Econometrics II
Course content
Econometrics II is the final course in the compulsory BSc. course sequence in statistics and econometrics. The course Econometrics I focuses on linear regression and instrumental variables estimation of the linear regression model for cross‐sectional data. The current course discusses dependent observations and gives a detailed account of the econometric analysis of time series data. Econometrics II also goes into more detail with the estimation principles and the likelihood analysis, and it presents the generalized method of moments. Concepts such as stationarity, unit roots, cointegration and error correction, and autoregressive conditional heteroskedasticity (ARCH) are introduced. As an integral part of the course, students are introduced to statistical tools for analysing time series data and students will learn how to carry out, present, and discuss an empirical analysis based on economic time series on their own.
The outline of the course is the following:
 The linear regression model for time series data.
 Dynamic models for stationary time series.
 Unit root testing.
 Dynamic models for time series with unit roots. Cointegration and error correction.
 Models with timevarying conditional volatility.
 Generalized method of moments.
BSc programme in Economics  mandatory
After completing the course, the student should be able to demonstrate the following:
Knowledge:
 Give an account for the important differences between (independent) crosssectional data, analyzed in detail in Econometrics I, and time series data.
 Give a precise definition and interpretation of the concept of stationarity of time series data, and precisely describe the conditions under which the results from the linear regression analysis for crosssectional data can be used also on time series data.
 Give an account for the motivation and intuition for different principles for estimation and inference – specifically the method of ordinary least squares (OLS), method of moments (MM), maximum likelihood (ML), and generalizes method of moments (GMM) – and discuss relative advantages and drawbacks.
 Give an account for the sufficient conditions for consistent estimation and valid inference in the statistical model.
 Give a precise definition of the concept of unit roots, explain the consequences of unit roots in economic time series data, and interpret statistical models for stationary and nonstationary time series.
 Give a precise definition and interpretation of the concepts cointegration and error correction, and give an account of statistical models based on cointegration and error correction.
 Give a precise definition and interpretation of the concept of autoregressive conditional heteroskedasticity (ARCH), and give an account of 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 (MM) and maximum likelihood (ML). 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 and error correction 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 research papers containing applied econometric time series analyses.
The course is based on a combination of lectures (4 hours per
week) and exercises (2 hours per week). Activities to challenge and
activate students, such as Socrative quizzes and peerdiscussions,
are an important part of the lectures. Students are required to
prepare before lectures by reading, watching online videos, and
completing online quizzes. Finally, peer feedback is used to
provide detailed feedback on the assignments.
During the semester there are five written assignments covering
each of the major topics in the course. After handing in each
assignment students give peer feedback on each other’s assignments
through the peergrade.io platform.
Marno Verbeek: A Guide to Modern Econometrics, 4th Ed., Wiley. ISBN 9781119951674.
 Chapter 13 (cursory reading) p. 193 (93*).
 Section 4.14.5 (cursory reading) 94112 (18*).
 Section 4.64.11: p. 112136 (25).
 Chapter 56 p. 137205 (69).
 Section 7.1.17.1.6 p. 206217 (12).
 Section 7.3 p. 231238 (8).
 Chapter 8 p. 278337 (59).
 Section 9.19.3 p. 338350 (13).
 Section 9.49.7 (cursory reading) p. 350371 (22*)
Lecture notes:
1. Introduction to Time Series (13).
2. Linear Regression with Time Series Data (22).
3. Introduction to Vector and Matrix Differentiation (cursory reading) (6*).
4. Dynamic Models for Stationary Time Series (28).
5. NonStationary Time Series and Unit Root Testing (21).
6. Cointegration and Common Trends (31).
7. Modeling Volatility in Financial Time Series: An introduction to ARCH (16).
8. Generalized Method of Moments Estimation (31).
The course requires knowledge equivalent to that achieved in 'Probability Theory and Statistics' and Econometrics I.
Schedule:
2x2 hours of lecturing and 2 hours of excercises per week for 14
weeks
Timetable and venue:
To see the time and location of lectures and exercise classes
please press the link/links under "Se skema" (See
schedule) at the right side of this page (16E means Autumn 2016,
F17 means Spring 2017). The lectures is shown in each link.
You can find the similar information partly in English at
https://skema.ku.dk/ku1617/uk/module.htm
Select Department: “2200Økonomisk Institut” (and wait for
respond)
Select Module:: “2200E16; [Name of course]” or “2200F17; [Name
of course]”
Select Report Type: List
Select Period: “Efterår/Autumn – Weeks 303” or “Forår/Spring –
Week 429”
Press: “ View Timetable”
Please be aware regarding exercise classes:
 The schedule of the exercise classes is only a preplanned
schedule and can be changed until just before the teaching begins
without the participants accept. If this happens it will be
informed in KUnet or can be seen in the app myUCPH and at the above
link.
 If too many students have wished a specific class, students will
be registered randomly at another class.
 It is not possible to change class after the second registration
period has expired.
 If there is not enough registered students or available teachers
the exercise classes may be jointed.
 The student is not allowed to participate in an exercise class
not registered, because the room has only seats for the amount of
registered student.
 The teacher of the exercise class cannot correct assignments from
other students than the registered students in the exercise class.
 That all exercise classes will be taught in
English.
for enrolled students. More information about registration, schedule, rules, courses etc. can be found at the student intranet for courses (MAEnglish) and student intranet for courses (BA Danish).
Registration and information for prospective foreign speaking students not enrolled at the University of Copenhagen please find more information at Study Economics.
For enkelfagsstuderende sker tilmelding via Åbent Universitet og Merit.
 ECTS
 7,5 ECTS
 Type of assessment

