This is a work-intensive applications-oriented course on econometric methods for time series data beyond the beginner's level. The follow-up course, Econ 7630, will deal mainly with cross-sectional and panel data issues.
The basic idea of this course is (i) to enable doctoral students to work through the empirical portion of a dissertation or academic paper; (ii) to provide masters-level students with job skills as an applied economist; (iii) to enable all students to understand the current literature in applied economics.
The specific course objectives are to provide students with
The final grade will be based on a mid-term exam, a final exam, and a set of assignments. Each of the two exams counts 30 percent toward the final grade, the set of assignments 40 percent.
Textbook: The course is not based on a particular textbook. However, Walter Enders' book (see references below) would be good to have. Books identified with an asterisk are also recommended. Some notes will be provided on line. They will be available for download. A password is needed in order to start the download.
Computer Use: The Getting Started web page will help all students to review the use of computer programs that relate to this and other courses. Information on many computer programs of relevance to economists is provided here. Much of the course will rely on free packages, in particular GRETL and R. Also useful are JMULTI and SVAR. Some use will also be made of the commercial package STAMP.
Office hours: by appointment and via E-mail. You are expected to check questions and problems with me first via E-mail. Read your E-mail regularly, as I may make use of this medium to post messages on such things as homework assignments, additions, and corrections.
Special Note: Students with a disability that may require assistance or accommodation, or with questions related to any accommodations for testing, note takers, readers, etc., should contact the instructor as soon as possible. Students may also contact the Office of Disabled Students Services (898-2783) with questions about such services.
1. Box-Jenkins Time Series Models
2. Models Nonlinear in the Mean
3. Volatility Modeling
4. Unobserved Components Models
5. State Space Modeling
6. General to Specific Modeling of Time Series Regressions
7. Unit Root Testing and Single-Equation Cointegration
8. Vector Autoregressions
9. Multivariate Cointegration
Baltagi, Badi H., Econometrics, 2nd rev. ed., Springer 1999.
Berndt, Ernst R., The Practice of Econometrics: Classic and Contemporary. Addison-Wesley, 1991.
Box, George, Gwilym M. Jenkins, and Gregory Reinsel, Time Series Analysis: Forecasting & Control, 3rd ed., Prentice Hall, 1994.
Brockwell, Peter J., and Richard A. Davis, Introduction to Time Series and Forecasting, 2nd ed., Springer, 2002.
Campbell, John Y., Andrew W. Lo, and A. Craig MacKinlay, The Econometrics of Financial Markets, Princeton University Press, 1997.
Clements, Michael P., and David F. Hendry, Forecasting Non-stationary Economic Time Series, MIT Press, 1999.
Charemza, Wojciech W., and Derek F. Deadman, New Directions in Econometric Practice. 2nd ed., Edward Elgar, 1997.
Commandeur, Jacques J.F., and Siem Jan Koopman, An Introduction to State Space Time Series Analysis. Oxford University Press, 2007.*
Cuthertson, Keith, Stephen G. Hall, and Mark P. Taylor, Applied Econometric Techniques, University of Michigan Press, 1992.
Davidson, Russell, and James G. MacKinnnon, Econometric Theory and Methods, Oxford University Press, 2004.
Durbin, James, and Siem Jan Koopman, Time Series Analysis by State Space Methods. Oxford University Press, 2001.
Enders, Walter, Applied Econometric Time Series. 2nd ed., Wiley, 2004.
Fair, Ray C., Testing Macroeconometric Models. Harvard University Press, 1994.
Favero, Carlo A., Applied Macroeconometrics. Oxford University Press, 2001.
Franses, Philip Hans, Time Series Models for Business and Economic Forecasting, Cambridge University Press, 1998.
Franses, Philip Hans, and Dick van Dijk, Non-Linear Time Series Models in Empirical Finance, Cambridge University Press, 2000.*
Gourieroux, Christian, and Alain Monfort, Time Series and Dynamic Models, Cambridge University Press, 1997.
Greene, W.H., Econometric Analysis. 4th edition, Prentice Hall, 2000.
Hamilton, James D., Time Series Analysis, Princeton University Press, 1994.
Harvey, Andrew C., Forecasting, Structural Time Series Models, and the Kalman Filter, Cambridge University Press, 1989.
Harvey, Andrew C., Time Series Models, MIT Press, 1993.
Hendry, David F., Dynamic Econometrics. Oxford University Press, 1995.
Johnston, Jack, and John Dinardo, Econometric Methods. 4th ed., McGraw-Hill, 1997.
Juselius, Katarina, The Cointegrated VAR Model: Methodology and Applications. Oxford University Press, 2006.*
Kennedy, Peter, A Guide to Econometrics. 5th ed., MIT Press, 2003.
Kim, Chang-Jin, and Charles R. Nelson, State Space Models with Regime Switching. MIT Press, 1999.
Kleiber, Christian, and Achim Zeileis, Applied Econometrics with R. Springer, 2008.
Lütkepohl, Helmut, New Introduction to Multiple Time Series Analysis. Corr. 2nd. printing, Springer, 2007.
Lütkepohl, Helmut, and Markus Krätzig, Applied Time Series Econometrics, Cambridge University Press, 2004.
Maddala, G.S., and In-Moo Kim, Unit Roots, Cointegration, and Structural Change, Cambridge University Press, 1998.
Makridakis, Spyros, Steven C. Wheelwright, and Victor E. McGee, Forecasting: Methods and Applications, 2nd ed., Wiley, 1983.
Mills, Terence C., Time Series Techniques for Economists. Cambridge University Press, 1990.
Pindyck, R.S. and D.L. Rubinfeld, Econometric Models and Economic Forecasts. 4th ed., McGraw-Hill, 1998.
Rao, B. Bhaskara (ed.), Cointegration for the Applied Economist. St. Martin's Press, 1994.
Stock, James H., and Mark W. Watson, Introduction to Econometrics, Addison-Wesley, 2003.
Tsay, Ruey S., Analysis of Financial Time Series. 2nd ed., Wiley, 2005.*
Vandaele, Walter, Applied Time Series and Box-Jenkins Models, Academic Press, 1983.
Verbeek, Marno, A Guide to Modern Econometrics, Wiley, 2000.
More specialized readings will be suggested in the lecture notes.