Courses NonDegree Display 2022-2023

Course Description To PDF
Course title Econometric Methods I
Course code EBC2111
ECTS credits 6,5
Assessment Whole/Half Grades
Period
Period Start End Mon Tue Wed Thu Fri
5 17-4-2023 9-6-2023 L X X
Level Advanced
Coordinator Alain Hecq
For more information: a.hecq@maastrichtuniversity.nl
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.
Description
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, ...).
Literature
Greene, W. (2012), Econometric Analysis, 7th ed., Pearson.
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 Surfyourself 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.
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
Bachelor Business Analytics Year 3 Elective Course(s)
Bachelor Econometrics and Operations Research Year 2 Compulsory Course(s)
Bachelor Fiscal Economics Year 3 Elective Course(s)
Pre-master Economics Compulsory Course(s)
Pre-master Financial Economics Compulsory Course(s)
Transitional Regulations See prerequisites
SBE Exchange Bachelor Bachelor Exchange Courses
SBE Exchange Master Bachelor Exchange Courses
SBE Non Degree Courses Bachelor Courses