NOTE: This course will comprise the first 8 weeks of classes for Econ608, from January 19th - March 9th. The other half of the course will be taught by Professor Xiye Yang, who will provide his own syllabus for his part of the course.

Econometrics II (Econ 608) - MSMF
Professor Norman R. Swanson
Spring 2021


A picture is worth a thousand words. But so is a statistic ...


In the economics department, this is the third course in the econometrics sequence, and the first elective econometrics course. The course primarily covers topics in time series analysis. However, the class has been modified for the MSMF class. The aim of the course is to familiarize students with time series methods from both an applied and a theoretical perspective. Emphasis in the final project will be on empirical analysis, bootstrap and Monte Carlo techniques, while emphasis for any in-class test that may be given will be on methodological issues discussed in class.

Learning Goals and Assessment

Departmental learning goals and assessment for graduate classes are detailed at the following website:

Additionally, departmental learning goals and assessment for masters students are detailed at the following website:

In this course, and as fully detailed at the above referenced documents, learning goals and assessment will include:
(i) Attain marked ability, scholarship, research and leadership skills in economics, with specialization in selected sub-disciplines
(ii) Engage in and conduct original research
(iii) Prepare to be professionals in careers that require training at the highest levels in economics and selected sub-disciplines

Additionally, note that your course grade will be based on the results from 1 in class paper presentation (35%), in class midterm examination (35%), and a final project (30%). Note, if in class midterm is cancelled, then grade will be deterimned by equally weighting the in-class presentation and written class handbook and the final project.

The main focus of this course is on time series econometrics. Throughout the course, we will discuss and review topics including LM, LR, and Wald tests, ARIMA models, and maximum likelihood estimation. We will also cover VAR models, unit roots, cointegration, spurious regression, and Granger causality. Finally, we will discuss other time series topics including forecasting, continuous time financial models, bootstrapping, Monte Carlo methods, and GARCH. The overall focus of the course will be on financial and macro econometrics.

Important Dates

·  Tuesday Feb 23rd: In class group presentations (see below for details).

·  Friday March 12th: Final project due (see below for details).

Course Syllabus and Reading Lists

·  Econometrics 608 Course Syllabus. PDF Version.

·  Econometrics 608 List of possible presentation papers. Note that this list is not current, and so I encourage you to explore the latest literatures of interest to you. PDF Version.

·  Econometrics 608 Additional Reading List. PDF Version.

Additional Notes and Possible In-Class Lectures (Time Permitting)

·  Forecasting Lecture Notes. PDF Version.

·  Predictive Density Construction and Accuracy Testing with Multiple Possibly Misspecified Diffusion Models - 2009 PDF Version.

·  Predictive Density Construction and Evaluation - 2010 PDF Version.

·  Predictive Density Construction and Evaluation - Lecture Notes - 2011 PDF Version.

·  Density and Conditional Distribution Evaluation and Construction - 2012 PDF Version.

·  Methods for Short Term Forecast Model Estimation and Accuracy Assessment - 2012 PDF Version.

Practice Problems

·  Set of Practice Problems (do problems 1,2,3,4,6) PDF Version.

·  Another Set of Practice Problems (do all) PDF Version.

·  Solution Set for "Another Set of Practice Problems" PDF Version.

Old Tests

·  old midterm exam (do problems 1a, 2, 3) PDF Version.

·  old midterm exam (do all) PDF Version.

·  old midterm exam (do problem 3) PDF Version.

·  old final exam (do problems 1,4) PDF Version.

Software Examples and Discussion

·  Basic Introduction to EVIEWS

·  Gauss Monte Carlo Experiment Example

·  Gauss Program #1

·  Gauss Program #2

·  Gauss Program #3

·  Gauss Program #4

In-Class (Group) Paper Presentations

Groups will be assigned by the professor, and all students are required to participate in group presentation preparation, although only one student is required to present to the class on the date stated above.

Prepare a presentation of a topic from an econometrics forecasting paper or set of related papers either from the list of presentation papers given above, or of your own choosing, in accord with your desired research area. Contact me with the topic that you have chosen and I will deem it acceptable, or not.

Alternatively, you may choose to prepare your presentation based on a key forecasting topic, including:

1. forecasting using time series
2. forecast model specification and selection
3. forecast model accuracy assessment and testing
4. forecasting using GARCH (generalized autoregressive condition heteroscedasticity) models
5. simulation and forecasting using discrete time series models
6. simulation and forecasting using continuous time series models
7. forecasting in financial markets
8. value at risk forecasting
9. forecasting using linear versus nonlinear models
10. forecasting using big data methods

I will tell you in class how long each presentation will be. All papers/topics must be approved by me. General "topics" of interest to the class (rather than particular papers) may also be allowed; again subject to my approval. Provide an overview and a critique of the paper(s) or topic, with focus on (i) the methodological/theoretical contributions or tools used in the paper/topic. Prepare a comprehensive handout to be emailed to members of the class and myself on the day of your presentation. The handout should contain a complete discussion of all methodology developed, econometric tools used, and econometric theory in the paper or for the topic. You are encouraged to use additional related papers and/or textbooks to help you "flesh" out the methodology and theory in the paper (topic).

Final Project

Each student will be required to carry out a unique forecasting analysis, in which the objective is to forecast variable(s) of interest to be selected by the student. A formal written paper is required for this part of the course, and all papers must be emailed to me by the date listed above. It is recomended to carry out this requirement by building on the methods that are discussed in your group presentation, although this is not required. Details of project to follow and to be discussed in class.

Project Due Date: last class.


·  Technical Notes.

·  papers as they are discussed in class

Additional Links

·  Resources for Economists: Data Links, Econ Dept's, Conferences, and Economists

·  EVIEWS home


·  Queries or comments? Please click here ---> ---

·  Back to my home page