• Offered by Research School of Economics
  • ANU College ANU College of Business and Economics
  • Classification Advanced
  • Course subject Economics
  • Areas of interest Econometrics, Economics

This course will teach the basics of programming and computational skills for economic analysis and enable the students to take numerical approach to familiar mathematical problems. Students will learn to graphically represent familiar ideas such as supply and demand curves, equilibrium prices and consumer choice. They will explore how these choices and equilibria change with shifts in policy instruments, preferences and technologies. In the process they will learn to use common computational solution methods, such as root finding and optimization. Students will also learn how to obtain, manipulate and represent data, using tools such as scatterplots and histograms.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

Upon a successful completion of this course, students should be able to:

  1. Algorithm and data manipulation and visualization of economic data
  2. Basic programming skills (conditions, loops, flow control, iteration, etc.)
  3. Ability to implement familiar mathematical methods on a computer
  4. Reinforcement of key ideas from economic analysis
  5. Algorithm and data manipulation and visualization of economic data

Other Information

See the course outline on the College courses page. Outlines are uploaded as they become available. 

Indicative Assessment

  • Individual test-assignment with feedback (by week 4)
  • Midterm exam (40%)
  • Final exam (60%)

The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

Workload

2 hour lecture + 2 hour tutorial in computer lab

Requisite and Incompatibility

To enrol in this course you must have previously completed ECON2125 or ECON4413 or ECON8013 or equivalent. Incompatible with ECON3127 or ECON4414.

Prescribed Texts

Jérôme Adda, Russell W. Cooper “Dynamic Economics: Quantitative Methods and Applications”, MIT Press, 2003

Preliminary Reading

Edward R. Tufte. The Visual Display of Quantitative Information. Graphics Press, 2001

  1. R K Sundaram. A First Course in Optimization Theory. Cambridge University Press,1996.
  2. Kevin Sheppard. Introduction to Python for Econometrics, Statistics and Data AnalysisKevinSheppard.com (August 05, 2014) https://www.kevinsheppard.com/images/0/09/Python_introduction.pdf
  3. Quantitative Economics online resource
 

Assumed Knowledge

General knowledge of math and basic economics

Fees

Tuition fees are for the academic year indicated at the top of the page.  

If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Student Contribution Band:
3
Unit value:
6 units

If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees.  Where there is a unit range displayed for this course, not all unit options below may be available.

Units EFTSL
6.00 0.12500
Note: Please note that fee information is for current year only.

Offerings, Dates and Class Summary Links

The list of offerings for future years is indicative only.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.

Second Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
8369 27 Jul 2020 03 Aug 2020 31 Aug 2020 30 Oct 2020 In Person N/A

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