ULMS Electronic Module Catalogue
The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
Title ADVANCED ECONOMETRICS
Code ECON920
Coordinator Dr R Bu
Economics
Ruijunbu@liverpool.ac.uk
Year CATS Level Semester CATS Value
Session 2019-20 Level 7 FHEQ Second Semester 15

Pre-requisites before taking this module (other modules and/or general educational/academic requirements):
 

Modules for which this module is a pre-requisite:
 

Programme(s) (including Year of Study) to which this module is available on a required basis:
 

Programme(s) (including Year of Study) to which this module is available on an optional basis:
 

Teaching Schedule
  Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
Study Hours 24

     6

     30
Timetable (if known)              
Private Study 120
TOTAL HOURS 150

Assessment
EXAM Duration Timing
(Semester)		 % of
final
mark		 Resit/resubmission
opportunity		 Penalty for late
submission		 Notes
Examination There is a resit opportunity. Standard UoL penalty applies for late submission. Marked anonymously Assessment Schedule (When): 2  2 hours    80       
CONTINUOUS Duration Timing
(Semester)		 % of
final
mark		 Resit/resubmission
opportunity		 Penalty for late
submission		 Notes
Individual project There is a resit opportunity. Standard UoL penalty applies for late submission. Marked anonymously Assessment Schedule (When): 2  -2500 words    20       

Aims

The aim of this module is to build on the first semester econometrics module and give the student an understanding of more advanced econometric and statistical methods suitable for financial and economic data series. Extensive use will be made of the econometrics package EViews in tutorials to supplement the theory with applications and to provide hands-on experience. The aims are that the student will:

Understand the main tools of modern time series analysis;

Limited dependent variable models;

Understand panel data techniques;

Understand the assumptions and limitations;

Be confident in the use of an econometric computer programme (EViews) for a range of methods and applications.

Learning Outcomes

(LO1) Formulate and estimate time series models;

(LO2) Formulate and estimate panel data models.

(LO3) Perform all the calculations required via EVIEWS.

(S1) Problem solving

(S2) Numeracy

(S3) Communication skills

(S4) Lifelong learning skills

Teaching and Learning Strategies

Lectures x 24 hours

Laboratory Work x 6 hours

Self-directed learning x 120 hours

Syllabus
 

Univariate time series models;

Models for stationary time series;

Estimation, testing and choosing a model;

Prediction testing for unit roots and random walks;

Autoregressive conditional heteroskedasticity;

Multivariate time series models;

Vector autoregressive models;

Cointegrated variables;

Limited dependent variable models;

Logit and probit models;

Panel data models;

Random and fixed effects models.

Recommended Texts
Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module.