EC916-7-SP-CO:
Quantitative Economics

The details
2024/25
Economics
Colchester Campus
Spring
Postgraduate: Level 7
Current
Monday 13 January 2025
Friday 21 March 2025
20
21 August 2024

 

Requisites for this module
(none)
(none)
(none)
(none)

 

(none)

Key module for

MSC L1N212 Economics of Business and Management

Module description

This module offers an introduction to econometrics for students with little or no previous background in economics. The module will focus on the fundamentals of probability, statistics, and regression analysis. The module will complement the theory with case studies, applications, and policy-relevant debates that are relevant for business and management.

Module aims

The aims of this module are:



  • To provide students with an understanding of the fundamentals of econometrics, with a particular focus on: probability, statistics, and regression analysis.

  • To provide students with a broad base of knowledge that allows them to undertake more advanced study in specialised areas of economics.

Module learning outcomes

By the end of this module, students will be expected to be able to:



  1. Demonstrate a comprehensive understanding of the fundamentals of econometrics.

  2. Demonstrate knowledge of probability, statistics, and regression analysis.

  3. Demonstrate knowledge and critically evaluate the current debates in each of the areas of study.

Module information

Syllabus



  • The Nature of Econometrics and Economic Data, Basic Mathematical Tools

    • Wooldridge, Chapter 1 and Appendix A



  • Fundamentals of Probability

    • Wooldridge, Appendix B



  • Fundamentals of Mathematical Statistics

    • Wooldridge, Appendix C



  • The Simple Regression Model

    • Wooldridge, Chapter 2



  • Multiple Regression Analysis (Estimation)

    • Wooldridge, Chapter 3



  • Multiple Regression Analysis (Inference)

    • Wooldridge, Chapter 4



  • Multiple Regression Analysis (OLS Asymptotics)

    • Wooldridge, Chapter 5



  • Multiple Regression Analysis (Further Issues)

    • Wooldridge, Chapter 6



  • Multiple Regression Analysis with Qualitative Information (Binary Variables)

    • Wooldridge, Chapter 7



  • Heteroskedasticity

    • Wooldridge, Chapter 8

Learning and teaching methods

This module will be delivered via:

  • One 2-hour lecture per week
  • One 1-hour class per week.

The lectures and classes are face-to-face. The lectures and classes will be inclusive to all, including those with additional learning needs.

Bibliography

This module does not appear to have a published bibliography for this year.

Assessment items, weightings and deadlines

Coursework / exam Description Deadline Coursework weighting
Coursework   Assignment    100% 
Exam  Main exam: In-Person, Open Book, 120 minutes during Summer (Main Period) 
Exam  Reassessment Main exam: In-Person, Open Book, 120 minutes during September (Reassessment Period) 

Exam format definitions

  • Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
  • In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
  • In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
  • In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary, for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.

Your department will provide further guidance before your exams.

Overall assessment

Coursework Exam
50% 50%

Reassessment

Coursework Exam
50% 50%
Module supervisor and teaching staff
Dr Catherine Van Der List, email: catherine.vanderlist@essex.ac.uk.
Lectures and classes: Dr. Catherine Van Der List
For further information, send an email message to pgteco@essex.ac.uk.

 

Availability
No
No
No

External examiner

Miss Maria Kyriacou
Resources
Available via Moodle
No lecture recording information available for this module.

 

Further information
Economics

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