Empirical SFC Modelling
A semester of courses and project work at graduate level (30 ECTS)
Teaching staff: Sebastian Valdecantos, Mikael Byrialsen, Hamid Raza and Luis Reyes.
Overall presentation
This comprehensive semester program provides students with the theoretical foundations and practical skills needed to develop and analyse empirical Stock-Flow Consistent (SFC) models. Associate professor Sebastian Valdecantos is teaching at this SFC course.
It is possible to attend the course online. The semester is structured in two distinct phases:
- During the first phase (September to mid-October), students simultaneously attend the intensive foundational modules 1, 2 and 3 (5 ECTS each) to acquire the knowledge required for empirical SFC modelling.
- Following the autumn break, the second phase (late October to early January) consists of an extensive project (module 4) where students apply their knowledge in creating and validating their own empirical SFC model, culminating in final examinations at the end of January.
Module 1: Principles of Stock-Flow Consistent Models (5 ECTS)
This course is designed to introduce students to the core concepts and techniques of SFC modelling within the context of a monetary economy. The course content begins by familiarizing students with the principles of SFC models, emphasizing their importance in ensuring consistency between stocks (e.g., wealth, debt) and flows (e.g., income, expenditure) over time. As the course progresses, students will learn how to connect the SFC matrices to the system of national accounts, building a set of equations that represent the financial and real transactions between different sectors of the economy.
The modelling of institutional agents (households, firms, government, and banks) is covered in detail, providing students with a comprehensive understanding of how each sector interacts within an SFC framework. Students will also develop practical skills in calibrating, solving, and simulating theoretical models, allowing them to analyse economic dynamics under different scenarios. The pedagogy combines theoretical lectures with hands-on modelling exercises, culminating in the use of SFC models for policy analysis and scenario planning, equipping students with the tools to apply these models in real-world economic contexts.
Module 2: National Accounts and Economic Data (5 ECTS)
This course is designed to provide a comprehensive understanding of the system of national accounts (SNA), the data it generates, and its significance for macroeconomic modelling. The course progresses from a foundational introduction to the structure of national accounts, helping students understand the assumptions and criteria that underpin the compilation of these data and how these factors influence their use in economic models. Students will explore the relationships between key national economic variables and those at the sectoral and industry levels, gaining insights into how national accounts bridge the real and financial sides of the economy, particularly in the context of a monetary economy.
Through hands-on data exercises, students will develop proficiency in using national accounts data for economic analysis and policy evaluation. The course emphasizes practical skills in manipulating raw economic data, preparing it for use in economic modelling to ensure its accuracy and relevance for various analytical purposes. The pedagogy combines theoretical instruction with practical data analysis, encouraging students to apply their knowledge to real-world economic issues.
Module 3: Time Series Analysis (5 ECTS)
This course teaches methods and techniques required for utilizing time series data. The module is organized as an interaction between theoretical understanding and practical application. The module starts with covering basic univariate time series models used for forecasting. Afterwards, the module teaches various multivariate time series models, aimed at exploring dynamic relationships. The module builds the research foundation of students, which enables them to conduct research of empirical nature.
Upon completion of this course students are expected to be able to deal with real world time-series. They are expected to be able to find relevant data, identify important patterns in the data, and then perform various econometric applications. They are expected to be able to formulate an appropriate empirical model, estimate its parameters, test hypothesis, and evaluate the model.
Project-module 4: Empirical SFC Modelling Project (15 ECTS)
The project module provides students with a structured environment to apply their theoretical knowledge in developing a complete empirical SFC model. Through a series of lectures and associated workshops, students work in groups to progressively build their models under the guidance of an assigned supervisor. The module follows a systematic approach to model development, beginning with scope definition and proceeding through data collection, equation specification, and model validation. Each step is supported by dedicated lectures and workshop sessions where groups can present their progress and address challenges.
The project is structured around eight key stages:
- Defining the scope of the model
- Building the database
- Defining the system of equations and matching them with data
- Building the exogenous model
- Estimating the behavioural equations
- Incorporating the estimated equations into the model
- Generating and validating a baseline model
- Building and analysing scenarios
Throughout the project, students will learn to prepare and generate essential data, fill gaps in statistical information, ensure stock-flow consistency, and incorporate econometrically estimated behavioural equations. The workshop-style sessions facilitate peer learning and provide opportunities for feedback and problem-solving. Each student group works under the guidance of a supervisor who provides regular support and feedback throughout the development process.
