# Econometrics II (p)

### Course content

Econometrics II gives a detailed account of principles for estimation and inference based on the likelihood function and based on generalized method of moments estimation with application to cross-sectional data and time series data.

In addition, Econometrics II presents the econometric analysis of time series data, applying the concepts of non-stationarity, unit roots, co-integration, vector autoregressions, and autoregressive conditional heteroskedasticity (ARCH).

As an integral part of the course, students will learn how to carry out, present, and discuss an empirical analysis on their own.

Education

MSc programme in Economics - mandatory course, if not passed before.

Bacheloruddannelsen i økonomi – Prioriteret valgfag på 3. år (angivet med et p).

The Danish BSc programme in Economics - prioritized elective at the 3rd year (symbolized by ‘p’).

The course is open to:

• Exchange and Guest students from abroad
• Credit students from Danish Universities
• Open University students
Learning outcome

After completing the course the student is expected to be able to:

Knowledge:

• Account for the different principles for estimation and inference – specifically the method of maximum likelihood, the (generalized) method of moments – and discuss relative advantages and drawbacks.
• Give a precise definition and interpretation of the concept of stationarity of time series data.
• Describe the conditions for consistent estimation and valid inference in a statistical model.
• Give a precise definition of the concept of unit roots.
• Explain the consequences of unit roots in economic time series data.
• Interpret statistical models for stationary and non-stationary time series.
• Give a precise definition and interpretation of the concepts cointegration and error correction
• Account for statistical models based on cointegration and error correction.
• Give a precise definition and interpretation of the concept of autoregressive conditional heteroskedasticity (ARCH).
• Account for statistical models with ARCH in financial time series.

Skills:

• Identify the characteristic properties of a given data set of economic time series and suggest and construct relevant statistical models.
• Derive estimators of the statistical model’s parameters using the principles of method of moments and maximum likelihood. Estimate and interpret the parameters.
• Construct misspecification tests and analyze to what extent a statistical model is congruent with the data.
• Construct statistical tests for unit roots in economic time series.
• Construct statistical tests for cointegration in economic time series.
• Formulate economic questions as hypotheses on the parameters of the statistical model and test these hypotheses.
• Use statistical and econometric software to carry out an empirical analysis.
• Present a statistical model and empirical results in a clear and concise way. This includes using statistic and econometric terms in a correct way, giving statistically sound and economically relevant interpretations of statistical results, and presenting results in a way so that they can be reproduced by others.

Competencies:

• Choose the relevant statistical model given the characteristics of a given data set of economic time series and apply the statistical tools to carry out, present, and discuss an empirical analysis and test specific economic hypotheses.
• Read and critically evaluate research papers containing applied econometric time series analyses.

Lectures and exercise classes.

Activities to challenge and activate students, such as in quizzes and peer-discussions, are used in lectures and as preparation. The exercise classes are both theoretical and applied with written assignment covering important topics in the course. If possible some of the exercise classes will be organized as workshops with all students together.

Marno Verbeek: A Guide to Modern Econometrics, 5th Ed., Wiley. ISBN 978-1-119-472117.

Lecture notes.

The course requires knowledge equivalent to that achieved in "Probability Theory and Statistics" and "Econometrics I" at the Bachelor of Economics, University of Copenhagen.

Schedule:

Autumn:
2x2 hour lectures each week from week 36 to 50 (except week 42).
2 hours of workshops/exercise classes from week 36/37 to 50 (except week 42).

Spring:
2x2 hour lectures each week from week 6 to 20 (except holidays).
2 hours of workshops/exercise classes each week from week 6/7 to 20 (except holidays).
ital Exam portal, Absalon, the personal schema at KUnet and myUCPH app etc.

Written
Oral
Individual
Collective
Continuous feedback during the course of the semester
Peer feedback (Students give each other feedback)

Students will receive written feedback at the assignments through peerfeedback. Students will rate the feedback received.

