Chair of Public Finance

    Computational Economics

    Contents & Objectives:

    This course introduces the numerical implementation of economic models. Students will first learn how to program in FORTRAN and to apply numerical methods for solving linear and non-linear equation systems. These methods are then applied in three areas: tax policy analysis with static general equilibrium models, portfolio choice analysis and option pricing, life-cycle decision making and overlapping generation models.

    After finishing this course students are able to

    (1) implement simple economic models on the computer using Fortran 90,

    (2) using Monte-Carlo techniques to find optimal portfolio structures and option prices,

    (3) simulate simple reforms of the tax and transfers system,

    (4) interpret the simulation results economically.

    Course Structure:

    Computational Economics (summer term 2021)

    Room 414, October 4th – October 15th 2021

    Due to COVID-19 the BA course „Computational Economics“ will be taught within two weeks in October. During the course, students have to sit in distance with a mask.  In the following, I will explain the course content, structure and timeline, the course material, as well as requirements to complete the course successfully.

    The course combines seven days (4.-12.10) of intensive lectures and exercise classes. Students need to bring their own computer to lectures and exercise classes. In the first lecture you will install the free programming language FORTRAN on your computer. Then you will learn to write code and solve simple numerical exercises in FORTRAN. On this basis we can study the theoretical structure of various economic models and implement these models in FORTRAN.

    Over the weekend, you have to prepare an assignment where you write a code in FORTRAN in a team consisting of not more than two members. When the exercises are finished on Tuesday, there are two days (13/14.10) to prepare for the final exercise and/or come up with questions. On Friday (15.10) the last day of the course, you have to solve a programming exercise by yourself. In this exercise, you will receive a FORTRAN code, which contains a number of programming errors. You have to correct these bugs and run the program. The programming exercise as well as the team assignment are both graded. The average of both marks defines your final grade. However, you need to pass both tests in order to complete the course successfully.

    Daily time schedule for classes:  

    9:00-10:30 and 11:00-12:30 - Lecture class, where the specific material is explained.

    14:00-17:00 - Exercise class where you mostly programme by yourself.   

    It is absolutely necessary to attend the lecture classes in order to manage the exercises! If there is an exam on a specific day, we will try to reorganize the schedule. Every participant will receive a set of Lecture Notes free of charge in the first lecture. The material there can (and should) be studied before attending the respective lectures.

    The programming exercise on the last day will last for 90 minutes from 9:00-10:30.

    Detailed course plan:  

    Monday: Introduction to programming with Fortran 90

    Tuesday: Numerical solution methods: Nonlinear equation systems and function minimization

    Wednesday: The static general equilibrium model

    Thursday: Portfolio choice and option pricing

    Friday: The life-cycle model and intertemporal choice

    Weekend: Prepare teamwork assignment

    Monday: The overlapping generations model: Long-run equilibrium

    Tuesday: The overlapping generations model: Transitional dynamics and welfare

    Wednesday and Thursday: Prepare for programming exercise

    Friday: Programming exercise


    Advanced study or preparation:

    In case you want to prepare in advance or study additional material, you can consult selected chapters of the following books, which you can find in the library:

    Hans Fehr and Fabian Kindermann (2018): Introduction to computational economics using Fortran, Oxford: Oxford University Press.