Courses Bachelor Display 2022-2023
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Course title | Econometric Methods I | |||||||||||||||||||||||||||||||||||||||
Course code | EBC2111 | |||||||||||||||||||||||||||||||||||||||
ECTS credits | 6,5 | |||||||||||||||||||||||||||||||||||||||
Assessment | Whole/Half Grades | |||||||||||||||||||||||||||||||||||||||
Period |
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Level | Advanced | |||||||||||||||||||||||||||||||||||||||
Coordinator |
Alain Hecq For more information: a.hecq@maastrichtuniversity.nl |
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Language of instruction | English | |||||||||||||||||||||||||||||||||||||||
Goals |
Students will have a good knowledge of econometric methods. They will have the skills to apply these methods to a set of economic data.
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Description |
PLEASE NOTE THAT THE INFORMATION ABOUT THE TEACHING AND ASSESSMENT METHOD(S) USED IN THIS COURSE IS WITH RESERVATION. A RE-EMERGENCE OF THE CORONAVIRUS AND NEW COUNTERMEASURES BY THE DUTCH GOVERNMENT MIGHT FORCE COORDINATORS TO CHANGE THE TEACHING AND ASSESSMENT METHODS USED. THE MOST UP-TO-DATE INFORMATION ABOUT THE TEACHING/ASSESSMENT METHOD(S) WILL BE AVAILABLE IN THE COURSE SYLLABUS.
This course is part of the programme for second-year econometrics students. The challenge of econometrics is to answer the question, what everyday reality has to tell about economic theories. Here, everyday reality takes the form of numerical observations or 'data', while economic theories are translated into a formal statistical 'model' with corresponding hypotheses. In order to extract as much information as possible out of the former concerning the latter, an appeal is made to statistical induction. These are the 'econometric methods' that are the subject of this course. They comprise mainly the estimation of the model parameters, the testing of the model hypotheses, and making (conditional) predictions with the model. We will study the most frequently used statistical methods and techniques in the first place for the classical linear model, but we mainly focus of the matrix notations of usual linear estimators and test statistics (e.g., OLS, OLS, the t-tests, F-test). Those estimators will be implemented during the tutorial meetings using the software packages R and Eviews. Further some important assumptions will be relaxed and alternative estimators (GLS, SURE) will be investigated in the presence of autocorrelation and heteroskedasticity. This course also emphasize dynamic models and time series econometrics (ARMA, VAR, cointegration, unit root, VECM, ...). Applied works (R, Eviews) will be carried out during tutorial meetings. The course Econometrics Methods II in the programme for the third-year econometrics students, covers issues that we do not do in this course (IV, GMM, ML, ...). |
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Literature |
Greene, W. (2012), Econometric Analysis, 7th ed., Pearson.
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Prerequisites |
This course is in transition for the pre-master Human Decision Science.
The following rule applies to pre-master Human Decision Science students who started the programme prior to academic year 2022/23. TRANSITIONAL REGULATION (EBC2111): Students who did not pass the course EBC2111 can repeat it, or replace it with "(Business) Research Methods for Pre-master" (EBC2170). Use Ask SBE to register for education (deadline is February 26, 23:59). See the Transitional Regulations section in the Bachelor Education and Examination Regulations for more information. PREREQUISITES: A first course in econometrics (see, e.g. Empirical Econometrics). Exchange students should have advanced knowledge of: 1) Mathematical statistics, 2) probability theory, 3) matrix algebra, 4) introduction to quantitative methods with an emphasis to the linear model An advanced level of English. |
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Teaching methods (indicative; course manual is definitive) | PBL / Presentation / Lecture / Assignment / Groupwork | |||||||||||||||||||||||||||||||||||||||
Assessment methods (indicative; course manual is definitive) | Participation / Written Exam / Presentation | |||||||||||||||||||||||||||||||||||||||
Evaluation in previous academic year | For the complete evaluation of this course please click "here" | |||||||||||||||||||||||||||||||||||||||
This course belongs to the following programmes / specialisations |
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