Information About the Course
The course gives an introduction to time-series econometrics. You will learn how to estimate long-run multipliers of economic variables, how to test relevant economic hypotheses, how to use econometric models to forecast future developments in economic variables, and how to model time-varying risk on financial assets.
Main Learning Outcome
After completing the course, you should be able to:
Identify the characteristic properties of a given data set, suggest and construct relevant statistical models, analyze to what extent a statistical model is congruent with the data, estimate and interpret the parameters of the model, formulate economic questions as hypotheses on the parameters of the model, and test these hypotheses.
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.
Topic-specific learning outcomes are specified for each of the five topics.
Pedagogical Principles
We strongly believe that you learn by working actively with the course content while receiving continuous feedback on your learning. This belief is based on modern learning theory. On that basis, the main pedagogical goals of the course are that you work actively with the course materials inside and outside of the classroom and that you continuously receive more and better feedback in various forms. To achieve these goals, we have used recent research on effective teaching to structure the course.
Through the use of online videos, quizzes, tutorials and written solutions for exercises, and the discussion forum you can work with the course content at your own pace and time. That gives you autonomy over your learning experience, but it also requires that you become self-directed learners. We encourage you, however, to collaborate as learning is ultimately a social experience.
Throughout the course, we will continuously evaluate the teaching. It is your responsibility to let us know which activities help your learning and how we can improve the activities to help you learn more. In return, we promise that changes and, hopefully, improvements will be made based on the results of the evaluations.
The Assignments and the Peer Feedback
The course is structured around five major assignments covering the five topics of the course. The assignments are empirical case-studies with open questions where you use time-series econometrics to solve real problems in line with the main learning outcome of the course listed above. The teaching is structured around the assignments, so the assignments guide (and hopefully motivate) your learning experience.
In the assignments, you must use econometric theory, estimate the relevant models, present your results in a precise and concise way, and discuss the results and limitations of your approach.
You are allowed to hand in the assignments individually or in groups of up to three students. The assessment criteria are the same if you hand in individually or in a group. We strongly encourage you to work in groups.
The assignments must be written in English and they can be maximum 5 normal pages of text plus 2 pages with tables and figures. The assignments must anonymous and they must be handed in on the Peergrade platform.
Peer Feedback
You are required individually to provide peer feedback on each other's assignments via the Peergrade platform. The peer feedback is anonymous and based on specific rubrics which focus on what can be improved in an assignment. In cases of potentially wrong feedback, you have the opportunity to flag feedback as problematic and the teacher can comment on it. After receiving peer feedback you have to assess the quality of the feedback you have received.
Note that you do not grade each others' assignments and you will not receive feedback from the teaching assistants. However, you will receive general feedback on common problems and misunderstandings from the teacher during lectures.
Through the peer feedback you practice critical reading and giving constructive feedback, and you receive feedback focused on what you can improve in your assignment.
Qualification for the Exam
To qualify for the exam you must 1) hand in 4 of the 5 assignments individually or in groups of up to three students, 2) for those 4 assignments individually provide peer feedback on two hand-ins through the Peergrade platform (so in total, you must individually provide peer feedback on a minimum of 8 hand-ins), and 3) you must rate the quality of the feedback you have received. The hand-ins and the peer feedback must be carried out before the deadlines specified in the Course Schedule. Unconstructive or inadequate peer feedback will not be accepted as qualification for the exam.
The Exam
The exam is a portfolio exam which consists of three of the five assignments (the teachers select which ones) plus a new theoretical part. You can use the peer feedback you have received to improve your assignments before handing it in for the exam. You will only be assessed based on your final hand-in.
The exam period is:
Friday, May 18, to Friday, May 25, 2018.
The Lectures and Preparations for Lectures
The lectures and exercise classes are structured so that you will work actively with the content. You have to prepare for lectures by reading selected parts of the curriculum, watch a 10-minute Youtube-video, and complete a review quiz with 5-10 multiple choice questions. The required preparations are listed in the Course Schedule.
