Advanced Macroeconomic Modeling Summer School in Lisbon, Portugal

July 4 - July 8
Advanced Macro Policy Modeling in Iris/Matlab

 

Application Deadline: June 13

Paper Submission Deadline (optional): May 30

August 1 - August 5
Advanced Macro Policy Modeling in Iris/Matlab

 

Application Deadline: July 10

Paper Submission Deadline (optional): June 27

July 11 - July 15
Advanced Macro Policy Modeling in Iris/Matlab


Application Deadline: June 20

Paper Submission Deadline (optional): June 6

August 8 - August 12
Advanced Macro Policy Modeling in Iris/Matlab

 

Application Deadline: July 17

Paper Submission Deadline (optional): July 3

July 18 - July 22
Introduction to Python and R for Economists

 

Application Deadline: June 27

Paper Submission Deadline (optional): June 13

August 15 - August 19
Introduction to Python and R for Economists

 

Application Deadline: July 24

Paper Submission Deadline (optional): July 10

July 25 - July 29
Semi-Structural and DGSE Models in Dynare–Julia

 

Application Deadline: July 3

Paper Submission Deadline (optional): June 20

August 22 - August 26
Semi-Structural and DGSE Models in Dynare–Julia

 

Application Deadline: July 31

Paper Submission Deadline (optional): July 17

Olá! Bem Vindo a Portugal

 

FPAS Mark II is the next evolutionary step of central bank analytical frameworks that emphasizes the role of uncertainty during the analytical process. The purpose of Summer School 2022 is to lay the foundation for the new analytical framework. The first half of the courses begin with bringing some of the foundational elements from Mark I (Mind the Gaps) and expanding on them in the context of doing analysis under uncertainty, namely scenario building. To bolster this effort, we will conduct regular scenario analysis under the banner of the Global Forecasting School (GFS) that uses the US as an example of thinking through important economic issues of the day with a global reach. The second half of the courses will delve into models and analytical tools using open-source software that will underpin the new generation of macro modelling and analysis software (Python/Julia).

The Hybrid Summer School will take place in Carcavelos, Portugal from July 4 to August 26. This summer we offer 3 courses (details and dates below):

 

Paper Submission: All participants are welcomed to present their research work to course lecturers. The lecturers will be happy to provide feedback and comments. The authors of the best papers will be given a chance to present at The Better Policy Project's Seminar Series.

 

All of our courses start with introduction to and application of  GFS (Global Forecasting School) Scenario Builder.

The GFS is a great example of training and learning by doing that mixes different approaches and tools to economic analysis. The first stage of the GFS will revolve around four key areas:

  1. GFS Scenario Builder: an application that is designed to help articulate well-reasoned scenarios easily and efficiently.  The first example will be applied to the US economy given its global importance as a financial shock emitter, but later will be extended to other countries.

  2. Narrative Approach: rich discussions on globally relevant macroeconomic issues of the day.

  3. Semi-Structural and DSGE Models: Begin with a simple US model with monetary policy relevant output gaps as well as another for financial cycle output gaps and merging the two into a single framework.

  4. Credit-to-GDP Gaps: Using our own statistical filter and judgment to generate more realistic credit-to-GDP gaps.

Future developments will build on these four areas, in particular, building out the coverage of the semi-structural model part where it becomes a truly global model with a wider variety of commodity prices including oil.

Advanced Macro Policy Modeling in Iris/Matlab

This course is based on using the historical-narrative approach to develop plausible estimates of output gaps that are relevant for assessing conventional monetary policy trade-offs as well as other measures that are useful for measuring lower-frequency financial cycles. The course follows the work done in the Mind the Gaps paper.

 

Half the course will be hands-on using IRIS/MATLAB for modeling exercises, but at some point, there will also be versions in Dynare/JULIA, which is 100% free open-source software.

The course includes daily lectures on topics such as adding macroprudential, fiscal policy and oil market.

The course will also introduce participants to the Global Forecasting School and the modeling and analysis tools being developed under that project which includes a scenario builder, open-source surveillance reports and methods for thinking about financial stability.

What will you learn?

  • GFS Scenario Builder.

  • Small open economy models in Iris/Matlab useful for monetary policy and financial stability.

  • Foundational knowledge of FPAS Mark I central banking analytical frameworks.

