Econometrics (pre-Master's)
Course infoSchedule
Course moduleMAN-BPRA203PM
Credits (ECTS)6
Language of instructionEnglish
Offered byRadboud University; Nijmegen School of Management; Bachelor Economics and Business Economics;
PreviousNext 1
drs. L.J.P. Buijs
Other course modules lecturer
B. Hiepler, MSc
Other course modules lecturer
dr. O. Kyrychenko
Other course modules lecturer
dr. O. Kyrychenko
Other course modules lecturer
dr. O. Kyrychenko
Other course modules lecturer
Academic year2023
2  (06/11/2023 to 28/01/2024)
Starting block
Course mode
RemarksWorkgroup registration is via Brightspace
Registration using OSIRISYes
Course open to students from other facultiesYes
Waiting listNo
Placement procedure-

To teach students a variety of techniques: regression analysis with cross sectional data, regression analysis with time series data, granger causality and analysis of panel data. Students must understand these concepts, analyze and interpret computer results and must be able to work with the program R (including R-studio) to attain these results. Students have to write reports on their findings.

More specifically; at the end of the course, students will be able to: 

1.       Use various techniques of regression analysis with cross sectional data, time series analysis and panel data  
2       Interpret output empirical outcomes of the various techniques [cross sectional data, time series data and panel data]             
3      Have knowledge of various techniques  and show that you are able to apply them in different situations 

4.     Make a clear choice between the different techniques
In week 1 during the lecture, Mr. Buijs will give an overview of the course and Mr. Veerhoek will give a very short introduction to R. Thereafter, Mr. Buijs will continue with regression analysis and will discuss a few mathematical issues. During the computer session of week 1 Mr. Veerhoek will explain R in more depth and teach the students how to work with data in R.
In the week 2 lecture, Mr. Veerhoek will explain how to conduct an ordinary least squares (OLS) regression analysis in six steps. In the computer instruction session, the students will start with more advanced data cleaning in R and then learn how to estimate and evaluate bivariate and multivariate analyses, such as correlation tests and OLS regression.  
In Week 3, Mr. Veerhoek explains dummy variables in an OLS regression and the application of interaction analysis. During the computer instruction sessions, the students work on an assignment in which these techniques are applied.
In the Week 4 and 5 of the course, Mr. Buijs will discuss regression models for time series analysis, based on data from several moments in time. During lectures, mar. Buijs will also pay attention to Granger causality.  During the computer instruction sessions, a time series assignment will be made.
In week 6 and 7 of the course, Mr. Kyrychenko focuses on the analysis of panel data. Mr. Kyrychenko will discuss different forms of panel data and the application of several techniques for panel analysis. During the computer instruction session, various panel datasets will be analyzed.

This course is accessible only for students in premaster's programmes and student who are following the the programme Law and Economics.

Presumed foreknowledge
Academic Skills, Mathematics and stat (BIN 119 A), alternatively knowledge of Statistics and Mathematics is highly recommended.
Test information
Written exam and multiple assignments. These assignments include two pass fail assignments (to make sure students are able to work with the program R (or R - studio). The other assignments (dummies and interaction, time series and panel data) will be graded and count for 40% of the total grade for the course. The exam will be count for the remaining 60% of the course.   
The assessment of the individual parts is described, in more detail, in the Course manual under the heading Assessment. Partial results from previous years stay valid, but strict criteria apply. Please contact the course coordinator.


Instructional modes
Type of instructional modeLecture

Preparation of meetings
Read the material described in the schedule of the course manual

Lectures are provided in each week. Before the exam, weblectures are released to help with your preparation.

Working group
Type of instructional modeLab course

Preparation of meetings
Attend the lectures (and prepare for those)

Contribution to group work
Here you are required to work in groups on econometric assignments, by using the program R.

R computer - lab session.

Test weight1
Test typeDigital exam with SOWISO
OpportunitiesBlock 2, Block 3

Theoretic and pratical apllication within the econometric framework is part of the exam. Not included in the examination are R skills.

The grade in OSIRUS consists of the exam and the assignments.