Econometrics II (Econ 608)
Professor Norman R. Swanson
Fall 2020


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


NOTE: Class never meets during the first recitation of a semester, if said recitation falls on a day befoere the first class of the semester. When recitations are run, you will be given ample notification prior to the recitation.

This is the third course in the econometrics sequence, and the first elective econometrics course. The course primarily covers topics in time series analysis. 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 nad Monte Carlo techniques, while emphasis for the in-class test 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, as fully detailed in 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

Your course grade will be based on the results from 1 in class paper presentation (35%), 1 in class midterm examination (35%), and a final project (30%), or as announced by the professor in class.

Course Objective

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 (subject to change)

·  Monday October 5th or as determined by class demand: GAUSS demo.

·  Monday October 5th or as determined by class demand: EVIEWS demo.

·  Monday October 19th: Time will be allotted for in class midterm examination problem solving and questions.

·  Monday October 26th: In class midterm examination.

·  Monday November 2nd and 9th: In class (zoom) presentations.

·  December 8th: Final project due in class, on date of last Econ508 class meeting.

Course Syllabus and Reading Lists

·  Econometrics 608 Course Syllabus. PDF Version.

·  Econometrics 608 Lists of possible presentation papers. PDF Version.

·  Econometrics 608 Additional Reading List. PDF Version.

Various Prediction Methods Presentations (that may be covered in class, 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

Course Requirement: Paper Presentation

Prepare a 12 to 15 minute presentation of an econometrics paper either from the list of presentation papers given above, or of your own choosing in accord with your desired dissertation research area. All papers must be approved by me. Provide an overview and a critique of the paper, with focus on (i) the methodological/theoretical contributions or tools used in the paper; and (ii) any empirical and/or simulation content in the paper. Emphasis should be placed on item (i), however. Prepare a comprehensive handout to be given to members of the class 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. You are encouraged to use additional related papers and/or textbooks to help you "flesh" out the methodoogy and theory in the paper.

Course Requirement: Final Project

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

·  Queries/Comments? => ---

·  Home Page