SYLLABUS
MGTSC 707: Applied Business Analysis of Time Series and Panel Data (Fall, 2009)
Time / Location: Mondays 10.00 - 12.50, Bus B-12 Instructor: Dr. Ke-Li Xu, Assistant Professor
Office: Bus 3-40N Office Hours: by email appointment Telephone: 780-492-8076 Fax: 780-492-3325
E-mail: [email protected]
Course Overview
This course is organized into two parts. Part I covers univariate and multivariate time domain models of stationary and nonstationary time series. Topics covered include univariate time series models, volatility models, unit root tests, time series regression modeling, systems of regression equations, vector autoregressive models for multivariate time series and cointegration. In Part II the course introduces the issues and opportunities that arise with panel data and the main statistical techniques used for its analysis.
Topics covered include fixed-effects models, random-effects models, dynamic models and limited dependent variable models. The course will illustrate the estimation and inference strategies using the software . It is normally taken by students in the second year of the Business Ph.D. program.
Prerequisites
MGTSC 705 or a graduate-level course on linear model or econometrics.
Reading materials
[1] Tsay, R. S. (2005), Analysis of Financial Time Series, 2nd edition, Wiley-Interscience.
[2] Wooldridge, J. (2002), Econometric Analysis of Cross Section and Panel Data. The MIT press.
As their names suggest, I will select materials on time series from [1] and panel data from [2]. I will indicate which topics and chapters you should read as the course proceeds.
The second book is available online through the University library website. I recalled both books for reserve in the Winspear business library and they should be available shortly after the semester starts.
The following books are also useful for further reading: for time series,
[3] Hamilton, J.D. (1994), Time Series Analysis, Princeton University Press.
[4] Enders, W. (2004), Applied Econometric Time Series, Second Edition, John Wiley.
for panel data,
[5] Arellano, M. (2003), Panel Data Econometrics, Oxford: Oxford University Press.
[6] Baltagi, B. H., (2005), Econometric Analysis of Panel Data, Third Edition, John Wiley.
The software is free and can be downloaded from www.r-project.org. The following books are especially useful for learning R:
[7] W.N. Venables, D.M. Smith and the R Develop Core Team (2007), An Introduction to R.
(www.r-project.org)
[8] W.N. Venables and B.D. Ripley (2003), Modern Applied Statistics with S (4th Edition). Springer.
[9] C. Kleiber and A. Zeileis (2008), Applied Econometrics with R. Springer.
Problem Sets and Final Project
Assignments 85%
In-class participation 15%
The homework assignments are designed to familiarize students with the particular statistical skills taught in the previous classes. I will specify a deadline for each assignment. A zero is given for a missed or late assignment. Assignments are dropped in the dropbox on the 3rd floor of the Business building. R codes and outputs (or codes of other software) should be included in the assignments.
Academic Honesty
The University of Alberta is committed to the highest standards of academic integrity and honesty. Work submitted by students must be their own. Copying another student’s file for an assignment or the term project is not acceptable under any circumstances. Students are encouraged to discuss the course materials with other students (and myself), but they are not allowed to show the written work or numerical answers to other students. When you quote an article, book, webpage or any other source in your project, you must reference that source.
