Econometrics

Course goals

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 (OLS) 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 and explain the implications of such estimates for economic theory;
• Translate simple economic theory into a statistical hypothesis, and test that hypothesis using regression analysis;
• Interpret various empirical research results both econometrically and economically, and evaluate the research design used;
• Understand the challenges of identifying causal effects.

Content

This course cannot be combined with ECB3METWIS.

Do economic conditions affect election outcomes? What is the monetary return to education? Do better-looking workers earn higher wages? Economists specify, analyse and quantify relationships between economic variables. The course in Econometrics is a follow-up on the first-year course on Statistics and introduces econometric (estimation) techniques that are useful for economic analysis and for understanding scientific articles, economic policy documents, as well as data analysis performed by businesses. Emphasis will be on the linear regression model (estimation, functional form, model selection, misspecification, and various tests) These will also be applied to analyse data sets. In addition, attention is paid to time-series models and models with a binary dependent variable.

Real world perspective
The course pays attention to the  multidisciplinary application of econometric techniques. This is done in both the lectures and the tutorials. Examples are the study of illegal markets (criminology, psychology & economics), gender violence in India (sociology & economics), the impact of physical attractiveness on wages (non-classical economics), performance pay in baseball (sports science & economics), inequalities in healthcare use between migrants and non-migrants (economics & health sciences), labour market discrimination (sociology & economics), and the impact of economic conditions on re-election probabilities (political science & economics). Tutorial exercises use a wide range of real-world datasets and research questions, which students learn to answer step-by-step using empirical analysis.

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) using more complex assignments. 

 
Information processing

• Being able to work with data software, such as R.
• Being able to correctly interpret empirical research results.

 
Academic research

• Being able to execute an instructed empirical research.
• Being able to apply theoretical concepts in empirical research.
• Being able to draw clear and correct conclusions from empirical findings.

Academic reasoning

• Thinking conceptually, thinking in terms of theory.
• Asking critical questions, having a curiosity-driven and critical attitude.

Assessment method
50 % of the final grade is based on the score on the Midterm exam in week 5 of the course.
50 % of the final grade is based on the score on the Endterm exam in week 9 of the course.
Both exams consist of theory and applied econometric questions, and multiple-choice questions make up a maximum of 25% of the total examination. There is also formative assessment during the tutorials, which is not part of the grade.

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
- Attendance in at least 5 out of 7 tutorials
- Assignment completed during tutorial

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. Repeaters are not enrolled in tutorials.
The assessment method for repeaters is as follows:
•         The grade consists of 50% of the midterm and 50% of the endterm
•         There is no effort requirement.
•         The grade conditions for the retake apply equally to repeaters.

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. Separate or spare codes are usually not available.