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Macroeconometrics

Advanced Bayesian Macroeconometrics

Advanced theory applications in Bayesian macroeconometric modeling.

17.5h (5 days)

€1,470

Face-to-face

English

Next edition: July 5-9, 2027

Early Bird deadline: April 15, 2027

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Macroeconometrics

Advanced Bayesian Macroeconometrics

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Who is this Course for?

Advanced Bayesian Macroeconometrics

Course overview

Bayesian macroeconometrics has become central to modern empirical macroeconomic research, forecasting, and policy analysis because it provides a disciplined way to combine economic theory, data, and uncertainty. The rapid expansion of macro-financial datasets, the need for density forecasts and scenario analysis, and the use of structural models in central banks and international institutions make advanced Bayesian tools especially relevant today.

Participants will learn methods that are directly useful for academic research and applied policy work: specifying priors, estimating Bayesian VARs and structural VARs, working with time-varying parameters and stochastic volatility, comparing models, and communicating uncertainty through posterior distributions, impulse responses, historical decompositions, and forecast densities.

This advanced course goes beyond introductory Bayesian econometrics by focusing on frontier macroeconomic applications: large Bayesian VARs, structural identification, DSGE-informed priors, time-varying parameters, stochastic volatility, density forecasting, and policy counterfactuals.

The course combines theoretical foundations with hands-on implementation and interpretation.

Faculty

Who is this course for?

This course has been designed for:

Master’s and PhD students in economics, finance, statistics, or related fields who already have a foundation in econometrics and want to work with advanced Bayesian macroeconomic models
Researchers who use macroeconomic time series data and want to incorporate Bayesian inference, model comparison, and uncertainty quantification in their work
Economists and analysts in central banks, finance ministries, international organizations, research departments, and private institutions who use forecasting or policy-analysis models
Faculty and applied researchers looking for a compact, research-oriented update on modern Bayesian macroeconometric tools

Learning outcomes

Upon completion of this course, you will be able to:

Specify and estimate Bayesian macroeconometric models, including Bayesian VARs and structural VARs, and understand the role of priors, likelihoods and posterior inference
Implement posterior simulation methods used in empirical macroeconomics, including Gibbs sampling and Metropolis-Hastings steps, and diagnose the output of these algorithms
Use Bayesian models for impulse-response analysis, historical decomposition, density forecasting, fan charts, model comparison, and policy-relevant scenario analysis
Work with advanced extensions such as large-scale VARs, time-varying parameters, stochastic volatility, and DSGE-informed priors

Key topics for Advanced Bayesian Macroeconometrics course

This advanced course will cover the following topics:

Bayesian foundations for macroeconometrics

Bayesian inference for macroeconomic time series; priors, likelihoods and posterior distributions
The curse of dimensionality in VAR models; Minnesota-style priors and shrinkage
Introduction to posterior simulation and interpretation of Bayesian output

Bayesian VARs and model comparison

Conjugate and non-conjugate Bayesian VARs
Gibbs sampling and Monte Carlo methods
Marginal likelihood, hierarchical priors and DSGE-informed priors

Structural analysis and identification

Structural VARs and identification of macroeconomic shocks
Zero, sign and narrative restrictions; impulse responses and historical decompositions
Policy interpretation and communication of uncertainty

Time variation, stochastic volatility and forecasting

VARs with time-varying coefficients; forward filtering/backward sampling and the Carter-Kohn algorithm
Stochastic volatility and Metropolis-Hastings algorithms
Density forecasting, fan charts, and forecast evaluation

Large models and applied policy analysis

Large Bayesian VARs and factor-augmented approaches
Model comparison, robustness and sensitivity to priors
Applied lab and discussion of participant research or policy applications

List of References

Here is a list of texts that may help you to prepare for this course.

Articles and Books

Arias, J. E., Rubio-Ramírez, J. F. and Waggoner, D. F. (2018). Inference based on structural vector autoregressions identified with sign and zero restrictions. Econometrica.
Bańbura, M., Giannone, D. and Reichlin, L. (2010). Large Bayesian vector autoregressions. Journal of Applied Econometrics.
Chan, J., Koop, G., Poirier, D. J. and Tobias, J. L. (2019). Bayesian Econometric Methods, 2nd edition. Cambridge University Press.
Del Negro, M. and Schorfheide, F. (2011). Bayesian macroeconometrics. In The Oxford Handbook of Bayesian Econometrics.
Fernández-Villaverde, J., Rubio-Ramírez, J. F. and Schorfheide, F. (2016). Solution and estimation methods for DSGE models. In Handbook of Macroeconomics.
Koop, G. (2003). Bayesian Econometrics. Wiley.
Primiceri, G. E. (2005). Time varying structural vector autoregressions and monetary policy. Review of Economic Studies.
Rubio-Ramírez, J. F., Waggoner, D. F. and Zha, T. (2010). Structural vector autoregressions: theory of identification and algorithms for inference. Review of Economic Studies.
Sims, C. A. and Zha, T. (1998). Bayesian methods for dynamic multivariate models. International Economic Review.

