Postgraduate Course: Advanced Microeconometrics (ECNM11048)
Course Outline
| School | School of Economics |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | This course introduces students to the econometric analysis of duration data (lectures 1, 2 and 3) and regression with Big Data using Machine Learning techniques (lectures 4, 5 and 6). The course maintains a dual focus on theory and application and considers the use of econometric models for descriptive analysis, prediction and for the estimation of causal effects. |
| Course description |
Not entered
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
Students MUST have passed:
Econometrics 1 (ECNM11043) AND
Econometrics 2 - Microeconometrics (ECNM11091)
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | Students should be enrolled on MSc Economics, MSc Economics (Econometrics), MSc Economics (Finance) or MSc Mathematical Economics and Econometrics.
Any other students must email sgpe@ed.ac.uk in advance to request permission.
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Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
|
| Academic year 2024/25, Available to all students (SV1)
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Quota: None |
| Course Start |
Block 4 (Sem 2) |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 18,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
78 )
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| Assessment (Further Info) |
Written Exam
100 %,
Coursework
0 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
2-hour final exam (100%) |
| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
| This module explores further topics in applied econometrics. Students will be introduced to various tools that are part of the basic econometric training of professional economists. The course is intended for students who want to be professional economists or who want to go on to PhD study, i.e. at aspiring economists rather than aspiring econometricians.
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Reading List
Cameron and Trivedi, ¿Microeconometrics: Methods and Applications¿
James, Witten, Hastie and Tibsharani (2021), ¿An Introduction to Statistical Learning: with Applications in R,¿
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | Not entered |
Contacts
| Course organiser | Prof Jesper Bagger
Tel:
Email: |
Course secretary | Miss Quincy Sugiuchi
Tel: (0131 6)50 8361
Email: |
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