This programme develops the theoretical and econometric toolkit used in top policy units, central banks, economic consultancies and research institutes. You will master micro and macro foundations, causal inference methods and applied domains — public finance, development, trade and environmental policy. The research capstone produces an empirical paper or policy evaluation meeting professional standards for clarity, identification strategy and transparent limitations.
MSc Economics & Policy is taught as one award, not a list of unrelated modules. The published length is 24 months, and the credit total is 36. Students move from Advanced Microeconomics through Advanced Microeconomics; Macroeconomics & Monetary Policy; Econometrics I: Regression & Inference; Mathematical Methods for Economics; Econometrics II: Causal Inference; Public Economics & Fiscal Policy, and finish on MSc Economics Research Capstone.
Each course has a question, a method, and a submission. In this field, students say who decides, under which rule, and draft a note a professional could read. Reading is a statute or instrument, a case or policy paper, and a commentary. The artefact a marker expects is a memo or draft clause with sources and a revision note.
The award is built so that a graduate can do the following in practice: Apply microeconomic and macroeconomic models to real policy questions Estimate causal effects using modern econometric designs Evaluate fiscal, trade and development programmes with transparent methods
Teaching assumes the student can read a source, attempt a problem before the seminar, and revise after feedback. Attendance at live seminars is part of the design. The capstone or final course must use the methods of the earlier courses; a project that ignores them does not pass.
This course is academic. It does not admit the student to practise law and it is not a qualifying law degree.
The pages for each course name the topics that are examined. Those topics are the syllabus. A brochure line is not a substitute for them.
Mathematical preparation is scaffolded in Term 1. Software training centres on Stata and/or R for reproducible policy research. Suitability for future PhD applications is supported through research methods depth.
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Nasza historia od 1969
