STA501: Introduction
The course runs through basic concepts in microeconomics that are key frameworks in data-based decision making. With the beneift of applied statistical models widely used in microeconomics literature, such as treatment effects, diffs-and-diffs, and propensity score matching, microeconomic theories are re-accessed in terms of data analysis.
The reason the program emphasizes economics training at the early stage of the coursework is because economics is a stream of social science that most leverages hard science tools in mathematics and statistics, and it is highly likely you will see not laboratory data but social science data in real world. Many people are confused that data-based research is just about data and its visualization, but what truly research work is based on is mathematical and statistical tools that help interpreting data in deeper level with robust logic. Economics so far has achieved a status of the most advanced social science discipline in this regard.
Course topics
Although the course is self-contained, for the student with little prior exposure to economics are recommended to read any basic text for economic intuition. Some recommendations are listed in the reading section
Economics topics discussed will be
- Comparative advantage
- Consumer choice
- Difference-in-difference
- Partial effect
- Demand & Supply curve estimation
Some of the business cases that we will apply above economics topics are
- Spirits vs. Beer: are they complements?
- Top school admission: is it really DNA? or is it money?
- Salary negotiation: why my salary won't go up?
Weekly problem sets are due in every week. Together with the problem sets, comprehensive final exam also strongly emphasize the fundamental understanding of core concepts. Together with math, stat and structural mind set for programming, economics is one of the most important skill sets required to successfully finish the program. Students must be familiar with every concept discussed in the lecture for the final exam, and the dissertation.
Course schedule
The course combines lectures, handouts, problem sets and weekly TA sessions.
All lecture videos are provided at the beginning of the course. In addition to the regular weekly class, pre-recorded TA sessions for problem set discussions will also be available for week 2 to week 8.
Toward the end of the course, class 7 and 8 are dedicated to previous final examinations to help students review the course and be ready for the final exam.
Class discussion
The school strongly encourages in-class discussion, which covers 10% of the final grading. Students are given a discussion forum in all Moodle course pages, and various types of participations will be added to the final mark.
Plz note that only productive discussion activities will be positively marked. If any abusing is found, the student or the group of students will lose all 10% mark.
Final Examination
There will be a take-home final exam with 48 hours, which is usually provided on a friday 2 weeks after the last class.
Refer the sample exam questions for more details.
Grading and evaluation
Final marks will be broken down as below.
- 80%: Final examination
- 10%: Problem set submission (not graded - submission w/ reasonable amount of work is sufficient)
- 10%: Forum discussion
For business track students, instead of final examination and problem sets, there will be an essay requirement covering 90% of the grading.
Essays are graded based on following criteria.
- Critical thinking
- Effective use of in-class knowledge
- Problem detection and solving in data scientific cases
All essays must not exceed 3,000 words.
Language
All contents must be submitted in English, although the school does not refrain students relying on AI tools for translation.