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Course module: ECB2METRIE
ECB2METRIE
Econometrics
Course infoSchedule
Course codeECB2METRIE
ECTS Credits7.5
Category / Level2 (Bachelor Elaborating)
Course typeCourse
Language of instructionEnglish
Offered byFaculty of Law, Economics and Governance; Undergraduateschool REBO; Bachelor in Economics and Business Economics;
Contact persondr. T.W. Dulam
E-mailT.W.Dulam@uu.nl
Lecturers
Contactperson for the course
dr. T.W. Dulam
Feedback and availability
Other courses by this lecturer
Lecturer
dr. A.M. Salomons
Other courses by this lecturer
Teaching period
2  (11/11/2019 to 02/02/2020)
Teaching period in which the course begins
2
Time slotBC: See 'Help'
Study mode
Full-time
RemarkRequired.
Enrolment periodfrom 03/06/2019 up to and including 30/06/2019
Course application processOsiris
Enrolling through OSIRISYes
Enrolment open to students taking subsidiary coursesYes
Pre-enrolmentNo
Post-registrationYes
Post-registration openfrom 21/10/2019 up to and including 22/10/2019
Waiting listNo
Aims
Learning objectives
At the end of the course the student is able to:
•       Understand the linear (bivariate and multivariate) regression model, including the ordinary least squares estimator and its statistical properties, functional form and model misspecification, and testing hypotheses;
•       Specify, estimate, and interpret various cross-sectional and time-series regression models, and quantify the implications of an estimate for economic theory;
•       Translate simple economic theory into a statistical hypothesis, and test that hypothesis using regression analysis;
Assess the quality of the data used to address the empirical research question
Content
Does a lower lending rate lead to a change in consumption? Is it age or experience that affects the hourly wage? Economists specify, analyse and quantify relationships between economic variables. The course Econometrics is a follow-up on the first-year course Statistics and introduces econometric (estimation) techniques that are useful for understanding both scientific articles and policy documents. Emphasis will be on the linear regression model (estimation, functional form, model selection, misspecification, and various tests), which will be applied to analyse data sets. In addition, attention is paid to time-series models and models with a binary dependent variable. Students will individually empirically investigate an economic research question, resulting in a midterm report counting towards the course effort requirement.

Multidisciplinary aspects
The course has multidisciplinary applications of econometric techniques included in both lectures and tutorials. Examples are the study of illegal markets (criminology & economics), gender violence in India (sociology & economics), the impact of physical attractiveness on wages (non-classical economics), labour market discrimination (sociology & economics), and the impact of economic conditions on re-election probabilities (political science & economics).
Students can also choose to write their individual midterm report on a multidisciplinary topic, such as the lasting impact of slavery on economic development (history, geography & economics); the determinants of happiness (sociology, psychology & economics); the extent to which prison sentences deter criminal behaviour (criminology, psychology & economics), the effect of personnel management practices on sales (psychology & management). Topic availability varies: questions for the midterm report change year by year to avoid plagiarism.

Academic skills
This course focuses on the following academic skills:
Analytical skills
•        Being able to solve problems (identifying the problem, devising a path towards the solution, following this path, verifying the outcome) for more complex assignments
 
Communication skills
•        ​Being able to write a compact and instructed paper on a specific subject, both individually and in groups
•        Being able to accept and process feedback from others on a presentation or small assignment
 
Information processing
•        Knowledge of potential sources for literature and data and the skills to explore these independently for a small research project.
•        Being able to detect plagiarism and being able to avoid any kind of plagiarism.
•        Providing correct references in text in a small research project (APA style).
•        Providing a correct reference list for a small research project (APA style).
•        Being able to present data in a correct and useful manner in a small and instructed research project.
•        Being able to work with data software, such as Excel and Stata.
 
Academic research
•        Being able to design a proper problem definition within the scope and instruction of the course.
•        Being able to execute the instructed research design.
•        Being able to search and select (additional) sources for the research.
•        Being able to execute an instructed empirical research.
•        Being able to apply theoretical concepts in research.
•        Being able to use correct references (APA style).
•        Being able to draw clear and correct conclusions.
 
Social responsibility
•        Being able to work effectively in teams for a specific project with limited intervention or instruction. 
 
Format
Lectures, tutorials, project groups. 

Assessment method
60 % of the final grade: Basic material Econometrics: Formative assessment during the tutorials, which is not included in the grade. A summative individual exam in week 9 of the course. The exam consists of theory questions. Multiple choice questions make up a maximum of 25% of this examination.
40 % of the final grade: Quality of an Empirical project paper. In the first week, students form small project teams. Registration in a project group is done during the first tutorial: participation in the first tutorial is therefore obligatory. Formative assessment of the project during the meetings with the lecturer, and feedback on the draft paper in week 4 of the course. 

Further information on assessment methods, academic skills, deadlines and procedures when having failed the exam(s) can be found on the course website and in the course manual. 

Effort requirements
•         Participation in at least 5 out of 8 tutorials, including the first tutorial;
•         Participation in all project group meetings;
•         Handing in a project report draft of a satisfactory level in week 4 of the course (see Blackboard and the course manual for a description of the requirements). 

Course repeaters
Students who have failed this course in the previous academic year (either by failing the exams or by not having disenrolled within 2 weeks after commencement of the course) will take part in a repeater’s course, which consists of following the lectures and tutorials optionally.
The assessment method for repeaters is as follows:
•         Repeaters do not write a project paper: their grade consists of the final exam (100%).
•         There is no effort requirement.
•         The grade conditions for the retake apply equally to repeaters.

Honours component
Honours students write a midterm paper in small groups on a more challenging dataset. They additionally have the option of defining their own research question.
 
Courses that build on Econometrics
Labour economics (ECB3ARBE), Bachelor Thesis (ECB3OKVECO)

In case online access is required for this course and you are not in the position to buy the access code, you are advised to contact the course coordinator for an alternative solution. Please note that access codes are not re-usable meaning that codes from second hand books do not work, as well as access codes from books with a different ISBN number. Separate or spare codes are usually not available.
Competencies
-
Entry requirements
Prerequisite knowledge
Students are expected to have knowledge of
Statistics (ECB1STAT), Mathematics (ECB1WIS)
Required materials
Handouts
Lecture slides.
Study guide
Course manual.
Recommended materials
Book
Studenmund, A.H. (2017). Using Econometrics: A Practical Guide, 7th edition. Pearson Publishing. ISBN 10: 1-292-15409-8; ISBN 13: 978-1-292-15409-1
Instructional formats
Lecture

Project group

Tutorial

Tests
Final exam
Test weight60
Minimum grade1

Project
Test weight40
Minimum grade1

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