  • Surveillance in Python and R.

  • Lectures on Adding Macroprudential, Fiscal Policy and Oil Market.

Requirements:

  • This course is designed for people working in central banks, ministries of finance and financial institutions.

  • Have at least intermediate knowledge in statistics and macroeconomics.

  • MATLAB 2017a or later versions. IRIS-Toolbox-Master will be provided by instructors.

Lecturers: Douglas Laxton and others

Price: 1000 Euros (1 participant, 1-week course)

Schedule: Monday – Friday (Lisbon Time (GMT+1))

  • 10:00 – 13:00 Lectures,

  • 13:00 – 14:00 Lunch,

  • 14:00 – 17:00 Assignments and Presentations.

 

Introduction to Python and R for Economists

Central banks, universities and other research institutions spend massive amounts of resources every year on software licences. With the development of open-source software (Python, R, Julia etc) there is an enormous opportunity to save and use these resources more efficiently to develop human capital and improve the quality/quantity of central bank policy analysis, forecasting and policy-relevant research.

 

This course guides participants from the basics of Python and R to becoming skilled users. It is designed for economists and researchers to help them organize and report data in a fast, effective, and beautiful way. Unlike other courses which only provide general knowledge of Python or R, this course is result-oriented and focuses on using both of them for surveillance. By the end of the course participants will have a powerful framework that can be used for database management, visualization, reporting, estimation, near-term forecasting, etc.).

What will you learn?

  • GFS Scenario Builder​.

  • Basics and advantages of Python and R.

  • Data structures in Python and R.

  • Data manipulation and database management.

  • Data visualization.

  • Statistical analysis and filters.

  • Bayesian hierarchy models.

  • Web scraping, data Extraction and automation.

  • R Markdown.

  • R Shiny: Creating interactive web apps.

Requirements:

  • ​Python 3.9.

  • Anaconda.

  • R (Version 4.0.3 or the latest ones up to 4.1.1).

  • RStudio.

  • MiKTeX.

 

Lecturers: Douglas Laxton and others

Price: 1000 Euros (1 participant, 1-week course)

Schedule: Monday – Friday (Lisbon Time (GMT+1))

  • 10:00 – 13:00 Lectures,

  • 13:00 – 14:00 Lunch,

  • 14:00 – 17:00 Assignments and Presentations.

 

Semi-Structural and DGSE Models in Dynare – Julia

Welcome to the big leagues! This course will provide a tour through the development of state-of-the-art semi-structural and DSGE models. These are Overlapping Generations (OLG) models with well-defined steady states, where we can study among other things the transitional dynamics from one steady state with low levels of government debt to steady states with much higher levels of government debt.  Participants will be taught how to think through the economics of large-scale DSGE models like Global Integrated Monetary and Fiscal Model (GIMF) as well as semi-structural models like MULTIMOD and Flexible System of Global Models (FSGM).  

Participants will also be given a crash course in understanding divide-and-conquer strategies to solve mixed-complementarity problems that involve nasty occasionally-binding constraints. Examples of occasionally-binding constraints include the Effective Lower Bound (ELB) on the Policy Rate as well as potentially efficient unconventional policy strategies that are designed to replace the policy space that is lost by hitting the ELB.

The course will be partly hands on showing participants how to build semi-structural closed-economy and open-economy models in a free and open-source Julia-based version of DYNARE.

Course includes elements from the Global Forecasting School, using R and Python for Surveillance, and daily lectures on examples of useful DSGE models.

What will you learn?

  • GFS Scenario Builder.

  • Small open economy models.

  • GIMF for fiscal policy (multipliers, stock-flow dynamics, distortionary taxes, government investment on infrastructure, etc.).

  • Lectures on Adding Macroprudential, Fiscal Policy and Oil Market is semi-structural and DSGE models.

Requirements:

  • Dynare 5.1.

  • Julia v1.7.2.

  • Visual Studio Code (If the participants do not have the required software, instructors will help to install those).

Lecturers: Douglas Laxton and others

Price: 1000 Euros (1 participant, 1-week course)

Schedule: Monday – Friday (Lisbon Time (GMT+1))

  • 10:00 – 13:00 Lectures,

  • 13:00 – 14:00 Lunch,

  • 14:00 – 17:00 Assignments and Presentations.