Teaching Methods

Lectures introducing the econometric theory and the macroeconomic interpretation of each method
Hands-on labs using macroeconomic datasets to estimate models, produce impulse responses, compute forecasts, and interpret posterior uncertainty
Guided discussion of selected papers and applied examples from monetary policy, fiscal policy and forecasting

Software / Hardware

MATLAB will be used during the course. Participants will receive a free, time-limited MATLAB license before the program starts
Please install MATLAB on your computer before the course begins for use in practical sessions
Participants must bring their own laptop to participate in the practical sessions

Why join our Summer School?

All BSE Summer courses are taught to the same high standard as our Master’s programs. Join us to:

1

Network with like-minded peers

2

Study in vibrant Barcelona

3

Learn from world-renowned faculty

Admissions and Requirements

All BSE Summer School applicants must meet the entrance requirements.

Next edition: July 5-9, 2027

Early Bird deadline: April 15, 2027

Requirements

Summer School applicants normally demonstrate one or more of the following:

A strong background in Economics or a field closely related to the course topic (Statistics, Law, etc.)
A postgraduate degree or current Master’s/PhD studies related to the course topic
Relevant professional experience

Requirements for Advanced Bayesian Macroeconometrics course

Graduate-level training in economics, finance, statistics, or a related quantitative field.
Solid knowledge of econometrics and time series analysis, including regression, VAR models, and basic statistical inference
Familiarity with macroeconomic models and empirical macroeconomic questions is recommended
Basic programming experience in MATLAB or a similar language is strongly recommended for the practical sessions

Schedule

Here is your schedule for this edition of BSE Macroeconometrics Summer School Advanced Bayesian Macroeconometrics course.

Time

5

mon

6

tue

7

wed

8

thu

9

fri

11:30-13:30

Lecture

16:30-17:45

Practical

Credit Transfers (ECTS)

To be eligible for credit transfer, students must complete a final project.

Students will deliver a short final project one week after the summer school finishes. It will consist in solving a final problem that will include the practical and empirical issues worked on in class.

Consult the Summer School Admissions page for more information about this option.

Certificate of Attendance

Participants who attend more than 80% of the course will receive a Certificate of Attendance, free of charge.

Course

Advanced Bayesian Macroeconometrics

Bayesian Estimation of RANK and HANK Business Cycle Models

Forecasting with Machine Learning

Introductory Bayesian Macroeconometrics

Introduction to Nowcasting and Forecasting

Structural Macroeconometrics: Foundations

Structural Macroeconometrics: Advanced Topics

Modality

Face-to-face

Total Hours

17.5

ECTS

1

Regular Fee

€1,470

Reduced Fee*

€840

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

Multiple discounts are available.

For more information on discounts for participants funding their own course, please click here.

For more information on discounts for companies and institutions enrolling their employees, please click here.

Full discount conditions are available here.

FAQ

Here are some commonly asked questions by participants. Any further queries, please contact our Admissions Team.

Can I see the full Summer School calendar?

You can view the full Summer School calendar here.

Is accommodation included in the course fee?

Accommodation is not included in the course fee. Participants are responsible for finding accommodation.

Are the sessions recorded?

Sessions will NOT be recorded; however, the materials provided by the professor will be available for a month after the course has finished.

How much does each Summer School 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 Summer School courses. See more information about available discounts or request a personalized discount quote by email.

Can I take more than one course?

Yes! you can combine any of the Summer School courses (schedule permitting). See the full course calendar.

Cancelation and Refund Policy

Please consult BSE Summer School policies for more information.

Are there any evening activities during the course?

Yes, a social dinner is held once a week for all participants, it is free to attend.

Contact our Admissions Team

Mix and match your summer courses!

Remember that you can combine this program with courses in any of the other BSE Summer School programs (schedule permitting). Maximise your learning this summer and take advantage of our multiple-course discount.

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