing participants to implement the models and work with real-world data. By the end of the course, participants will be able to confidently design, estimate, and interpret advanced Bayesian macroeconomic models, skills that are highly valuable for both policy-oriented analysis and academic research.

Faculty

Learning Bayesian macroeconometrics with BSE gives participants a unique experience

1

Comprehensive Bayesian Toolkit: Learn how to apply Bayesian inference across a spectrum of macroeconomic models, from small-scale VARs to large structural systems and understand how to tailor priors for effective analysis.

2

Hands-On Experience with Advanced Techniques: Get practical experience with Gibbs sampling, Metropolis-Hastings, and other MCMC methods that form the backbone of modern empirical macroeconometrics.

3

Model Comparison Made Practical: Master techniques like marginal likelihoods and Bayes factors to evaluate, compare, and choose models with confidence.

4

From Theory to Real-World Application: Work directly with real macroeconomic data in MATLAB, applying Bayesian methods to generate policy-relevant insights and replicable results.

5

Built for Academics and Professionals: Whether you're a PhD student or a policy analyst, this course offers the applied knowledge and tools needed to conduct high-quality Bayesian macroeconomic research.

6

Expert Instruction: Learn from a leading expert in Bayesian time series and applied macroeconometrics, with deep experience in both academic research and practical applications.

7

Flexible Online Learning: Live sessions with recorded content for flexible learning.

Who is this course for?

The course has been designed for the following profiles:

Researchers who want to use the latest advances in Bayesian Time Series Analysis
Master’s and PhD students who want to extend their knowledge of Bayesian Methods and learn more about frontier research topics
Central bank practitioners and those in private and public institutions seeking to update knowledge and acquire the latest techniques

Learning Outcomes

By the end of this course, participants will have:

Developed a deep understanding of advanced Bayesian methods for macroeconomic modeling using Bayesian BVARs
Gained practical skills in applying Bayesian techniques to real-world macroeconomic data for forecasting and policy analysis
Learned to construct various Bayesian models such as BVAR, DSGE, and Factor-Augmented VARs, with practical exercises in model specification, estimation, and evaluation

Key Topics for Bayesian Macroeconometrics Course

Take a look at the themes covered during this course.

Introduction

Curse of dimensionality in VAR models
Bayes’ formula
The likelihood principle
Common misconceptions about unit roots and cointegration
The Minnesota prior

Bayesian Vector Autoregressions

The independent Normal-Inverse Wishart prior
Gibbs sampling
The conjugate Normal-Inverse Wishart prior
Monte Carlo sampling
Marginal likelihood and hierarchical priors
Priors from DSGE models

VARs with time-varying coefficients

Forward filtering/backward sampling algorithms
Carter-Kohn algorithm

VARs with time-varying volatilities

The Kim, Shepard, and Chib algorithm
Metropolis-Hastings algorithms
The Jacquier-Polson-Rossi approach
Volatility in mean model and leverage model

Large Bayesian VARs

Homoskedastic VARs with conjugate prior
Triangularization
Large Bayesian VARs with drifting volatilities and non-conjugate priors
Density forecasting and fan charts

Why should you attend BSE Executive Education courses?

All BSE Executive Education courses are taught to the same high standard as our Master’s programs.

1

Network with like-minded peers from around the world

2

Short courses allow you to learn without a big time commitment

3

Try something new and expand your knowledge and career prospects, or advance your thesis

Admissions

Are you thinking of applying to BSE Bayesian Macroeconometrics Executive Education course? Check you meet the requirements below.

Applications for this course are closed

Next edition: TBA

Requirements

Candidates are assessed on an individual basis according to their professional or academic background

Bayesian Macroeconometrics Requirements

This is an intermediate-level course for students and practitioners who, in order to follow and get the most out of it, are expected to have some background in Bayesian Econometrics and Time Series Econometrics
Students must have their own laptop or desktop computer and good Internet connection to be able to follow and fully benefit from the course

Course Schedule

The times listed are Central European Time (CET). Compare with your time zone on time.is

Instructors, topics, and schedules are subject to change.

Week 1

Time

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Fri

14:30-16:30

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Practical

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Week 2

Time

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Mon

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Tue

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Wed

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Thu

5
Fri

14:30-16:30

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Course Materials and Software

Every participant will receive a time-limited personal free MATLAB license before the course starts. You’ll need to install it on your own computer for practical sessions
Additional materials will be provided, and instructors will be available to discuss your research ideas and projects throughout the course

Certificate

Participants who attend at least 80% of the course will receive a Certificate of Attendance free of charge. Participants will not be graded or assessed during the course.

Fees

A 10% discount applies when the confirmation payment is completed on or before the announced Early bird deadline.

Multiple course discounts are available. Find out more information in our Fees and Discounts document.

Fees for courses in other Executive Education programs may vary.

* Reduced Fee applies for PhD or Master’s students, Alumni of BSE Master’s programs, and participants who are unemployed.

FAQ

Interested in applying but need more information?

Are the sessions recorded?

Sessions will be recorded and videos will be available for a month once the course has finished.

How much does each Executive Education course cost?

Fees for each course may vary. Please consult each course page for accurate information.

Are there any discounts available?

Yes, BSE offers a variety of discounts on its Executive Education courses. See more information about available discounts or request a personalized discount quote by email.