Programme And Module Handbook
Course Details in 2020/21 Session

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Module Title LH Advanced Econometric Theory
SchoolBirmingham Business School
Department Birmingham Business School
Module Code 08 29161
Module Lead Marco Barassi
Level Honours Level
Credits 10
Semester Semester 1
Restrictions Available to all students who have been allowed onto the final year of a degree programme for which it is a compulsory module or who have passed 08 21726 Econometric Methods (08 21726) and Mathematical Statistics for Economics
Description This module is designed to provide a rigorous training in econometric theory in order to enable students to develop and apply advanced econometric knowledge and skills. It is strongly maths-based and covers advanced material. Topics covered in the first part of the module include: Maximum Likelihood Estimation in general; properties of the score, information, efficiency, consistency, asymptotic distributions. Tests based on MLE: Likelihood ratio, Wald and Lagrange Multiplier. In the second part of the module, stationary and non-stationary time series, unit root testing and cointegration, GARCH models are discussed.
Learning Outcomes By the end of the module students should be able to:
  • demonstrate in depth knowledge and ability to derive likelihood estimators for various models;
  • identify and critically appraise the properties of estimators;
  • demonstrate systematic understanding of statistical theory and properties of stationary and non-stationary time series models.
Assessment 29161-01 : Exam : Exam (Centrally Timetabled) - Written Unseen (50%)
29161-03 : Canvas MCQ test : Class Test (50%)
Assessment Methods & Exceptions Assessments: Canvas MCQ test (50%), 1-hour final exam (50%) Reassessment: by failed element
Reading List