22-30.104 Computational Economics

Lehrende: Prof. Dr. Olaf Posch

Veranstaltungsart: Interaktive Lehrveranstaltung

Anzeige im Stundenplan:

Semesterwochenstunden: 3

Credits: 6,0

Unterrichtssprache: Englisch

Min. | Max. Teilnehmerzahl: - | 45

Kommentare/ Inhalte:

The lecture "Computational Economics" goes virtual. All lectures will be held via the platform Zoom, there is no recording of the lectures. For more information see

https://www.rrz.uni-hamburg.de/services/weitere/medienkompetenz/videokonferenzen/zoom.html

Participation is restricted to registered students. Please check this platform for the necessary information for obtaining online access.

Many interesting economic models cannot be solved analytically. This course introduces computational methods in order to solve dynamic stochastic nonlinear economic models. It illustrates that most numerical methods exploit the recursive structure of dynamic economic models. This course does not make any attempt to cover the numerous numerical techniques or potential economic applications. It instead chooses to develop only a relatively small number of techniques that can be applied easily to a wide variety of economic problems. It also demonstrates how to use some of the available toolkits.

Lernziel:
After this course, the students are able to

• explain different approaches of solving optimization problems by means of numerical approximation techniques
  
• categorize the numerical techniques covered in the lecture
  
• solve a given dynamic problem by applying a reasonable numerical technique
  
• apply a toolbox in order to solve dynamic general equilibrium models
  

Vorgehen:

• this course emphasizes practical numerical methods, not mathematical proofs
  
• focus on techniques that is particularly useful in economics
  
• the examples in this lecture cover a wide range of models in economics
  
• provide working examples and use the CompEcon toolbox
  
• the students program in Matlab by themselves and develop their own computational economic applications
  

1. Matlab primer: introduction, conditional statements and looping, scripts and functions, debugging and programming style
   
2. Basic numerical methods: linear and nonlinear equation methods, complementarity methods, finite-dimensional optimization, numerical integration and differentiation, and function approximation
   
3. Methods for solving dynamic stochastic models: dynamic programming, rational expectations in discrete and continuous time
   

Literatur:

• Miranda, Mario J. and Paul L. Fackler, Applied Computational Economics and Finance, MIT Press, 2nd edition, 2004.
  CompEcon Toolbox available at http://www4.ncsu.edu/~pfackler/compecon/toolbox.html 
  

• Heer, Burkhard and Alfred Maussner, Dynamic General Equilibrium Modelling - Computational Methods and Applications, Springer, 2nd edition, 2009.
  

Zusätzliche Hinweise zu Prüfungen:
There will be four problem sets with the possibility of improving the final grade of the exam by 0.3/0.4 (good performance) or 0.6/0.7 (exceptional performance) points. The minimum number of solved problems sets must be three out of the four problem sets (respecting the deadlines) in order to qualify for the grade improvement. Handing in the problem sets is not required to take the exam.

Please note that the exam will take place in the form of of a take-home exam. All participants have 90 minutes to answer the exam questions and will be given additional time to upload the required documents on a shared folder. There will be the possibility for clarifying questions. Please make sure that your programs are properly installed and ready to use as there will be no technical assistence during the exam.

TAKE-HOME EXAM:

Time to process the exam: 90 min

Time frame in which the exam can be completed: 120 min
First exam: 1 March 2021, 3:30 pm - 5:30 pm
Second exam: 22 March 2021, 10:45 am - 12:45 pm.

The examiner of your course will provide information about the hand out of examination tasks / assignments and their submission.