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Applied Econometrics

Module description

Summary:

The Applied Econometrics module is a practical course that aims to enhance your 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 you 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, you will be well-equipped to conduct empirical economic analysis in preparation for becoming full-fledged economists.

Employability

This module will equip you with practical and critical thinking empirical skills which are highly sought after in the labour market. They are especially important for those 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 you 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)

Details of learning activities and teaching methods

Formative assessment

Summative assessment (% of credit)

Details of summative assessment

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

Re-assessment notes

Deferral – if you have been deferred for any assessment you will be expected to submit the relevant assessment. The mark given for a re-assessment taken as a result of deferral will not be capped and will be treated as it would be if it were your first attempt at the assessment.

Referral – if you have failed the module overall (i.e. a final overall module mark of less than 40%) you will be expected to submit the relevant assessment. The mark given for a re-assessment taken as a result of referral will be capped at 40%

Indicative learning resources - Basic reading

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

Web-based and electronic resources:

• UK Data Service ( http://ukdataservice.ac.uk/ )
• http://www.nber.org/data/

Key words search

Applied Econometrics, Data Analysis, Applied Economics, Empirical Analysis