The review quizzes give you instant feedback on whether you understood the main points, and it provides the teachers with feedback on which parts you find difficult so that we can follow up on that in the lectures. At the end of the review quiz, you have the opportunity to ask questions about the parts that you find difficult to understand.
We start the lectures by reviewing the content covered in the readings, video, and quiz, and the teacher answers the questions posed at the end of the review quiz. Thereafter, we built on the content you have studied during the preparations by combining short lectures with activities such as theoretical exercises, Socrative quizzes, think-pair-share discussions, and live simulation experiments. The aim of the activities is to assess your understanding, correct common misunderstandings, to get you to reflect on important aspects, and to provide intuition of main results. You are expected to participate actively in lectures.
Note that the lecture does not repeat the content covered in the videos, so you are expected to actively prepare for each lecture by reading a few pages, watch the 10-minute video, and complete the review quiz.
Time and place for lectures:
Wednesday, 13:15-15:00 in CSS 35.01.44 (basement of building 35).
Thursday, 8:15-10:00 in CSS 35.01.04 (basement of building 35).
The Exercise Classes
The goals of the exercise classes are to help you complete the assignments. For each topic, there is a Problem Set with empirical exercises that guide you through a specific empirical analysis. The teaching assistants will cover selected parts of the exercises and they will do their best to answer your questions. To help you work through the exercises at your own pace and at your own time, we have created written solutions, videoes with empirical illustrations, and online tutorials for the exercises in the Problem Sets. The videos and online tutorials guide you through the steps of the empirical analyses in OxMetrics.
Time and place for exercise classes:
Class 1: Dan Nolsøe Olsen. Monday, 8:15-10:00 in CSS 5-1-16.
Class 2: Laurits Rømer Hjort. Monday, 8:15-10:00 in CSS 2-1-36.
Class 4: Birk Houmark Løfqvist. Monday, 8:15-10:00 in CSS 2-2-24.
Questions
Throughout the course, we encourage you to ask questions regarding the curriculum, the assignments, etc. There is no such thing as stupid questions. In fact, you are most likely not the only student with a specific question. So please do not hesitate to ask questions during lectures, after lectures, during exercise classes, and using the Discussion Forum here on Absalon.
Instead of sending questions by email, please use the Discussion Forum so that other students can see your question and replies. In the Discussion Forum, you find a thread for each of the five topics and you can ask questions anonymously if you prefer.
Curriculum
The curriculum consists of eight lecture notes written by Heino Bohn Nielsen and the textbook "A Guide to Modern Econometrics", 5th Edition, by Marno Verbeek.
Lecture Note 1 - Introduction to Time Series Download Lecture Note 1 - Introduction to Time Series (13 pages).
Lecture Note 2 - Linear Regression with Time Series Data Download Lecture Note 2 - Linear Regression with Time Series Data (22 pages).
Lecture Note 3 - Introduction to Vector and Matrix Differentiation Download Lecture Note 3 - Introduction to Vector and Matrix Differentiation (cursory readings, 6 pages).
Lecture Note 4 - Dynamic Models for Stationary Data Download Lecture Note 4 - Dynamic Models for Stationary Data (28 pages).
Lecture Note 5 - Non-stationary Time Series and Unit Root Testing Download Lecture Note 5 - Non-stationary Time Series and Unit Root Testing (21 pages).
Lecture Note 6 - Cointegration and Common Trends Download Lecture Note 6 - Cointegration and Common Trends (31 pages).
Lecture Note 7 - Modeling Volatility in Financial Time Series - An Introduction to ARCH Download Lecture Note 7 - Modeling Volatility in Financial Time Series - An Introduction to ARCH (16 pages).
Lecture Note 8 - Generalized Method of Moments Estimation Download Lecture Note 8 - Generalized Method of Moments Estimation (33 pages).
Verbeek, M., "A Guide to Econometrics: A Modern Approach", 5th edition.
The main curriculum is the lecture notes, but the book is a great supplement and it covers some elements and details that are not included in the lecture notes.