Policy makers, firms, interest groups and society in general frequently require information about the economic impacts of actual or potential policies. Although analytical or graphical economic models are invaluable tools for structured economic thinking and policy analysis, they often cannot capture the complexity necessary to answer real-world policy questions as faced by policy makers. Adding such complexity to the models, for example, by introducing multiple product markets and countries, more economic actors, production factors, or varying economic mechanisms, renders them quickly insolvable for standard analytical approaches.
This course covers the formulation of computable, applied economic models, as commonly used for real-world policy analysis, and their implementation and numerical solution utilizing the mathematical modelling system GAMS. Such models are built on real world data and allow for quantitative and simultaneous evaluation of all inter- and counteracting mechanisms at once. GAMS facilitates easy implementation of such equations system which then can be applied to simulate scenarios answering all kinds of what-if policy questions.
The module provides a degree of understanding which allows building, modifying and using simple policy simulation models as well as interpreting and judging policy simulation results from third party researchers to inform policy makers, other stakeholders, researchers and general society.
This module is designed to equip students in a series of combined lecture and hands-on classes with
- the theoretical concepts required for analyzing real world policies and their economic consequences, such as the consequences of import tariffs or production subsidies.
- the skills to abstract and cast policy analysis questions into mathematical economic models.
- working knowledge of a tool (the GAMS software) allowing the transformation of theoretical models into applied models which are then used, together with real world economic data, for simulating and assessing alternative policy scenarios with the help of a computer.
- sufficient background knowledge of the models, data requirements and problems to allow an educated judgment of results and conclusions from applied policy analysis studies.