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 ECONOMETRICS 2
Code ECON213
Coordinator Dr Y Li
Economics
Yuyi.Li@liverpool.ac.uk
Year CATS Level Semester CATS Value
Session 2022-23 Level 5 FHEQ Second Semester 15

Pre-requisites before taking this module (other modules and/or general educational/academic requirements):
ECON121 PRINCIPLES OF MICROECONOMICS; ECON123 PRINCIPLES OF MACROECONOMICS; ECON212 ECONOMETRICS 1 

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

       5

 35
Timetable (if known)              
Private Study 115
TOTAL HOURS 150

Assessment
EXAM Duration Timing
(Semester)		 % of
final
mark		 Resit/resubmission
opportunity		 Penalty for late
submission		 Notes
Assessment 2: Individual Online Test Duration: 1 hour Weighting: 10% Reassessment Opportunity: Yes Penalty for Late Submission: Standard Anonymous Assessment: Yes  1    10       
Assessment 3: Unseen Examination Duration: 2 hours Weighting: 65% Reassessment Opportunity: Yes Penalty for Late Submission: Standard Anonymous Assessment: Yes Final Assessment: Yes  2    65       
CONTINUOUS Duration Timing
(Semester)		 % of
final
mark		 Resit/resubmission
opportunity		 Penalty for late
submission		 Notes
Assessment 1: Group Project Size: 2000 words Weighting: 20% Reassessment Opportunity: Yes Penalty for Late Submission: Standard Anonymous Assessment: Yes Assessment Notes: Reassessment of   0    20       
Assessment 3: Seminar Participation Weighting: 5% Reassessment Opportunity: Yes Penalty for Late Submission: N/A Anonymous Assessment: No Assessment notes: Students receive 1% for each semina  0    5       

Aims

The aims of this module are to build on ECON212 by extending the treatment of regression to the multiple regression model and to develop practical research skills which would be expected from a graduate in Economics either as a foundation for postgraduate study or for work as a professional economist recruited at graduate level.

Learning Outcomes

(LO1) Students will be able to explain the assumptions required for OLS multiple regression to be Best Linear Unbiased

(LO2) Students will be able to explain the problem of multicollinearity, how it is detected and how it can be resolved

(LO3) Students will be able to conduct single and joint hypothesis tests

(LO4) Students will be able to test restrictions on coefficients

(LO5) Students will be able to construct and interpret confidence intervals around estimates and forecasts

(LO6) Students will be able to propose and implement model building strategies and criteria for evaluating model adequacy

(LO7) Students will be able to explain, use and interpret dummy variables

(LO8) Students will be able to explain and implement the generalised method of moments using instrumental variables

(LO9) Students will be able to conduct independent econometric research and present the results in a professional manner

(LO10) Students will be able to develop a knowledge of the appropriate quantitative tools used inaddressing real world economic issues.

(S1) Problem solving skills

(S2) Numeracy

(S3) Teamwork

(S4) Organisational skills

(S5) Communication skills

(S6) IT skills

(S7) Lifelong learning skills

Teaching and Learning Strategies

Teaching Method: Lecture
Scheduled Directed Student Hours: 24
Attendance Recorded: Yes

Teaching Method: Seminar
Scheduled Directed Student Hours: 6
Attendance Recorded: Yes

Teaching Method: Whole-group Workshop
Scheduled Directed Student Hours: 5
Notes: this provides additional support related to STATA (econometrics software package) and interpretation of STATA outputs.

Self-Directed Learning Hours: 115
Description: These independent learning hours are aimed at supporting the directed student learning. The module leader will provide guidance in the form of suggested readings and topics to examine with the expectation that students are well prepared to understand the content of lectures. Self-Directed Learning will include research activity, developing academic writing skills, and wider reading to support the module

There are the following non-modular requirements:
ECON121, ECON123, ECON212 or equivalent

This modul e is a pre-requisite for the following modules:
ECON312

Skills/Other Attributes Mapping

Skills / attributes: Lifelong learning skills
How this is developed: the group project develops general research skills. Econometrics itself enables one to conduct empirical investigations, which can be part of Life Long Learning
Mode of assessment (if applicable): Group Project

Skills / attributes: IT skills
How this is developed: the seminar/workshop sessions and group project will will develop IT skills
Mode of assessment (if applicable):Group Project

Skills / attributes: Communication skills
How this is developed:
Mode of assessment (if applicable):Group Project and Examination

Skills / attributes: Organisational skills
How this is developed: during the group project, and throughout the independent study hours in order to balance effort across the project and final exam
Mode of assessment (if applicable): Group Projec t and Examination

Skills / attributes: Teamwork
How this is developed: during the seminar sessions and group project
Mode of assessment (if applicable): Group Project

Skills / attributes: Numeracy
How this is developed:
Mode of assessment (if applicable): Group Project and Examination

Skills / attributes: Problem solving skills
How this is developed
Mode of assessment (if applicable): Group Project, and Examination

Syllabus
 

Multiple Regression
OLS assumptions and properties of OLS estimators
Multicollinearity: problems, detection and solutions
Distribution of OLS estimators and construction of confidence intervals
Tests of single and joint hypotheses
Testing restrictions on coefficients and incorporating non-sample information into estimation
Use and interpretation of dummy variables
Model building strategies and model selection criteria
Generalised Least Squares and instrumental variable estimation
Reporting the results of econometric research

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