| CODE | ECN5223 | ||||||||||||||||
| TITLE | Advanced Econometrics | ||||||||||||||||
| UM LEVEL | 05 - Postgraduate Modular Diploma or Degree Course | ||||||||||||||||
| MQF LEVEL | 7 | ||||||||||||||||
| ECTS CREDITS | 10 | ||||||||||||||||
| DEPARTMENT | Economics | ||||||||||||||||
| DESCRIPTION | The study unit focuses on aspects of both theoretical and applied econometrics. It covers the following topics: core methods in econometrics, including ordinary least squares (OLS), maximum likelihood estimation (MLE) and the generalised method of moments (GMM); topics in time series econometrics, including vector autoregression (VAR) and the vector error correction model (VECM); models for cross sectional data, including binary and multinomial models; static and dynamic panel data models; as well as treatment evaluation methods and prediction with big data. It emphasises how assumptions of the classical linear regression model are violated and how they may be overcome. Study-unit Aims: Students of econometrics are often motivated by empirical applications. This module is designed with this in mind, but good use of econometrics requires that students learn enough econometric theory to understand its strengths and limitations. Against this background, the module has the following aims: - To introduce students to aspects of theoretical econometrics; - To expose students to econometric techniques used in empirical economics; - To enable students to read and criticise applied econometrics papers published in leading economics journals; and - To acquire the skills required to carry out empirical research. Learning Outcomes: 1. Knowledge & Understanding By the end of the study-unit the student will be able to: - Identify and employ the use of advanced panel data, time-series and microeconometric techniques within an economic setting; - Recognize when the use of these techniques is appropriate and know how to evaluate and interpret results obtained from such methods; - Provide a critique of the available applied research in the econometrics literature that explores the use of these methods. 2. Skills By the end of the study-unit the student will be able to: - Assess the theoretical relevance of econometric techniques; - Perform the econometric estimation routines using the various techniques illustrated within the study unit; and - Critically evaluate econometrics work published in leading academic journals. Main Text/s and any supplementary readings: Main Texts: - Cameron, A.C. and Trivedi, P.K. (2010) Microeconometrics: Methods and Applications, Cambrdige. - Verbeek, M. (2012) A Guide to Modern Econometrics, Wiley. - Hill, R.C., Griffiths, W.E. and Lim, G.C. (2019) Principles of Econometrics (5th ed.), Wiley-Blackwell. Supplementary Readings: - Angrist, J.D. and Pischke, J.S. (2009) Mostly Harmless Econometrics (4th ed.), Princeton University Press. - Enders, W. (2014) Applied Econometric Time Series (4th ed.), Wiley. |
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| ADDITIONAL NOTES | Pre-Requisite Study-Units: ECN2031, ECN2041 |
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| STUDY-UNIT TYPE | Lecture and Tutorial | ||||||||||||||||
| METHOD OF ASSESSMENT |
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| LECTURER/S | Daniel Gravino |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2023/4. It may be subject to change in subsequent years. |
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