Master’s Programme in Economics (Research track). Open to doctoral students in economics.
Basic studies in mathematics. In addition, the student is assumed to be familiar with the neoclassical growth model, dynamic optimisation, and household and firm behaviour to the extent covered in a Bachelor-level macroeconomics course.
Any course beyond the Bachelor-level core courses in microeconomics, macroeconomics and probability supports learning of the course material.
After the course, the student should
- Understand and be able to reproduce the deterministic version of the Ramsey-Cass-Koopman macroeconomic model, in both discrete and continuous time (infinite horizon Lagrangian and Hamiltonian techniques)
- Understand the difference between exogenous and optimal taxation in the above framework, and be able to reproduce both approaches technically
- Be able to solve the models with dynamic programming and value function iteration methods and understand the advantages of the model over the Lagrangian/Hamiltonian structures
Annually in the first period
The course first covers the deterministic version of the Ramsey-Cass-Koopman growth model, both in discrete and continuous times, and solves it using an infinite horizon Lagrangian/Hamiltonian. The model is then used to study taxation. Two approaches are covered: the case where taxes are exogenously given and when they result from optimisation of the Ramsey planner. Finally, the course introduces dynamic programming and value function iteration methods and compares them with the above-mentioned methods in the same model environment
In addition to the lecture material, selected parts of Recursive Macroeconomic Theory by Ljungqvist and Sargent, 3rd edition (2012, MIT Press; 2nd edition, 2004, available online); Applied Intertemporal Optimization by Wälde (2011, available online); Macroeconomic Theory: A Dynamic General Equilibrium Approach by Wickens, 2nd edition (2012); Introduction to Modern Economic Growth by Acemoglu (2008, available online) that are covered in the course are recommended.
Course material is delivered through the course website. The website also contains moderated discussion groups that support learning. Problem sets are designed to support learning of the course material.
The grade on a scale from 0 (fail) to 5 is based on the points earned in the final exam. At least 40% of the homework assignments must be completed to take the exam
The course consists of lectures (24 hours) and exercise sessions (8 hours), where solutions to the homework assignments are discussed. Participation in lectures and exercise sessions is not mandatory, but completing 40% of the homework assignments is required for taking the exam. There is a written final exam based on the lecture material and the homework assignments. The homework assignments consist of analytical exercises. They familiarise the student with the theory and calculations typically required in applying and extending the models that have been studied in the lecture.