AF6045 - Advanced Econometrics

What will I learn on this module?

The focus of this module will be on advanced econometric techniques, building upon the foundations acquired in the level 5 econometrics module. This module will include selected topics in applied econometrics, with a focus on connecting theory with practical applications. The lectures will be supported by computer classes using secondary data to explore the various estimation techniques. The module will make use of econometrics software packages for the estimations of cross-sectional, panel and time-series models. By the end of the module students will demonstrate an in-depth understanding of modern econometrics, with practical application to both microeconomics and macroeconomics analysis. This will be useful to students interested in postgraduate study in economics as well as the many disciplines outside of economics that require quantitative analysis.



The topics covered in this module include:



Ordinary Least Squares Model

Generalized Least Squares and Maximum Likelihood Estimation

Hypotheses testing

Endogeneity in Linear Regression Models

Simultaneous Equations Estimation

Limited Dependent Variables

Time Series Models

Panel Data Models

How will I learn on this module?

You will be supported in this module by a comprehensive teaching and learning plan (TLP), which clearly specifies lectures and computer workshops as well as tutor-directed study and independent reading. The lectures and seminars will cover the theoretical aspects of econometrics alongside the computer workshops, which will demonstrate the practical aspects of advanced modern econometrics. Workshops will also be used to provide clarity or further discuss aspects of the lectures that you may have questions on. You will have the opportunity to interact with the teaching team and benefit from questions or discussions from other students in your class.



The topics in this module will have practical aspects using computer classes based on data from empirical studies published in top-tier journals. The use of both lectures and computer classes will give you an in-depth understanding of the different components of advanced econometrics that will be taught during lectures and these will provide the opportunity to critically evaluate the techniques learned. In the computer workshops, you will use econometrics software packages for estimations and analyses, and this will be preceded by introductory lectures on how to use econometrics software packages in model estimations.

How will I be supported academically on this module?

You will be supported in this module by an e-learning module site, which will provide materials for lectures, computer workshops and other relevant readings for your independent study. The teaching team will support you by delivering the content of the lectures, providing answers to your questions about the materials, and practical guidance/assistance during computer workshops. You will have access to the computer laboratory to practice at your own pace the various econometric techniques/methods that will be taught during lectures and workshops. There will be fixed schedules for office hours with the teaching team which will give you the opportunity to discuss or ask questions about this module. In addition, you can contact the lecturer via email outside the scheduled sessions should you have any queries about any aspects of the lectures or computer workshops.

What will I be expected to read on this module?

All modules at Northumbria include a range of reading materials that students are expected to engage with. The reading list for this module can be found at: http://readinglists.northumbria.ac.uk
(Reading List service online guide for academic staff this containing contact details for the Reading List team – http://library.northumbria.ac.uk/readinglists)

What will I be expected to achieve?

Knowledge & Understanding:

You will develop a sound knowledge of advanced econometric techniques and analysis (MLO1).

You will be able to comprehend empirical studies using econometric methods and critically analyse the results and the techniques adopted (MLO2).

You will be able to identify which econometric techniques are best suited to address specific research questions (MLO3)



Intellectual / Professional skills & abilities:

You will develop the ability to apply econometric techniques and methods to solving practical and real-world problems (MLO4).



Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):

Critically evaluated personal strengths and weaknesses and have demonstrated the ability to engage in reflective self-development (MLO5)

How will I be assessed?

Formative Assessment:

The formative assessment will comprise of discussion questions and problem sets which will be distributed to you in advance. There will be individual and group discussion of the answers to these problem sets and questions during the workshops. This will encourage your active participation in the learning process throughout the semester. The e-Learning portal will be used to permanently host these tasks after release to ensure that you can access the information required at all times. You will be provided with the opportunity to get one to one feedback on the summative assignment.





Summative Assessment:



The module is assessed by:



A 1,500 word group report and a 500- word individual reflective log (40% weight). In the report students will be required to put into practice some of the econometric techniques acquired from lectures and computer workshops. The individual reflective log will include a self-assessment of strengths and weaknesses across a range of interpersonal and intrapersonal skills as well as a peer assessment of other group members using a standardised peer assessment format. The topic will be assigned to students in Week 2, and it will be due for submission in Week 10 (MLO1, MLO2, MLO3, MLO4, MLO5).

There will be an end of semester 2-hour examination (closed book) for this module (60% weight), where students will be required to answer four questions out of six. The examination will assess students’ understanding of econometric models and estimation techniques taught in lectures and computer workshops. (MLO1, MLO2, MLO4).

Pre-requisite(s)

None

Co-requisite(s)

None

Module abstract

Econometric analysis provides a solid approach for estimation in many quantitative-inclined disciplines. In recent years, modern econometrics has witnessed an improvement in estimation techniques and these techniques have been widely used in many empirical works, both economics and non-economics disciplines. Also, there has been an advancement in econometrics software packages that makes it possible to undertake complex econometric and statistical analyses. This module aims to develop and enhance your knowledge and ability to evaluate and carry out a wide range of econometric analysis. You will apply econometric theory and estimation techniques to investigate practical and real-world problems using data sets from articles published in top-tier journals. This module will equip you with the requisite knowledge and analytical skills required for a rigorous empirical analysis.

Course info

UCAS Code L110

Credits 20

Level of Study Undergraduate

Mode of Study 3 years full-time or 4 years with a placement (sandwich)/study abroad

Department Newcastle Business School

Location City Campus, Northumbria University

City Newcastle

Start September 2024 or September 2025

Fee Information

Module Information

All information is accurate at the time of sharing.

Full time Courses starting in 2023 are primarily delivered via on-campus face to face learning but may include elements of online learning. We continue to monitor government and local authority guidance in relation to Covid-19 and we are ready and able to flex accordingly to ensure the health and safety of our students and staff.

Contact time is subject to increase or decrease in line with additional restrictions imposed by the government or the University in the interest of maintaining the health and safety and wellbeing of students, staff, and visitors, potentially to a full online offer, should further restrictions be deemed necessary in future. Our online activity will be delivered through Blackboard Ultra, enabling collaboration, connection and engagement with materials and people.

 

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