Subject description
This subject introduces students to the data analysis methods used in industry and academia. The subject builds upon material covered in ECON253 and introduces the modern framework for causal analysis and prediction. The topics covered include framework for causal analysis, matching with observational data, difference-in-differences and panel data methods, probability … For more content click the Read More button below.
Enrolment rules
Pre-Requisite
Tutorial enrolment
Students can enrol online via the Tutorial Enrolment link in SOLS
Delivery
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Engagement hours
Contact Hours:3 hours per week
Learning outcomes
On successful completion of this subject, students will be able to:
1.
Understand the framework for causal analysis of the experimental and observational data.
2.
Formulate research questions based on the available data that can be addressed through empirical analysis.
3.
Implement data analysis techniques such as matching, difference-in-differences and panel data using statistical software such as R and/or Stata.
4.
Apply basic prediction and forecasting techniques.
5.
Discuss and interpret empirical results, and understand their internal and external validity.
6.
Present empirical analysis in the form of a research report.
Assessment details
Tutorial quizzes
Empirical Research Report
Final Exam
Work integrated learning
Embedded WIL:This subject contains elements of "Embedded WIL". Students in this subject will experience activities that relate to or simulate professional practice as part of their learning.
Textbook information
“Data Analysis for Business, Economics, and Policy" by Békés and Kézdi.