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23525-01 - Lecture: Computational Economics 3 CP

Semester spring semester 2023
Course frequency Every spring sem.
Lecturers Dietmar Maringer (dietmar.maringer@unibas.ch, Assessor)
Content The area of "Computational Economics" combines a wide array of numerical methods and approaches for all sort of applications in economics, finance, and business. This course highlights some of these and provides participants with computational techniques any modern-day economist should have in their methodological toolbox. The first part covers Monte Carlo methods which can be used to analyse models and systems that involve randomness. Topics include sampling, path generation, modelling uncertainty and risk, and evaluating simulations. This will be followed by methods for modelling and analysing complex and adaptive systems in an economic context. Real world situations often exhibit heterogeneity, butterfly effects, network-effects, self-organization or critical situations that are difficult to analyse with traditional economic approaches. Agent-based Modelling and agent-based simulation are increasingly used in this context, and the course addresses these topics.

The course is very much hands-on, allowing for numerous own implementations and experiments. This will help participants to get a solid understanding of these methods, their practical application, their strengths and limitations.
Learning objectives Successful participants will be familiar with fundamental numerical methods, necessary to approach and solve quantitative problems in economics and business. Also, they will acquire programming skills to implement economic / management models and the necessary methods.
Bibliography Course material will be provided.


*) Miranda, M. J. & Fackler, P. L. Applied Computational Economics and Finance The MIT Press, 2002

*) Brandimarte, P. Handbook in Monte Carlo Simulation. Applications in Financial Engineering, Risk Management, and Economics Wiley, 2014

*) Brandimarte, P. Numerical Methods in Finance and Economics, Wiley-Interscience, 2006

*) Gilli, M.; Maringer, D. & Schumann, E. Numerical Methods and Optimization in Finance, Academic Press, 2nd edition 2019. (or 1st ed., 2011)

*) Kroese, D. P.; Taimre, T. & Botev, Z. I. Handbook of Monte Carlo Methods Wiley, 2011

*) Jones, O.; Maillardet, R. & Robinson, A. Introduction to Scientific Programming and Simulation Using R, CRC Press, 2009

*) Langtangen, H. P. A Primer on Scientific Programming Using Python Springer, 2014

*) Easley, D. & Kleinberg, J. Networks, Crowds and Markets. Reasoning about a Highly Connected World Cambridge University Press, 2010

*) Hommes, C. Behavioral Rationality and Heterogeneous Expectations in Complex Economic Systems Cambridge University Press, 2013

*) Jackson, M. O. Social and Economic Networks Princeton University Press, 2008

*) Tesfatsion, L. & Judd, K. J. (Eds.) Handbook of Computational Economics Vol. 2: Agent-Based Computational Economics North-Holland, 2006

Specific recommendations and additional literature to be announced during the course.
Comments Throughout the course, we will use Python to implement methods and concepts. Prior programming skill help, but are not required; material and references will be provided for those new to Python.
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Admission requirements Completed Bachelor in Business and Economics
Course application To register for the course, including the exam, please fill out the registration form, which you can find under the following link:
https://adam.unibas.ch/goto.php?target=crs_1489583_rcodeP2fTbUfLmH&client_id=adam
Registration is possible from January 1 to February 2, 2023, 8 p.m. at the latest. Please note that you are re-registered for spring semester 2023 and that the tuition fees are paid at the time of registration.
A deregistration is possible until February 7, 2023 8pm by Email to gregor.lenhard@unibas.ch.
Your enrollment in the Online Services will then be automatically registered after the official enrollment deadline, i.e. after March 20, 2023.


Language of instruction English
Use of digital media No specific media used

 

Interval Weekday Time Room
Block See individual dates

Dates

Date Time Room
Monday 06.02.2023 10.15-16.00 Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Tuesday 07.02.2023 10.15-16.00 Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Wednesday 08.02.2023 10.15-16.00 Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Thursday 09.02.2023 10.15-16.00 Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Friday 10.02.2023 10.15-16.00 Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Modules Module: Field Electives in Economics and Public Policy (Master's Studies: Economics and Public Policy)
Module: Risk Analysis (Master's Studies: Actuarial Science)
Module: Specific Electives in Data Science and Computational Economics (Master's Studies: Business and Economics)
Specialization Module: Areas of Specialization in International and/or Monetary Economics (Master's Studies: International and Monetary Economics)
Specialization Module: Quantitative Methods (Master's Studies: Business and Economics (Start of studies before 01.08.2021))
Assessment format record of achievement
Assessment details Combination of active participation, assignment(s), and final exam.
written exam: 9.3.23, 09:00-09:45; WWZ S14: A-Z.

Assessment registration/deregistration Registration/deregistration: teaching staff
Repeat examination no repeat examination
Scale 1-6 0,1
Repeated registration as often as necessary
Responsible faculty Faculty of Business and Economics , studiendekanat-wwz@unibas.ch
Offered by Faculty of Business and Economics

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