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Course module: 35V3A1-B-6
35V3A1-B-6
Computational Aspects in Econometrics
Course info
Course module35V3A1-B-6
Credits (ECTS)6
CategoryBA (Bachelor)
Course typeCourse
Language of instructionEnglish
Offered byTilburg University; Tilburg School of Economics and Management; TiSEM: Econometrics and OR; Econometrics & Operations;
Is part of
B Econometrics and Operations Research
Lecturer(s)
Lecturer
dr. R.C.M. Brekelmans
Other course modules lecturer
Lecturer
dr. E.A.M. Caron
Other course modules lecturer
Academic year2019
Starting block
SM 1
Course mode
Full-time
Remarks-
Registration openfrom 19/08/2019 up to and including 24/01/2020
Aims
In this course students will learn a number of important IT-concepts and computational skills. After this course students should be able to convert (econometric/OR/financial) models and ideas into sound, well-structured, and well-documented computer applications in four main modules.
  • MATLAB: Students should be able to perform common tasks, such as equation solving, regression, interpolation, and visualization using efficient MATLAB methods.
  • AIMMS: Students should be able to implement medium-scaled optimization problems accompanied by a user interface, which handles input and output of data, presents problem data and results, and offers the user the option to solve different variations of the problem.
  • Databases: Computer science has developed various methods for storing, retrieving, and processing large amounts of data. In the databases module, students learn about one of these methods, namely the relational model, the related modeling approaches, and the SQL query language for data retrieval.
  • Python: Based on the popular computer language Python in the data science community, a number of advanced computational aspects will be explained and practiced: object-oriented programming, advanced data structures, database access via Python, regular expressions, and data preparation & data mining in Python.
Content
  • MATLAB
    • efficient coding in Matlab and using the debugger/profiler
    • structuring Matlab code, writing functions
    • advanced methods: cell and structure arrays, anonymous functions
    • visualization: advanced figure properties, 3D figures
    • common tasks: equation solving, regression, interpolation
  • AIMMS
    • element parameters, sparse execution, efficiency with higher dimensions
    • page building, templates
    • callbacks
    • input/output using database tables
  • Databases
    • relational databases and their theory
    • relational algebra and the SQL query language
  • Python
    • object-oriented programming
    • data types for managing large data sets
    • database access via Python
    • regular expressions
    • data preparation and data mining in Python
Course available for exchange students
Conditions of admission apply
Contact person
dr. R.C.M. Brekelmans
Timetable information
Computational Aspects in Econometrics
Written test opportunities
DescriptionTestBlockOpportunityDate
Written test opportunities (HIST)
DescriptionTestBlockOpportunityDate
Computer tentamen (40%) / Computer exam (40%)EXAM_01SM 1110-01-2020
Computer tentamen (40%) / Computer exam (40%)EXAM_01SM 2223-06-2020
Required materials
Handouts
Additional sources provided via Blackboard such as handouts, slides, MS SQL documentation, Python documentation.
Recommended materials
Manual
MATLAB documentation, online on www.mathworks.com; selected chapters.
Manual
AIMMS documentation, online available on www.aimms.com; selected papers.
Literature
-
Title:Sams Teach Yourself Microsoft SQL Server T-SQL in 10 Minutes
Author:B. Forta (2016)
Literature
Available online
Title:How to Think Like a ComputerScientist: Learning with Python 3 Documenation
Author:Peter Wentworth, Jeffrey Elkner,Allen B. Downey and Chris Meyers (2019)
Edition:3
Tests
Assignment 1(15%)

Assignment 2 (15%)

Assignment 3 (15%)

Assignment 4 (15%)

Computer exam (40%)

Final Result

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Kies de Nederlandse taal