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University of Exeter Business School

Applied Econometrics

Module titleApplied Econometrics
Module codeBEE2032
Academic year2023/4
Credits15
Module staff

Dr Jingya Zeng ()

Duration: Term123
Duration: Weeks

0

11

0

Number students taking module (anticipated)

60

Module description

The Applied Econometrics module is a practical course that aims to enhance students' empirical economic analysis skills. With the ever-growing volume of economic and financial data and its increasing use to inform decision-making, there is a pressing need for economists in the private and public sectors, as well as in academia, to perform empirical analysis. This course provides students with hands-on training in applying the most widely used econometric analysis techniques using a statistical analysis software and associated coding language. By doing so, students will be well-equipped to conduct empirical economic analysis in preparation for becoming full-fledged economists.

Additional Information:

Employability

This module will equip students with practical and critical thinking empirical skills which are highly sought after in the labour market. They are especially important for students who want to work as economists in the private or public sector, or in any profession where data reports are used, and they are essential for students aspiring to pursue academic careers. The coding component of the course will also serve as a first or additional programming training for students interested in data science-related careers.

Internationalisation
The applications discussed in the module are based on examples and datasets from around the world.

Module aims - intentions of the module

 

This module aims to provide students with a high degree of understanding as well as extensive hands-on experience in implementing and analysing the most often used empirical analysis techniques in economics. The module will focus on data skills (organisation and manipulation of data, descriptive and explorative analysis), and applied econometrics (regression models for cross-sectional, panel and time series data). You will learn to apply those techniques using one of the main statistics software.

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

On successfully completing the module you will be able to...

  • 1. Demonstrate ability to understand the important features and properties of economic data, and perform the necessary operations to organise and manipulate the data.
  • 2. Apply appropriate quantitative techniques based on the research question and features of the data.
  • 3. Perform independent empirical analysis using a statistical software.

ILO: Discipline-specific skills

On successfully completing the module you will be able to...

  • 4. Show proficiency in using quantitative and data skills to apply knowledge from economics and econometrics theories to complete an empirical research work.

ILO: Personal and key skills

On successfully completing the module you will be able to...

  • 5. Demonstrate analytical and critical thinking.
  • 6. Demonstrate the ability to program within a statistical software.

Syllabus plan

• Introduction to Stata
• Exploratory Data Analysis
• Linear Regression Analysis
• Functional Form / Interaction Effects
• Missing Data
• Binary Dependent Variables
• Marginal Effects
• Panel Data
• Time Series

Learning activities and teaching methods (given in hours of study time)

Scheduled Learning and Teaching ActivitiesGuided independent studyPlacement / study abroad
321180

Details of learning activities and teaching methods

CategoryHours of study timeDescription
Schedule learning and teaching22 hoursLectures
Scheduled leaning and teaching10 hoursTutorials

Formative assessment

Form of assessmentSize of the assessment (eg length / duration)ILOs assessedFeedback method
In class discussion/exercisesWeeks 1 to 111-6Verbal/ELE

Summative assessment (% of credit)

CourseworkWritten examsPractical exams
20080

Details of summative assessment

Form of assessment% of creditSize of the assessment (eg length / duration)ILOs assessedFeedback method
Practical Exam803 hours1-6Discussion
Homework tasks 20Approx. 6 pages A41-6ELE/Turnitin
0

Details of re-assessment (where required by referral or deferral)

Original form of assessmentForm of re-assessmentILOs re-assessedTimescale for re-assessment
Practical ExamPractical Exam (80%) 1-6August Examination Period
Homework tasksHomework tasks (20%)1-6August Examination Period

Indicative learning resources - Basic reading

The module does not rely on a textbook. All relevant material will be presented in class and in the lecture notes. Additional reading may be given for certain topics.


- The theoretical content is covered in Jeffrey M. Wooldridge, Introductory Econometrics, 7th Edition (2020), Cengage.

- More practical content with examples and applications in Stata can be found here:

  • Cameron, A.C and Trivedi, P.K. (2022) Microeconometrics using Stata, 2nd revised edition, Stata Press.
  • Hill, R.C, Griffiths, W.E and Lim, G.C (2018) Principles of Econometrics, 5th edition, Wiley.
  • Adkins, L.C. and Hill, R.C. (2018) Using Stata for Principles of Econometrics, 5th edition, Wiley.

Indicative learning resources - Web based and electronic resources

UK Data Service (http://ukdataservice.ac.uk/ )

http://www.nber.org/data/

Indicative learning resources - Other resources

A Gentle Introduction to Stata by Alan C. Acock

Data Analysis Using Stata by Ulrich Kohler and Frauke Kreuter

Interpreting and Visualizing Regression Models Using Stata by Michael N. Mitchell

An Introduction to Stata Programming by Christopher F. Baum

Key words search

Applied Econometrics, Data Analysis, Applied Economics, Empirical Analysis

Credit value15
Module ECTS

7.5

Module pre-requisites

BEE2031 

Module co-requisites

BEE2031 or BEE2006

NQF level (module)

5

Available as distance learning?

No

Origin date

01/09/2014

Last revision date

10/03/2023