EC114-4-FY-CO:
Introduction to Quantitative Economics

The details
2023/24
Economics
Colchester Campus
Full Year
Undergraduate: Level 4
Current
Thursday 05 October 2023
Friday 28 June 2024
30
24 October 2023

 

Requisites for this module
(none)
(none)
(none)
MA108, MA114

 

EC252

Key module for

BSC LL14 Economics and Politics (Including Foundation Year),
BSC LL2F Economics and Politics,
BSC LL3F Economics and Politics (Including Year Abroad),
BSC LL4F Economics and Politics (Including Placement Year),
BSC LG01 Economics with Data Science,
BSC LG02 Economics with Data Science (Including Year Abroad),
BSC LG03 Economics with Data Science (Including Placement Year),
BSC LG04 Economics with Data Science (Including Foundation Year),
BA C841 Economics with Psychology,
BA C851 Economics with Psychology (Including Year Abroad),
BA C861 Economics with Psychology (Including Placement Year),
BSC C148 Economics with Psychology,
BSC C149 Economics with Psychology (Including Foundation Year),
BSC C158 Economics with Psychology (Including Year Abroad),
BSC C168 Economics with Psychology (Including Placement Year)

Module description

This module introduces students to the methods of quantitative economics, i.e. to how data are used in economics. Beginning from an elementary level (assuming no background in statistics), the course shows how economic data can be described and analysed.


The elements of probability and random variables are introduced in the context of economic applications. The probability theory enables an introduction to elementary statistical inference: parameter estimation, confidence intervals and hypothesis tests. With these foundations, students are then introduced to the linear regression model that forms a starting point for econometrics. Throughout the course the emphasis is on the practical application of economic analysis from an empirical perspective.

Module aims

The aim of this module is:



  • To enhance students' knowledge and conceptual understanding of the treatment of data in economics.

Module learning outcomes

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



  1. Be aware of the main sources of economic data; know how to construct and interpret graphs of the data; know how to construct summary statistics.

  2. Have acquired a knowledge of the statistical methods needed for the analysis of economic issues.

  3. Have learned how to interpret the estimates of simple economic models and to conduct tests of hypotheses about the model's parameters.


Skills for your Professional Life (Transferable Skills)


The module provides the students with a wide set of tools which will prove to be particularly relevant during their working careers.



  1. Their ability to read, understand and properly manipulate data will be strongly enhanced, from both a theoretical and empirical point of view.

  2. Students are introduced to the knowledge of widely used statistical computational packages and plenty of examples from real datasets will reinforce student's control of the most important statistical techniques.

Module information

First year students with a background in mathematics may substitute EC114 for the more advanced modules MA114 and MA108 offered by the department of Mathematical Sciences with permission from the department.

Learning and teaching methods

The module will be delivered via:

  • Two lectures per week.
  • One class per week.
  • Support class.

Feedback for this module will occur through class meetings where we will go over the answers to problem sets and where you will be able to ask questions about your own method of solution; answers that will be posted on the website for the module that will give you written guidance on the appropriate method to approach the problems, assignments, and tests; and office hours where any additional questions can be addressed. You should be sure that you use these methods to understand how to improve your own performance. For modules including a term paper, the term paper will be returned with individualised feedback that addresses what the marking criteria are and how you could improve your own work.

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   Autumn Midterm Test  24/11/2023  50% 
Coursework   Spring Assignment    50% 
Exam  Main exam: In-Person, Open Book, 180 minutes during Summer (Main Period) 
Exam  Reassessment Main exam: In-Person, Open Book, 180 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
Mr Shunsuke Tsuda, email: shunsuke.tsuda@essex.ac.uk.
Dr David Zentler-Munro, email: david.zentler-munro@essex.ac.uk.
Lectures: Dr Shunsuke Tsuda (AU) and Dr David Zentler-Munro (SP) / Classes: Various teachers
For further information, please send an email to ueco@essex.ac.uk

 

Availability
Yes
Yes
No

External examiner

Dr Giancarlo Ianulardo
University of Exeter Business School
Lecturer in Economics
Resources
Available via Moodle
Of 118 hours, 116 (98.3%) hours available to students:
0 hours not recorded due to service coverage or fault;
2 hours not recorded due to opt-out by lecturer(s), module, or event type.

 

Further information
Economics

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