The lecturer will, if deemed relevant, provide oral collective feedback in lectures based on a sample of the assignments. Continuous feedback is available from online review quizzes in the lectures and from teaching assistants in exercise classes.

Office hours: Time and place will be informed by the lecturer in Absalon.

ECTS
7,5 ECTS
Type of assessment
Portfolio, 48 hours
Type of assessment details
The exam is a written assignment consisting of two parts:
• Part 1: The first part is based on two of the mandatory assignments worked on during the course. The student can use the peer feedback received during the course to improve these assignments. The repeat assignments are chosen at random and reveals with the release of the exam.
• Part 2: The second part is a new assignment given in English. It takes approximately 24 hours to answer the new assignment.

In the assessment part one is weighted approximately 2/3 of the grade and part two is weighted approximately 1/3. The overall grade depends on the overall impression of the answer.

Please be aware that:
• The new assignment can be written individually or by groups of maximum three students.
• The plagiarism rules and the rules for co-written assignments must be complied.
• All parts must be answered in English
• All parts must be uploaded to Digital Exam in one file.
Exam registration requirements

To qualify for the exam the student must no later than the given deadlines during the course:

• Hand in a minimum of 3 out of 4 mandatory assignments.
• Provide useful written peer feedback based on specific criteria for a minimum of 3 out of the 4 assignments to two other students.

• The teaching assistant and/or lecturer control the assignments and the feedback.
• The assignments can be written individually or by groups of maximum three students.
• The peer feedback must be written individually.
• The plagiarism rules and the rules for co-written assignments must be complied.
• The assignments and the peer feedback must be written in English.
• The mandatory assignments and the peer feedback are part of a portfolio exam. See “Type of assessment”.
Aid

All aids are allowed for the written exams.

Use of AI tools is permitted. You must explain how you have used the tools. When text is solely or mainly generated by an AI tool, the tool used must be quoted as a source.

For further information about allowed aids for the re-examination, please go to the section "Re-exam".

Marking scale
Censorship form
No external censorship
for the written exam.
The oral re-examination may be with external assessment.
Exam period

Exam information:

More information available in Digital Exam from the middle of the semester. In special cases, the exam can change to another day and/or time than announced.

More information about examination, rules, aids etc. at Master(UK), Master(DK) and Bachelor(DK).

Re-exam

The reexam is a 20 min. oral exam with 20 min. preparation.

All written aids allowed during the preparation time. Notes made during the preparation allowed at the examination.

The questions cover the entire curriculum and are based on the written mandatory assignments.

Reexam info:

Day, time and place: Digital Exam in Februar/August

##### Criteria for exam assessment

Students are assessed on the extent to which they master the learning outcome for the course.

In order to obtain the top grade “12”, the student must with no or only a few minor weaknesses be able to demonstrate an excellent performance displaying a high level of command of all aspects of the relevant material and can make use of the knowledge, skills and competencies listed in the learning outcomes.

In order to obtain the passing grade “02”, the student must in a satisfactory way be able to demonstrate a minimal acceptable level of  the knowledge, skills and competencies listed in the learning outcomes.

Single subject courses (day)

• Category
• Hours
• Lectures
• 56
• Class Instruction
• 28
• Preparation
• 74
• Exam
• 48
• English
• 206

### Kursusinformation

Language
English
Course number
AØKA08007U
ECTS
7,5 ECTS
Programme level
Full Degree Master
Bachelor
Duration

1 semester

Placement
Autumn And Spring
- Go to 'Signup' for information about registration and enrollment.
Price

Information about admission and tuition fee:  Master and Exchange Programme, credit students and guest students (Open University)

Schedulegroup
and venue:
- For teaching: Go to 'Remarks'.
- For exam and re-sits: Go to 'Exam'.
Studyboard
Department of Economics, Study Council
##### Contracting department
• Department of Economics
##### Contracting faculty
• Faculty of Social Sciences
##### Course Coordinator
• Rasmus Søndergaard Pedersen   (3-7576734368667271316e7831676e)
Saved on the 30-04-2024

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