Please note: there may be some adjustments to the teaching arrangements published in the course catalogue for 2020-21. Given current circumstances related to the Covid-19 pandemic it is anticipated that some usual arrangements for teaching on campus will be modified to ensure the safety and wellbeing of students and staff on campus; further adjustments may also be necessary, or beneficial, during the course of the academic year as national requirements relating to management of the pandemic are revised.

Econometrics 2 ECON5128

  • Academic Session: 2022-23
  • School: Adam Smith Business School
  • Credits: 20
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 2
  • Available to Visiting Students: No
  • Available to Erasmus Students: No

Short Description

Econometrics II develops advanced knowledge and skills in statistical methods used in applied economics. The course content covers causal inference, generalized method of moments (GMM), time series methods, and non-linear models.

Timetable

20 hours of lectures (2 hours per week, during 10 weeks) and 20 hours of lab sessions (2 hours per week, during 10 weeks)

Requirements of Entry

ECON5079.

Excluded Courses

None.

Co-requisites

None.

Assessment

ILO being assessed

Main Assessment In: April/May

Course Aims

This course aims to deepen theoretical understanding of modern econometric tools and to provide training on computational implementation of the methods.

Intended Learning Outcomes of Course

By the end of this course students will be able to:

1. Critically analyze a wide range of the theoretical and practical issues associated with econometric models

2. Identify, conceptualize, define and motivate a series of estimators and estimation methodologies/algorithms, and their optimal use in various empirical scenarios

3. Demonstrate extensive, detailed and critical knowledge and understanding of concepts and ideas discussed in applied econometrics articles at the research frontier.

4. Solve significant specialized applied problem, creatively using a wide range of computer-based packages

5. Collaborate effectively within a group work environment

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.