Estimation and Inference in Econometrics
Postgraduate: Level 7
Thursday 03 October 2019
Saturday 14 December 2019
09 October 2019
Requisites for this module
MSC L11024 Applied Economics and Data Analysis,
MSC L100KE Economics,
MSC L10112 Economics and Econometrics,
MSC L101EK Economics and Econometrics,
MSC L101KE Economics and Econometrics,
MSC L101UH Economics and Econometrics,
MSC L11412 Financial Econometrics,
MSC L10212 Financial Economics and Econometrics
This module begins with a brief review of the mathematical and statistical prerequisites needed for econometrics illustrated using ordinary least squares methods in the classical linear regression model. It This module begins with a brief review of the mathematical and statistical prerequisites needed for econometrics illustrated using ordinary least squares methods in the classical linear regression model. It then proceeds to cover the use of asymptotic methods in econometrics, classical hypothesis tests, generalized least squares, instrumental variables and the generalized method of moments, and maximum likelihood.
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.
This module is a first year graduate level econometrics module. It aims to provide students necessary technical fundamentals in econometrics that would be important for their research in the future. The students will learn about OLS, WLS, GLS, GMM, and MLE estimation techniques and the rigorous properties of those estimators by using linear algebra.
Upon successful completion of this module students will possess a thorough understanding of the principles of estimation and inference in econometrics. In addition, students should be able to justify, or criticise where appropriate, the use of particular econometric methods of estimation and inference in a variety of situations. In completing the problem-sets, students will demonstrate their problem-solving, analytical, and deductive skills.
Employability skills include: Academic skills: Literacy, numeracy, problem-solving and ICT skills; Professional working skills: adaptability, flexibility, decision-making; External awareness: economic and business environment and policy; Personal development planning: Time management, self management, reflection and evaluation.
No additional information available.
One 2 hour lecture per week, weeks 2-11. One 1 hour class per week, weeks 3-11.
- Hayashi, Fumio. (c2000) Econometrics, Princeton, N.J.: Princeton University Press.
The above list is indicative of the essential reading for the course. The library makes provision for all reading list items, with digital provision where possible, and these resources are shared between students. Further reading can be obtained from this module's reading list.
Assessment items, weightings and deadlines
|Coursework / exam
||180 minutes during Summer (Main Period) (Main)
Module supervisor and teaching staff
Miss Neslihan Sakarya, email: firstname.lastname@example.org.
Dr Neslihan Sakarya
For further information, send a message to email@example.com
Dr Roberto Bonilla Trejos
The University of Newcastle-upon-Tyne
Available via Moodle
Of 44 hours, 32 (72.7%) hours available to students:
12 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).
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