Portfolio, 7 daysThe final exam is a written assignment consisting of four parts. The first three parts are based on three of the assignments worked with during the semester. Students can use the peer feedback they receive during the semester to improve these assignments for the final exam. The forth part of the exam is a new assignment.
The written exam can be handed in individually or by groups of maximum three students. The exam is given in English and must be answered in English. The final exam must be uploaded to the Digital Exam portal in one file.  Aid
 All aids allowed
 Marking scale
 7point grading scale
 Censorship form
 No external censorship
Criteria for exam assessment
Students are assessed on the extent to which they master the learning outcome for the course.
To receive the top grade, the student must be able to demonstrate in an excellent manner that he or she has acquired and can make use of the knowledge, skills and competencies listed in the learning outcomes.
Single subject courses (day)
 Category
 Hours
 Lectures
 56
 Class Exercises
 28
 Preparation
 102
 Exam
 20
 English
 206
Kursusinformation
 Language
 English
 Course number
 AØKA08007U
 ECTS
 7,5 ECTS
 Programme level
 Bachelor
 Duration

1 semester
 Price
 Schedulegroup

Teaching:
Autumn: Week 3650
Spring: Uge 620
Timeschedule: See "Remarks"
Exam and resits: See "Exam"  Studyboard
 Department of Economics, Study Council
 Department of Economics
Course responsibles
 Rasmus Søndergaard Pedersen
(37475724267657170306d7730666d)
Spring  Morten Nyboe Tabor
(1870727577687131717c6572683177646572754368667271316e7831676e)
Autumn
Teacher
Lectures: See ‘Course responsibles’
Autumn 2016:
Teachers of exercise classes:
Ex. Class 1: Cancelled
Ex. Class 2: Martin Vasilev Stoyanov
Ex. Class 3: Joachim Vilhelm Koch
Ex. Class 4: Dan Nolsøe Olsen
Ex. Class 5: Martin Vasilev Stoyanov
Ex. Class 6: Sebastian Schäber
Ex. Class 7: Dan Nolsøe Olsen
Ex. Class 8: Cancelled
Ex. Class 9: Cancelled
Ex. Class 10: Sebastian Schäber
Spring 2017:
Ex. Class 1: Dan Nolsøe Olsen
Ex. Class 2: Sebastian Schäber
Ex. Class 3: Sebastian Schäber
The schedule of the estimated preplanned exercise classes can be
changed up to the start of the semester.
All classes will be taught in English.
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