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 ECONOMETRIC AND STATISTICAL METHODS
Code ECON814
Coordinator Dr Y Rao
Economics
Y.Rao@liverpool.ac.uk
Year CATS Level Semester CATS Value
Session 2023-24 Level 7 FHEQ First 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 20

 5

         25
Timetable (if known)              
Private Study 125
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. This is an anonymous assessment. Assessment Schedule (When): Semester 1  24    100       
CONTINUOUS Duration Timing
(Semester)		 % of
final
mark		 Resit/resubmission
opportunity		 Penalty for late
submission		 Notes
Mid-term test There is a resit opportunity. Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedule (When): Semester 1  1    0       

Aims

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

Understand the multiple regression model including the matrix and statistical background;

Be apply to apply statistical tests estimate regression models;

Understand the assumptions and limitations;

Understand the maximum likelihood principle and be able to perform the relevant specification tests;

Understand the principle underlying instrumental variables and GMM estimation;

Be confident in the use of econometric software such as EViews for a range of methods and applications.

Learning Outcomes

(LO1) Formulate and estimate regression models.

(LO2) Perform diagnostics on regression models.

(LO3) Perform all the calculations required via EVIEWS.

(LO4) Perform maximum likelihood estimation and be aware of the properties of the estimators.

(LO5) Perform GMM estimation.

(S1) Problem solving skills

(S2) Numeracy

(S3) IT skills

(S4) Communication skills

Teaching and Learning Strategies

2 hour lecture x 10 weeks
1 hour seminar x 5 weeks
Self-directed learning x 125 hours

Syllabus
 

Statistical and matrix background;

Inference in multiple regression models

Endogeneity;

Instrumental variables and generalised method of moments;

Maximum likelihood estimation and specification tests;

Introduction to asymptotics.

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