INTRODUCTORY ECONOMETRICS - 2022/3
Module code: ECO2047
In light of the Covid-19 pandemic the University has revised its courses to incorporate the ‘Hybrid Learning Experience’ in a departure from previous academic years and previously published information. The University has changed the delivery (and in some cases the content) of its programmes. Further information on the general principles of hybrid learning can be found at: Hybrid learning experience | University of Surrey.
We have updated key module information regarding the pattern of assessment and overall student workload to inform student module choices. We are currently working on bringing remaining published information up to date to reflect current practice in time for the start of the academic year 2021/22.
This means that some information within the programme and module catalogue will be subject to change. Current students are invited to contact their Programme Leader or Academic Hive with any questions relating to the information available.
This module will provide students with the basic mechanics, both in terms of the theoretical background and the practical skills, for carrying out applied econometrics. Throughout there is an emphasis on understanding the assumptions of the methods so as gain an appreciation of what such techniques can and cannot deliver. An important part of the course is the training in the use of the econometrics software package, Stata.
MARTELLOSIO Federico (Economics)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 5
JACs code: L140
Module cap (Maximum number of students): N/A
Overall student workload
Workshop Hours: 16
Independent Learning Hours: 74
Guided Learning: 33
Captured Content: 27
Prerequisites / Co-requisites
Indicative content includes:
- The relationship between economic and econometric models
- Simple OLS regressions
- Multiple OLS regression
- Properties of OLS regression
- Dummy variables
- Model specification
- Introduction to time series data
|Assessment type||Unit of assessment||Weighting|
|Online Scheduled Summative Class Test||ONE MULTIPLE CHOICE TEST (45 MINUTES)||15|
|Online Scheduled Summative Class Test||ONE COMPUTER LAB TEST (45 MINUTES)||15|
|Examination Online||EXAMINATION (120 MINUTES)||70|
The assessment strategy is designed to provide students with the opportunity to demonstrate:
Their understanding of econometric modelling, and their ability to use the econometric computer package Stata.
Thus, the summative assessment for this module consists of:
- One Multiple Choice test in week 7. This will provide students with an assessment of their understanding of basic concepts studied in weeks 1-6. Worth 15% of the final mark.
- One computer lab test in week 11. This will test students’ ability to produce and interpret econometric results using the econometric package STATA. Worth 15% of the final mark.
- 2 hour examination. Students are required to solve exercises and answer theoretical questions. Worth 70% of the final mark.
Formative assessment and feedback
Students receive verbal feedback during both lectures and tutorials. During lectures, smaller questions and exercises are discussed, while the problems discussed in tutorials are more substantial. After the test, students receive verbal and written feedback in the form of correct answers and a discussion of common mistakes.
- introduce students to basic econometric techniques
- provide students with the tools necessary for the correct interpretation of empirical work in economics
- train students to use the econometrics software package, Stata.
|1||Be able to formulate economic hypotheses as statistical tests and be able to carry out these tests and interpret their results||KC|
|2||Be able to show how regression analysis can be implemented using econometric software||KCP|
|3||Have gained experience in the analysis and use of empirical data in economics||KC|
|4||Have learnt how to turn an economic model into an econometric model||KC|
|5||Be able to provide an economic interpretation of parameters (e.g. in levels and elasticities)||KC|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Methods of Teaching / Learning
The learning and teaching strategy is designed to:
- Enhance skills in interpreting econometric results
- Train students to learn how to manipulate data and extract information from economic dataset by means of econometric software
The learning and teaching methods include:
- 2-hour lecture per week, x 11 weeks
- 1-hour class devoted to solving problems sets in a computer lab per week x 10 weeks
Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.
Upon accessing the reading list, please search for the module using the module code: ECO2047
Programmes this module appears in
|Business Economics BSc (Hons)||1||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
|Economics and Finance BSc (Hons)||1||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
|Economics BSc (Hons)||1||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
|Economics and Mathematics BSc (Hons)||1||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2022/3 academic year.